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Employment Policyin Developing CountriesA Survey of Issues and Evidence

A World Bank Research Publication

SI

Employment Policy* in Developing Countries

A Survey of Issues and Evidence

Lyn Squire

PUBLISHED FOR THE WORLD BANK

Oxford University Press

Oxford University Press

NEW YORK OXFORD LONDON GLASGOWTORONTO MELBOURNE WELLINGTON HONG KONG

TOKYO KUALA LUMPUR SINGAPORE JAKARTADELHI BOMBAY CALCUTTA MADRAS KARACHI

NAIROBI DAR ES SALAAM CAPE TOWN

© 1981 by the International Bankfor Reconstruction and Development / The World Bank

1818 H Street, N.W., Washington, D.C. 20433 U.S.A.

All rights reserved. No part of this publicationmay be reproduced, stored in a retrieval system,

or transmitted in any form or by any means,electronic, mechanical, photocopying, recording,

or otherwise, without the prior permission ofOxford University Press. Manufactured in the

United States of America.

The views and interpretations in this book are theauthor's and should not be attributed to the World

Bank, to its affiliated organizations, or to anyindividual acting in their behalf.

Library of Congress Cataloging in Publication Data

Squire, Lyn, 1946-Employment policy in developing countries.

Bibliography: p.Includes index.1. Underdeveloped areas-Labor supply.

2. Underdeveloped areas-Manpower policy. 3. Un-derdeveloped areas-Full employment policies.I. World Bank IL Title.HD5852.S65 331.12'042'091724 81-2844ISBN 0-19-520266-X AACR2ISBN 0-19-520267-8 (pbk.)

Foreword

This book was originally written as a background study for theWorld Development Report, 1979, the second of a series of annualreports produced by the World Bank's economic staff. Each yearthe best of these studies are separately published for the use ofscholars and practitioners in specific fields. The present work isone of three monographs dealing with problems of industrializa-tion and urban development, the main themes of the 1979 report.

Low rates of growth in industrial employment, high rates ofunemployment for new entrants to the urban labor market, andlow levels of labor productivity and remuneration are the threeissues addressed in this paper. Squire demonstrates that, in com-parison with historical experience, the sectoral transformation ofthe labor force in developing countries has been retarded by theunusually fast growth of the labor force rather than the slow paceof industrialization. The concentration of high rates of unemploy-ment among young, inexperienced, and first-time entrants to theurban labor market is attributable to the varying rates at whichwages in different segments of the market have adjusted to the un-precedented expansion in the supply of such workers, and to theability of the more affluent families to support their dependentsduring a period of job search.

Low productivity and remuneration are due primarily to in-appropriate macroeconomic policies rather than to labor marketdistortions. Accordingly, Squire's policy discussion is concernedwith identifying the more important determinants of labor de-mand and supply and the extent to which the growth of labordemand has been restrained-and labor supply advanced-by in-appropriate policies. On the demand side, industrial trade policy,agricultural growth, and the operation of capital markets aresingled out for discussion; on the supply side, attention is focusedon population and education policy.

v

vi Foreword

As do other World Bank research studies, Squire takes a broadcomparative view of his subject. His policy recommendations aresoundly based in economic theory but supported as well by awealth of empirical illustrations drawn from the Bank's opera-tional work.

Hollis B. CheneryVice President

Development PolicyWorld Bank

Contents

Foreword v

List of Tables x

1. Introduction 3

Organization 5

Conclusions 6

Part I Statistical Overview 11

2. A Historical Comparison 15

Factors Operating on the Supply Side 15Factors Operating on the Demand Side 20Industrial LaborAbsorption in the 1960s 23Factors Determining Industry 's Share of the Labor Force 26Technical Note 31

3. A Cross-Sectional Analysis 42

Population and Labor Force 42

Sectoral Structure of the Labor Force 47Educational and Occupational Structures of the Labor Force 49Productivity and Real Wage Rates 53Summary 56

4. Unemployment and Underemployment 57

Analytical Content 58Estimates of Unemployment 66Estimates of Underemployment 69

Conclusion 74

Part II. The Operation of Labor Marketsin Economic Development 77

5. Models of the Dual Labor Market 79

6. Determination of Rural Wages 83

Utilization of Rural Labor 83Rural Wage Rates 90

7. Rural-Urban Migration 98

Recent Trends 98

vii

viii Contents

Theories 100Evidence 100Policy Implications 105

8. The Operation of Urban Labor Markets 109Minimum Wage Legislation and Trade Unions 109Hiring Practices of Modern Sector Firms 114Social Security Legislation 117Hiring Practices in the Public Sector 118Labor Heterogeneity 121 ,Market Disequilibrium 122Labor Market Adjustment 123

9. Policy Implications 125Unskilled Labor 125Educated Labor 130Conclusion 132

Part IIL. Policies Affecting Labor Demand 133

10. Labor Absorption in Services and Informal Activities 135Demand for Services 136Productivity in Services 140Informal Sector 140Conclusion 143

11. The Employment Effects of Industrial Trade Policy 144Intercountry Comparisons 144Labor Intensity of Manufactured Tradables 149Conclusion 151

12. Employment in Agriculture 153Internal Terms of Trade 153Farm Size 155Distortions in Factor and Input Markets 157Recent Evidence 162Policy Inference 164

13. Capital Markets 166Capital-Labor Ratios 167Determinants of Saving 170Conclusion 1 72

14. Synthesis 173

Part IV. Policies Affecting Labor Supply 1 75

15. Population Growth in Economic Development 1 77Consequences of Rapid Population Growth 1 77

Contents ix

Population Growth and GNP per Capita 181

Population Growth, Structure

of the Labor Force, and Wage Rates 183Scope for Policy Intervention 185

16. Education Policy 194

Role of Education in Economic Growth 194

Educational Expansion and Its Implications 195

Social and Private Rates of Return 199

Vocational and On-the-Job Training 201Conclusion 204

References 207

Index 223

Figure 1. Wage Employment, Self-Employment, and Underemployment 60

Tables

1. Sectoral Structure of the Labor Force in Developed and DevelopingCountries, 1880-1960 12

2. Sectoral Distribution of the Labor Force for Developed Countries, 1]880,and Developing Countries, 1960 13

3. Average Annual Growth Rates of Population, Labor Force, and Urban-ization in Developing and Developed Countries, 1800-19 70 16

4. Age Structure of the Population in Developed Countries, circa 1900,and Developing Countries, circa 1960 1 7

5. Educational Attainment and Growth Rates for Developed Countries,circa 1900, and Developing Countries, circa 1960 19

6. Crude Estimates of Sectoral Value Added and Productivity Growth Ratesfor Developed Countries, 1880-1900, and Developing Countries,1960-70 20

7. Occupational Structure of the Labor Force in the United States andLatin America 22

8. Average Annual Rates of Growth of the Labor Force by Sector for D)e-veloped Countries, 1880-1900, and Developing Countries, 1960-70 23

9. Crude Estimates of Sectoral Value Added and Productivity for De-veloped Countries, 1880, and Developing Countries, 1960 27

10. Population and Labor Force by Region, 1950-2000 44

11. Sectoral Distribution of the Labor Force by Region, 1950-70 48

12. Educational and Occupational Structures of the Labor Force in SelectedCountries, 1960 49

13. Age-specific Enrollment Ratios by Level of Education and Country In-come Group 50

14. Occupational Structure of the Labor Force by GDP per Capita,1960-70 51

15. Level and Growth Rate of Productivity by Sector and Region 52

16. Average Annual Rates of Change in Wages, Employment, Prices, andGDP per Capita by Region, 1964-72 54

17. Percentage of the Labor Force in Wage Employment in Selected Coun-tries, circa 1970 58

18. Open Unemployment Rates in Selected Economies 67

19. Urban and Rural Unemployment Rates in Selected Economies i58

20. Urban Unemployment by Age and Sex in Selected Countries 70

x

Tables xi

21. Unemployment by Educational Attainment in Selected Countries 71

22. Estimates of Underemployment in Selected Countries 72

23. Hours Worked in Rural Areas in Selected Economies 84

24. Labor Utilization in Three African Countries: Division of Twelve-HourDay among Activities 85

25. Wage Employment and the Agricultural Labor Force in Selected Coun-tries 86

26. Labor Market Participation in Malaysia and Egypt 87

27. Distribution of Employed Labor Force between Agricultural and Non-agricultural Activities in Rural Areas of Selected Economies 88

28. Seasonal Variation in Labor Usage in Three Countries 89

29. Net Rural-Urban Migration in Selected Countries, 1950-70 99

30. Intersectoral Wage Differentials for Low-skill Labor in Selected Coun-tries 102

31. Time Required for Migrants to Find First Job in SelectedCountries 104

32. Wage Differentials and the Share of the Labor Force in Mining for Se-lected Mineral-Producing Countries, circa 1970 116

33. Extent of Public Sector Employment in Selected Countries 119

34. Job Preference by Level of Education for Unemployed Urban MalesAged 15-24 with No Previous Work Experience, Sri Lanka, 1968 120

35. Non-Estate Labor Force by Education and Age, Sri Lanka,1969-70 124

36. Numerical Simulations of the Effect of Minimum Wage ]Legislation onthe Structure of the Labor Force and on Productivity 126

37. Employment in New and Old Services in Developed and DevelopingCountries 137

38. Employment in Intermediate Services in Developed and DevelopingCountries 139

39. Variation in Sectoral Productivity with Level of Development 141

40. Share of Industry in Total Labor Force by Development Pattern andGDP per Capita for Selected Countries, 1970 146

* 41. Wage Rates, Unemployment and the Sectoral Structure of the LaborForce in Four Countries, 1950-70 148

42. Ratio of Labor Coefficients in Exportables and Import Substitutes inSelected Countries 150

43. Contribution of Agriculture and Manufacturing to GDP and GDP Growthunder Different Assumptions about Protection in SelectedEconomies 154

44. Relative Yields and Labor Intensity by Farm Size in Colombia and Paki-stan, 1960 155

45. Average Farm Size and Farm Size Distribution in Selected Economies,1960 156

xii Tables

46. Sources of Agricultural Loans in Selected Economies 15847. Percentage Distribution of Institutional Credit by Farm Size in Selected

Economies 160

48. Formal and Informal Rural Interest Ratesin Selected Economies 161

49. Recent Agricultural Development in Japan, Taiwan, and Mexico 16250. Fixed Assets per Job in Direct Employment for Four Countries 168

51. Capital Productivity by Size of Enterprise for Five Countries 169

52. Estimated Age Structure of the Population by Region, 1975 1 78

53. Gross Domestic Investment per New Labor Market Entrant in SelectedCountries, 1975 179

54. Average Annual Growth Rates of Crop Area and Agricultural Populationfor Selected Countries, 1970-75 180

55. Percentage Decline in Crude Birthrate by Social Setting and ProgramEffort, 1965-75 186

56. Total and per Capita Funds for Family Planning Programs in SelectedAreas 191

57. Comparison of Gross Discounted Lifetime Earnings among EducationalLevels in Selected Countries 196

58. Average Social Rates of Return by Educational Level in Developed andDeveloping Countries 197

59. Comparison of Modem Sector Job Vacancies and Educated Labor Mar-ket Entrants in Selected Countries, 1973 198

60. Educational Expenditure by Region 201

Acknowledgment

Helpful comments on early drafts of this book were received from ShankarAcharya, Suman Bery, Roberto Cuca, Alan Gelb, Peter Hazell, Don Keesing,Timothy King, Deepak Lal, Mark Leiserson, Johannes Linn, Dipak Mazum-dar, Guy Pfeffermann, Garry Pursell, Graham Pyatt, Frances Stewart, RichardWebb, and Manuel Zymelman. Frequent discussions with Mark Leisersonwere especially instructive.

Nancy Enikeieff and Ben Sands provided highly competent research as-sistance. The entire manuscript was expertly typed by Banjonglak Duangrat,and it was edited for publication by Jane Carroll. Brian J. Svikhart super-vised production of the book, Raphael Blow prepared the figure, ChrisJerome read and corected proofs, andJames Silvan and Ralph Ward providedthe index.

xiii

4

It

I

Employment Policyin Developing Countries

A Survey of Issues and Evidence

a

1

Introduction

This survey is concerned with three issues: the sectoral structureof the labor force, unemployment, and underemployment.

It is frequently claimed that the industrial sector's absorptionof labor in developing countries has been inadequate in the sensethat only a small proportion of the incremental labor force hasobtained industrial jobs, the remainder being forced to acceptlow-productivity jobs in agriculture and services. It is shownhere, however, that industrial employment in developing countrieshas increased at almost twice the historical rate of the developedcountries and that, in relation to the existing labor force, industryin developing countries has absorbed labor at about the same rateas in the developed countries during the late nineteenth century.These results reflect the rapid growth of industrial output in cur-rently developing countries. Nevertheless, changes in technologyand unprecedented increases in the labor force combined to limitindustry's share of the labor force in the developing countries of1960 to less than half of that in developed countries at the turn ofthe century.

Of itself, this need not be a matter for concern. To the extentthat it reflects a suboptimal use of resources, however, it becomesof major importance. Once attention is focused firmly on resource

* allocation rather than on the sectoral distribution of the laborforce, it is conceivable that some policies to improve the allocationof resources may retard the structural transformation of the labor

* force. For example, agricultural labor demand in many countrieshas been suppressed by inappropriate pricing policies and anunequal and inefficient distribution of investable resources. Elimi-nating these biases may improve resource allocation and incomedistribution but may reduce industry's share of the labor force.

Unemployment is measured by the number of people activelyseeking jobs. This implies that two conditions must be fulfilled

3

4 Introduction

before positive unemployment rates can be expected in developingcountries: first, the financial return to job search must be positive,which, in turn, requires the existence of wage differentials andimperfect information; and second, nonlabor income must beavailable to finance the unemployed. It follows that the con-centration of high rates of unemployment among young, in-experienced but educated, first-time entrants to the urban labormarket can be attributed to the varying rates at which wages indifferent segments of the market have adjusted to the unprece-dented expansion in the supply of such workers, and to the abilityof relatively rich families to support their dependents during aperiod of unemployment.

Wage differentials for unskilled, uneducated labor have alsoattracted considerable attention, not because unemploymentrates are correspondingly high, the poor being unable to financea prolonged job search, but because of the implied misallocation oflabor resources. Minimum wage and social security legislation,trade union activity, and the hiring practices of large-scale fimis-so-called institutional factors-are often alleged to have created"high-wage" sectors, with the result that the sectoral allocationof labor is less than optimal. It is argued here, however, that theextent of institutional wage determination has been exaggeratedand that, to the extent that such distortions do exist, their re-moval would have little effect on the economy-wide marginalproduct of labor.

The concept of underemployment has suffered from a be-wildering variety of definitions. It is defined here as the existenceof workers whose earnings from wage or self-employment liebelow a given cutoff, this being the approach most frequentlyadopted in the recent literature. It is therefore conceptually simi-lar to measures of the extent of poverty. Concern for the under-employed, thus defined, can arise for two reasons: first, becausetheir low earnings are thought to be the consequence of frag-mented factor markets, distorted product markets, and otherdivergences between social and private measures of costs andbenefits; and second, because society may consider the achieve-ment of a more equal distribution of income a legitimate goal.In this book attention is directed to the first reason, and policyconclusions are drawn accordingly. Conclusions for a more egali-

Introduction 5

tarian approach, though remaining implicit, can be deduced fromthe discussion in many instances.

Within these limits, the obvious policy prescription is theremoval of distortions in the labor market. The premise of thisbook, however, is that this is unlikely to increase labor productiv-ity significantly. Much of this study, therefore, is concerned withthe identification of the more important determinants of labordemand and supply and with the extent to which the developmentof labor demand has been restrained, and that of labor supplyadvanced, by inappropriate or inadequate policies. On the de-mand side, industrial trade policy, agricultural growth, and theoperation of capital markets are singled out for discussion, and onthe supply side attention is focused on population and educationpolicy.

Organization

The book comprises four sections. Part I provides a statisticaloverview of the three issues identified above. Historical and cross-sectional comparisons are used to place in perspective the quanti-tative dimensions of the growth of population, labor force,sectoral employment, and the supply of educated labor. Recenttrends in labor productivity, developments in real wages, andestimates of unemployment and underemployment are also re-viewed in Part I.

The operation of labor markets and the determination of wagesare discussed in Part II. The determination of rural wage ratesand the causes and consequences of rural-urban migration areexamined first. The bulk of Part II, however, is concerned with theoperation of urban labor markets. Simple numerical exercisesillustrate the quantitative significance of the elimination of institu-tionally induced distortions in the market for unskilled labor.The causes of educated unemployment are also examined.

In Parts III and IV selected policies affecting, respectively,labor demand and supply are reviewed. On the demand side threepolicies are considered: the promotion of manufacturing, thedevelopment of agriculture, and efforts to increase the efficiencyof capital markets. On the supply side, population programs areobviously relevant; education policy is also considered because ofthe high rates of unemployment recorded for educated labor.

6 Introduction

Conclusions

The policy conclusions relate mainly to factors influencinglabor demand and supply, and not to factors influencing theoperation of labor markets. This reflects a major proposition ofthis study-namely, that labor markets work reasonably well.This is not to deny the significance of labor market imperfectionsin certain instances; it is to suggest, however, that the condition ofthe underemployed will not be significantly improved by increas-ing the efficiency of labor markets unless policies are implementedto increase labor demand and reduce labor supply. Accordingly,labor market policies are treated relatively briefly, with moreattention given to policies affecting labor demand and supply.

The most frequently invoked labor market policy is minimumwage legislation. It should be recognized that such legislation canserve a useful purpose, especially where oligopsonistic conditionsallow employers to take advantage of unorganized workers. As a"floor," legislated minimum wages are to be encouraged, but asa standard-setting rate for a significant part of the unskilled laborforce, they serve only to disrupt the efficient allocation of laborresources. The salary structure adopted by the public sector is theother major mechanism the state can use to determine wages.Frequently, the public sector is the main employer of educatedlabor and can therefore exercise considerable influence over thestructure of salaries. The high rates of educated unemploymentobserved in many countries indicate that adjustments in the labormarket have been inadequate. In part, this may reflect the failureof recent school leavers to recognize and accept changes in labormarket conditions; in part, however, it also reflects the failure ofsalary structures to adjust to changed conditions of labor supply.The first failure indicates the need to improve information flowsin the labor market-information services, labor exchanges, andjob-placement agencies-and the second, the need to increaseflexibility in the public sector's salary structure.

Labor mobility is essential for a well-functioning labor market,but current rates of rural-urban migration are frequently describedas excessive. The roots of this problem are shown here to lie notin the labor market, but in policies that suppress the demand foragricultural labor by bringing about excessive protection for

Introduction 7

industry in relation to agriculture and capital market imperfec-tions, and in policies that increase the costs of urbanization byproviding free or subsidized public services. The solution, there-

fore, is to be found not in the imposition of quantitative restric-tions on rural-urban migration, but in the reformulation of pricingand investment policies.

The discussion of labor demand issues is confined to an analysisof policies that improve the efficiency of resource allocation. Thisexercise, therefore, may be viewed as an attempt to identify thosepolicies that not only yield greater efficiency but also substantiallyincrease the demand for labor. On the assumption that labor mar-kets operate reasonably well, efforts to expand labor demand ina given sector can be expected to exert upward pressure on wagesin other sectors.

Industrial trade policy is considered first. Manufactured exportsare usually more labor intensive than import substitutes, so thatthe removal of the bias against exports implicit in many import-substitution policies can be expected to increase labor demand inthe short run. Of more importance, however, are the potentiallong-run benefits. The change in policy can be expected to in-crease both the gross domestic product (GDP) and the return toinvestment, particularly in the industrial sector, because such apolicy switch redresses the balance between imports and exportsand usually implies a movement away from quantitative restric-tions. In the long run, therefore, an increase in the economy-widerate of investment and a reallocation of investable resources infavor of industry can be expected. The resulting increase in thecapital stock will allow an expansion in labor demand, and thereallocation of investment flows will hasten the transformation ofthe sectoral structure of the labor force.

Although the direction of the change appears clear, the quanti-tative impact on labor demand is more difficult to discern. Ingeneral, the impact will be large if existing policies are severelybiased against exports and reliance on quantitative restrictions isheavy; if complementary factors-physical and human capital-are in elastic supply; and if the initial size of the industrial sectoris significant in relation to the rest of the domestic economy butnot in relation to the international economy. This suggests that,for one reason or another, the rationalization of industrial tradepolicy, although it would improve efficiency, is unlikely to have

8 Introduction

a significant effect on labor demand in most low-income Asianand African countries. The consequences for employment will be(and in several cases have been) more substantial in the middle-income countries.

The low-income countries have more to gain from redressing thebalance between agriculture and industry and encouraging small-scale agriculture. Agriculture can be highly labor intensive; it alsoremains the most important source of employment in low-incomecountries. Agricultural growth, therefore, can be expected toincrease considerably the demand for labor. Pricing policies whichdiscriminate against agriculture in general, and agricultural labor inparticular, should be modified. This includes policies which haveturned the internal terms of trade against agriculture as well aspolicies which have reduced the cost of capital, especially tractors,in relation to wages. At the same time, small-scale agriculture imustbe assured stability of tenure and equal access to credit, the water-seed-fertilizer technology, and markets. Finally, the need forfurther technological advances suggests that research efforts willhave to be redoubled.

Serious efforts to promote agricultural growth in the low-income countries will, of course, retard the transformation in thesectoral structure of the labor force. They will do so, however,,only to the extent that they raise labor's supply price to the in-dustrial sector. This is desirable since it would improve both ef-ficiency and equity.

The final factor examined on the demand side is the efficiencyof capital markets. In the short run, the elimination of policy-induced distortions such as interest rate ceilings and subsidizeclcredit will improve the efficiency of resource allocation. This canbe expected to have a substantial effect on the demand for agricul-tural labor. The effect on industrial labor demand, however, isambiguous; it will depend on the technological characteristics ofproduction in the previously segmented markets. In the longrun, the improvement in resource allocation will yield an increasein GDP, which in turn will result in higher levels of saving. Savingsmobilization can also be improved by expanding the array offinancial assets and services and reducing transaction costs in thecapital markets. An expansion of saving will allow a correspondingexpansion in the capital stock and should therefore unambiguous-ly increase labor demand.

Introduction 9

Much of the discussion of demand factors is concerned with thedynamic consequences of improvements in resource allocation.Improvements in the allocation of resources within agriculturemay well be the only potentially substantial benefit to employ-ment in the short run, especially in the low-income countries.Apart from this, labor demand will benefit from a more efficientallocation of resources, not so much because of sectoral changesin the distribution of a given quantity of investable resources, butmainly because of the dynamic ramifications of the resulting in-creased rate of capital accumulation. This in tum will redress thecurrent imbalance between rates of capital accumulation and laborforce growth.

On the supply side, population programs are frequently ignoredin discussions of employment issues on the ground that for short-term policymaking the future labor force can be treated as given.For example, if a country's fertility rate had been halved in 1975,the male labor force would not have been affected for fifteenyears and by 2000 would have been reduced by only one-eighth.The reduction, however, would be concentrated in the under-twenty-five age group, which by 2000 would have been halved,and it is precisely this group which has suffered most from un-employment. In the medium and long term, population policy iscrucial.

Unfortunately, many of the countries with high rates of popula-tion growth are among the poorest in the world and seem leastinclined to initiate population programs. Most low-income Africanand Asian countries (with the notable exceptions of India, Indone-sia, and Sri Lanka) have hardly begun to implement family plan-ning programs. Of the middle-income countries, many in LatinAmerica are without population programs despite annual popula-tion growth rates close to or in excess of 3 percent. Obviously,the costs and benefits of these programs can be identified only inthe context of each country. Nevertheless, in the aggregate, popu-lation control emerges as an important long-run means of in-creasing the return to labor and advancing the transformation inthe industrial structure of the labor force.

Developments in the markets both for educated labor andfor education itself are also important. The former has beencharacterized by excess supply and the latter by excess demand.The excess supply of educated labor reflects the slow adjustment

10 Introduction

of the labor market to the rapidly changing supply conditions.Wage rate adjustments and a downward revision of job expecta-tions may gradually eliminate the excess, but only at the cost ofreducing the return to education. The excess demand for educa-tion reflects the general government practice of subsidizing thesector as well as education's dual role as a consumption and aninvestment good.

These arguments suggest that plans for the expansion of sec-ondary education should be carefully reviewed in the light of theexpected decline in future returns. The gap between formalsecondary education and specific job requirements should bebridged by the provision of vocational training establishmentswhich are responsive to labor market developments. Curtailingthe expansion of secondary education, however, will exacerbatethe problem of excess demand for it. The use of the pricemechanism (school fees) may be politically acceptable in somecountries, but even full-cost pricing may be insufficient to elirni-nate all excess demand if education really is a consumption good.In most countries, nonprice rationing of limited secondary schoolplaces will be necessary for many years to come.

Implementation of the above policies can be expected to im-prove resource allocation, increase the demand for labor, raise thelevels of skill and education of the labor force, and in the long runreduce the supply of labor. The degree of success, as measured byincreases in labor's supply price, will vary among countries, de-pending on their resource and other constraints. In some countriesthe optimal package of policies, even if it could be defined andimplemented, would not be enough to increase labor's supplyprice substantially; countries are poor not only because of inap-propriate policies. Nevertheless, whatever the magnitude of theimprovement, the recommended policies can be expected to yieldsome improvement in the return to labor and should therefore bepursued.

PART I

Statistical Overview

The process of economic development in the now developed coun-tries was characterized by a major transformation in the sectoralstructure of the labor force. As shown in table 1, the share of thelabor force employed in agriculture declined from more than55 percent in 1880 to about 20 percent in 1960. In addition toa corresponding increase in the total share of the nonagriculturallabor force, the share of services expanded in relation to that ofindustry; thus in 1880, 24 and 20 percent of the labor force werein industry and services respectively compared with 36 and 41percent in 1960.1 Clark (1957) has attributed this pattern ofstructural transformation to underlying changes in the composi-tion of demand associated with increasing incomes and to inter-

sectoral variations in the rate of growth of labor productivity.In short, Clark argued that as income per capita increases, "therelative demand for agricultural products falls all the time, and. . . the relative demand for manufacture first rises, and then fallsin favor of services," and that "real product per man-hour inmanufacture . . . nearly always advances at a greater rate than realproduct per man-hour in other sectors of the economy" (Clark,1957, pp. 493-94). Together, the two tendencies adequately ac-

count for the observed change in the structure of the labor force.2

1. The statistics reported in this paragraph and table 1 are from Bairoch and Limbor

(1968). As the authors make clear, the data, drawn from a variety of sources, are subject

to considerable margins of error and should be used only to indicate broad trends. The

details of estimation and the sources used are reported fully in Bairoch and others

(1968). For this analysis, agriculture also includes forestry, hunting, and fishing; industry

covers mining and quarrying, manufacturing, construction, and utilities; and services

covers commerce, transport, storage, communications, and services proper.

2. Clark's analysis is essentially confirmed by the subsequent study undertaken by

Kuznets (1966).

11

12 Statistical Overview

Table 1. Sectoral Structure of the Labor Forcein Developed and Developing Countries, 1880-1960(percentage of total labor force)

Sector 1880 1900 1920 1930 1950 1960

AgricultureDevelopingcountnesa n.a. 77.9 77.6 76.6 73.3 70.7Developed countriesb 56.2 48.1 39.9 36.2 30.7 22.9

IndustryDeveloping countries n.a. 9.8 9.9 10.0 9.9 11.5Developed countries 24.1 28.7 31.3 30.5 32.9 36.0

ServicesDeveloping countries n.a. 12.3 12.5 13.4 16.7 17.8Developed countries 19.5 23.3 28.8 33.3 36.5 41.1

n.a. Not available.Note: All estimates are subject to considerable margins of errors.a. Developing countries include the countries of Africa except South Africa; Latin

America; Asia with the exception of Japan, China, the Democratic Republic of Korea,Mongolia, and North Vietnam; and Oceania with the exception of Australia and NewZealand.

b. Developed countries include Japan, Australia, New Zealand, South Africa,Canada, the United States, and countries in Western Europe.

Source: Bairoch and Limbor (1968), tables IV and VL

The recent historical experience of the now developing COUnI-tries, however, is different in two respects. First, agriculture ac-counts for a much larger, albeit declining, share of the total laborforce; table 1 reveals that as late as 1960 agriculture still ac-counted for more than 70 percent of the labor force.3 Andsecond, within the nonagricultural sector, services have con-sistently accounted for a considerably larger proportion of thelabor force than has industry. For example, in 1950 services emn-ployed 63 percent of the nonagricultural labor force comparedwith 3 7 percent in industry. Table 1 shows that the share of thelabor force in services in the developing countries in 1960 wassimilar to that of the developed countries in 1880. A more de-tailed breakdown of the labor force, shown in table 2, revealsclearly that the distribution of labor within services as well as thetotal share of the labor force in the service sector in the develo,p-ing countries of 1960 are similar to those of the developed coun-tries in 1880. There are marked differences, however, with respect

3. A comparable division of the labor force between agriculture and nonagriculturewas recorded in the developed countries of Western Europe and North America arotnd1800 (Bairoch and Limbor, 1968, p. 325).

Statistical Overview 13

Table 2. Sectoral Distribution of the Labor Forcefor Developed Countries, 1880, and Developing Countries, 1960(percent)

Developed Developingcountries, a countries,a

Sector 1880 1960

Agriculture 56.2 70.7Industry 24.1 11.5

Mining and quarrying 1.7 0.6Manufacturing 18.8 8.9Construction 3.6 2.0

Services 19.5 17.8Commerce 5.0 5.9Transport, storage,

and communications 2.8 2.2Other services 11.7 9.6

a. Defined as in table 1.Source: Bairoch and Limbor (1968), tables IV and V.

to their industrial labor forces: whereas the developed countrieshad almost 25 percent of their labor force in industry in 1880,the developing countries had less than 12 percent in 1960. Thusthe main structural difference lies in the relatively immaturedevelopment of the industrial sector in general and manufacturingin particular in the developing countries of today. From table 2it can be seen that a transfer of 10 percent of the labor force indeveloping countries from agriculture to manufacturing wouldyield a sectoral distribution almost identical to that of the de-veloped countries in 1880.

The relatively small proportion of the labor force in industry isoften regarded as a failure of the development process by thosewho consider agriculture and services to be low-productivitysectors. 4 Moreover, many of the developing countries are alsoexperiencing unusually high rates of open unemployment. Anextensive study of the data available in 1970 indicates rates ofurban unemployment in excess of 10 percent in several developingcountries in Asia, Africa, and Latin America (Turnham, 1971).

These high rates of unemployment, with large numbers ofworkers remaining in the low-productivity sectors, are generally

4. Services are not necessarily a low-productivity sector; see chapter 1 0.


attributed to the failure of the high-productivity industrial sectorto provide adequate employment opportunities. 5 This sectionpresents a statistical overview of these issues with the specificobjectives of both assessing their dimensions and identifying theirunderlying causes. The analysis proceeds by means of a compari-son initially between developed countries circa 1900 and develop-ing countries circa 1960 and then among groups of developingcountries today.' The first comparison pinpoints the majorfactors which could account for the differences in the structuralchanges experienced by developed countries historically and bydeveloping countries currently, while the second comparisonemphasizes the variation of experience among developing coun-tries. The available evidence on unemployment is then examined,and the analytical significance of different concepts of under-employment is discussed.

5. This view has been expressed by, among others, Baer and Herve' (1966) and Mora-wetz (1974).

6. It is not claimed that the years chosen necessarily correspond to similar stages ofdevelopment or industrialization. Indeed, differences in the overall level of developmentare treated as potentially important factors underlying the observed differences in therates of structural transformation of the labor force.

2

A Historical Comparison

Much can be gleaned from a comparison of the industrializationexperience of the now developed countries with the currentsituation of today's developing countries. The main lessons emergenot from the similarities of experience but from the major con-trasts. On the supply side, the evidence reveals marked differencesin population growth rates and educational attainments. As aresult, today's development efforts must contend with high ratesof labor force growth, increasingly better educated new entrantsto the labor market, higher dependency ratios, and rapid rates ofurbanization. And on the demand side, the high-productivitysector in today's developing countries has several characteristics-especially its much faster growth of output and productivity,and its relative skill intensity-that differ noticeably from thehistorical experience of the developed countries. These differencesare documented below.

Factors Operating on the Supply Side

Table 3 records growth rates for total population, labor force,and urban population for developing and developed countriessince 1800. The single most important conclusion to be drawnfrom this table is that the developing countries are experiencingpopulation growth rates three times as large as those encounteredby the developed countries. Thus, throughout the nineteenth cen-tury annual population growth was only 0.8 percent in developedcountries compared with 2.4 percent in developing countries for1950-70. A population growing at an annual rate of 0.8 percentdoubles in eighty-seven years; a population growing at 2.4 percenta year doubles in only twenty-nine years.

Different population growth rates have different implicationsfor labor force participation. As a result of the low birthrates and

15


Table 3. Average Annual Growth Rates of Population,Labor Force, and Urbanization in Developingand Developed Countries, 1800-1970(percent)

Item 1800-1900 1900-50 1950-70

Total populationDeveloping countriesa 0.4 1.1 2.4Developed countriesb 0.8 0.8 1.2

Labor forceDeveloping countries (0.4) 0.8 1.7Developed countries (0.9) 0.7 1.1

Urban population 1850-1920 1920-60

Developing countnes n.a. 4.0Developed countries 2.5 1.9

n.a. Not available.Note: AU estimates are subject to considerable margins of errors, especially those in

parentheses.a. Defined as in table 1.b. Defined as in table 1 with the inclusion of the U.S.S.R.Source: Bairoch (1973), tables 1, 2, and 6.

deathrates in the developed countries, for example, their popula-tion has been aging. This, together with the extension of retire-ment schemes and the rise in school attendance rates, has led toa declining participation rate. The decline, however, has beenslight: from 45 percent in 1900 to 40 percent in 1960. In thedeveloping countries, however, low mortality rates are coupledwith extremely high fertility rates and a consequent broadening ofthe base of the age pyramid (see table 4). While variation amongdeveloping countries is marked, the overall result has also been adecline in the participation rate from 43 percent in 1900 to 38percent in 1960, reflecting the increasing share of inactive childrenin the total population.'

The declining participation rates during the twentieth centuryare reflected in growth rates of the labor force (shown in table 3),which are consistently below the corresponding population growthrates. Nevertheless, during the 1950-70 period the annual rate of

1. Bairoch and Limbor (1968), table 1. Participation rates in the developing countriesare subject to considerable margins of error, mainly as a result of differences among coun-tries in the treatment of unpaid family workers, especially females. This point is examinedbelow (see chapter 3).

A Historical Comparison 1 7

Table 4. Age Structure of the Populationin Developed Countries, circa 1900,and Developing Countries, circa 1960(percent)

Developed Developing* countries,a countries,b

Age at last birthday circa 1900 circa 1960

0-14 30.9 42.115-24 17.9 18.725-44 28.9 24.645-64 16.8 11.365+ 5.5 3.3Dependency ratioC 0.57 0.83

a. The developed countries and dates of observation are: United States, 1919-21;Belgium, 1900; France, 1899-1903; Netherlands, 1901; Sweden, 1903-07; United King-dom, 1901;Australia, 1911.

b. Defined as in table 1.c. The dependency ratio shows the number of dependents (those under 15 or over

65) per member of the population of working age (15 to 65).Sources: ILO (1977), vol. 5; and Keyfitz and Flieger (1968).

growth of the labor force in the developing countries was 1.7percent compared with a rate of about 0.9 percent experiencedby the developed countries throughout the nineteenth century.Thus, the developing countries have to cope with a rate of growthof the labor force almost twice as large as that of the developedcountries during their period of industrialization.

Apart from differences in the growth rates of the total popula-tion and the labor force, developing and developed countries alsohave very different patterns of change in the spatial distributionof their populations. Froml850 to 1920 the urban population inthe developed countries increased at an annual rate of 2.5 percent,more than three times faster than the rate of increase of the totalpopulation. In 1920-60, however, the urban population of thedeveloping countries increased at an annual rate of more than 4percent. During the decade of the 1950s it increased at the un-precedented rate of 5.1 percent, which, although considerablylarger than the corresponding rate for developed countries, isnevertheless only twice the growth rate of the total populationin developing countries.

A further consequence of the disparity in population growthrates is the difference in the age structure of the population. Table


4 reveals that the developing countries of 1960 had more than 60percent of their population below the age of twenty-five comparedwith less than 50 percent for the developed countries in 1900.Such a young population can be expected to have at least twoeconomic consequences. First, the dependency ratio 2 will belarger; thus, from table 4, everyone of working age in developingcountries has to support 0.8 dependents, whereas their counter-parts in developed countries had less than 0.6 dependents. Second,the new entrants to the labor market will outnumber those in theolder age brackets by an ever larger margin. For example, bothgroups of countries have roughly the same percentage of theirpopulation in the 15-24 age group, the age at which workers firstenter the labor market, but in the developing countries the shareof the population in the 45-64 age group is only 70 percent o[that in the developed countries. It follows that the expansion ofjobs must be much faster in developing than in developed coun-tries if the new entrants to the labor force are to be fully em-ployed.

This last point is, of course, simply another way of saying thatthe rate of growth of the labor force in today's developing coun-tries exceeds that formerly experienced by developed countries.This fact takes on added significance, however, when it is relatedto the rapid growth of educational facilities in developing coun-tries. The evidence in table 5 reveals that in 1900, 15 percent ofthe population of the developed countries attended primaryschool. Compulsory primary education became more or lessgeneral toward the end of the nineteenth century, so that rates ofexpansion (1.6 percent) began to reflect population growth. Inthe developing countries, however, only 8 percent of the 1960population attended primary school, but the annual rate of ex-pansion was more than 5 percent. At the secondary level the situa-tion is very different: although only 0.4 percent of the developedcountries' population attended secondary school in 1900, comi-pared with 1.6 percent in the developing countries of 1960, theirannual rates of expansion (8.0 percent) were very similar. Primaryeducation in the developing countries, therefore, has been increas-

2. The dependency ratio shows the number of dependents (those under 15 or over 65)per member of the population of working age (15 to 65).

A Historical Comparison 19

Table 5. Educational Attainment and Growth Ratesfor Developed Countries, circa 1900,and Developing Countries, circa 1960

Item Primary School Secondary School

Percentage of population attending

Developed countries,19ooa 15.0 0.4

Developing countries,1960b 8.1 1.6

Average annual rate of expansionin attendance

Developed countries,1890-1900C 1.6 8.3

Developing countries,1960-70b 5.4 8.4

a. The developed countries in this table include Japan, Sweden, Italy, France, Nor-way, the United Kingdom, the United States, the Netherlands, and Belgium.

b. All countries with GDP per capita less than US$2,000 in 1975, except countrieswith populations of less than 1 million and centrally planned economies.

c. As in note a. The period covered for Italy is 1901-11, and for the Netherlandsand Belgium, 1900-10.

Sources: Kaser (1966); World Bank data; and World Bank (1980), Annex 2.

ing more rapidly but from a lower base than in the developedcountries, whereas secondary education has been growing at thesame rate but from a higher base.

Clearly, the rapid expansion of education in the developingcountries must be reflected in an increased number of educatedentrants to the labor market. It follows that not only are first-time entrants to the labor market much more numerous thanthose withdrawing from the market, but also they have receivedmuch more formal education. In other words, while the quantity

of new jobs required is increasing as a result of population growth,the quality of the required jobs is also likely to be increasing asa result of the expansion in educational facilities. This is becauseeducated entrants to the labor market will expect jobs similar tothose held by comparatively educated workers in the recentpast. On the basis of this analysis, it is not altogether surprisingthat many developing countries are experiencing high rates ofunemployment for those with primary or secondary education(see table 21).


Table 6. Crude Estimates of Sectoral Value Addedand Productivity Growth Rates for Developed Countries,1880-1900, and Developing Countries, 1960-70(percent)

Average annual growth rate by sector

Groupand period Agriculture Industry Services Total

Value addedDeveloped countries,a

1880-1900 1.5 (1.7) 4.1 (1.8) 2.9 (1.0) 2.7 (1.1)Developing countries,b

1960-70 3.2 (1.4) 8.4 (3.8) 6.3 (4.1) 5.6 (2.4)

Labor productivityc

Developed rountries,a1880-1900 1.1 2.0 0.8 1.5

Developing countries,b1960-70 2.1 4.6 2.4 3.7

a. Developed countries include France, Germany, Italy, Sweden, the United King-dom, Canada, the United States, Japan, and Australia. The reported mean is the un-weighted average of individual country growth rates. Standard deviations are reportedin parentheses.

b. Developing countries include all those with a population of more than 20 millionin 1976 except Brazil, Vietnam, and Zaire (lack of data). The reported mean is theunweighted average of individual country growth rates. Standard deviations are reportedin parentheses. The corresponding annual growth rates computed from the World Bankglobal projection model are 2.7 percent for agriculture, 7.6 percent for industry, and 6.7percent for services (World Bank, 1979a).

c. Derived from growth rates of sectoral output and of sectoral labor force reportedin table 8. The growth rates of output reported in note b above and the labor forcegrowth rate reported in the note of table 8 yield growth rates of productivity of 1.5percent for agriculture, 4.6 percent for industry, and 2.2 percent for services. Thus.,although there is some variation, the broad pattern is very similar to that shown above.

Sources: Kuznets (1956), appendix tables 1, 3, 4, 9, 10, 14, 15, 17, and 18; Kuznets(1957), appendix table 2; and World Bank (1979a), table 2.

Factors Operating on the Demand Side

The rate of growth in employment depends on both the rateof growth in output and changes in average labor productivity.Table 6 presents the available evidence on sectoral output andproductivity growth rates. Because the data have been drawnfrom a variety of sources, they are not precisely comparable.Nevertheless, the regularity of growth rate patterns among theindividual countries suggests that the differences in reported


growth rates reflect real phenomena and not merely statisticalquirks. The table reveals that industrial output growth has beenmuch faster in the present developing countries (more than 8percent) than formerly in the developed countries (4 percent).Doubling output in the developing countries takes about tenyears; it took twenty years in the developed countries at theturn of the century.

Table 6 also shows that the rate of growth of labor productivityhas been considerably higher in the developing countries than inthe developed countries in all sectors. The data are consistentwith the view that the technology being adopted by developingcountries is much more advanced than that used by the developedcountries during the late nineteenth century. For example, thedeveloped countries achieved a growth rate for labor productiv-ity in industry of 2 percent, whereas the developing countriesare currently achieving a growth rate of more than 4 percent. 3

If the higher rate of growth in industrial labor productivityachieved by the developing countries can indeed be attributed toimproved technology, the qualitative composition of the in-dustrial labor force can be expected to differ from that of thedeveloped countries in the past; more advanced technologyrequires greater complements of higher quality labor. A compari-son of the occupational structure of the labor force in the twogroups of countries may not be very revealing, however, becauseof the dominance of the agricultural labor force in the developingcountries. For the purpose at hand, therefore, it may be moreappropriate to confine the analysis to Latin American countriesbecause the structure of their labor force is the most advanced.Table 7 presents a comparison between the United States in 1870and Latin America in 1950. The distributions of the broad occupa-tional groups adopted are roughly similar for the two regions atthe stated points in their respective developments. Of significance,however, is the difference in the changes in the composition ofthe labor force. Unlike the United States, in which the number ofblue-collar workers expanded rapidly during 1870-1920, Latin

3. As noted above, historical data must be treated with caution. Other studies, however,confirm the orders of magnitude reported here. For example, Phelps Brown (1973, table II)calculates annual rates of increase in industrial productivity of 2.2, 2.3, 0.36,and 1.6per-cent in Germany, Sweden, the United Kingdom, and the United States respectively circa1900.


Table 7. Occupational Structure of the Labor Forcein the United States and Latin America

Regionand period Unskilled Blue collar White collar

Percentage of labor force

United States, 1870 70.9 18.6 3.5Latin America, 1950 69.7 15.5 5.1

Changes over time(percentage points per decade)

United States,1870-1920 -4.9 +2.0 +2.01920-60 -5.1 +0.6 +3.1

Latin America,1950-61 -3.6 +0.4 +2.2

Note: "White collar" includes professionals, technicians, and administrative and cleri-cal workers; "blue collar" includes craftsmen, operators, transport and communicationsworkers, and miners; "unskilled" includes farmers, service and manual workers, andothers. Percentages do not add to 100 because of the exclusion of managers-owners andsalesmen.

Source: Ramos (1970), table 4-7.

America experienced a very low rate of expansion between 19 50and 1961. In fact, its expansion was more like the recent, ratherthan the historical, experience of the United States. One plausibleexplanation is that Latin America is bypassing the historicalphase of rapid expansion in the number of blue-collar workersbecause its industrialization is based on a very different tech-nology. The proportion of white-collar workers, however, hasexpanded quite rapidly in Latin America, reflecting the increaseduse of high-quality labor, not only in industry but also in services,especially in the public sector.

The historical evidence, then, indicates that the growth of theindustrial sector in both output and productivity has been muchfaster in the developing countries than was ever achieved in thedeveloped countries. Moreover, there is evidence from LatinAmerica, at least, to suggest that the developing countries requirea higher quality of labor than did the developed countries. Botlhthe rapid increase in productivity and the greater skill intensityof industry in developing countries are consistent with the viewthat technological developments have substantially changed thenature of the industrialization process.


Table 8. Average Annual Rates of Growthof the Labor Force by Sector for Developed Countries,1880-1900, and Developing Countries, 1960-70(percent)

Groupand period Agriculture Industry Services Total

Developed countries,a1880-1900 0.4 2.1 2.1 1.2

Developing countries,a1960-70 1.1 3.8 3.9 2.0

a. Defined as in table 1. For all developing countries reported in the World Develop-ment Indicators (World Bank, 1979a), the corresponding growth rates are 1.8 percentfor agriculture, 3.0 percent for industryi and 3.4 percent for services.

Sources: Bairoch and Limbor (1968), table IV; and ILO (1977), vols. 1, 3, and 5.

Industrial Labor Absorption in the 1960s

Against the background of dramatic changes on both the supplyand demand sides, this section presents a brief review of theperformance of industry in absorbing labor in the developingcountries during the decade of the 1960s. As will become ap-parent, different measures of labor absorption yield differentviews regarding the success of the developing countries in thisrespect in relation to that of the developed countries in the latenineteenth century. The data for this analysis are reported intable 8.

The percentage growth rate of industry's share in the totallabor force equals the difference between the percentage growthrate of the industrial labor force and that of the total labor force.From table 8 the share of the labor force in industry is seen to beincreasing more quickly in the developing countries of the 19 60s-1.8 percent a year-than it did in the developed countries in the1880s-0.9 percent a year. Thus, at least by this criterion, trans-formation of the structure of the labor force is currently proceed-ing in the developing countries at a faster rate than formerly in thedeveloped countries.

This result, however, is partly a consequence of the small shareof the labor force in industry in the base year for developingcountries: a low base means that even a small absolute increasetranslates into a large percentage increase. As an alternative mea-


sure, it may be appropriate to examine the increase in the in-dustrial labor force in relation to the existing total labor forcebecause this measure is independent of industry's initial share ofthe labor force.4 Since the share of the labor force in industry indeveloped countries circa 1880 was more than twice that ofdeveloping countries circa 1960 (see table 1), if the incrementalincrease in the industrial labor force in relation to the existingtotal labor force is to be the same in both cases, the growth rateof the industrial labor force in the developing countries must beat least twice that of the developed countries. Table 8 reveals thatthe growth rate of the industrial labor force in developing coun-tries was in fact 80 percent larger than that achieved historicallyby the developed countries. Thus, contrary to popular assertion,the industrial sector of today's developing countries has absorbedlabor at rates only slightly lower than those in the developedcountries of yesterday, despite its substantially lower initialshare of the labor force. Similarly, the relation between the rateof industrial labor absorption and the growth rate of industrialoutput in the developing countries is comparable to that of thedeveloped countries. From tables 6 and 8, the employmentelasticity (that is, the ratio of industrial labor force growth to thatof industrial output growth) is calculated to be 0.45 in thedeveloping countries compared with 0.51 in the developed coun-tries. The success of the developing countries in absorbing laborinto industry, despite that sector's initially low share of thelabor force, is thus a direct reflection of the very high rate ofindustrial output growth-more than twice that of the developedcountries (see table 6). In this respect, the developing countriesare compressing the development process: the growth rates ofindustrial output, productivity, and employment are all well inexcess of those achieved historically.

These relatively favorable assessments of the record have to, bebalanced against the observation that in relation to the annualincrement in the total labor force, the increment in the industriallabor force is substantially smaller in the developing countries

4. This measure can be deduced from tables 1 and 8 by multiplying the share of thelabor force in industry by the growth rate of the industrial labor force. For develcpingcountries the result is 0.44 percent a year compared with 0.51 percent for the developedcountries.


than in the developed countries.5 From tables 1 and 8, industryin the developing countries absorbed 22 percent of the incrementin the total labor force during the decade of the 1960s, whereasindustry in the developed countries absorbed 42 percent duringthe 1880s. In relation to the increment in the labor force, there-fore, the success of developing countries in absorbing labor in theindustrial sector is considerably less than that of the developedcountries. On the basis of this measure, it is frequently arguedthat, had the labor force in the developing countries grown at thehistorical rate of 1.2 percent a year instead of at the observedrate of 2.0 percent a year, industry's share of the labor forcewould have been substantially larger. There is, however, no reasonto suppose that if labor force growth is reduced everything elsewill necessarily remain the same.

The high growth rate of labor productivity in the developingcountries has also been advanced as a factor inhibiting the in-dustrial sector's ability to absorb labor. That is, had productivitygrown at the historical rate of 2 percent a year rather than at theobserved rate of 4.6 percent a year, the rate of growth of theindustrial labor force in the developing countries, it is argued,would have been 2.6 percent a year higher. A lower rate ofproductivity growth, however, does not necessarily mean a higherrate of labor absorption because output growth may be reduced;that is, rapid growth in productivity may be fully consistent withthe efficient allocation of resources.

Despite the success of developing countries by some criteria,critics have argued that high rates of growth in industrial produc-tivity and in the total labor force have limited industrial laborabsorption and thus retarded the structural transformation of thelabor force. As a result, the share of the labor force in industryhas not increased as quickly as it might otherwise have done.Accordingly, the next section presents a preliminary review of thefactors that determine the size of the industrial labor force andintroduces some of the issues addressed in more detail in sub-sequent chapters.

5. This measure is derived from tables 1 and 8 by multiplying the share of the laborforce in industry by the growth rate of the industrial labor force and dividing the resultby the growth rate of the total labor force.


Factors Deterniining Industry's Share of the Labor Force

There are at least three possible, mutually consistent explana-tions of why the industrial share of the labor force in developingcountries in 1960 was smaller than that of the developed countriesin 1880: differences in the level of general development in thetwo groups; differences in rates of capital accumulation and laborforce growth; and differences in the factors governing the relationbetween the composition of output and that of the labor force.These explanations are explored below.6

With regard to the first explanation, the smaller initial value ofindustry's share in the labor force may reflect a lower initial grossdomestic product (GDP) per capita and hence a relatively im-mature pattern of demand as hypothesized by Clark (1957). Itis difficult to test this assertion because of the problems of deriv-ing internationally and intertemporally comparable measures ofreal income. Bairoch (1975, table 52), however, suggests that thenational income per capita of the developing countries in 1960was approximately US$170 (at 1970 prices), whereas the nowdeveloped countries enjoyed a national income per capita of aboutUS$640 (also at 1970 prices) in 1900. On the basis of these ad-mittedly crude calculations, it may be concluded that the devel-oped countries of 1880 probably did have a higher per capita in-come than the developing countries of 1960, and this may implydifferences in the composition of demand.

The evidence in table 9 on the sectoral composition of valueadded is also consistent with the view that GDP per capita in thedeveloping countries of 1960 was less than that in the developedcountries of 1880, although, in this respect, the development ofinternational trade must be assumed to have weakened the linkbetween the composition of demand and that of output.7 To the

6. The arguments developed in this section are reviewed more rigorously by using athree-sector, two-factor model of international trade in the technical note appended to thischapter. Although the model confirms the points made in the text, it is important t:o keep inmind the simplicity of the model's structure when interpreting results. In particular, be-cause the analysis is conducted in terms of comparative statics, dynamic considerationsare excluded. For further discussion of these models, see Kemp (1969) and Komiya(1967).

7. This particular issue is addressed in the technical note, where it is shown that, if alow GDP per capita is assumed to be the consequence of a smaller stock of capital inrelation to the existing labor force, both the demand for and the domestic supply of in-dustrial goods will be lower than at a higher level of GDP per capita.


Table 9. Crude Estimates of Sectoral Value Addedand Productivity for Developed-Countries, 1880, and

Developing Countries, 1960

Groupand year Agriculture Industry Services

Composition of value added (percent)

Developed countries,a1880 33.0 24.2 42.7

Developing countnes,b1960 38.4 22.8 38.8

Relative productivityC

Developed countries,a

1880 0.6 1.0 2.2Developing countries,b

1960 0.5 2.0 1.6

a. As in note a to table 6.b. As in note b to table 6.c. Sectoral productivity in relation to economy-wide productivity.Sources: Kuznets (1957), appendix table 2; and World Bank (197 9a),

table 3.

extent that developing countries consume a larger proportion of

imported industrial goods and export a larger proportion of

agricultural output than did the developed countries, the composi-

tion of output will be affected accordingly (Berry, 1978).8 This

could be an additional explanation of agriculture's larger contribu-

tion and industry's smaller contribution to GDP in today's de-

veloping countries compared with yesterday's developed countries.

This in turn may reflect differences in the net barter terms of

trade (the ratio of export prices to import prices) confronting

developed and developing countries. Data to test this assertion,

however, are severely limited in both coverage and reliability.

8. Total trade (exports plus imports) is estimated to approximate 30 percent of GDPfor a group of eight developed countries-Canada, Denmark, France, Germany, Japan,Sweden, the United Kingdom, and the United States-in the late nineteenth century(Kuznets, 1967, appendix table 1) compared with about 45 percent for seventy-two de-veloping countries in or around 1965 (Chenery and Syrquin, 1975, table S3). For thedeveloped countries, primary commodities accounted for more than 90 percent of exportsonly in Denmark and Sweden, and manufactured goods accounted for more than 60 percentof imports only in Canada and Japan (Kuznets, 1967, table 9). In the developing countries,however, primary commodities accounted for more than 90 percent of exports in fifty-five out of seventy-four countries, and manufactured goods accounted for more than 60percent of imports in forty-seven out of sixty-one countries (World Bank, 1979a, tables9 and 10).


Bairoch (1975) presents data to show that the net barter terms oftrade for primary products in relation to manufactures may haveimproved by between 10 and 25 percent between 1872 and 1928.He also shows that several indexes available for 1926-29 to 1950-52 indicate a further improvement of between 15 and 25 percent.Finally, for 1950-70 Bairoch, using U.N. data, reports a declinein the net barter terms of trade of 12 percent. Thus, while theevidence, especially for the early years, must be treated withcaution, it is consistent with the differences in the sectoral com-position of output between developed and developing countriesshown in table 9.

Berry (1978) has also advanced several reasons the contri-bution of services to GDP in relation to that of industry is largerin the developing countries of 1960 than in the developed coun-tries of 1880. The most important causes Berry described arethe larger role of the public sector in many developing countriescompared with the developed countries of the late nineteenthand early twentieth centuries, the greater emphasis on the pro-vision of social services such as education (see table 4), and themore extensive reliance on international trade and the associa-tedneed for transport and commercial services. Berry's argumentswere applied to Latin American developing countries and do notseem to be especially relevant to an understanding of the statisticsreported in table 9, unless it is thought that, in the absence ofthese developments, and given the lower level of GDP per capita,the output of services would have been even smaller.

Differences between the rates of capital accumulation andlabor force growth in developing and developed countries (thesecond explanation) could contribute to the arguments of thepreceding paragraphs. If, because of rapid population growth,the ratio of the rate of capital accumulation to that of labor forcegrowth is smaller in the developing countries than in the developedcountries, the passage of time will increase the disparity betweencapital per worker in the two groups and limit the growth rate ofGDP per capita in developing countries. 9 Crude calculations of

9. Empirical verification of a negative relation between rapid population growth andthe growth rate of GDP per capita, however, has proved elusive. In a dynamic corntext,arguments have been advanced to support the view that rapid population growth can havepositive as well as negative implications for the growth of GDP per capita. The availableevidence and conflicting arguments are reviewed in chapter 15, which also includts a dis-cussion of models that treat population growth in a dynamic context.


the rate of capital formation in relation to the rate of popula-tion growth illustrate this point vividly. For ten developed coun-tries in the late nineteenth century, the ratio of gross capitalformation to the increment in the population was more thanseven times larger than the corresponding ratio for the develop-ing countries in the 1960s, despite similar rates of capital forma-

tion in relation to GDP.10 In part, this reflects the higher level ofGDP per capita in the developed countries, but it is also a productof the high population growth rate-2.4 percent a year-in thedeveloping countries compared with 0.8 percent a year in thedeveloped countries. These results suggest that rapid populationgrowth is a factor limiting the rate at which capital per workercan be increased; developing countries have not been able toincrease their rates of capital accumulation to match their higherrates of population and labor force growth."

With respect to the third explanation, the evidence on relativelevels of sectoral productivity (also shown in table 9) suggeststhat the relation between the structure of output and that of thelabor force has been substantially modified. Compared with theirrespective economy-wide levels of productivity, industrial produc-tivity is higher in the developing countries than it was formerly inthe developed countries, whereas the reverse is true of agricultureand services. As suggested earlier, one possible interpretation isthat developing countries are bypassing the phase of industrializa-tion that relies most heavily on unskilled labor because of tech-nological advances that occurred during the prior industrializationof the developed countries and because of the greater availabilityof skilled manpower.

10. Gross capital formation in relation to the increment in the population is calculatedfrom information on the share of gross capital formation in GDP, GDP per capita, andpopulation growth rates. In reverse order, population growth rates are taken from table 3,and GDP per capita from the discussion at the beginning of this section. GDP per capitafor developed countries in 1880 is derived by application of the GDP per capita growthrate of 1.9 percent a year (see tables 3 and 6) to the 1900 GDP per capita of US$640.This method yields a level of GDP per capita of about US$440 in 1880. Finally, the un-weighted average for the proportion of gross domestic capital formation in GDP is esti-mated to be 0.15 (0.04) for ten developed countries-Australia, Canada, Denmark, Ger-many, Italy,Japan, Norway, Sweden, the United Kingdom, and the United States-in1850-1915, and 0.16 (0.07) in eighty-four developing countries for 1960. Standard devia-tions are reported in parentheses. Data for developed countries are from Kuznets (1961,table 1) and for developing countries from World Bank (1979a, table 5).

11. If industry is assumed to be more capital intensive than either agriculture or ser-vices, an increase in the labor force in relation to the capital stock reduces GDP percapita and industrial output and employment (see the technical note to this chapter).


In an open economy, however, labor-saving technical progressin the industrial sector is likely to affect the size and composi-tionof international trade, and by allowing increased output in theform of import substitutes or additional exports, it may imply theuse of more rather than less labor in industry. Technical or eco-nomic restrictions on the economy's capacity to expand industrialoutput, however, increase the likelihood that labor-saving techni-cal progress will lead to a lower labor input and a higher level oflabor productivity. For example, technical restrictions on thedegree of factor substitution within sectors can limit the scopefor increasing industrial output in response to labor-saving techni-cal advances. Similarly, if the industrial labor market is subject towage legislation and if distortions in product markets for tradablegoods limit the development of export and efficient import-substituting industries, the potential for increasing industrialoutput is reduced." 2 In either event, provided the scope forexpanding output is limited, entrepreneurs can be expected torespond to labor-saving technical improvements by reducing laborinput and thereby increasing labor productivity.

If the expansion of industrial output is constrained by technicalfactors, there is no reason to suppose that the allocation of re-sources is inefficient. But if distortions in factor and productmarkets are constraining the expansion of industrial output, thereis every reason to believe that resources are being allocated in-efficiently. In this event, the high rates of productivity growthmay indicate that labor absorption has been restricted and thatimprovements in resource allocation would increase both in-dustrial output and industrial labor input.

Improvements in the quality of the industrial labor force canalso be assumed to have contributed to the increase in labor'sproductivity in industry. If, as the Latin American experiencesuggests, industry in the developing countries of today requireslarger inputs of skilled labor than was the case in the developedcountries of 1880, productivity in terms of "unskilled laborequivalents" could be more or less the same in the developingand the developed countries, and yet productivity in terms oflaborers would be substantially higher in the former than in thelatter group. Again this difference could be fully consistent with

12. These points are established in the technical note to this chapter.


the efficient allocation of resources in developing countries,provided the markets for both skilled labor and the services oftraining and education are thought to be free of distortion. Atthe same time, a sudden and large increase in the availabilityof educated labor can be expected to exert unusual pressure onthe labor market. Any inflexibility in this market during such aphase of dramatic transformation and development would leadto serious consequences for the employment of educated laborat least in the short run.

Much of the discussion in Parts II, III, and IV further elaboratesthe extent to which the factors identified in this chapter (otherthan the technical characteristics of production and the generallevel of development) may have contributed to the relativelymodest development of the industrial labor force in developingcountries. In particular, chapters 6, 7, and 8 assess the extent towhich labor markets operate efficiently; chapters 11, 12, and 13examine the significance of distortions in product and nonlaborfactor markets; chapter 15 explores the justification and scope forpopulation policies; and the role of education and training in thedevelopment process is reviewed in chapter 16.

Technical Note

To illustrate the role of the three factors-the general levelof development, unusually high rates of labor force growth inrelation to the rate of capital accumulation, and rapid rates oftechnical progress-identified as shaping the structure of the laborforce, consider the following model of a three-sector, open econ-omy. 3 When linear, homogeneous production functions areassumed in each sector, the first-order conditions of profit maxi-mization require that

Pifi =P2 f2 =P3 f3 (1)

Pi (fA - ki f)=p 2 (A - k2 f')=p 3 (f3 - k3f3) (2)

where the Pi are output prices, fi describes the technologicalrelations between output per unit of labor (L) and input of capi-tal (K) per unit of labor, f is the marginal product of capital in

13. For further discussion of these models, see Kemp (1969) and Komiya (1967).


the ith sector, and ki equals KiLi .14 Equation 1 imposes the condi-

tion that the marginal product of capital be equal in all uses, whileequation 2 imposes the corresponding condition for the marginalproduct of labor.

Sectors 1 (agriculture) and 2 (industry) are assumed to producetradable commodities, the prices of which are fixed in worldmarkets. The output of sector 3 (services), however, is not tradedinternatonally; its price is determined within the domestic econ-omy. Since the technological relations (f;) are functions ofcapital-labor ratios (ki) only, equations 1 and 2 provide fourindependent equalities that can be solved for the ki and p3, theprice of the nontradable commodity.

Under competitive conditions, both factors of production arefully employed:

ELi = L (3)

I k.L. = K (4)i Z

where L and K are the endowments of capital and labor respec-tively. The supply and demand balance for the nontradable corn-modity requires that

L3 f 3 = D3 (I,Pi) i = 1, 2, 3 (5)

where L3 f3 is total output and D3 denotes demand for serviceswritten as a function of total income (I) and prices. Given that

I= XpiLifi (6)

equations 3, 4, 5, and 6 may be solved for the Li and I in termsof the ki (capital-labor ratios) andp 3 .

The model is completed by introducing the equilibrium condi-tions in the output markets for commodities 1 and 2. Since thesecommodities are traded internationally, supply and demandbalance is represented by

LI f1 - E = DI (I,pi) i = 1, 2, 3 (7)

and L 2 f2 +M=D 2 (I,pi) i= 1, 2, 3 (8)

14. Raw land is not treated explicitly. It is assumed that all available raw land is fullyused for agricultural purposes. Land-improving investments, however, are included in thedefinition of capital.


where E denotes agricultural exports and M industrial imports.Given that the derivation of the demand curves assumes that allincome is spent, z pi Di = I. Together with equations 5, 6, 7, and8 this last result ensures that the economy's external account isbalanced (that is, p1 E = P2 M). Equations 7 and 8 can be usedto solve for E and M, once the previous equations have beensolved. Because the level of exports and imports are not relevantto subsequent discussion, equations 7 and 8 are not referred toagain.

In the ensuing exercise in comparative statics, it is assumedthat k2 > k, and k2 > k 3 ; that is, industry is assumed to be morecapital intensive than both agriculture and services. If a lowerlevel of GDP per capita is equated with a smaller capital stock inrelation to the labor force, then a lower level of GDP per capitaand an unusually high rate of growth in the labor force in rela-tion to the rate of capital accumulation have a similar effect onthe structure of the labor force. That effect can be examined byinvestigating the consequences of an expansion in the labor forcein relation to the existing stock of capital. Accordingly, we firstexamine the effect of an increase in the labor force and then turnto that of a labor-saving technical improvement.

Labor Force Growth

Since equations 1 and 2 are functions of international prices(pi and p2) and technology, a change in the size of the laborforce does not affect the profit-maximizing conditions; there-fore, the capital-labor ratios (ki) and the price (P3) of the non-tradable commodity remain unchanged. Concern now centersexclusively on equations 3, 4, 5, and 6. Totally differentiating thissystem of four equations yields

I dLi= dL (9)

X k dLi ° (10)

f 3 dL 3 -D,d= (11)

e pithe dLta dI= b (12)

where dL is the change in the total labor force. The solution for


dL2 is given by

AL2 = ( 1 1iC3 63 AL (13)\ r2tY2

where C3 = p3 aD3 laI and is the marginal propensity to consumeservices, e3 = L3 a(L3 f3 )/(L3 f3 ) UL3 and is the elasticity ofoutput with respect to labor in the service sector, ir2 = L2 /L andis the share of labor in industry, A denotes percentage change,and ,i = 1 - (ki/k, ), i = 2, 3, and is a measure of relative laborintensity.

Given the assumptions with respect to labor intensity, 72 < 0-

It follows that A L2 5 0 as c3 e 3 73 5 1. If services are more capi-tal intensive than agriculture (k3 > k 1 ), then Y3 < 0 and AL2 isunambiguously negative. If, however, k3 < kI, then 0 < 73 < 1,and given the assumptions of constant returns to scale and positivemarginal products 0 < e 3 < 1. Thus, two elements (e3 and '3 ) ofthe term C3 e3 T3 are unambiguously < 1. The third term, C3 , isthe marginal propensity to consume services. Although Y ci mustequal unity, it does not necessarily follow that C3 < 1, since cl orc2 could be negative. Empirical evidence, however, suggests thatthis is highly unlikely for the broad aggregates of commoditiesconsidered here. For example, Lluch, Powell, and Williams (1977)present estimates of the marginal propensity to consume for ser-vices (personal care, transport, recreation, and miscellaneousservices) ranging from 0.266 for Greece to 0.499 for Puerto Ricowith an unweighted mean for nine developing countries of 0.344.It follows that, given the restrictions on 73 and e3 and the likelyrange of values for c3 , the term c3 e3 73 will almost certainlybe less than one and AL2 will be negative even if 73 > 0. More-over, since AlT2 = AL2 - AL and AL > 0, it may be concludedthat the share of the labor force in industry decreases as the totallabor force increases.

This result may be rationalized intuitively as follows. First, asa result of an increase in the labor force, total income (I) increasesby the product of labor's marginal revenue product and the in-crease in the labor force. Second, since all labor intensities and theprice of the nontradable remain unchanged, and since demand forthe nontradable is positively related to income, both output andemployment in services must increase. From equations 9, 10, I 1,and 12 we have dL3 = c3 e3 dL. If, as has been argued, 0 < C3 e3


< 1, the part of dL not absorbed in services must be absorbed ineither agriculture or industry. The problem is now exactly that ofanalyzing the impact of an increase in the labor force in the stan-dard two-sector, two-factor trade model (see Kemp, 1967). In thismodel, because labor intensities remain constant, the extra laborcan be absorbed only by an expansion of the labor-intensive sector(agriculture) and a contraction of the capital-intensive sector(industry). Thus, an increase in the labor force is associated withan increase in the labor force in agriculture and services and adecrease in that in industry.

Labor-Saving Technical Progress

To explore the implications of labor-saving technical progressin industry, we may rewrite the technological relation betweenoutput per unit of labor and capital per unit of labor in industryas

f2 =f 2 (k2/X)

where X is a shift parameter representing labor-saving technicalprogress and is initially set equal to unity. An increase in X allowsthe same level of output to be produced with less labor and thesame amount of capital.

To allow for this change, equations 1 and 2 must be rewrittenas

PI fl = P2 f2 = P3 f3 (14)

Pi (fi -k 1 fi)=P 2 (kf 2 -k 2 f2)=p 3 (f 3 - k 3 f) (15)

Because we are investigating the effect of a change in X, it can nolonger be expected that capital-labor ratios and the price of thenontradable will remain constant. Totally differentiating equations14 and 15 yields

p f, dk1 = P2 f2 dk2 - P2 f2"k2 dX = f3 dp3 + p3 f3"dk3 (16)

-Pl fi k, dkl = -P2 f2 k2 dk2 + (P2 f2 - P2 f2 k2 +PZf2"k 2 k 2 ) dX

= -p 3 f3 k3 dk3 +(f3 - k3 f3)dp 3 . (17)


Solving for Ak1 and Ap3 we obtain

U

Aki = X Ax i= 1, 3 (18)

Ak 2 = (1+ 2 k2 ) X (19)62 7Y2 ki

and tP3 = (I e3)y'3 AX (20)Y2

where ai fi (fi- kifi)

ki f- fi i

and is the elasticity of substitution in the ith sector. Given a> 0 and

72 < 0, Ak, and Ak3 are unambiguously negative. Ak2 , however,is negative only if G2 > e2 [1 - (k I /k 2 )] . Since values of aboutunity are frequently cited for a2,15 and since both e2 and1 - (k, /k 2 ) are less than unity, the presumption must be thatAk2 is negative. Finally, Ap3 is negative or positive dependingon whether -y3 is positive or negative; that is, on whether agri-culture or services is the more capital intensive.

Armed with this information, we can now reexamine thetotal differential of equations 3, 4, 5, and 6. Since X must beintroduced into equation 6 to allow for the effect of technicailprogress on total output (L 2 f 2 ) in sector 2, the total differen-tial is given by

E dL. =0 (21)

2' k dL + . L dk ° (22)

f3 dL 3 +L3 f3 dk3 - Dp dp3 - D dI= 0 '23)

15. See Morawetz (1976). Although the thrust of Morawetz's argument is the substantialrange of estimates for the elasticity of substitution, of the 64 estimates reported fer 18

industries in different countries, 53 equaled or exceeded 0.75 and 22 exceeded 1.0 (Mora-

wetz, 1976, table 1).


.p pifid Li + pi.f'L.dk.+f 3 L 3 dp 3 - dI (24)

=P2 L2 (jf2 -k 2 f2) dX.

The solution for AL 3 , the percentage change in the labor force inservices, is given by

AL 3 = (1-e3 ( 7373 + 2C3 ) eC 03 ] A(25)

where 73 = (Dp p3 /D3 ) + c 3 and is the pure substitution elasticityso that rq3 < 0. If _y3 > 0 (that is, if agriculture is more capital in-tensive than services) AL3 is positive. If Y3 < 0, however, the signof AL3 is indeterminate.

From equations 21, 22, and 25 the impact of technologicalprogress on the use of labor in industry is seen to be

ty 3 17 3 E T k .lAk.AL2 = 3 IT3 AL3 + 7 r A (26)72 IT2 r2 r2 k

Similarly, the impact on labor productivity (f2 ) is

Af2 = { 1- a2 / [1- (k1 /k2 )] } Ax. (27)

Since the effect of technical progress on industrial output is sim-ply the sum of the change in labor input and productivity, equa-tions 26 and 27 allow an assessment of the impact of technologi-cal improvement on industrial output, labor use, and productivity.

On the assumptions that Ak2 > 0 and that agriculture is morecapital intensive than services (that is, 73 > 0), equation 26 showsthat industrial labor use will increase with labor-saving technicalprogress. In the event that services are more capital intensive thanagriculture (that is, 73 < 0), it is necessary to examine equation 26


in more detail. Using equations 18, 19, and 25, equation 26 maybe rewritten as

+37T3 (1e3) / 7373 1T2C3\AL2 7 - + IAX

tY2 7rl 2 7rA3

2 3 6 [3 + (1-e3 ) kl A

+ E ri ki Aki i= 1, 2. (28)y 2 ir 2 k,

Since 73 I 72 r2 /1T3 c 3 , and 713 are all less than unity either byassumption or empirical observation,"6 the element of the secondterm in parentheses represents the difference between the product oftwo numbers, both of which are less than unity, and the product ofanother two numbers, which are again less than unity. Whether theterm is positive or negative is unclear; that the term will be absolute-ly small is without doubt. Since the remaining two terms of equation28 are positive, it may be concluded that, provided the marginalpropensity to consume services (C3 ) remains small in relation to thecompensated own-price elasticity for services (R3) and the elasti-cities of substitution (a,), industrial labor use can be expected toincrease even if y3 < 0.

From equation 27, labor productivity decreases if 02 > 1 -(k 2 /k I ). Since 1 - (k2 /k, ) < 1, this condition is probably usuallyfulfilled. Inspection of equations 19, 26, and 27 reveals that in-dustrial output (L2 f2) will increase provided 73 > 0, but unless theterm containing C3 is small in relation to the other terms in equation28, or labor productivity increases as a result of technical progress,industrial output may decline if 73 < 0.

The intuitive rationalization of these results may be developedas follows. First, since returns to scale are constant, total outputexactly equals total costs if factors are costed at their marginalproducts. Technical progress, however, will reduce costs per unit ofoutput in sector 2. Factors must be shifted, therefore, to secure an

16. Values ranging from -0.3 to -0.6 are reported for 13 by Lluch, Powell, and Wil-liams (1977, tables 3-11 and 3-13).


increase in costs in sector 2 in relation to sector 1. If sector 2 isrelatively capital intensive (k2 > k1 ), this can be achieved by in-creasing the "cost," or marginal product, of the factor (capital)used intensively in sector 2 in relation to the "cost" of the factor(labor) used intensively in sector 1. An increase in the ratio of themarginal product of capital in relation to that of labor is achievedby reducing capital intensity in sector 2. Second, since the ratio ofthe marginal product of labor in sector 1 in relation to that in sector2 must equal the ratio of internationally fixed output prices, andgiven a similar requirement for the ratio of marginal products ofcapital, the increase in capital's marginal product in relation to thatof labor noted above must also occur in sector 1. This again requiresa reduction in capital intensity. Third, a similar point applies to sec-tor 3, except that in this case both output price and capital intensitycan adjust to restore the intersectoral equivalence of marginalrevenue products. The price of services increases or decreases de-pending on whether services are more capital intensive than agri-culture.

Fourth, total income changes as a result of two possibly compet-ing forces: the technical improvement in sector 2 increases totalincome whereas the change in the price of services reduces totalincome if it is negative and increases total income if it is positive.The effect on the demand for services is thus ambiguous. If theprice of services increases, total income definitely increases; as aresult, the demand for services is encouraged by the increase in in-come and discouraged by that in price. Alternatively, if the priceof services falls, then it is possible that total income also falls, andagain the demand for services is subject to conflicting forces. Thedemand for labor by the service sector is also influenced by thereduction in capital intensity. If this latter effect dominates, the ef-fect of technical progress on the output of services is immaterial.

Fifth, if the labor input into services does indeed increase, thenlabor available for agriculture and industry is reduced. Given theincreased labor intensity in both sectors, it follows immediatelythat the labor-intensive sector (agriculture) must contract and thecapital-intensive sector (industry) must expand in order to rationthe available labor resources between the competing uses. As aresult, employment in industry will increase. Because the totalavailable labor force remains constant in this analysis, it may beconcluded that technical progress in industry is probably associated


with an increase in the shares of the labor force in industry andservices and a decrease in the share in agriculture.

If it is now assumed that the scope for altering factor propor-tions within sectors is limited (that is, if vi 0), then

AL2 rY3T3 (1-C 2 ) (137y3 + 372C3 - 1 (!29)L 72 7r2 7Y2 7r3 1-(k 1 /k2)

and Af2 . AX. (30)

In the analysis of equation 28 it was argued that AL2 wouldprobably be positive because the (possibly) negative first termwould be more than offset by subsequent positive terms. Inequation 29, however, the first term remains the same, whereasthe second term is negative and greater than unity. It may beconcluded that AL2 is negative. But labor productivity can nowbe expected to increase. As a result, it is not possible to concludewhether industrial output increases or decreases; it is clear, how-ever, that the difference between the change in output whensubstitution possibilities are great and the change when they arelimited is positive. Thus, restrictions on the scope for factorsubstitution increase the likelihood that industrial labor use willdecrease, that labor productivity will be increased, and thatindustrial output expansion will be smaller or even negative.

Alternatively, output may be restricted by economic factors,.For example, assume that imports of industrial commodities areprohibited, and that domestic demand is not responsive to changesin either income or price, so that

Xf2 L 2 =D2 - (31)

Assume further that wage legislation effectively determines thereal wage rate in the market for industrial labor; that is

(w/p 2 )= Xf2 - k2 f2 (32)

Solving equations 31 and 32 for A L2 and Af2 yields

AL 2 = - (102) AX (33)

and Af 2 (1- a2 2 ) X- (34)


That is, with output constant, labor-saving technical progressreduces industrial labor use and increases labor productivity ifthe elasticity of substitution is less than unity." 7 The reverse holdsfor an elasticity greater than one.

17. Of the 64 elasticities reported by Morawetz, only 22 exceed unity (Morawetz, 1976,table 1).

3

A Cross-sectional Analysis

Apart from historical differences between developed and develop-ing countries, variation among the developing countries is alsosignificant. The statistical overview continues, therefore, with anexamination of differences among broad groups of developingcountries with respect to such factors as population growth,labor force structure, and levels of education, productivity, andreal wages. Countries are grouped either by region or by GDP

per capita depending upon the availability of data. In general, thedifferences among groups of developing countries are less markedthan those emerging from the historical analysis; nevertheless,significant differences are observed in the growth rates of thelabor force, in the industrial, educational, and occupationalstructures of the labor force, and in levels and growth rates ofsectoral productivity. Regional differences in growth rates of realwages are also identified, but the underlying data are severelylimited both in coverage and reliability.

Population and Labor Force

The regional population growth rates reported in table 10 forthe period from 1960 to 1970 lie between 1.4 percent in southernEurope and 2.9 percent in East Asia.' The main determinant offuture population growth is the expected level of fertility. Mortal-ity decline will not be an important factor in future populationgrowth. In parts of Latin America and East Asia mortality ratesare already approaching those of the developed countries. Inlow-income Asian countries mortality is relatively higher, but,given its current level, future declines will have a smaller impacton population than in the past. Although mortality remains a

1. This and the subsequent paragraph are based on Cassen (1978).

42

A Cross-sectional Analysis 43

major demographic problem in Africa, prospects for a rapiddecline are not encouraging.

With respect to fertility, declines have occurred in East Asia(for example, Malaysia, Taiwan, and Singapore), in some low-income countries in Asia (India, Indonesia, and Sri Lanka), and inLatin America (Argentina, Colombia, Uruguay, and Chile). Manyof the remaining Asian and Latin American countries andvirtually all countries in Africa (the main exceptions being theArab Republic of Egypt and Tunisia) have experienced eitherconstant levels of fertility or modest declines.

Labor force growth is determined mainly by past populationgrowth, the lag being of the order of fifteen years. It follows thatthe increasing rates of population growth in sub-Saharan Africa,low-income Asia, and the Middle East and North Africa shown intable 10 have yet to be reflected in their respective labor forcegrowth rates. The recent rates of labor force growth reported forsub-Saharan Africa (2.1 percent), low-income Asia (1.7 percent),and the Middle East and North Africa (1.9 percent), although highby historical standards, will be surpassed in the 1980s and 1990s,as will the very high rates (2.4 percent) reported for Latin Americaand the Caribbean.

Changing rates of labor force participation may mnodify thisoutcome, but, as shown in table 10, the observed and projecteddecreases in participation rates are not great. 2 Regardless of thelevel of development, early all males in the 25-55 age groupare in the labor force.3 In the early stages of economic growthand industrialization there is a fairly rapid decline in the partici-pation rates of those under 20 or over 65, but subsequent declinein the male crude participation rate is slight.4 Ranking countriesaccording to an index based on energy consumption per capita andthe share of the labor force in nonagricultural activities, Durandreports that the participation rates for the 15-19 age group and forthose over 65 are 75.5 and 63.4 percent respectively in the leastdeveloped quintile of countries (according to his index), compared

2. For extensive surveys of participation rates in developing countries, see Durand(1975), Standing (1978a), Denti (1968), and Hartman (1977).

3. Rates in excess of 95 percent are recorded almost universally for males between30 and 44 (Durand, 1975, p. 148).

4. The crude participation rate is determined by the joint influence of age-specificparticipation rates and the age structure of the population.

Table 10. Population and Labor Force by Region, 1950-2000

1990-Region 1950 1960 1970 1980 1990 2000 1950-60 1960-70 1970-80 1980-90 2000

Population (millions) Population growth rate (percent)

Low-incomeAsiaa 589.0 716.4 909.2 1,134.5 1,405.9 1,694.2 2.0 2.4 2.2 2.2 1.9

Sub-SaharanAfricab 169.3 212.2 272.0 359.9 480.1 613.5 2.3 2.5 2.8 2.9 2.5

Middle East andNorth Africac 74.1 94.1 121.1 159.1 205.6 255.4 2.4 2.6 2.8 2.6 2.2

East Asia andPacificd 80.5 105.8 139.6 175.2 214.3 248.6 2.8 2.8 2.3 2.0 1.5

Latin Americaand Caribbean 154.4 207.9 273.0 354.6 454.3 556.0 3.0 2.8 2.6 2.5 2.0

Souuileril Europe 83.1 96.6 iii.2 128.6 i44.9 160.2 i.5 i.4 1.5 1.2 1.0All developing

countries 1,150.4 1,443.0 1,826.1 2,311.9 2,905.1 3,527.9 2.3 2.4 2.4 2.3 2.0

Lebor force (millions)' Labor force growth rate (percent)

Low-incomeAsiaP 259.4 297.7 351.4 428.8 523.8 623.2 1.4 1.7 2.0 2.0 1.9

(44) (42) (39) (38) (37) (37)Sub-Saharan

Africab 78.5 93.7 115.4 143.1 182.5 235.4 1.7 2.1 2.2 2.5 2.6(46) (44) (42) (40) (38) (38)

Middle East andNorth Africac 22.9 26.9 32.6 42.2 56.0 70.0 1.6 1.9 2.6 2.9 2.2

(31) (29) (27) (27) (27) (27)East Asia and

Pacificd 35.5 43.8 55.5 71.7 89.6 108.9 2.1 2.4 2.6 2.3 2.0(44) (41) (40) (41) (42) (44)

Latin Americaand Caribbean 54.2 67.1 84.8 110.2 147.9 192.8 2.2 2.4 2.7 3.0 2.7

(35) (32) (31) (31) (33) (35)Soutiern Europe 37.5 42.0 45.3 51.7 58.6 65.9 1.1 0.8 1.3 1.3 1.2

(45) (43) (41) (40) (40) (41)All developing

countries 488.0 571.2 685.0 847.7 1,058.4 1,296.2 1.6 i.8 2.2 2.2 2.0

a. Includes Afghanistan, Bangladesh, Bhutan, Burma, India, Indonesia, Cambodia, Laos, Maldives, Nepal, Pakistan, Sri Lanka, and Vietnarn.b. Excludes the Republic of South Africa.c. Excludes capital-surplus oil exporters.d. Excludes Japan.e. Figures reported in parentheses are participation rates.Source: World Bank data.


with corresponding rates of 61.6 and 29.5 percent in the mostdeveloped quintile.5 Weighting age-specific activity rates by the1960 age structure of the world population, Durand shows thatthe male standardized participation rate declines from 81.0 per-cent for the least developed quintile of countries to 73.1 percentfor the most developed quintile, the unweighted mean for allcountries (100) being 76.8 percent.

Secular trends in female labor force participation rates areless easily discerned, mainly because cross-sectional comparisonsreveal enormous differences. In part, this may reflect statisticaldeficiencies rather than real differences. For example, the Algeriancensus of 1966 reported 23,315 female agricultural workers,whereas the census authorities estimated that an additional 1.2million females were actually engaged in agricultural work. The1954 census, in fact, reported a female participation rate of 25.2percent compared with the 1.8 percent reported in 1966. In-clusion of the "missing" 1.2 million females increases the 1966figure to 21.7 percent.6 Some of the very low rates reported forMoslem countries may well reflect underenumeration.

Standing suggests a fourfold classification of countries accord-ing to urban and rural female labor force participation rates:

Arab countries: low rates in both urban and rural areasLatin America: low rural rates and high urban ratesAfrica and India: high rural rates and low urban ratesSoutheast Asia: high rural and urban rates.

With development, low and high rates tend to converge. The netresult in developing countries as a group has been a very modestdecline since 1945 in female participation rates (Standing, 1978a).

Recent historical experience thus suggests that, although themale participation rate may decline further, the impact of changingparticipation rates on the growth rate of the labor force will benegligible compared with that of population growth. The resultingincrements in the labor force (shown in table 10) are unprece-dented. Between 1970 and 2000 the labor force in low-income

5. The country grouping is described in Durand (1975, appendix H). The leastdeveloped quintile includes such countries as Pakistan, Zaire, Bolivia, and Sierra LeUne,while the most developed quintile includes the United States, Canada, and Denmarkamong others. Observations are for 1960.

6. Durand (1975, appendix G) provides a number of such illustrations.

A Cross-sectional Analysis 4 7

Asia is projected to increase by more than 270 million to approxi-mately 620 million; although less daunting, the increases in sub-Saharan Africa (120 million) and Latin America and the Caribbean(110 million) are nevertheless sizable.

Sectoral Structure of the Labor Force

Changes in the sectoral structure of the labor force between1950 and 1970 are reported in table 11. In 1950 low-incomeAfrica and Asia still had 90 and 75 percent of their respectivelabor forces engaged in agriculture. Apart from East Asian andPacific and sub-Saharan countries, the middle-income countrieswere considerably more developed in this respect, agriculture'sshare of the total labor force having already fallen to around60 percent or less.

All groups of countries experienced some degree of transforma-tion in the industrial structure of their labor force between 1950and 1970. In the low-income countries the share of the labor forcein agriculture declined by only 3 percentage points between 1950and 1970, whereas the middle-income countries secured a reduc-tion of around 15 percent in agriculture's share of the labor force,about two-thirds of the decline being absorbed in the servicesector.

A number of statistical studies have identified the generalpattern of change in the sectoral structure of the labor forceduring the process of development. Chenery and Syrquin, forexample, regress the sectoral shares of the labor force on GDP

per capita and population. For a country with a population of10 million and per capita GDP of US$500 in 1964, their estimatesshow that the partial elasticity of agriculture's share in the laborforce with respect to per capita GDP is -0.50. The correspondingelasticities for industry and services are 0.39 and 0.2 7.7 Thesefigures indicate that, given the structure of the labor force at thislevel of development, an increase in GDP per capita is associatedwith a decline in agriculture's share of the labor force, which isabsorbed in almost exactly equal proportions by industry andservices.

7. Calculated from Chenery and Syrquin (1975), table 7.

Table 11. Sectoral Distribution of the Labor Force by Region, 1950-70(percentage of total labor force)

Middle-income countriesa

Middle LatinLounrinesa Sub- East and East America All

Sector countries Saharan North Asia and and Southern developingand year Africab Asia All Africab Africa Pacific Caribbean Europe All countries

Agriculture1950 90 75 78 79 62 72 54 66 65 731960 87 74 76 73 58 67 48 59 60 701970 83 73 75 66 51 58 41 47 51 66

at4 Change, 1950-70 -7 -2 -3 -13 -11 -14 -13 -19 -14 -7Industry

1950 4 9 8 7 14 10 19 16 14 101960 5 10 9 9 16 11 20 21 16 121970 7 10 10 12 21 15 21 26 19 13Change, 1950-70 +3 +1 +2 +5 +7 +5 +2 +10 +5 +3

Services1950 6 16 14 14 24 18 27 17 21 171960 8 11 14 18 25 22 32 19 24 181970 10 17 16 22 28 28 38 27 30 21Change, 1950-70 +4 +1 +2 +8 +4 +10 +11 +10 +9 +4

a. The dividing line between low- and middle-income countries is GNP per capita of US $330 in 1977.b. Low-income Africa and middle-income sub-Saharan Africa correspond to sub-Saharan Africa as shown in table 10.Source: World Bank data.


Table 12. Educational and Occupational Structuresof the Labor Force in Selected Countries, 1960(percentage of the labor force)

Annual productivity per worker(1960 U.S. dollars)

Education and More than Less thanoccupation 1,500 700-1,500 700

EducationaDegree level or above 3.8 2.4 0.8Completed secondary

school or above 16.0 13.9 2.8Completed primary

school or above 90.5 51.2 23.6Mean years of school 9.0 5.7 2.9

OccupationbProfessional, technical,

and related 8.7 4.6 2.4Administrative, execu-

tive, and managerial 4.0 1.9 0.6Clerical 9.8 6.3 2.4Sales 8.5 8.1 6.9Other 69.0 79.2 87.7

Note: The figures reported here are unweighted means.a. Sample of seventeen countries taken from Layard and Saigal (1966), table 6.b. Sample of twenty-six countries taken from OECD (1971), table Fl.

Educational and Occupational Structures of the Labor Force

The educational and occupational structures of the labor forcealso change in the process of economic development. This isillustrated in table 12 for a 1960 cross-section of countriesgrouped by productivity per worker. In the high-productivitygroup (annual productivity per worker in excess of US$1,500 at1960 prices), more than 90 percent of the labor force have com-pleted primary school, and nearly 10 percent are classified asprofessionals or technicians. In the low-productivity group (annualproductivity per worker less than US$700 at 1960 prices), how-ever, less than 25 percent of the labor force have completed pri-mary education and less than 3 percent are in the professional andtechnical category.

Statistical analysis clarifies the relation between productivityper worker and the educational and occupational structures of thelabor force. Regressions relating the share of the labor force at


Table 13. Age-specific Enrollment Ratios by Levelof Education and Country Income Group(percent)

Country income group

Educational Inter- Alllevel Low mediate Upper developing

aand year Low middleb middleC middled countries

Primary1960 42 47 53 72 471965 50 53 63 76 541970 52 55 70 80 581975 56 58 75 85 62

Secondary�1960 15 8 11 20 141965 21 13 15 27 191970 23 16 20 33 221975 25 21 28 45 26

Tertiary 5

1960 0.9 2.3 1.8 4.5 1.51965 1.4 3.4 2.7 5.7 2.21970 2.3 4.0 4.3 6.7 3.2

1975 2.4 4.8 7.6 11.3 4.4

a. Less than US$265 per capita in 1975.b. Between US$265 and US$520 per capita in 1975.c. Between US$520 and US$1,075 per capita in 1975.d. Between US$1,075 and US$2,000 per capita in 1975.c. Proportion of group aged 6-11 years enrolled in primary schools.f. Proportion of group aged 12-17 years enrolled in secondary schools.g. Proportion of group aged 18-23 years enrolled in higher education.Source: World Bank (1980), annex 3.

selected educational levels to productivity per worker yieldelasticities of 0.9 for higher and secondary education and 0.75for primary education. Similar exercises relating occupationalshares to productivity reveal elasticities of 0.5 for professionaland clerical occupations, 0.6 for administrative occupations, and0.2 for sales occupations (Layard and Saigal, 1966).

Of course, not all countries fit the statistical relation equallywell. Japan, for example, lies in the medium-productivity group intable 12 but has an educational structure akin to that of the high-product.ivity group. Chile illustrates the opposite case: it is a high-productivity country with the educational structure of a medium-productivity country. Similarly, low-productivity countries suchas the Republic of Korea and the Philippines should be ranked


Table 14. Occupational Structureof the Labor Force by GDP per Capita, 1960-70

Countries Percentage of the labor forcewith 1970 bGDP White collara Blue collar OtherCper capita 1960 1970 1960 1970 1960 1970

Less thanUS$300 12 16 18 21 70 63

US$300 toUS$700 23 28 31 33 46 39

Greater thanUS$700 30 38 42 38 28 24

a. Includes professional, administrative, clerical, and sales occupations.b. Includes craft, transport, and production process occupations.c. Includes all other occupations.Source: Oberai (1978), table 6.

with medium-productivity countries according to their educationalstructures, whereas Peru, although included in the medium-productivity group, has an educational structure characteristic oflow productivity.

Changes over time in the educational structure of the laborforce are mainly supply-induced, depending to a large extenton the expansion in educational facilities. Recent changes in age-specific enrollment rates are reported in table 13. By 1975 evenlow-income countries enjoyed enrollment rates in excess of 55percent for primary education and 20 percent for secondaryeducation. For all developing countries, the enrollment rate atsecondary level almost doubled between 1960 and 1975. Changesat the tertiary level were even more dramatic: over the sameperiod the enrollment ratio almost tripled.

Changes in the occupational structure of the labor force, how-ever, will depend on both supply and demand factors. The changesobserved between 1960 and 1970 are reported in table 14 forcountries grouped according to GDP per capita. All groups ex-perienced an increase in the share of the labor force in white-collar jobs and a decrease in the share in "other" jobs. The twolow-income groups also increased the share of their labor force inblue-collar jobs, whereas the high-income group reduced its share.This is a further manifestation of how technology affects the

Table 15. Level and Growth Rate of Productivity by Sector and Region

Average annualgrowth rate, 1960-70Country (Relative level 1 9 7 0 b (percent) c

groupinga Agriculture Industry Services Agriculture Industry Services

Low-income 0.60 2.11 2.24 0.95 ( 0.62) 3.63 (0.38) 3.32 (0.44)

Africa 0.52 2.39 4.06 -0.38 ( 1.29) -1.18 (1.31) 3.98 (0.54)

Asia 0.61 2.05 2.04 1.17 ( 0.56) 4.24 (0.32) 3.05 (0.44)

Middle-income 0.34 1.90 1.55 2.57 ( 0.11) 4.16 (0.47) 2.68 (0.61)

Sub-SaharanAfrica 0.39 2.91 1.76 0.78 ( 0.54) 3.84 (0.56) 0.43 (0.91)

Middle Eastand NorthAfrica 0.28 2.44 1.25 2.07 ( 0.23) 5.11 (0.48) 3.47 (0.45)

East Asia andPacific 0.45 1.90 1.68 3.66 ( 0.19) 5.38 (0.52) 3.39 (0.58)

Latin Ameri-ca andCaribbean 0.34 1.73 1.29 2.58 ( 0.17) 2.95 (0.51) 2.22 (0.65)

SouthernEurope 0.34 1.23 1.92 4.22 (-0.56) 6.22 (0.29) 3.93 (0.52)

a. The country groupings for value added and labor force are not strictly comparable. The general coverage is described in the notes to tables

10 and 11.b. Sectoral productivity relative to economy-wide productivity.c. Figures in parentheses are employment elasticities defined as the rate of growth of the sectoral labor force divided by that of sectoral value

added. An elasticity greater than one indicates declining labor productivity; an elasticity less than one implies increasing labor productivity.Source: World Bank data.


composition of labor demand: more advanced technologies re-quire fewer blue-collar workers. To the extent that industrializa-tion in developing countries isbased on the technology of de-veloped countries, the changes in the occupational structure of thelabor force observed in Latin America and reported in table 8will be duplicated elsewhere.

Productivity and Real Wage Rates

The rate of change in labor's share of GDP equals the differencebetween the rates of change in real wages and productivity. Aninterest in the factor distribution of income thus presupposes aninterest in the changes in real wages and productivity. The avail-able data on sectoral productivity and real wage rates are reportedin tables 15 and 16.

Table 15 reveals that sectoral productivity generally differsmore widely in the low-income countries than in the middle-income countries, and that agriculture is universally the leastproductive sector. Industry has the highest growth rate of produc-tivity in all groups except low-income Africa. Productivity growthin low-income countries is consistently below that in middle-income countries in both agriculture and industry but not inservices; thus the observed tendency for GDP per capita to growfaster in middle-income than in low-income countries is reflectedin two out of three sectoral productivity growth rates. The em-ployment elasticities (shown in parentheses in table 15) revealessentially the same pattern: the slower rate of productivityincrease observed in the low-income countries is reflected in theirhigher employment elasticities.

Unfortunately, data on real wage rates for the same groupingof countries are not available. Nevertheless, the data reported intable 16 suggest that at least in industry and agriculture, increasesin real wages have probably not exceeded productivity increases.Given the differences in coverage and period of observation, how-ever, too much weight cannot be placed on comparisons betweentables 15 and 16; in particular, it would be premature to drawconclusions concerning labor's share in GDP from this approach.

Table 16 shows that real wages have increased in all threesectors in each of the five regions. A simple regression of manu-facturing on agricultural rates of wage change for a sample of


Table 16. Average Annual Rates of Change in Wages,Employment, Prices, and GDP per Capita by Region, 1964- 72(percent)

CentralAmerica

South and Mediter- TotalItem Americaa Caribbeanb raneanC Asiad Africae sample

Real manu-facturingwages 2.5 2.9 4.3 1.6 1.8 2.5

Manufactur-ing employ-ment 2.0 7.4 3.1 6.1 9.2 6.5

Real con-structionwages 0.3 3.7 3.0 3.3 1.4 2.3

Constructionemploy-ment 4.3 -2.4 6.4 4.5 7.7 5.2

Real agri-culturalwages 1.9 2.9 3.8 0.1 2.5 1].9

GDP percapita 2.2 3.0 3.7 2.4 2.3 2.6

Consumerpriceindex 16.9 2.9 3.1 7.6 4.2 7.2

Relativemanu-facturingwagesf 1.27 1.52 0.96 0.44 0.65

(0.22) (0.64) (0.25) (0.18) (0.44)

a. Includes Chile, Peru, Brazil, Argentina, and Uruguay.b. Includes Guyana, Ecuador, Trinidad and Tobago, Nicaragua, Jamaica, Barbados,

Panama, Puerto Rico, Dominican Republic, Honduras, Venezuela, El Salvador, Guate-mala, Mexico, and Colombia.

c. Includes Turkey, Algeria, Cyprus, Egypt, and Syria.d. Includes Republic of Korea, Taiwan, Sri Lanka, Burma, Vietnam, India,

Thailand, Singapore, Philippines, and Pakistan.e. Includes Kenya, Tanzania, Zambia, Uganda, Rhodesia, Ghana, Malawi,

Mauritius, Sierra Leone, and Nigeria.f. Relative to sample mean. The coefficient of variation is reported in parentheses.Sources: Gregory (1975), table 3; ILO, Yearbook of Labour Statistics (Geneva,

1977); and International Monetary Fund (1978).


twenty-three countries drawn from table 16 yielded a significantcoefficient of 0.8, indicating a nearly constant proportional rela-tion (Gregory, 1975).8 A similar exercise relating wage-ratechanges in agriculture and construction indicated an even strongerrelation, the coefficient being 0.99 (Gregory, 1975). Althoughnot conclusive, these results suggest that sectoral labor marketsmay be more closely integrated than is usually thought. 9

A similar conclusion emerges from multiple regression analysis.In one of the few attempts to construct a simultaneous-equationmodel of wage-rate determination, Glytsos (1977) reports astatistically significant coefficient of 0.97 relating the percentagechange in manufacturing wages to the percentage change inaverage agricultural income.'" At this level of aggregation, there-fore, the evidence is consistent with the hypothesis of reasonablywell-integrated labor markets.

Table 16 also presents data on rates of growth in sectoralemployment and GDP per capita, but the level of aggregationprecludes the deduction of meaningful conclusions. A moredetailed study (Bose, 19 78) of seven developing countries-Kenya, Ghana, Mauritius, Sri Lanka, Republic of Korea, Mexico,and Uruguay-shows that rising real wages are associated withrapidly rising real GDP per capita (at a rate of more than 3 per-cent a year) and rapid employment expansion in the nonagri-cultural sectors (in Korea and Mexico). Virtual stagnation in realwages is associated with slow GDP per capita growth (less than1 percent a year) and moderate transformation of the sectoralstructure of the labor force (in Uruguay, Mauritius, and Ghana).Even in countries (such as Kenya and Sri Lanka) experiencing

8. For the 1956-64 period, however, Smith (1969) found no signilicant correlationbetween manufacturing and agricultural wages in his sample of ten countries.

9. Intersectoral differences in the level of wages is discussed in chapters 6 and 8,which are concerned exclusively with the operation of the labor market.

10. The estimated regression is:

Aw = 0.07 + 2.21p + 0.97 Ay + 1.21 At R2 = 0.96(0.36) (0.06) (0.25)

where w = the nominal manufacturing wage, p = manufacturing productivity at currentprices, y = average agricultural income, t = the domestic terms of trade, and A indicatespercentage change (Glytsos, 1977, table 1). The coefficient on the percentage change inprice deflators for agricultural and nonagricultural output was not statistically significant.


moderate increases in GDP per capita (about 2 percent a year),real wages more or less stagnated.

The next to last row of table 16 illustrates regional dispersionof average wages in manufacturing. As might be expected, theLatin American and Mediterranean countries exhibit the highestrelative wages. Wages in Africa are well below the sample mean butsubstantially above those in Asia. While probably indicative of thegeneral relation between regional wage rates, the doubtful reli-ability of the underlying data caution against an unqualified ac-ceptance of the observed differentials.

Summary

The main implications of the cross-sectional analysis for theremainder of the study are:

1. The future growth rates of the labor force will exceed thoseof the recent past because of the high and increasing populationgrowth rates in the 1960s and 1970s, which have yet to show theireffects. The effect of declining participation rates is likely to benegligible by comparison.

2. Rapid expansion in educational output and the possibility ofa technologically induced change in the occupational structure oflabor demand suggest that extreme and unusual pressures are beingexerted on the labor market. The ability of the labor market t.oaccommodate these changes thus becomes a central concern.These developments also highlight the need to allow for skilldifferentials when interpreting wage differentials among sectors.

3. Trends in sectoral real wages indicate that labor markets arenot as tightly compartmentalized as some characterizations sug-gest. Efforts to expand labor demand in a given sector can there-fore be expected to exert upward pressure on wages in othersectors.

4

Unemployment and Underemployment

The concepts of unemployment and underemployment have beenextensively debated in the literature on developing countries. Ithas been pointed out that measures of unemployment are moreappropriate for developed countries, where the payment andconditions of employment are generally subject to contractualagreements and labor legislation and where social security pro-vides financial support for the unemployed. In these circum-stances, it is relatively easy to divide the labor force into themutually exclusive categories of employed and unemployed.In developing countries, however, a smaller percentage of thelabor force is engaged in wage employment, the majority beingself-employed or unpaid family members, and social securitysystems remain correspondingly underdeveloped. While there isconsiderable variation among countries, table 17 reveals clearlythat wage employment accounts for a much larger proportionof the labor force in the industrialized countries than in themiddle- and low-income countries.' Thus, in a country such asChile, where 70 percent of the labor force is in wage employment,the open unemployment rate may be a good measure of theunderutilization of labor resources. In India or Tanzania, however,it is often argued that the rate of open unemployment has littlesignificance because formal labor market transactions are relativelyfew.

The insignificance of wage employment, on the one hand, andthe large number of workers remaining in low-productivity agri-

1. The statistical relation between the share (n) of wage employment in the totallabor force and GDP per capita (y) for thirty-nine countries has been computed to be:

In n = -130.15y -' - 4.41

(R = 0.863, a = 0.12, DW = 2.06)Thus, the elasticity of n with respect to y equals 130.15 y-' (Lecaillon and Germidis,1975).

57


Table 17. Percentage of the Labor Forcein Wage Employment in Selected Countries, circa 1970

Industrialized Middle-income Low-incomecountries Percent countries Percent countries Percent

Sweden 91 Spain 74 Sri Lanka 54United States 90 Argentina 71 Mozambique 40United 88 Portugal 70 Indonesia 33

Kingdom 87 Chile 70 Sudan 25Canada 85 Mexico 62 Pakistan 22Switzerland 85 Algeria 60 India 17Australia 84 Venezuela 59 Tanzania 9Germany 83 Brazil 55Norway 80 Egypt 54Denmark 79 Tunisia 54Austria 79 Yugoslavia 50Belgium 78 Ecuador 49Finland 70 Guatemala 48Italy 66 Peru 47Ireland Iran 44

Greece 42Syria 42Philippines 40Paraguay 39Korea, Rep. of 38Morocco 37Turkey 28Thailand 15

Source: ILO, Yearbook of Labour Statistics, 1974 and 1977.

culture and services, on the other hand, have led some analyststo enmphasize the rate of underemployment as an additional ormore appropriate measure for developing countries. In the fol-lowing, the analytical content of the concepts of unemploymentand underemployment is investigated and the relevance of theseconcepts for developing countries is assessed. In addition, availableestimates of unemployment and underemployment are presentedand discussed.

Analytical Content

The objective of this section is to examine the relation betweenthe theoretical concepts of excess labor supply and labor misallo-cation, on the one hand, and the empirical concepts of rates ofunemployment and underemployment on the other hand. In

Unemployment and Underemployment 59

analyzing employment, unemployment, and underemploymentin developing countries, the evidence in table 17 makes clear thatexplicit allowance must be made for self-employment. 2 Thedemand curve for wage employment is shown in figure 1 asDwDw and that for total (wage and self-) employment as DTDT.In the absence of institutional or other constraints on wagedetermination, equilibrium is achieved at the point of intersectionof the demand and supply curves. If the supply curve is given bySS, total employment is NT, wage employment is Nw, and thereturn to the self-employed exactly equals the market wage W.

The market for wage labor in developing countries, however, isoften thought to be subject to a variety of distortions. In partic-ular, assume that minimum wage legislation leads to the enforce-ment of a market wage at W1

.3 As a result, wage employment falls

from NW to NW, and the demand curve for total labor shiftsfrom DTDT to DTDT because the demand curve for wage laboris now given by D WNW. If it is assumed that the wage sectoremploys those with the lowest supply prices, 4 self-employmentchanges from NWNT to NWNT. Compared with the previoussituation, two important changes have occurred. 5 First, someof the workers indicated by U would not be prepared to acceptself-employment but would accept wage employment at the

2. This analysis abstracts from imperfections arising from uncertainty, inadequateinformation flows, and transaction costs; that is, adjustment in the labor market isassumed to be instantaneous. The significance of this assumption is examined below. Forsimplicity, both sectors are assumed to produce commodities, the prices of which arefixed in world markets. Capital and other nonlabor inputs are assumed to be sectorspecific. Labor is assumed to be homogeneous. The model is therefore an abbreviated,partial equilibrium version of the one presented in the technical note to chapter 2.

3. In reality, the coverage of wage legislation is usually less than complete. Thisdoes not affect the substance of the present argument, although it is clearly of im-portance when assessing the impact of wage legislation empirically.

4. Given the distortion, there is of course a much larger number of workers seekingemployment at the distorted wage than there are jobs. It follows that, if the wagesector employs those whose supply price exceeds WS, excess supply will be lower, butintersectoral productivity differentials will be larger. Obviously, there exists an infinitenumber of possible combinations of excess supply and sectoral productivity differentials,but the particular outcome does not affect the general points made in the text.

5. In a two-sector general equilibrium model of the type presented in the technicalnote to chapter 2, an increase in an exogenously specified wage confronting the capital-intensive sector will reduce the amount of labor used in that sector, increase the quantityof labor used in the labor-intensive sector, and increase the divergence between sectoralmarginal products for labor. These results parallel those reported in the text but allowfully for movement of capital between sectors.


Figure 1. Wage Employment, Self-Employment, and Underemployment

CL

2

0

3 W - -

N W Nb, I T

NWM I

Employment

distorted wage if it were available; the distortion in the labormarket thus produces excess supply and a decline in total employ-ment. Second, the marginal product in the wage sector (equal toWl ) now exceeds that achieved in self-employment (Ws); thedistortion is therefore also reflected in sectoral differentials inmarginal product and hence there is a misallocation of laborresources. 6

To determine the policy significance of estimates of unemploy-ment, it is necessary to establish the relation between the analyti-cal concept of excess supply depicted in figure 1 and the statisti-cal measure of unemployment used in labor surveys and censusdata. Two points in particular warrant discussion. The first con-cems the significance of the imperfections -uncertainty, inade-quate information flows, and transaction costs-which were

6. Other factors besides minimum wage legislation can cause sectoral differentials inmarginal product. These will be reviewed in chapters 5 through 8. At this stage, theessential point is the existence of these differentials rather than their precise cause.


omitted by assumption from the analysis based on figure 1. Thesecond concerns the limitation of the statistical measure of theunemployed to those "actively seeking work." These points arediscussed below.

In defining unemployment for statistical purposes, most coun-* tries follow the ILO recommendations: that is, the reference

period is usually one week, part-time workers are generally in-cluded in the total of employed, and the unemployed includethose who did not work or who worked less than one day duringthe reference period and were actively seeking work., It is notclear, however, that those denoted by Uin figure 1 would beactively seeking employment if complete information on thelabor market were available. Although their supply price is belowthe wage, they would know that jobs are not available and wouldtherefore refrain from a pointless job search. The theoreticalmodel thus predicts a zero rate of unemployment defined in thestatistical sense. It is concluded that the intersectoral variationin marginal products implies a sectoral misallocation of laborresources but is not a sufficient condition for the existence ofunemployment.

Labor markets, however, do not adjust instantaneously, andinformation costs are not zero. The theoretical analysis shouldtherefore be recast in terms of the dynamics of adjustment bytreating time explicitly. Distortions now arise, not only fromconstraints on wage determination, but also from imperfectinformation, uncertainty, and other transaction costs; activejob search becomes a rational exercise; and nonzero estimates ofstatistical unemployment can be expected. The financial return toor reward for job search, and hence the duration of search, will bepositively related to the dispersion of wage rates or degree ofsegmentation in the labor market. The duration of search will alsodepend on the searcher's ability to finance a period of unemploy-ment. This suggests that rates of measured unemployment will behigher for those types of labor that offer their services in seg-mented labor markets and that are in a position to finance ex-tended periods of job search. 7

7. For further discussion of models of unemployment in developing countries, seeBerry and Sabot (1978).


Adjustment costs also play a role on the demand side. Seg-mentation can occur not only as a result of institutional factors,such as minimum wage legislation, but also because the return towage-rate adjustments varies among enterprises. It may, forexample, be administratively more costly to change wage ratesin a large firm than in a small one. Similarly, a small firm mayhave more direct access to labor market information than alarge one. Either way, positive rates of unemployment can beexpected even if the market is free of institutional constraints.

This analysis also suggests that unsuccessful job-seekers willeventually abandon active job search. This has led to attemptsto estimate the number of discouraged job-seekers by relaxingthe qualification that they be actively engaged in a job search.Surveys designed to distinguish between those actively searchingfor jobs and those willing to accept jobs at going wage rates butnot actively looking suggest that the conventional approach failsto capture all those unemployed in the sense of being in excesssupply. Turnham (1971), for example, cites the case of WestMalaysia in 1967 where the unemployment rate was increasedfrom 6.8 to 8.8 percent by the inclusion of discouraged workers.In a careful study of the Tanzanian urban labor market in 1971,Sabot (1977) shows that inclusion of discouraged workers in-creases the rate of urban unemployment from 8.0 to 12.0 per-cent. A similar study in the Sudan, however, produced corres-ponding estimates of 5.3 and 5.9 percent (Mulat, 1975). Clearl]y,the phenomenon of the discouraged worker varies considerablyin its effect. Nevertheless, in interpreting the open unemploy-ment rates presented below, the presumption should be thatthey are minimum estimates.

The statistical measurement of unemployment is sometimesextended to allow for those who are working but would like towork longer hours at the going wage rate. Those so identifiedare usually referred to as the visibly underemployed. Obviouslv,they cannot be added directly to estimates of unemployment toobtain a "total unemployment," but the visibly underemployedare conceptually similar to the unemployed.

Estimates of unemployment, whether or not inclusive of dis-couraged job-seekers, and of visible underemployment fail toindicate the existence of sectoral differences in marginal produc tiv-ity. Accordingly, empirical efforts have been made to measure


the proportion of the labor force engaged in sectors in whichlabor's marginal product lies below that in some other sector.The workers thus identified are usually described as being in dis-guised unemployment. While it is clearly analytically appropriateand relevant to policymaking to measure the extent. of labormisallocation by estimating the rate of disguised unemployment,empirical efforts have not always been well focused. Two broadtrends can be discerned. In the early literature, following thetheoretical lead of Lewis (1954), attention was directed primarilytoward the agricultural sector and the measurement of surpluslabor-the quantity of labor that could be withdrawn from theagricultural sector without reducing agricultural output. Sub-sequently, with the emergence of a large low-productivity sectorin most major cities, attention switched to urban areas and frommeasures of labor utilization to measures of income or produc-tivity. Those below some specified level of income or productiv-ity were described as invisibly underemployed. These approachesare reviewed briefly below.

Unlike the diagrammatic analysis presented above, the explana-tion advanced by Lewis (1954) for the sectoral differential inlabor's marginal product rested on the assumed importance of thepractice of income sharing in family enterprises. In such circum-stances it is possible, but not necessary, that the intersectoralallocation of labor will be based on an equivalence between labor'saverage product in family enterprises and labor's marginal productin profit-maximizing firms. While this provides a rationale forsectoral differences in marginal product, by definition surpluslabor in agriculture is labor that can be withdrawn without anyreduction in agricultural output and without any increase in non-labor factors of production or any major reorganization of produc-tion. This in turn was thought to require that labor's marginalproduct in agriculture be zero.

Typically, empirical estimates of surplus labor are based on acomparison between labor requirements and labor availability,the difference between them being equated with surplus labor.Although many refinements have been introduced, this basicapproach suffers from serious drawbacks. First, by focusing on"requirements" and "availabilities," the approach abstracts fromthe notions of labor demand and supply. Second, it does notestablish that the difference between available and required


labor (however measured) corresponds to the theoretical conceptof surplus labor. And third, it is not obvious why interest shouldcenter only on a withdrawal of labor that leaves output constant;any reduction in output may nevertheless be small compared withthe withdrawn labor's contribution to output in some othersector.

Sen (1966) provided a microeconomic clarification of most ofthese issues by constructing a theoretical model of income-sharingfamily enterprises to explore the ramifications of the withdrawalof labor. The starting point of Sen's analysis was the observationthat the subsistence family enterprise will allocate labor to produc-tion up to the point where the utility value of additional productexactly compensates the disutility of additional work. This formu-lation allows for the withdrawal of labor with no reduction inoutput whether or not labor's marginal product is zero. That is,if the ratio of the marginal utility of consumption and the mar-ginal disutility of effort are constant in the relevant range, labor'smarginal product (and hence total farm output) must also remainconstant to fulfill the labor allocation rule regardless of the sizeof the family labor force. In other words, within this range laborcan be withdrawn from agriculture with no output loss even iflabor's marginal product is positive, because the remaining mern-bers increase their supply of labor. Sen showed that zero marginalproductivity is not necessary for the existence of surplus labor andthat, if income-sharing arrangements in family enterprises were thecause of a low, but not necessarily zero, marginal product of laborin agriculture, in deducing the consequences of the withdrawal oflabor from the agricultural sector, one must allow for the laborsupply response of those remaining behind. Estimates of surpluslabor based on simple comparisons of labor requirements andavailabilities should therefore be interpreted as descriptive oflabor utilization rather than as measures of the quantity of laborthat can be withdrawn from agriculture without any adverse con-sequence for agricultural output. 8

Invisible underemployment is usually defined to include allthose whose earnings fall below some critical, exogenously deter-mined level. It follows almost immediately that estimates ofinvisible underemployment tend to increase monotonically with

8. Accordingly, empirical estimates of surplus labor are reviewed in chapter 6.


the given cutoff point. For example, if the cutoff is equal to thefree-market wage of W in figure 1, the number of underemployedis M. In the earlier literature on surplus labor in agriculturedescribed above, zero marginal product was the chosen cutoffpoint. Frequently, the cutoff is equated with the official minimumwage and thus has a direct link to the analysis of figure 1. This isa conceptually acceptable approach since it identifies those who

can be expected to benefit from a restoration of a freely function-ing labor market.

Many estimates of invisible underemployment, however, arebased on a cutoff level of income that is equated with somenotion of a minimally acceptable standard of living. Clearly, theseestimates need have nothing to do with a labor market imperfec-tion. In fact, many such estimates do not attempt to identify thecause of low earnings but simply include all those below thegiven cutoff, whatever the underlying cause. This criticism alsoapplies, but with less force, to estimates that use the official mini-mum wage as the cutoff, because as soon as labor heterogeneityis admitted the distribution of earnings will reflect not only theinfluence of minimum wage legislation but also the distribution ofpersonal attributes, skills, and education. The earnings of somemembers of the labor force may be low, not because they areexcluded from certain jobs by minimum wage legislation butbecause they do not have the required skills or education to com-pete in the market protected by legislation. It may be concludedthat estimates of invisible underemployment, whether or notthey use a cutoff point based on an official minimum wage, areprimarily of interest as measures of poverty rather than as indi-cations of labor market imperfections.

Identifying two broad schools of thought will place this discus-sion in perspective. On the one hand, a number of authors arguethat "a somewhat more hopeful approach in the long term tomeasuring the size of the employment problem and degree ofprogress towards its solution is, we believe, offered by an em-phasis on poverty" (Turnham, 1971, pp. 18-19) and that theopenly unemployed are only "the tip of the iceberg" (Edwards,1974, p. 13). The emphasis here, then, is clearly on invisibleunderemployment. This approach has received its most enthusias-tic support in the series of country reports prepared by the Inter-national Labour Office (ILO), in which the extent of under-


employment as measured by an income criterion became animportant part of the overall employment problem. 9 On theother hand, it has been argued that it is important to maintainthe analytical distinction between a problem of poverty, whichmay indeed be reflected in low labor earnings, and a problem inthe labor market, which may be indicated by open unemploymientor sectoral differences in labor's marginal product. This view hasbeen expressed by, among others, Bruton (1973, p. 4), Sen (1975,p. 51), Sabot (1977, p. 401), and Stewart (1975, p. 3) and isadopted in subsequent discussion of the employment problem;that is, estimates of unemployment and intersectoral differencesin productivity are taken to be indications of market imperfection,and estimates of underemployment are interpreted as measures ofpoverty.

A further conclusion of importance for subsequent discussionconcerns the policy significance of intersectoral wage differentialsand unemployment. The above arguments suggest that inter-sectoral wage differentials imply a corresponding intersectoralmisallocation of labor resources but are not a sufficient conditiionfor the existence of unemployment. Eliminating wage differen-tialscaused by such factors as minimum wage legislation would thusimprove resource allocation. To eliminate or reduce unemploy-ment, however, it is necessary to make the job search less reward-ing. This, in turn, entails accelerating the rate of labor market ad-justment on both the demand and the supply sides by, amongother things, improving information flows.

Estimates of Unemployment

The estimates of open unemployment reported in table 18range from 16.1 percent for Bolivia to 0.2 percent for Thailanc[.Sabolo (1975b) estimates unemployment in the developingcountries as a group to be 7.4 percent in 1970 compared withonly 2.2 percent for the developed countries in the same year.Africa is shown to have the highest rate of open unemployment(9.6 percent), followed by Asia (7.1 percent) and Latin America

9. See, for example, ILO (1970), p. 15; ILO (1972), p. 1; ILO (1974), p. 7; anlJolly (1973), p. 23.

Unemployment and Underemploy ment 67

Table 18. Open Unemployment Rates in Selected Economies

Rate of openunemploy ment

Economy Year (percent)

Bolivia 1974 16.1Trinidad

and Tobago 1973 14.0Sri Lanka 1969-70 13.2Tanzania 1971 10.0Honduras 1972 8.0Malaysia 1967-68 6.8Panama 1973 6.5Ghana 1970 6.0Korea 1974 5.4Philippines 1971 5.3El Salvador 1975 5.2Syria 1973 4.5India 1971 3.9Mexico 1970 3.7Brazil 1970 2.0-2.4Indonesia 1971 2.2Pakistan 1972 2.0Taiwan 1972 1.5Egypt 1971 1.5Thailand 1969 0.2

Note: Because of differences in statistical practices, the estimates reported abovecannot be considered strictly comparable.

Source: Morawetz (1977), table 11.

(5.1 percent). 10 In the majority of countries for which estimatesare available, open unemployment is thus not a major problem.This is to be expected given the limited social security systems inthese countries and the prevalence of income-sharing familyenterprises. The reliability and consistency of unemploymentdata limit severely both international and intertemporal compari-sons of rates of unemployment. For a sample of ten developingcountries that conduct regular labor force surveys, Gregory ob-serves no definite trend in rates of unemployment during the1960s and early 197 0s and concludes that "the data do not offerany support for the proposition that employment conditionshave been deteriorating" (Gregory, 1980, p. 697).

10. Estimates of unemployment must be interpreted with caution because of dif-ferences in statistical practices.


Table 19. Urban and Rural Unemployment Ratesin Selected Economies

Unemployment Ratio of urbanrate (percent) to rural

Economy Year Urban Rural unemployment rates

Korea, Rep. of 1965 12.7 3.1 4.1Panama 1967 9.3 2.8 3.3Chile 1968 6.1 2.0 3.1Indonesia 1971 4.8 1.8 2.7Taiwan 1968 3.5 1.4 2.5Venezuela 1968 6.5 3.1 2.1Philippines 1967 13.1 6.9 1.9Trinidad and Tobago 1971 16.5 8.7 1.9Tanzania 1965 7.0 3.9 1.8India 1972-73 6.7 3.9 1.7Malaysia 1967 11.6 7.4 1.6Syria 1967 7.3 4.6 1.6Sri Lanka 1968 14.8 10.4 1.4Iran 1966 5.5 11.3 0.5

Sources: Turnham (1971), table III-7; World Bank (1973 and 1979b); and Govern-ment of India (1977).

Given the heterogeneity of the labor force, measures of totalunemployment are of limited use for identifying the labor marketsmost seriously affected by imperfections. It is of considerableinterest, therefore, to investigate the characteristics of the un-employed in more detail. Tables 19, 20, and 21 demonstrate thatunemployment is more serious in urban than in rural areas andthat within urban areas it is more serious for those aged 15 to 24than for the total labor force, for females than for males, and, atleast up to postsecondary education, for the more educated thanfor the less educated.

For six of the fourteen cases listed in table 19 the rate of urbanunemployment is at least twice that of rural unemployment.Moreover, with the notable exceptions of Iran and Sri Lanka,the rates of rural unemployment are not especially high. Focusingexclusively on urban unemployment, table 20 reveals that inseven of the twelve listed countries the unemployment rate formales in the 15-24 age group is more than twice that of the totalmale labor force."' For females the difference is less marked, only

11. The age distribution of unemployment in the United States is similar. In 1977the 16-24 age group experienced an unemployment rate of 13.6 percent compared with7.0 percent for the total labor force (U.S. Department of Labor, 1978).


three of the countries having unemployment rates for the 15-24age group twice that of the total female labor force. Table 20also allows a comparison of male and female unemploymentrates. In nine of the countries the rate of female unemploymentexceeds that for males. In this comparison, however, it should berecalled that female participation rates are much lower than thosefor men.

Table 21 shows the relation between unemployment and edu-cational attainment. In general, unemployment rates are lowerfor the illiterate and those with postsecondary education than forthose with primary or secondary education, the secondary schoolleaver often facing the most severe unemployment problem. 12

There are, however, notable exceptions to this generalization. InKenya, for example, the illiterate experience the highest rate ofunemployment, while in Sri Lanka the rate for primary schoolleavers is relatively low.

The data on unemployment rates examined above clearlypoint to the failure of the market for certain types of labor.The combination of high financial returns to job search andthe ability to finance unemployment is most evident in the mar-ket for young, inexperienced but educated workers in urbanareas. Chapters 8 and 9 will examine the operation of this marketin some detail.

Estimates of Underemployment

Estimates of underemployment may be divided into twodistinct categories: the first, visible underemployment, is definedto include those who are employed but would like to work longerhours; and the second, invisible underemployment, is defined inseveral ways but generally includes those whose earnings liebelow a given level. The two concepts are analytically very dif-ferent. Visible underemployment is closely related to open un-employment because it is caused by and reflects labor marketimperfections. As argued earlier, however, invisible underemploy-ment has significance primarily as a measure of poverty.

12. In part, this may reflect differences in age distribution, that of the educatedbeing skewed in favor of the young compared with that of the illiterate. Age-specificunemployment rates may show higher rates for the illiterate in the older age groups.

Table 20. Urban Unemployment by Age and Sex in Selected Countries

Male Female Ratio of male

Country 15-24 15-24 to femaleand area Year age group Total Ratioa age group Total Ratio a unemployment rate

Algeria (Departmentof Alger) 1966 41.1 25.9 1.6 13.4 6.6 2.0 3.9

Korea, Rep. of (non-farm households) 1966 16.4 9.3 1.8 15.3 7.9 1.9 1.2

Iran (Tehran) 1966 9.3 4.6 2.0 10.3 4.0 2.6 1.2Thailand (Bangkok) 1966 8.0 3.2 2.5 7.3 3.4 2.1 1.0Philippines (urban

areas) 1965 23.8 10.8 2.2 16.9 12.9 1.3 0.8'Trinidad 1969 23.0 12.0 1.9 27.0 15.0 1.8 0.8Guyana (mainly

urban areas) 1965 36.5 18.4 2.0 49.0 27.7 1.8 0.7Colombia (Bogota) 1968 21.8 10.3 2.1 24.3 18.5 1.3 0.6India (urban areas) 1972-73 8.1 5.6 1.4 7.7 9.2 0.8 0.6Sri Lanka (urban

areas) 1968 36.1 12.9 2.8 48.4 25.9 1.9 0.5Argentina (Buenos

Aires) 1965 4.3 2.9 1.5 9.0 7.0 1.3 0.4Malaya (urban areas) 1965 17.7 7.4 2.4 26.8 16.7 1.6 0.4

a. Ratio of unemployment rate of 15-24 age group to that of total labor force.Sources: Turnham (1971), table 111-2; World Bank (1973); and Government of India (1977).

'fable 21. Unemployment by Educational Attainment in Selected Countries(percent)

Country and Rate of unemploymentarea Year Illiterate Primary Secondary Postsecondary

Argentina (Buenos Aires) 1965 Illiterate Primary Secondary PostsecondaryTotal labor force 3.8 4.3 5.7 3.3

Colombia (Bogota) 1967 Illiterate 1-5 years education 6-11 years education 12+ years educationMale 11.5 15.3 14.9 13.2Female 4.1 22.0 16.3 11.3

India (urban areas) 1972-73 Illiterate Primary Secondary HigherTotal labor force 14.9 21.3 53.6 10.0

Kenya (Nairobi) 1970 No schooling 1-6 years education 7-8 years education 9+ years educationAfricanlaborforce 21.0 19.0 17.0 12.0

Higher certificate> Malaysia (urban areas) 1965 Illiterate Primary Grades 1 to 4 and above

Males, 15-24 10.4 19.5 30.9 15.5Females, 15-24 17.2 32.4 69.7 27.5

Primary Secondary I-ligherPeru (urban areas) 1970 Illiterate Incomplete Complete Incomplete Complete Incomplete Complete

Total labor force 3.0 3.0 6.0 11.0 9.0 8.0 5.0Elementary High school

Philippines 1968 No schooling Grades 1-3 Grades 4+ Grades 1-2 Grades 3-4 CollegeTotal labor force 4.4 4.5 6.8 13.7 15.3 12.2

Sri Lanka 1971 No schooling Primary Secondary 0 level AboveTotal labor force 4.6 3.0 22.0 32.1 12.8

Syria 1967 Illiterate Literate Elementary to secondary GraduateTotal labor force 4.3 5.2 11.7 4.4

Venezuela (urban areas) 1969 Illiterate Primary Secondary PostsecondaryTotal labor force 4.3 7.0 10.2 2.3

Sources: Tumham (1971), table 111-3: Richards (1977), table 10; Versluis (1974), table 1-4; ILO (1972), table 19; and Government of India(1977).


Table 22. Estimates of Underemploymentin Selected Countries

Rate ofunder- Definition of

Country and area Year employment underemployment

Visible underemployment

Colombia (urban areas) 1967 2.0 Persons working less than32 hours per weekand seeking morework

Tanzania (urban areas) 1971 5.0 Number working shorthours

Chile (metropolitan area) 1960 28.0 Employed persons want-ing to work longer

Invisible underemployment

Kenya (Nairobi) 1970Male 13.6 Those earning less thanFemale 31.8 K Sh200 a month

Philippines (urban areas) 1971 14.0 Methodology not clearEl Salvador (metropolitan

area) 1961 21.0 Those earning less thanthe considered abso-lute minimum

Brazil (Sao Paulo) 1970 34.6 Those earning less thanthe official minimumwage

Mexico 1969 37.6- Includes those working44.8 short hours or ea,rning

less than the officialminimum wage andmost unpaid familyworkers

Tanzania (urban areas) 1971 41.0 Number earning less thanurban minimum wage

Peru (urban areas) 1971 42.0 Based on hours workedand minimum wage

Dominican Republic(Santo Domingo) 1973 60.0 Based on stability and

level of earningsAfrica 1970 39.0 Includes those employedAsia 1970 26.0 part time or whoseLatin America 1970 20.0 productivity is partic-

ularly low.

Sources: Sabolo (1975b), appendix; Pazos (1975), p. 239;Jones (1968), table II;Schaefer (1975), table 3-9; Keesing (1977), p. 18; ILO (1970), table 1;ILO (1972),table 22; ILO (1974), p. 7; Sabot (1977), p. 400-01; Versluis (1974), table 1-9.


Estimates of visible underemployment in table 22 show asurprisingly small percentage of the labor force categorized asvisibly underemployed in Tanzania and Colombia. Even in thecase of Chile it is not clear to what extent the removal of under-employment would expand labor utilization, because informa-tion is lacking on the amount of additional labor that would beforthcoming from the currently underemployed. Turnham (1971,p. 59) concludes that "where attempts have been made to convertextra work demanded into an equivalent percentage of full-timeunemployed, the addition is usually rather meager-2 or 3%-although the proportion of the employed force wanting someadditional work may be quite high." Nevertheless, visible under-employment constitutes a further reason for treating reportedrates of open unemployment as minimum estimates.

The second part of table 22 presents estimates of invisibleunderemployment which range from 60 percent in the DominicanRepublic to 14 percent in the Philippines. The cutoff point ofearnings is described as fully as possible. When the official mini-mum wage has been used, the estimates convey certain informa-tion. In other cases, the information conveyed, if any, is far fromclear. For example, the procedure for arriving at the estimate ofunderemployment in the Philippines was described as follows:

Our rough estimate of total unemployment is based on aninadequate income concept using the gap between averagewages in the organized and unorganized urban sectors, theshare of the urban labor force in each sector, plus open un-employment. For the urban labor force in 1971, excludingprofessional and civil service categories, 70% of the labor forcewas employed in the unorganized sector, earning some 68%of the organized sector wage, and 11% was openly unemployed.If the wage gap were an accurate indication of the degree ofunderemployment in the unorganized sector, total unemploy-ment could be estimated as 33%, that is ([1.0 - 0.68] X 70)plus 11%.13

13. ILO (1974), p. 7n. The figure of 14 percent for invisible underemploymentreported in table 21 is arrived at by means of this method, but a different measureof the sectoral eamings differential is used.


Underemployment in this case, therefore, is dependent on thesectoral earnings differential and is not simply an estimate of thenumber below some cutoff point. Moreover, its addition to theopen unemployment rate to produce a measure of the "totalunemployment" problem seems especially indefensible becausethe two components bear no obvious relation. Open unemploy-ment is denominated in numbers of the labor force whereasunderemployment in this case is measured in units of output.

Equally indefensible are the regional estimates of invisibleunderemployment for Africa, Asia, and Latin America. Suchestimates involve the aggregation of individual country estimates(including, as it happens, that for the Philippines), each of whichis based on a different approach, or, if the approach is the same,a different cutoff level of earnings. International aggregation ofsuch a disparate set of country-specific estimates of underemploy-ment can only produce a meaningless total.

The above discussion and critique of estimates of underemploy-ment has been included to illustrate some of the confusion thaLtsurrounds the underlying concepts. Provided the cutoff level ofearnings is clearly specified, estimates of invisible underemploy-ment convey information in precisely the same way as estimates ofthe numbers below some poverty threshold. Such estimates, how-ever, should not be combined with the recorded rate of open un-employment to arrive at a measure of the total unemploymentproblem, nor should they be aggregated internationally to arriveat regional or global measures of underemployment.

Conclusion

Underemployment, defined in terms of low earnings, is a mani-festation of the excessive size of the labor force in relation tocomplementary factors of production. If labor markets are rea-sonably well integrated the solution to this problem must besought in factors affecting labor demand and supply. An im-portant premise of this argument is that unskilled labor marke-tswork reasonably well. To establish this proposition, the varioussources-of labor market distortion-minimum wage legislation,trade union activity, and social security provisions-must beexamined and their impact on resource allocation assessed.


The solution to the unemployment problem, however, isfound in the operation of particular labor markets. Here theemphasis is on improving information flows to accelerate adjust-ment in the labor market. Exogenous shifts in labor supply anddemand are also important in this respect because their magni-tude and speed determine the degree of required adjustment. Therecent rapid growth of population and the sudden increase in therate of school enrollments represent major changes in labor sup-ply conditions which can be expected to have exerted exceptionalpressure on labor markets.

In the subsequent sections, some of these issues are discussedin more detail. Part II is devoted to an analysis of labor marketsand is concerned primarily with the problems of unemploymentand the misallocation of resources. In Parts III and I]V variousfactors operating on the demand and supply curves for labor arediscussed. These sections, therefore, address the problem ofunderemployment and other problems arising from the relativelyslow rate of transformation in the sectoral structure of the laborforce.

PART II

The Operation of Labor Marketsin Economic Development

In this part the operation of labor markets is examined with theobjective of identifying the quantitative significance of labormarket distortions. It is argued that unskilled labor markets arereasonably efficient: rural wage rates are determined by supplyand demand, although not necessarily in a competitive frame-work; high rates of rural-urban migration attest to the mobilityof the labor force; and urban wage rates are less influenced byinstitutional factors than is commonly thought. Nevertheless,labor legislation and trade union activity have undoubtedlyinfluenced wages marginally in some countries and significantly ina few countries. The -removal of these distortions, however, isunlikely to raise the return to labor in the informal sector to anysignificant extent. Although the removal of distortions is to beencouraged in order to improve resource allocation, it is arguedhere that increases in informal incomes must be sought in mea-sures other than the elimination of labor market distortions.

Low rates of unemployment for unskilled labor contrast sharplywith the high rates experienced by young, educated workers. Thereward for job search and the ability to finance unemployment areapparently concentrated in this group. As noted in chapters 2 and3, the rapid growth in population and the simultaneous desire toincrease school enrollment rates have caused a major expansion inthe supply of young, educated workers. The consequent failureof the market to adjust adequately is attributed, in part, to theinflexibility of pay scales, especially in the public sector, and, inpart, to the slow rate of downward revision in job expectations,which may in turn be attributed to inadequate information flows.

In this section simple models of the dual economy are analyzedfirst, and some of their deficiencies are identified for subsequent

77

78 The Operation of Labor Markets

discussion. Rural labor utilization and the determination of ruralwages are then examined. This is followed by a discussion ofrural-urban migration, particularly the characteristics of migrantsand the determinants and consequences of migration. The bulk ofPart II, however, is concerned with the operation of urban labormarkets for both unskilled and educated labor.

5

Models of the Dual Labor Market

A dual labor market, in which the wage rate in one sector ofthe economy exceeds the marginal product of labor in another,has been a prominent feature in models of the structural trans-formation of the labor force during the process of economicdevelopment.' There have been two main variants of the model,which may be termed "traditional sector dualism" and "modemsector dualism."2 In the former, dualism occurs because the sup-ply price of labor from the traditional sector exceeds its marginalproduct in agriculture. In the latter, the source of dualism is aninstitutionally determined industrial wage that exceeds labor'ssupply price.

The supply price of labor in traditional sector dualism is usuallydetermined by the average product of labor in income-sharingrural households (Lewis, 1954) or by subsistence wage paymentsestablished by landlords (Fei and Ranis, 1961). Either way, it isassumed that labor's supply price exceeds its marginal product,which in turn is often viewed as equal to zero in the early stagesof development because the labor force is excessively large inrelation to complementary factors of production. 3 Because theindustrial wage is determined by labor's supply price, the transferof labor from agriculture to industry is thought to improve re-source allocation (the industrial wage being greater than labor's

1. This chapter draws on Bertrand and Squire (1980).2. Typically, the modem sector includes mining, medium- and large-scale manu-

facturing, public services, and plantation agriculture; the traditional sector includes

small-scale manufacturing, family-operated services, and peasant agriculture. For thisdiscussion, however, the essential distinguishing characteristic lies in the factors deter-mining dualism.

3. The conditions for a zero marginal product of labor on family farms have since

been shown to be implausible (Sen, 1966). The argument here, however, requires onlythat labor's marginal product be less than its supply price and not that it be zero (see

chapter 4).

79


forgone marginal product) but is not seen as a possible cause ofexcess supply of labor to urban areas (the industrial wage beingequal to labor's supply price).

The emergence of high rates of urban unemployment, how-ever, cast considerable doubt on the empirical plausibility of atheory based on market-clearing wages. Accordingly, unemploy-ment was made the focal point of modem sector dualism by as-suming that equilibrium in the labor market is secured by aquantity adjustment-a change in the rate of unemployment--rather than a price adjustment. 4 The exact mechanism precludingwage-rate adjustment is often not specified, but reference isusually made to public legislation, trade unions, or the hiringpractices of modem sector firms. Equilibrium in this situation ischaracterized by labor's supply price from the traditional sectorbeing equal to the expected industrial wage rate, which is assumedequal to the product of the actual wage rate and the probabilityof employment (Harris and Todaro, 1970). Because the proba-bility of employment is assumed to be a function of the rate ofunemployment, the rate of employment, rather than the fixedwage rate, becomes the equilibrating mechanism in the labormarket.

Modem sector dualism, as described above, is clearly far toosimple to reflect the complexity of the real world. The approachcan, however, be extended in several directions. First, a theory ofwage-rate determination, or a demonstration that the industrialwage is indeed determined by, for example, minimum wage legis-lation, is an essential component of analysis based on modemsector dualism. This subject receives considerable attention below.Second, a two-sector model is too limited to capture the multi-faceted dimensions of labor market transactions in developingcountries. Models have therefore been developed which in-corporate the basic assumption of modem sector dualism butwhich expand the analysis to three or more sectors.5 Of majorimportance has been the emergence of the urban informal sector.

4. As argued in chapter 4, in a world of perfect certainty measured unemploymentwould be zero even if excess labor supply were positive. Unless theories of modemsector dualism explicitly incorporate uncertainty, and hence a rationale for job search,they cannot explain unemployment.

5. See, for example, Harberger (1971), Collier (1975), Fields (1975), Mazumdar(1977), Sabot (1977), and Scoville (1977).

Models of the Dual Labor Market 81

Originally introduced by Hart (1973), the concept of the informalsector has suffered from a confusing variety of definitions. ForHart the distinction between wage and self-employment was theessential difference between the formal and informal sectors.This is also the definition advocated by Mazumdar (1977), al-though he suggests including in the informal sector the wageemployees of small establishments. ILO (1972) identifies theinformal sector by reference to characteristics such as the small-ness of scale of operation, reliance on indigenous resources, andfamily ownership of enterprises. For empirical exercises it maywell be necessary to adopt such approaches, but it is neverthelessimportant to have in the background a precise analytical distinc-tion between formal and informal. In the context of this exer-cise it seems appropriate to define the informal sector as that inwhich the return to labor, whether or not it be in the form ofwages, is determined by the forces of supply and demand. Theadvantage of this approach is that the informal sector is notdetermined by some physical characteristic, such as size of estab-lishments, but by means of an analytically significant character-istic.

The third direction in which models of the dual labor marketshould be expanded would relax the assumption that labor is ahomogeneous factor of production. Labor heterogeneity has notreceived sufficient attention in formal modeling 6 but is welldocumented in the descriptive literature.' The implications ofheterogeneity are devastating. For example, the dualism modelsdescribed so far purport to explain unemployment and wagedifferentials for labor of homogene,us quality by reference to theexistence of segmented labor markets. If, however, labor isheterogeneous, unemployment can be explained without referenceto segmented labor markets; unemployment can exist for sometypes of labor (for example, educated workers) and not forothers (for example, unskilled workers). This illustrates thegeneral point that the recognition of labor heterogeneity makesit very difficult to interpret earnings differentials. On the onehand, they could reflect quality differentials; on the other hand,they could indicate a distortion. As a result, pronouncements on

6. Exceptions are Fields (1974), Piinera and Selowsky (1978), and Collier (1979).7. See, for example, the essays in Kannappan ( 1977b).


the operation of particular labor markets must be treated withsome caution and should be recognized as the judgments of (pre-sumably) well-informed observers.

Additional effort with the dualism models to modify the as-sumptions concerning the behavior of the unemployed may aLsoprove beneficial. In the case of homogeneous labor, the unem-ployed are assumed to make their decision to accept the realiltyof unemployment now because of the future prospect of em-ployment in the high-wage sector. All the information requiredfor this decision is known with absolute certainty. Abandonin,gthe assumptions of perfect foresight and labor homogeneity altersthe picture substantially: the manner in which the unemployedadjust to changing labor market conditions, and to any divergencebetween expectations and reality, now becomes a legitimate areafor investigation. The skill-occupation or education-occupationmix thus emerges as a possible market-equilibrating mechanismn in-stead of or in addition to the unemployment rate in situationswhere the structure of wages is thought to be fixed institutionally.Most of the issues addressed above in general terms (wage deter-mination, labor heterogeneity, and the adjustment process) willbe discussed further in this part. The discussion of the informalsector, however, is deferred to chapter 10.

6

Determination of Rural Wages

This chapter reviews the evidence on rates of labor utilization andlabor market participation in rural areas, and assesses existingtheories and empirical investigations of rural labor markets andwage rates. As will become apparent, the paucity of empiricalanalyses seriously impairs any attempt to draw generalizations.Nevertheless, it will be argued that the forces of supply and de-mand, albeit in a variety of market structures-competitive, mo-nopolistic, and dualistic-are usually important determinants ofrural wage rates.

Utilization of Rural Labor

Low overall rates of labor utilization, marked seasonal variationin labor use, and low rates of labor market participation arefrequently cited as characteristic of rural employment in develop-ing countries. The available data, however, do not always supportthis view. Tables 23, 25, and 27 present a variety of internationalstatistics on rural labor utilization, while tables 24, 26, and 28provide more detail for particular regions or countries.

Table 23 reveals that the majority of the rural labor forcework more than forty hours a week. In Taiwan, for example,more than 95 percent of the male labor force work more thanforty-two hours a week. At the other extreme, less than 30 per-cent of the female labor force work more than forty hours a weekin the Philippines. Nevertheless, the overall impression from table23 is not that of a highly underutilized labor force. Moreover,aggregative statistics of this sort often fail to capture activities,such as travel to and from fields, which may not be directlyproductive but are still time consuming.

Time-budget studies, that is, detailed investigations of theallocation of time to all activities, avoid some of the problems

83


Table 23. Hours Worked in Rural Areas in Selected Economies

Cutoff Percentage of(number rural laborof hours force working

Economy Year Sex per week) less than cutoff

Ceylon 1968 Male 20 10.7Female 20 17.5

Chile 1968 Male 41 18.2Female 41 31.5

India 1961-62 Both sexes 43 41.2Korea, Rep. of 1963-6 7 Both sexes 40 46.0Philippines 1962 Male 40 30.4

Female 40 71.2Taiwan 1966 Male 42 4.8

Female 42 19.1Tanzania 1965 Both sexes 40 40.0Venezuela 1969 Both sexes 41 39.3

Source: Tumham (1971), table III- 1.

associated with census and survey data but are generally based onvery small samples. Three such studies for Africa are reported intable 24. Men devote between 30 (Cameroon) and 50 percent(Uganda) of a twelve-hour day to social activities or rest. Thecorresponding range for women is 20 (Ivory Coast) to 45 percent(Cameroon). Clearly, there is considerable variation both amongsamples and between sexes within samples.

This discussion also bears on the issue of surplus labor.' Evenif low rates of labor utilization are observed, it does not neces-sarily follow that the labor market is imperfect or that labor is insurplus; the returns to labor may simply be too low to make workan attractive proposition. What is required is estimates of thenumber of workers seeking additional work and of the amount ofwork they are prepared to undertake at the market wage. Suchinformation is rarely available. 2 A survey in the rural areas of thePhilippines in 1965, for example, revealed that 71.6 percent ofmen and 74.7 percent of women did not want additional work(Turnham, 1971). It did not, however, provide information on the

1. Surplus labor is generally defined as the quantity of labor which can be with-drawn from the agricultural sector without reducing agricultural output (see chapter 4).

2. Econometric estimates of labor supply curves in rural households indicate in-elastic responses to wage-r-te changes. See Bardhan (1979b), Barnum andSquire(1979), and Lau and others (1978).

Determination of Rural Wages 85

Table 24. Labor Utilization in Three African Countries: Divisionof Twelve-Hour Day among Activities(percent)

Cameroon Ivory Coast Uganda

Activity Males Females Males Females Males Females

Farm work 17 14 27 44 30 30Nonfarm work 22 9 18 7 17 7Domestic work 11 15 13 31 2 18Illness 18 17 6 2 4 3Social activities 23 27 14 15 10 4Rest 10 18 23 2 42 38

Source: Dasgupta and others (1977), tables 2-2, 2-3, and 2-4.

quantity of additional work sought by the remaining men andwomen. In the absence of such information, estimates of surpluslabor arrived at by subtracting actual work time from somearbitrary norm must be considered of doubtful value.

Apart from labor utilization, the extent of labor market partic-ipation is often not realized. Table 25 provides some indicationof the range among countries. Latin American countries oftenhave more than 30 percent of their agricultural labor force in wageemployment, whereas the corresponding figure for most of theAsian and African countries in table 25 is less than 25 percent.The markedly inverse relation between the share of the laborforce in agriculture and the share of wage employment in the agri-cultural labor force suggests that the latter share may bear an in-verse relation to the general level of development. Such a con-clusion, however, would be premature; the differences in the shareof wage employment could also be explained by the degree ofinequality in landholdings. In support of this view, the LatinAmerican countries, which typically have very unequal land distri-butions, are also seen to have the highest share of wage employ-ment. Moreover, Japan, the most developed country shown intable 25, has only 4.9 percent of its agricultural labor force inwage employment.

Of course, agricultural wage employment is only one wayin which rural households participate in the labor market; theyalso supply labor to nonagricultural activities. Table 26 pro-vides information on total labor market participation (that is,the extent of hiring in and hiring out) for agricultural households


Table 25. Wage Employment andthe Agricultural Labor Force in Selected Countries(percent)

Share ofShare of wage employmentlabor force in agricultural

Country Year in agriculture laborforce

Chile 1970 21.2 61.8Algeria 1966 50.4 60.4Argentina 1970 14.8 53.2Sri Lanka 1971 40.6 51.0Portugal 1970 29.6 50.9Mexico 1970 39.5 49.0Nicaragua 1971 46.8 45.8Spain 1970 24.8 42.6Egypt 1966 53.3 38.2Guatemala 1973 57.0 36.0Venezuela 1971 20.3 27.7Brazil 1970 44.3 25.4Iran 1966 41.8 25.3Indonesia 1971 64.2 23.6Peru 1972 40.9 22.3Mozambique 1970 73.4 22.1Morocco 1971 50.0 21.1Syria 1970 49.0 18.7Paraguay 1972 49.4 17.0Korea, Rep. of 1970 49.6 10.7Sudan 1973 66.5 9.9Pakistan 1972 56.9 7.7Yugoslavia 1971 44.6 7.1Japan 1970 19.1 4.9Greece 1971 40.6 4.8Thailand 1970 78.2 4.1Tanzania 1967 90.1 2.9India 1971 72.0 1.6

Source: ILO, Yearbook ofLabour Statistics (1974-77).

in Malaysia and Egypt, disaggregated by farm size and familysize. As constructed here, the table reveals a markedly inverserelation between hiring in and hiring out. Large families withsmall farms hire in a small proportion of their total labor input,but hire out a large proportion of their total labor supply. Forlandless families wage employment is the only option. 3 At theother extreme, small families with large farms hire in a large

3. Evidence on landlessness in South Asia is documented in Singh (1979).


Table 26. Labor Market Participation in Malaysia and Egypt

Off-farm work as a Hired labor as apercentage of percentage of

Family total work total labor inputSize of farm a labor force b Malaysiac Egypt d MalaysiaC Egyptd

Small Large 43 33 24 6.2Small Small 43 18 25 7.3Medium Large 28 14 40 10.9Medium Small 33 4 48 21.7Large Large 16 5 59 28.2Large Small 23 3 60 52.9

a. For Malaysia, small is less than 2.1 acres, medium is 2.1 to 4.3 acres, and large ismore than 4.3 acres. For Egypt, small is 0.5 to 2 feddan, medium is 2 to 5 feddan, andlarge is more than 5 feddan. One feddan is slightly more than one acre.

b. For Malaysia, small is less than two working members, and large is two to fourworking members. For Egypt, small is less than three, and large is more than three work-ing members.

c. Data refer to males and females.d. Data refer to males only.Sources: Goldman and Squire (forthcoming), tables 4 aupd 6; Hansen (1969), tables 2

and 3.

proportion of their total labor input, but offer very little of theirown labor on the market. Rosenzweig (1978) cities similar evi-dence from a 1970-71 all-India survey of more than 5,000 house-holds, which shows that almost all cultivator household partic-ipate actively in the labor market as either buyers or sellersof labor services in addition to using family labor on the farm.Thus, 88 percent of households cultivating less than 1.5 acresused some hired labor, and 79 percent had some family membersparticipating in off-farm employment. Of the largest farms (morethan thirty acres) 96 percent hired labor and 85 percent also usedfamily labor.

This point, though perhaps obvious, has important implications.In particular, it suggests that it may not be possible to substantiateempirically the common distinction in the theoretical literaturebetween agricultural households which make decisions affectinglabor supply and demand without reference to the market wage(subsistence or utility-maximizing households) and those inwhich such decisions are dependent on the market wage (large orprofit-maximizing farmers). If the large majority of agriculturalhouseholds, regardless of farm and family size, participate in the


Table 27. Distribution of Employed Labor Forcebetween Agricultural and Nonagricultural Activitiesin Rural Areas of Selected Economies

Primary employment

Economy Year Agriculture Nonagriculture

Taiwan 1966 51 49Iran 1972 67 33El Salvador 1975 68 32West Malaysia 1970 68 3 2 aChile 1970 70 30Philippines 1970 72 28Kenya 1969 72 28Indonesia 1971 72 28Colombia 1970 77 23India 1966-67 80 20Korea, Rep. of 1970 81 19Thailand 1972 82 18Guatemala 1964 86 14Brazil 1970 88 12

a. Excludes rubber processing.Source: Anderson and Leiserson (1978), table 1.

labor market either as buyers or sellers, the subsistence modelwould seem to be a misleading representation of reality. Labormarket participation should be an important component ofmodels of agricultural households. 4 A more meaningful way ofcategorizing households would then be whether a household isa net "importer" or "exporter" of labor. Changes in the marketwage can be expected to have different implications for house-holds categorized in this manner.

A further dimension of the diversity of labor market opportu-nities is demonstrated in table 27, which shows the division of therural labor force between agriculture and other activities. In eightof the fourteen cases listed, nonagricultural activities providethe primary source of employment for more than 25 percent ofthe rural labor force. High income elasticities of demand fornonfarm goods and services suggest that, as rural incomes increase,nonfarm employment in such activities as construction, com-

4. Models of this type are described and estimated in Yotopoulos and Lau (1S 74),Lau and others (1978), Barnum and Squire (1979), Rosenzweig (1978 and 1980), andBardhan (1979a and b).


Table 28. Seasonal Variation in Labor Usagein Three Countries

Coefficient of variationa

Labor usage Malaysia Nigeria Malawi

On-farm family 0.35 0.51 0.38Total family 0.20 0.19 0.19

a. The coefficient of variation is calculated from monthly observations.Sources: Goldman and Squire (forthcoming), table 5; Anderson and Lei-

serson (1978), annex 19; and Dasgupta and others (1977), table 2-17.

merce, service, transport, processing, and manufacturing willincrease more than proportionately. 5

The existence of opportunities for nonfarm employment sug-gests the possibility that, although labor input into agriculturemay be highly seasonal, total employment, on-farm and off-farm, may be less so. For the three countries shown in table 28,the effect of seasonality is much more pronounced when onlyon-farm family labor is considered than when off-farm activitiesare allowed for. The case of Malaysia is particularly interestingbecause information is available on the total input of both familyand hired labor into agriculture. Thus, the coefficient of variationfor total farm labor input is 0.50, indicating considerable seasonalfluctuation. As shown in table 28, however, the coefficient fallsto 0.35 for family input into on-farm activities and to 0.20for total family labor. Malaysian agricultural households, there-fore, are able to offset the seasonality inherent in agriculturalproduction both by hiring in labor to lessen the burden of peak-period demands and by hiring out labor during the slacker periodsof the agricultural cycle (Goldman and Squire, forthcoming). Adiversified economy and an active labor market have, at leastin this case, minimized the impact of the natural agriculturalproduction cycle on the seasonality of employment.

In most agricultural regions, however, seasonality remains afeature. Of itself a seasonal pattern of labor does not necessarilyimply market failure. More labor is utilized in the busy seasonprecisely because the return to labor use is high, and the oppositeis true in the slack season. The operation of rural labor markets

5. For further discussion see Anderson and Leiserson (1978).


is discussed subsequently, but two points which bear directly onthe issue of seasonality are introduced here. First, in a detailedstudy of Egyptian agriculture and rural employment, Hansen(1969, figures 1, 2, and 3) demonstrates a remarkably close cor-respondence between monthly movements in labor use and ruralwages. While not conclusive, the evidence clearly suggests thatvariations in the wage rate are consistent with the efficient opera-tion of the labor market. Second, analysis of aggregate employ-ment data for Thailand demonstrates that excessively long hoursare worked during the peak rainy season (over a quarter of thelabor force averaged more than seventy hours a week) and thatwomen and youngsters participate extensively in the rainy seasonwork force (Bertrand and Squire, 1980). Such behavior is con-sistent with the view that labor responds positively to the prospectof high returns and does not, of itself, provide evidence of marketfailure.

Rural Wage Rates

Wage rates in rural areas are usually thought to be determinedeither by subsistence or nutritional requirements or else by theforces of supply and demand, the latter explanation encompassingnot only competition, but also monopsony and dualism. It isargued here that the available evidence is more consistent with thesupply-and-demand explanation of wage determination than withthe subsistence explanation. Interpretation of these conclusions,however, must allow for the possibility that rural factor marketsmay be intimately linked in the sense that those party to a tranis-action in, say, the land-rental market may simultaneously be partyto a labor market transaction.

The first class of theories rests on the assumption that, becauselabor supplies are excessive in relation to complementary factors,wages will be held down to a subsistence level. The further as-sumption that labor supply would be perfectly elastic led to thestrong prediction of constancy in real wages over some not in-significant range regardless of changes in demand. This predictionhas not.been fulfilled. Wages may well be low in rural areas, butthey are generally observed to vary over both time and space.Moreover, in cases where rural wages have been the subject of


intensive study, the observed variations have been attributed, atleast in part, to factors of supply and demand. 6

A more plausible variant of the subsistence hypothesis focuseson the relation between nutrition and worker efficiency. A posi-tive relation between wages and the efficiency of labor may makeit profitable for employers to pay labor more than the subsistencewage (Mazumdar, 1959). This theory leads to several predictionsabout the wage payment system which can be tested empiricaly.Rodgers (1975) argues that labor-tying (the use of contracts ofrelatively long duration), an inverse relation between wages andthe earner-dependent ratio, and payment in the form of mealsfor the worker are predicted by the nutritional theory. In eachcase, the employer attempts to capture the benefits of greaterworker efficiency by improving nutrition through higher wages.

Bardhan (1977) offers a detailed critique of the nutritionaltheory in the Indian context. Her basic points are that the abovepredictions are not exclusive to the nutritional theory and that therequired assumptions (oligopsony and the absence of nonagricul-tural employment opportunities) may not be valid in any generalsense. The evidence for a thorough testing of the nutritionalhypothesis is not yet available. It thus remains possilble thatemployers do attempt to influence wages in a manner consistentwith the theory, but this possibility presumably diminishes as in-come rises and the nutritional status of the labor force improves.

Among the supply-and-demand theories of wage determination,one explanation rests on the existence of dualism and asserts thatthe supply price of family labor to off-farm work lies above thatfor work on the family farm. 7 As a result, the marginal productof labor on family farms will lie below that on commercial, labor-hiring farms. One obvious test of the theory is to compare themarginal product of labor on family and commercial farms. Usingdata for India, Desai and Mazumdar (1970) demonstrate that the

6. See Hansen (1966) for the case of Egypt; Goldman and Squire (forthcoming) forMalaysia; Bardhan (1979a andb) and Rosenzweig (1978 and 1980) forevidenceonlndia;ILO (1976a) for the Sudan; and Byerlee and Eicher (1972) for a more general discussionof the African situation.

7. See, for example, Mazumdar (1965) and Mabro (1971). This theory has also beenused to explain the higher labor intensity observed on small, family farms compared withlarge commercial farms.


marginal product of labor on farms hiring labor is significantlypositive but that on farms not hiring labor it is not signficantlydifferent from zero. This apparently convincing demonstrationof dualism must, however, be interpreted with some caution.The evidence in fact reveals not a difference in behavior but adifference in technology. The marginal product on family farnsis zero, not because labor is used to the point where its contribu-tion to output becomes insignificant, but because, according tothe estimated production function, labor does not contribute tooutput at any level of production. 8 Apart from tests based onanalysis of the production function, it is difficult to confirm orreject the existence of dualism. As shown, for example, by Mabro(1971), dualism within agriculture resulting from, say, thetendency to base off-farm labor supply decisions on average ratherthan marginal product, as suggested by Lewis (1954), is perfectlyconsistent with an upward-sloping labor supply curve, given dif-ferent endowments of land and unequal access to the land-rentalmarket. Rightward shifts in the demand curve for labor wouldthen lead to an increase in the market wage as predicted by thecompetitive model. The observation that market wages are deter-mined by demand and supply factors is therefore not sufficient topreclude the existence of dualism arising from the labor supplydecisions on family farms. More detailed empirical analysis ofmicroeconomic labor supply decisions in agricultural householdsis needed before the quantitative significance of dualism in rurallabor markets can be fully assessed.

The evidence on extensive labor market participation by bothbuyers and sellers points to the likelihood of reasonably competi-tive labor markets. Regression analyses-both cross-sectional (forexample, Bardhan, 1979b) and time series (for example, Hansen,1966)-have been used to indicate the importance of supplyfactors (such as the nonagricultural wage and the proportion cfworkers dependent on wage employment) and demand factors(such as cropping intensity and the area irrigated) in explainingthe variance in the wage rate. Of particular interest is the studyof interdistrict wage differences in India undertaken by Rosen-

8. That is, the coeffiient on the labor variable is not significantly different fromzero. The study by Brown and Salkin (1974) which treats family and hired labor cnVietnamese farms as separate inputs is open to the same criticism.


zweig. He concludes: "The results appear generally consistent withthe competitive market model and indicate that rural wage levelsand a measure of landholding inequality are negatively associated"(Rosenzweig, 1978, p. 848). He argues further that the latterresult "may partly reflect the monopsonistic restrictions of wages

* and employment by relatively large landowners" (Rosenzweig,1978, p. 860).

The empirical evidence on rural wage-rate determination isscant, but that which does exist is not inconsistent with Rosen-zweig's conclusion. In Malaysia, for example, where ]Land distribu-tion is relatively egalitarian, Goldman and Squire (forthcoming)argue that the market for agricultural labor approximates thecompetitive model. In India, where land distribution is moreunequal, Bardhan (1979a), while stressing that labor markets donot clear perfectly, arrives at a conclusion similar to Rosenzweig's.Studies of wage determination in Latin America, where landdistribution is extremely unequal and many people are land-less, would be of great value in this context, but such studiesunfortunately do not exist.

The operation of nonlabor factor markets may also bear onlabor utilization and the operation of the labor market. For ex-ample, if a landlord is in a monopoly position in the land-rentalmarket, he may be able to extract cheap labor services from histenants as partial payment for access to land. Similarly, an em-ployer who is the sole source of credit may be able to take ad-vantage of indebted laborers by means of low wage payments orvarious labor-tying arrangements. The theoretical aspects as wellas the empirical foundation of contractual arrangements in two ormore markets are only now emerging as the subject of intensiveresearch. 9

Most of the theoretical work has focused on the phenomenonof sharecropping. The original Marshallian proposition assertedthat on sharecropped farms output would be determined by theequivalence of labor's opportunity cost and the tenant's share oflabor's marginal product. The marginal product of labor (andother variable factors) on sharecropped farms would thereforelie above that in alternative uses, and labor would be under-

9. Bardhan (1980) provides a survey of the basic types of interlocked factor marketsand summarizes the available empirical and theoretical literature.


utilized. In an important contribution, Cheung (1969) arguedthat the efficiency of sharecropping could be restored if the land-lord were able to stipulate the level of the variable input (labor).It is reasonable to assume that since the landlord would seek tomaximize his total rent, he would select a level of labor inputconsistent with overall profit maximization, and efficiency wouldresult. To realize this outcome, the rental contract must containan agreement (implicit or otherwise) on labor use, and the land-lord must be able to enforce that agreement at zero cost.10 In theevent that enforcement costs are positive, it is difficult to ratio-nalize the existence of sharecropping because, given perfect factormarkets, even if production -were risky, a combination of wage andfixed-rent contracts would yield the same expected income forthe landlord and eliminate enforcement costs (Newbery, 1975).

Some recent rationalizations of sharecropping rest on explicitassumptions concerning the operation of the labor market.Mazumdar (19 78), for example, argues that if the labor marketis dualistic there will be both sharecropping and cultivation withwage labor. In the absence of an adequate means of controllinglabor intensity directly, the landlord will maximize total rent byallowing sharecropping when the higher yields resulting fromdualism more than offset the Marshallian inefficiency of produc-tion. When this is not the case, the landlord will choose to culti-vate his own land with wage labor. On the basis of a more fonnalmodel in which the main cause of dualism is the uncertainty ofoff-farm employment, Newbery (1975) argues that landlordswill tend to enter fixed-rent contracts with tenants who alreaclyown and fanm sufficient land to require hired labor since thetenants will equate labor's marginal product with the marketwage. When renting to a smallholder who operates entirely withfamily labor, however, the landlord will want to restrict theamount of land rented to the point where the tenant's retainedshare of the output times labor's marginal product exactly equalsthe probability of off-farm employment times the market wage.Thus, given some initial distribution of holdings, equilibrium will

10. Alternatively, the landlord may contribute to variable costs or he may seek toprevent the tenant from accepting off-farm employment.


be characterized by the existence of both sharecropping andfixed-rent contracts and production will be efficient."

Empirical evidence on the nature of contracts and the degreeto which the same agents conduct transactions in more than onefactor market is scant; large-scale surveys have rarely focused onthis phenomenon. An important exception is a 1975-76 villagesurvey in East India reported by Bardhan and Rudra (1978). Ananalysis of responses from 275 randomly chosen villages revealedthat 68 percent of the landlords identified self-cultivation as theirprincipal occupation, more than 40 percent of the tenants receivedproduction loans from their landlords, almost 60 percent of thetenancy contracts involved cost-sharing by the landlord, andlandlords made production decisions either for, or with, more than50 percent of all tenants. The evidence demonstrates that manylandlords are farmers who take a strong interest and actively partic-ipate in the operation of tenant farms. These observations, whichsuggest that supervision costs are not prohibitive, lend supportto Cheung's view that sharecropping is efficient. Further empiricalevidence on the nature of contracts is clearly a high priority forresearch.

Bardhan and Rudra also shed light on the empirical significanceof other linkages between factor markets. On the interrelationbetween tenancy contracts and obligatory labor on the landlord'sfarm, they comment: "It is clear that rendering unpaid or under-paid services by the tenant for the landlord is far from being theprevalent general pattern." And on the link between credit andobligatory labor they note that "bonded labor seems to be arelatively unimportant phenomenon in the agrarian economy ofEastern India" (Bardhan and Rudra, 1978, pp. 377, 379). Thisis not to deny that indebtedness to employers is relatively com-monplace or that interest payments are frequently deducted fromwages. Nevertheless, only 30 percent of attached laborers hadbeen with the same employer for more than five years. Although

I 1. Bardhan (1980, p. 88) concludes: "Risky labor markets (uncertain employmentor wages), costs of monitoring intensity of labor application on the part of employees,imperfect marketability of family labor (manual as well as managerial) and of draughtanimal labor service-all of these contribute to the existence and indeed the historicalpersistence of the institution of sharecropping."


not conclusive, the evidence does suggest that, at least in EasternIndia, bonded labor is far from being the dominant, or even animportant, contractual arrangement in the labor market. As notedabove, additional empirical research on the nature of contractsand, in particular, on the manner in which market structuredevelops and responds to economic change is highly desirable. Inthis respect, Bardhan comments:

But a whole generation of social anthropologists and empiricaleconomists have shown us how over the years the traditionalsystem of obligatory payments, custom-determined rewardsand communal sharing and insurance is being eroded by thesteady penetration of market forces. This erosion process isslower in some societies than others, but even in those casesthe evolving transitional patterns show a remarkable degreeof sensitivity to market stimuli, and transactions can hardlybe described as mere expressions of social obligations. Underthe circumstances simple economic propositions regardingtransactions in such societies made on the basis of assump-tions of market imperfections (and keeping in mind thepredominance of insurance motivation on the part ofdecision-making agents under the pervasive shadow of eco-nomic uncertainties) may not be widely off the mark, eventhough organized markets are not yet fully formed (Bardhan,1980, p. 85).

Although there are a few detailed case studies and specialsurveys, those seeking an understanding of rural labor marketsmust rely for the most part on the more aggregate data exam-ined earlier. In this regard, given the evidence on high ratesof labor market participation, low rates of open unemployment,and (as shown below) high rates of geographical and occupationalmobility, the presumption should be that rural labor markets aresubject to the forces of supply and demand in either a competi-tive, dualistic, or monopsonistic setting. This presumption, how-ever, does not imply that all is well in the rural sector. The rurallabor market may work reasonably effectively yet the return tolabor may be unacceptably low. This is undoubtedly the casein many developing countries. The presumption, if substantiated,however, does indicate that a solution to the problem of low re-turns to labor is not to be found in the operation of the labor


market. Instead, it is to be sought in the distribution of land-ownership, in the operation of capital markets, in the pricingpolicy for agricultural output, or in population or educationpolicy. In other words, attention should be directed to the factorsdetermining labor demand and supply, rather than to the opera-tion of the labor market itself.

7

Rural-Urban Migration

Evidence on rural-urban migration is a primary means of demon-strating the geographical mobility of labor. The large number ofmigration studies, conducted in a variety of countries, consistentlyattest to a high degree of labor mobility, which, moreover, ismotivated in the main by economic factors. The studies also revealthat migrants are concentrated in particular subgroups of thepopulation and, contrary to some popular views, obtain employ-ment at their point of destination relatively easily. These issuesand their implications for the analysis of labor markets are dis-cussed below.

Recent Trends

The quantitative significance of rural-urban migration for thegrowth of the urban population is well documented. Table 29provides an overview of the recent historical experience in selectedlocations. The data reveal two tendencies: first, with the excep-tions of Nepal, Cambodia, and Peru, the percentage of urbanpopulation growth attributed to migration declined between the1950s and the 1960s; and second, again with exceptions such asIndia, the contribution of migration to urban growth declineswith GNP per capita. Neither of these tendencies is surprising,because they merely reflect the increasing importance of urban inrelation to rural population. The case of Brazil illustrates thispoint: in the 1960s only 37 percent of the growth in the urbanpopulation was caused by migration, and yet this amounted tcomore than 8 million migrants, almost 4 million more than in anyother country. Migration in Brazil is small only when comparedwith its existing urban population.

98

Rural-Urban Mligration 99

Table 29. Net Rural-Urban Migrationin Selected Countries, 1950- 70

Number As percentage of(thousands) urban growth

Country 1950-60 1960-70 1950-60 1960-70

Low-income countriesNepal 36 241 56.3 81.4Uganda 123 287 80.9 80.2Cambodia 123 252 53.5 76.8Tanzania 153 314 76.9 64.7Pakistan 2,464 3,524 57.9 56.1Indonesia 2,476 3,486 53.5 48.6Kenya 185 189 62.9 48.0Burma 311 403 40.1 35.6India 3,971 4,630 22.0 18.2

Middle-income countriesIvory Coast 265 566 84.4 77.2Ghana 594 959 68.9 66.6Korea, Rep. of 3,647 3,540 92.3 63.8Zambia 193 315 65.9 59.8Uruguay 392 352 66.9 58.1Malaysia 729 1,020 63.6 54.2Tunisia 267 311 59.2 53.7Algeria 727 952 61.5 51.4Bolivia 83 99 48.3 46.3Morocco 695 968 52.9 46.2Nigeria 1,677 2,759 45.3 45.0Venezuela 1,263 1,451 55.2 43.4Chile 811 855 46.8 43.2Colombia 1,432 1,840 48.6 40.8Peru 590 708 38.0 40.4Guatemala 218 305 52.8 39.0Brazil 6,345 8,360 48.3 37.1Thailand 371 552 35.8 33.4El Salvador 41 57 29.5 24.5Mexico 2,833 3,803 31.0 24.3Argentina 742 843 28.5 20.6Paraguay 25 34 15.7 13.6

Note: The estimates of rural-urban migration are derived as the difference betweenthe actual increase in urban population and its hypothetical natural increase, which isassumed equal to that of the country as a whole.

Source: Carynnyk-Sinclair (1974), tables 1, 2, and 3.


Theories

Theoretical explanations of rural-urban migration have a longhistory, dating from at least the 1880s when Ravenstein (1885 and1889) first propounded his laws of migration. The importanceof the economic motive, the negative influence of distance, andthe role of step-migration (a series of short-distance movements)were some of the features of Ravenstein's approach which havesurvived most attempts at reformulation. Sjaastad (1962), forexample, couches his explanation of the same phenomena interms of human capital theory. He argues that individuals behaveas though migration were an investment in human capital. Heemphasizes complementary investments (for example, in training)and provides a simple explanation (the length of the period neededto recoup the costs of migration) of the universal tendency formigration rates to decrease with age. The present status of thetheory owes much to the recent work of Harris and Todaro(1970). As noted above, they focus on the simultaneous occur-rence of sectoral wage differentials, urban unemployment, andrural-urban migration.

Evidence

The various theories have stimulated considerable empiricalactivity, both econometric and descriptive. Recent surveys of therapidly expanding literature provide a fairly clear view of thedeterminants and consequences of migration and of the char-acteristics of the migrants.' Their main points are outlined below.

Field studies and econometric exercises point consistently tothe importance of the economic motive in the decision to migrate.The field studies, for example, invariably report that migrantscite the possibility of higher incomes or better jobs as the primaryreason for migration. And in the econometric exercises, income orwage differentials usually emerge as the most important explana-tory variables in the estimated functions. Some studies, for ex-ample, Barnum and Sabot (1977), have also demonstrated the

1. Carynnyk-Sinclair (1974), Byerlee and Eicher (1972), Todaro (1976a), Brigg(1973), Yap (1977), and Connell and others (1976).

Rural-Urban Migration 101

importance of the expectation of employment as a separate ex-planatory variable in the manner predicted by the Harris-Todarotheory.

The other single most important factor in the migration deci-sion is distance. Migrants into large cities come primarily fromneighboring states and often from peripheral urban areas. Simi-larly, the econometric estimates show that distance bears a highlysignificant, negative relation to migration. In addition to the costsof movement and information, both of which can be expectedto increase with distance, the possibility of encountering superiorincome-earning alternatives increases with the distance betweenone's point of origin and potential destinations (Levy andWadycki, 1974).

The field studies have also demonstrated conclusively themarked concentration of migrants within certain population sub-groups. Migrants are usually under thirty years of age, are bettereducated than nonmigrants, and can be male or female in LatinAmerica but in Africa and South Asia are usually male. Theselectivity of the migration process carries with it importantimplications for the econometric specification of both the mi-gration-response functions and the independent and dependentvariables. Ideally, functions should be estimated for subgroupsof the population disaggregated according to age, education,and sex. Such detail, however, is rarely attained.2 The moreusual procedure when explaining interregional migration is tointroduce an independent variable indicating the general level ofeducation in the region of origin.

The specification of the variable designed to capture the earn-ings differential encounters similar difficulties as soon as allowanceis made for differences either between migrants and nonmigrantsor within the migrant group. The use of such variables as averagerural-urban income differentials or agricultural-industrial productiv-ity differentials is obviously unsatisfactory, both because theymeasure the return not only to labor but to all factors of produc-tion, and because they fail to recognize the heterogeneity of labor.Thailand provides an extreme illustration of this point: ruralhousehold incomes ranged from 30 percent of urban incomes in

2. The work of Barnun and Sabot (1977) is one of the few attempts to disaggregateby sex, age, and education.


Table 30. Intersectoral Wage Differentialsfor Low-skill Labor in Selected Countries

Index of low-skill wages(agricultural index = 100)

Country Year Manufacturing Construction

Guatemala 1968 208 130Chile 1966 184 124Pakistan 1972 179 164Ivory Coast 1965 178 165Morocco 1966 177 173Mexico 1972 174 180Caneroon 1972 173 159Uruguay 1972 158 139Argentina 1972 150 161Panama 1970 140 148Sri Lanka 1966 135 127Kenya 1965 134 147Tunisia 1970 132 122Malawi 1965 124 141Trinidad

and Tobago 1968 114 111Venezuela 1968 113 134India 1972 112 89Costa Rica 1972 111 139Syria 1972 101 73Zambia 1972 99 99Tanzania 1970 92 120Malaysia 1967 90 103Ghana 1965 66 66

Source: Gregory (1975), table 7.

the Northeast to 70 percent in Bangkok-Thonburi; average laborproductivity in agriculture in 1970 was only 12 percent of that innonagriculture and only 10 percent of that in manufacturing. Andyet, for a relatively homogeneous category of unskilled labor(construction workers), wages paid in the Northeast were only 15to 20 percent below those paid in the Central Plain (Bertrand andSquire, 1980). This is not to deny the existence of large geographi-cal wage differentials in some countries, but it does underline theimportant point that, unless the return to labor is carefully speci-fied, geographical or sectoral comparisons can prove extremelymisleading.

Table 30 presents data on intersectoral wage differentials forlow-skill labor. The differential between agriculture and manu-

Rural- Urban Migration 103

facturing exceeds 50 percent in eight out of the twenty-threecases, and that between agriculture and construction exceeds50 percent in six cases. These data, however, probably raisemore problems than they solve. For example, the agriculturalwage rates may be biased in some cases by the inclusion of high-paying plantations in the sample, and in other cases by the ex-clusion of payment in kind. Similarly, the reported manufacturingwages do not generally include wage supplements such as familyallowances and medical benefits, the omission of which is espe-cially significant in Latin American countries. Moreover, eventhough the focus is on low-skill labor, sectoral differences in edu-cational attainment, experience, and labor force stability can stillcause important variations in quality. These issues are discussedfurther in the subsequent analysis of urban labor markets; it isnoted here, however, that the ratio between urban unskilled andagricultural wage rates in seven developed countries in the secondhalf of the nineteenth century ranged from 1.2 in Japan to 2.0 inAustralia, with an unweighted mean of 1.6.3 Thus, the historicalexperience of the developed countries is not dissimilar to therecent experience of the developing countries in this respect:either the data for the developed countries are very inaccurate, orlarge sectoral wage differentials for labor of apparently homo-geneous quality must be considered a not unusual feature of in-dustrialization. 4

The Harris-Todaro model of migration makes the migrationdecision a function not only of intersectoral wage differentialsbut also of unemployment rates. It is of some interest, there-fore, to examine the employment experience of recent migrants.The relevant data are reported in table 31 and show that between65 and 85 percent of migrants find work within one month ofmigration. Since the probability of obtaining a job in a relatively

3. The countries and dates of observation are: Australia, 1887; Denmark, 1872;France, 1892; Hungary, 1865;Japan, 1887; the United Kingdom, 1869; and the UnitedStates, 1890. See Clark (1957), table 11. Possible explanations of such a large wage dif-ferential in the absence of obvious institutional determination of wages are discussedin chapter 7.

4. Bardhan (1979b) notes that casual agricultural laborers in West Bengal indicatedthat a wage almost 90 percent higher than their current wage would be required topersuade them to work outside their village. Since neither the location nor the natureof the hypothetical job was specified, the observation is of limited value. Nevertheless,it illustrates one possible avenue of fruitful inquiry into urban-rural wage differentials.


Table 31. Time Required for Migrantsto Find First Job in Selected Countries

Cumulative percentage finding work

Country Within Within Withinand area Immediately one month three months six months

Chile (Santiago) 43 66 n.a. 85Brazil (six cities)

Male n.a. 85 n.a. 95Female n.a. 74 n.a. 90

Korea (Seoul) 26 64a n.a. 76Per-u (Lima) n.a. n.a. 75 n.a.Tanzania

(urban areas) n.a. 80 n.a. 90Chile (poor

section ofSantiago) 47 n.a. 91 n.a.

Argentina(BuenosAires) 7 4 b 85 n.a. n.a.

Brazil (Rio deJ aneiro)

Skilled n.a. 65 n.a. n.a.Unskilled n.a. 85 n.a. n.a.

Thailand(Bangkok) 56 n.a. n.a. n.a.

n.a. Not available.a. "Soon."b. Within two weeks.Sources: Yap (1977), table 3; and Carynnyk-Sinclair (1974), table K2.

short period of time is apparently quite high, it may be inferredthat migrants are more risk averse than is usually recognized.Many migrants may in fact move only when they are assured ofa job. Moreover, unemployment rates are usually found to belower for the migrant population than for the resident popula-tion. Migrants in Santiago, for example, had a 4.0 percent un-employment rate compared with 6.5 percent for residents; simi-larly, in Bombay the rates were 4.6 percent for migrants and 8.8percent for residents. 5 Some of these differences, however, maydisappear when a control is introduced for education. The evi-dence that migrants do not experience long periods of unemploy-ment suggests that the overall urban unemployment rate may rnot

5. Reported in Yap (1977). The results hold even when the data are disaggregatedby age.


be the most appropriate measure of job prospects for migrants.Nevertheless, if allowance is made for the heterogeneity of thelabor force, skill-specific rates of unemployment surely remainimportant determinants of migration, either because job offersbecome less frequent (hence reducing the flow of risk-aversemigrants) or because job prospects seem less attractive (hencereducing the flow of those prepared to gamble).

The available evidence also suggests that migrants fare betterafter they have moved and, with the passage of time, enjoy em-ployment and income opportunities similar to those experiencedby the resident population. 6 Surveys producing such conclusions,however, are usually conducted at the point of destination andhence fail to capture the unsuccessful migrants who have returnedhome or gone elsewhere. The few case studies covering this aspectof migration suggest that disappointed or unsuccessful migrantsconstitute a relatively small proportion of total return migration. 7

It is reasonable to conclude, therefore, that the process of migra-tion improves the lot of the average migrant substantially.

Policy Implications

Labor mobility is an essential attribute of a well-functioninglabor market. The presumption is, therefore, that public policyshould be concerned with the geographical and occupationalmobility of the labor force by improving transport facilities andinformation flows. Instead, the current rates of rural-urbanmigration are often considered excessive and are thought to leadto serious unemployment and underemployment in urban areas,to increase the drain on public revenue as authorities try to main-tain minimal levels of urban services for rapidly expanding popu-lations, and to deplete the rural labor force as the more skilled,energetic, and better educated workers depart for the cities.Given the widespread acceptance of these arguments and theirpotential significance for policy formulation, they warrant specialattention.

6. Peek and Antolinez (1976), for example, demonstrate that urban natives andmigrants in San Salvador had similar incomes and employment levels. They showfurther, however, that urban-urban migrants experienced higher incomes and employ-ment levels than rural-urban migrants.

7. The available evidence is documented in Yap (1977).


From the discussion in chapter 4, it is clear that migrants donot create unemployment; unemployment owes its existence lto

labor market imperfections. If unemployment is a major concern,the appropriate policy response is to improve the efficiency of thelabor market. This approach is discussed further in the subsequentanalysis of urban labor markets. It is unrealistic, however, toimagine that all imperfections can or will be removed, in whic'hcase migration may indeed contribute to unemployment. 8 Never-theless, the individual migrant probably benefits from migration,and at least in terms of the private costs and benefits migrationcannot be considered excessive.

Social and private net benefits, however, may differ. This isquite likely to happen if distortions in product markets cause thedivergences between social and private measures of labor's mar-ginal productivity to differ in urban and rural areas. For example,if agricultural export commodities are taxed (as is rice in Thailand)and industrial import substitutes are protected, the differencebetween rural and urban labor's marginal product at marketprices will not be an adequate approximation to the difference atborder prices. Similarly, if capital is misallocated between theurban and rural sectors or within the rural sector, the demandfor rural labor will be less than would otherwise be the case. Inthis event, even if the social marginal productivity of labor is thesame in the two sectors, the sectoral distribution of labor will bebiased in favor of urban areas. In either of these cases, however,the appropriate point for policy intervention is the relevant prod-uct or nonlabor factor market and not the labor market. 9

The argument concerning the cost of urban services is relevantonly if migration necessarily results in increased public expendi-ture and if the social costs of the services exceed their social

8. Some simple models demonstrate that the creation of one urban job will induceenough migration to increase the number of unemployed and to maintain the unemploy-ment rate (Mazumdar, 1976). This is achieved, however, by assuming that the geographi-cal income differential is set exogenously, a most unlikely circumstance. Todaro (1976b)argues that the rate of unemployment may be increased by urban job creation. Hissimple empirical test, however, is criticized by Blomqvist (1978) on the grounds that itrelates to the short-run impact of small changes in the rate of job creation on the rateof change in the rate of unemployment and that job tumover is neglected. In a morerealistic version of the Harris-Todaro migration model, Collier (1979) shows that emn-ployment expansion will not increase the size of the free-entry sector.

9. The internal terms of trade between agriculture and industry and the operalionof capital markets are examined in chapter 12.


benefits. Neither condition is especially plausible. It would beequally plausible to view high rates of migration as promptingcity managers to provide services that have a net benefit to society.Provided urban services are subject to an appropriate analysis oftheir social costs and benefits, there is no reason to suppose thatmigration imposes an undesirable burden on urban public finances.Excess demand for public services can occur, however, if theyare provided free of charge or at subsidized prices. This introducesa distortion in the market for public services but not in the labormarket. If urban planners choose to satisfy the excess demand(that is, if they fail to conduct an appropriate social evaluation),then migration may be excessive. Here again, however, the pre-ferred policy measure would be to introduce an appropriatepricing policy for public services and not to intervene in the labormarket.

The argument concerning the depletion of the rural populationis more compelling but not totally convincing. If indeed thesuperior members of the rural labor force migrate, the differencebetween average rural and urban incomes may increase. It is thensometimes argued that migration has not fulfilled its expected roleof reducing geographical income differentials. This argument, ofcourse, accepts the heterogeneity of labor when describing the de-parture of "superior" labor but reverts to the assumption of thehomogeneity of labor when complaining about migration's failureto remove income differentials. A reduction in the income dif-ferentials for the particular type of labor migrating is perfectlyconsistent with an increase in the differential between averageincomes.

Nevertheless, the argument does raise important questionsabout the spatial distribution of income. The emergence of pock-ets of extreme poverty is a distinct possibility if the propensityor ability to migrate is unevenly distributed. Connell and others(19 76), for example, argue that in India most village migrationis not from the very poorest households but from the relativelypoor and the relatively rich.J° This argument suggests the needfor intervention to improve income distribution, but it does notnecessarily follow that the most appropriate mode of intervention

10. Connell and others (1976) also argue that migration is, in part, a result of themaldistribution of landownership. Villages with very unequal land distribution experi-ence higher rates of migration.


is a ban or restriction on migration. In fact, increasing the abilityof the very poor to migrate may be the best solution.

In summary, then, the usual arguments in support of restrictingmigration are misdirected. The real culprit is not migration butlabor market imperfections or ill-considered public sector invest-ment or pricing policy. The appropriate policy should be not torestrict but to encourage migration in particular and labormobility in general.

8

The Operation ofUrban Labor Markets

Large wage differentials for unskilled labor and high rates of urbanunemployment, especially for educated labor, were demonstratedin chapters 7 and 4 respectively. There is therefore a strongpresumption that, unlike rural labor markets, many urban labormarkets are imperfect. Not all markets, however, are equallyimperfect, nor are they all subject to the same type of imperfec-tion. This analysis begins, therefore, with the range of experiencein selected labor markets. It is argued that minimum wage legis-lation (especially for unskilled labor) and the hiring practices ofthe public sector (especially for educated labor) are the majorcauses of distortion (that is, intersectoral variation in the mar-ginal product of labor of homogeneous quality) and that un-certainty and inadequate information flows are the primary causesof unemployment.

It is also argued that the rural-urban wage differentials in avariety of historical and contemporary economic environmentscan be explained without invoking institutionally effected dis-tortions. The first explanation focuses on labor heterogeneity,and the second, on the disequilibrium and dynamic character ofmigration. The role of adjustments in the job expectations of theeducated unemployed is also examined.

Minimum Wage Legislation and Trade Unions

Minimum wage legislation is an important feature of labormarkets in most developing countries. The precise form of thelegislation varies considerably from country to country, as does

109


the effectiveness of its implementation.' Here, three cases areexamined in some detail to demonstrate the consequences ofminimum wage legislation where it has been effectively enforcedas well as the difficulties of enforcement. The three countriesare Puerto Rico, Mandatory Palestine (between the two WorldWars), and Thailand. The evidence presented includes the numberof workers potentially affected by the legislation, the effectivenessof implementation, intersectoral wage differentials, and thenarrowing of skill differentials. Interwoven into the argument isan assessment of the role of trade unions in the maintenance ofreal wages.

The study of Puerto Rico by Reynolds and Gregory (1965)documents perhaps the classic case of an effectively enforcedminimum wage. The evidence on the coverage of the legislation,the correspondence between movements in actual and minimumwages, and the erosion of skill differentials consistently point tlothe importance of labor legislation in the determination of wages.

In 1938 the U.S. Fair Labor Standards Act established a mini-mum wage of 25 cents an hour for all industries engaged in inter-state commerce. At that time hourly earnings in Puerto Rico fortobacco stemming and needleworking ranged from 12 to 15cents. By 1940 the minimum had been increased to 40 cents, andas a result of enforcement measures many firms suspended opera-tions and there was widespread unemployment. Relief was soonforthcoming. Tobacco stemming was exempted from the pro-visions of the wage legislation, and although other industries,especially needleworking, suffered serious short-term reductionsin exports, by the end of 1940 the minimum had been reduced to20 cents with considerable variation allowed both within andamong industries. This attempt to impose mainland U.S. legisla-tion on Puerto Rico illustrates an important point: wage legisla-tion which is greatly out of line with the prevailing economicenvironment has little chance of success.

1. Descriptions, and in some cases analysis, of minimum wage legislation in partic-ular countries are contained in: Gregory (1975) for the Philippines, Mexico, Sri Lanka,and Kenya; ILO (1970) for Colombia; Frank (1968) for Ghana and Uganda; Kannappan(1977a) for the Sudan;Joshi and others (1974) for the Ivory Coast; Atasi (1968) forSyria; Fapohunda and others (1975) for Nigeria; Guisinger (1978) for Pakistan; Bertrandand Squire (1980) for Thailand; and Reynolds and Gregory (1965) for Puerto Rico. Aninternational survey of minimum wage legislation is available in Watanabe (1976).

Urban Labor Markets 111

By 1941 additional local legislation ensured that approximately60 percent of the total Puerto Rican labor force, including agri-cultural workers, were subject to some form of minimum wagelegislation. Since that date, wage legislation has been a majorfactor in the labor market. For example, in 1955 almost 70 per-cent of the workers in seventy-six export industries receivedwages within 5 cents of the minimum; 45 percent were paid exact-ly the minimum. Moreover, changes in the minimum have beenfollowed by corresponding changes in the wages of those near theminimum. Because higher wages were not always adjusted to thesame extent, the occupational structure of wages has narrowed.After the 1955 change in the minimum from 45 to 53 cents, forexample, average hourly earnings increased by only 4 cents. 2

Reynolds and Gregory conclude: "The closeness of actual hourlyearnings in most industries to the legal minimum, the parallelismin the timing of upward movements, and the tendency for theminimum to encroach gradually on the actual earnings level allsuggest that it is minimum wage awards which have been forcingthe pace of wage advance in Puerto Rico since 1950."3 It is diffi-cult to disagree with their conclusion.

Experience in other countries, however, has been markedlydifferent, partly because Puerto Rico must be considered a specialcase. In the first place, its labor force in the 1950s was little morethan half a million. Second, by 1955 almost 70 percent of thelabor force was already engaged in nonagricultural activities.And third, GNP per capita was already US$500 (at 1954 prices)in the mid-1950s. The effectiveness and coverage of wage legisla-tion is less complete in most other countries. The examples ofThailand and Mandatory Palestine illustrate this point, as well asthe role of trade unions, but in different ways.

Minimum wage legislation in Thailand is of relatively recentorigin. First introduced in 1973 for four provinces, it was rapidlyextended to cover the whole kingdom by 1974. Of particular

2. Unemployment rates remained close to 15 percent for males and 10 percent forfemales throughout the 1950s, indicating the presence of positive rewards for job searchand the availability of income transfers or uneamed income to support the unemployed.

3. Reynolds and Gregory (1965), p. 60. They also show that employers respondedto rising wage costs by increasing the efficiency of labor use. Reynolds and Gregorydismiss trade union activity in a footnote (p. 41): "Collective bargaining, on the otherhand, is as yet poorly developed and has relatively little effect on the wage structure."


interest in the Thai case is the rather close interaction betweenthe trade union movement and the legislature. For example, in1974, within fourteen days of a demand from striking textileworkers, the government reached agreement with labor leadersand on the same day increased the minimum wage to 20 bahtper day (Bertrand and Squire, 1980). Similar evidence from othercountries suggests that, as in this case, trade unions may have theirmain impact on wages through the agency of minimum wagelegislation.

Minimum wage legislation was not nearly so effective in Thai-land as in Puerto Rico, however. To begin with, average wagesin agriculture and construction remained below the minimum.,indicating that the effect of the legislation was confined mainlyto the manufacturing sector. Second, within the manufacturingsector less than 10 percent of the workers had wages below the1974 minimum (20 baht), although almost 40 percent were belowthe 1975 minimum (25 baht). And third, rapid inflation duringthe period quickly eroded the real impact of the legislation. Never-theless, the legislation probably introduced a temporary distortionin the market for low-paid labor, especially females. This is con-firmed by evidence on the narrowing of wage differentials: forexample, the 5 baht increase in the minimum between 1974 and1975 was fully reflected in the wages of low-paid workers (mainlywomen) but not in those of high-paid workers. The overall effectof the legislation on the labor market was thus rather slight,and even for the few workers affected the implied distortion wasrelatively minor.

The role of trade unions emerges more clearly from the nextcase study. In Mandatory Palestine between the two World Wars,the Hisadrut, the Jewish labor movement, was preoccupied withthe possibility that the standard of living of the Jewish workersof European origin would be reduced to that of the local unskilledArab labor. In a fascinating piece of historical research, Sussmandemonstrates that, despite the existence of well-establishedminimum wage legislation for Jewish labor, the supply of un-skilled Arab labor "exercised a considerable downward pressure onthe wages of unskilled Jewish labor, keeping them well below theinstitutional minimum wage" (Sussman, 1973, p. 96).

Sussman's main pieces of evidence are the large numbers oi.Jewish workers earning less than the minimum, the absence of any


noticeable erosion of skill differentials, and the tendency forJewish and Arab wages to move in tandem. With regard to the firstpoint, in 1937 almost 50 percent of all urban adult male workersand more than 40 percent of all rural adult male workers earnedless than the respective urban and rural minimums. With regardto the second point, a comparison of the occupational wagestructures in 1926 and 1937 reveals little narrowing that cannotbe explained by economic forces. And with regard to the compari-son of Jewish and Arab wages, Sussman shows that manufacturingand construction wages for both types of labor moved togetherthroughout the 1930s.

Sussman (1973, p. 110) concludes that the wages of Jewishunskilled labor "were greatly affected by the supply of Arabunskilled labor and far from being exogenously deternined."Unlike Puerto Rico, where the coverage of the wage legislationwas extensive, Palestine had a plentiful alternative supply ofcheap labor, which thwarted the attempt by the Hisadrut to con-trol Jewish wages. Rather than enforce the minimum rigidly andface the consequences of a switch from expensive Jewish labor tocheap Arab labor, the Hisadrut was forced to recognize the inter-dependency of the Jewish and Arab labor markets and to allowJewish labor to be hired at wages below the official minimum.

Three case studies hardly constitute an adequate base for draw-ing generalizations. Nevertheless, the experiences of Thailandand Mandatory Palestine are similar to those of many othercountries. Trade unions often attempt to influence wages throughpolitical lobbying rather than through collective bargaining; theimpact of trade unions, therefore, is often inseparable from thatof minimum wage legislation and the pronouncements of publicwage tribunals. 4 Furthermore, the joint influence of trade union

4. Kilby (1967, p. 501) reaches a similar conclusion on the basis of his anlysis ofNigerian labor relations: "In sum, there is little doubt that trade unions have raisedwages in the organized labor market appreciably higher than they otherwise would havebeen. However, this has not been achieved by private around-the-table bargaining be-tween representatives of employers and employees as premised in the British system ofvoluntary collective bargaining; rather it has been achieved by bringing political pressureto bear on the govemment, which in turn has established independent wage tribunals."See alsoJackson (1972, p. 187) on the role of trade unions in Indian industrial rela-tions. In addition, econometric estimates have usually found the impact of trade unionson wages to be insignificant; see House and Rempel (19 76) for Kenya, and Fong (1976)for Singapore.


activity and public intervention is generally limited in coverageand effectiveness.5

Hiring Practices of Modern Sector Firms

The hiring practices of modem sector firms are frequentlythought to be another potential source of labor market distortion.Berg summarizes the argument as follows: "The root of the w;ageproblem lies in one fact; the export giants and local monopoliesare willing, and often more than willing, to pay high wages."Included in this category are the large mining companies and rnostforeign manufacturing firms. Berg, however, is ambivalent on thelabor market implications of his diagnosis. On the one hand, hepoints out that those adopting a high-wage policy can "choosethe cream of the available labor force," thereby ensuring "commit-ment to the enterprise" and the "attraction of people most likelyto be interested in acquiring skills." That is, wage differentialsreflect labor heterogeneity. On the other hand, he observes thatthe result is a "distorted inter-industry wage structure, with a fewenterprises paying rates way out of line with those in the rest ofthe economy" (Berg, 1969, p. 296). That is, wage differentialsreflect a distortion. The basic lesson of Berg's analysis is that, bythemselves, wage-rate differentials convey little information.Supplemented with other information, such as measures of laborquality, wage differentials are an important part of labor marketanalysis. This suggests that human capital and institutional vari-ables (such as the size or ownership of firms) should be consideredjointly in explanations of wage differentials.

Econometric studies incorporating both human capital variablesand institutional factors are extremely rare. Mazumdar and Ah-med's study of Malaysia, however, does provide the necessarydepth of analysis and is therefore worth describing in detail.6

Dividing their sample into unskilled, blue-collar, and white-collarworkers, the authors demonstrate that, even after controlling forvariations in education and experience within the three groups,

5. Mexico offers an example of extensive minimum wage legislation, and yet largenumbers of workers remain below the minimum (Isbister, 1971; and Gregory, 1975).Watanabe (1976) presents similar evidence for a number of countries.

6. A comparable study is that of Fong (1976) for Singapore. His conclusions parallelthose of Mazumdar and Ahmed (1978).


plant size remained a statistically significant determinant of per-sonal incomes for blue- and white-collar workers but not for un-skilled labor. The demonstration that plant size affects laborearnings does not of itself provide any explanation of the phe-nomenon. Mazumdar and Ahmed hypothesize that labor effi-ciency responds more than proportionately to an increase in thewage and that such a wage-efficiency mechanism is more likelyto be associated with large than with small plants. In other words,the quality of labor becomes a function of the wage paid. 7 What-ever the correct explanation, the authors note that as a deter-minant of the earnings of blue- and white-collar workers "the rela-tive importance of the plant size variable is small." 8

Other authors have demonstrated that in foreign-owned firms,contrary to popular belief, wages are not much higher than thosefor comparable skills in domestic firms. 9 Further light can be shedon this issue by examining wage differentials in countries whereextractive industries are important. The argument here is that themining sector often harbors many large-scale foreign firms whichpay wages well in excess of the going rates. Table 32 reveals thatin at least three cases-Zambia, Venezuela, and Chile-averagewages in mining are considerably above those in manufacturing.

The significance of the extractive sector as a source of labormarket distortion can be increased if other segments of themodern sector keep their wages in line with those in mining.Zambia in 1966 is a good illustration of this tendency: the 22percent increase in wages enjoyed by miners was followed withineight months by similar or even larger percentage increases forcentral and local government workers, shopworkers, and those in

7. This explanation receives support from the analysis of the impact of minimumwage legislation on labor productivity in Puerto Rico by Reynolds and Gregory (1965).As Mazumdar (1979) argues in a subsequent paper, however, laborheterogeneity maystill underlie the unexplained wage differential if large firms require a more stable laborforce and the supply price of stable labor exceeds that of casual or temporary workers.

8. Mazumdar and Ahmed (1978), p. 33. Knight and Sabot (1980) report similarresults for Tanzanian manufacturing. They find that the contribution of differencesin firm characteristics to wage variance was less than 10 percent of that resulting fromdifferences in employee characteristics.

9. Lim (1977), for example, reports that the basic hourly wage for 117 foreignestablishments in Malaysia was 87 cents compared with 81 cents in a sample of 191Malaysian establishments. Similarly, in Africa 53 percent of the multinational firms arereported to pay the going rate for local blue-collar workers. A further 30 percent paidno more than 10 percent above the going rate (Knight, 1975, p. 81).


Table 32. Wage Differentials and the Shareof the Labor Force in Miningfor Selected Mineral-Producing Countries, circa 1970

Wage differential Share of

Mining- Manufacturing- force in miningCountry manufacturinga agricultureb (percent)

Nigeria 1.00 n.a. n.a.Bolivia 1.15 n.a. n.a.Zambia 1.89 0.99 4.2Syria 1.30 1.01 0.8Algeria 0.66 n.a. 0.9Venezuela 2.06 1.13 1.2Chile 1.76 1.84 2.9

n.a. Not available.a. Average wages in mining divided by average wages in manufacturing.b. For low-skill labor.Sources: ILO, Yearbook of Labour Statistics, 1977; and Gregory (1975), table 7.

construction, hotels, and agriculture and by a 33 percent increasein the general minimum wage (Knight, 1975). The examplesuggests, however, that the effect of increased wages in miningwill percolate through other sectors of the economy only if it issupported by the public sector either through wage increases forcivil servants or through changes in minimum wage legislation. 1 0

In the absence of such support, it is not clear that the mining

sector by itself would be able to generate serious distortions inthe labor market, especially if the higher wages paid in miningreflect, at least in part, differences in the quality of labor and ifthe mining sector employs a relatively small part of the total laborforce."l

10. Berg arrives at the same conclusion: "where wage fixing becomes centralized ...the existence of these leading industries . .. tends to pull wages up . . . In public sectorwage discussions, in collective bargaining where it exists, in industrial courts, wageboards, and commissions of inquiry, the high-wage sector becomes the point of compari-son" (Berg, 1969, p. 298). For three out of four countries shown in table 32, however,wages for low-skill labor in manufacturing and agriculture are not markedly differ-ent.

11. In many cases, trade unions have probably exerted upward pressures on wageswithin the mining sector. The mining unions are frequently well organized and are in astrong bargaining position because labor costs are such a small part of total costs.


Social Security Legislation

Social security programs and payroll taxation can also contrib-ute to labor market distortions in certain circumstances. Themajor programs are confined to Latin America and a few Asianand African countries. Colombia, Malaysia, Mexico, Sri Lanka,Venezuela, and Zambia, for example, allocate about 3 or 4 per-cent of GDP to social security, but some countries, such as Chile,allocate about 15 percent-as much as the industrialized countries(ILO, 1976b). Worker insurance, again with exceptions such asChile, usually covers 15-20 percent of the labor force in LatinAmerica (ECLA, 1973). Australia, Canada, Sweden, and theUnited Kingdom finance a large part of their social securitypayments from general revenue, but other industrialized countriesand most developing countries rely primarily on payroll taxation.In the latter, taxation rates of about 5 percent on employees and10 percent on employers are not unusual (U.S. Department ofHealth, Education, and Welfare, 1971).

The economic consequences of payroll taxation in developingcountries have not been well studied. Nevertheless, several theo-retical and empirical arguments can be advanced conceming itsimpact. For example, the imposition of a payroll tax creates adistortion only to the extent that labor views the future benefitsfrom social security as less valuable than the current cash incomeforgone in the form of tax payments. If labor is indifferent wheth-er it receives no future benefits and a take-home wage that in-cludes an amount equal to both the employee's and employer'sshare of tax payments that would otherwise be deducted, orwhether it receives guaranteed future benefits and a wage net ofpayroll taxation, then the entire tax would be borne by labor andneither employers nor employees would change their labor marketbehavior.

Presumably employees regard the prospect of future benefitsas at least partial compensation for the loss of current earnings,but, provided the two are not exactly offsetting, labor marketbehavior will be affected. In this event, the extent to which laborbears the tax will depend on conditions in product and labormarkets. In developed countries it is usually assumed that most, if


not all, of the tax is borne by labor in the long run. Brittain(1967), for example, concluded on the basis of cross-sectionalanalysis that, at any given level of productivity, in countrieswith relatively high employer payroll taxation the basic industrialwage is relatively lower by approximately the same amount. Thisevidence suggests, but certainly does not establish, that the fullburden of payroll taxation is borne by labor.

Conditions in developing countries, however, may be suffi-ciently different to nullify this result. In one of the few empiri-cal analyses of payroll taxation in developing countries, Rosen-berg (1977) argues that the supply of labor covered by socialsecurity legislation in the Philippines is so elastic that most of thepayroll tax is borne by labor. Rosenberg, in fact, suggests theuse of payroll taxation as a source of general revenue on groundsof improving both equity and efficiency.

Hiring Practices in the Public Sector

In most developing countries civil servants and the employeesof public enterprises make up a significant proportion of the totallabor force and an even larger proportion of wage employment.Since public sector employment is also relatively skill-intensive,the public sector is often the dominant employer of educatedlabor.12 Table 33 provides two measures of the extent of publicsector employment: its share in the total labor force and its sharein total wage employment. On average," 3 almost 8 percent of thelabor force is in public service. This varies greatly among countries,however, with Latin America generally having larger shares inpublic service than either Africa or Asia. The public sector's sharein total wage employment is much more stable, with most coun-tries reporting a share of about 15 percent. Thus, total wageemployment and public sector employment apparently expandwith development at more or less the same rate.

The public sector is therefore a very important wage employer.The significance of this point is that public pay scales are generallythought to be unresponsive to changes in labor market condi-

12. Blaug (1973, pp. 31-32) suggests that in developing countries "anything fromone-third to two-thirds of all manpower with secondary education or above is employedin the public sector."

13. Unweighted mean of the twenty-four countries shown in table 33.


Table 33. Extent of Public Sector Employmentin Selected Countries

Public sectorPublic sector Public sector share inemployment share in total total wage(thousands labor force employment

Country Year of workers) (percent) (percent)a

Trinidadand Tobago 1971 80.7 25.7 n.a.

Argentina 1970 1,403.5 15.2 21.4Venezuela 1969 417.8 14.0 23.7Chile 1970 324.9 11.3 16.1Jamaica 1972 67.6 10.6 n.a.Tunisia 1972 116.6 9.6 17.8Egypt 1967-68 875.0 9.4 17.4Singapore 1974 63.1 8.7 n.a.Dominican

Republic 1973 100.2 8.6 n.a.Algeria 1969 271.0 8.3 13.8Paraguay 1969 59.5 8.2 n.a.Bolivia 1970 125.5 7.9 n.a.Sri Lanka 1966 292.0 7.0 13.0Morocco 1971 266.0 6.7 18.1Colombia 1967 313.5 4.8 n.a.Kenya 1971 206.9 4.5 n.a.Ecuador 1967 79.8 4.2 8.6Burma 1972-73 447.3 3.8 n.a.Malawi 1973 65.2 3.2 n.a.India 1974 6,209.0 2.8 16.5Zaire 1973 214.0 2.2 n.a.Korea, Rep. of 1973 216.6 2.0 5.3Ivory Coast 1970 45.0 2.0 n.a.Upper Volta 1971 30.5 1.0 n.a.

n.a. Not available.a. Data on wage employment refer to 1970.Sources: Keesing (1975), tables 10 and 1;ILO, Yearbook of Labour Statistics,

1977; and table 17 above.

tions. 14 Sri Lanka provides a striking illustration of t]he conse-quences of rigid pay scales. Government pay scales there have longfavored clerical and administrative workers over professional andtechnical workers and continue to do so. For example, a civilservant, at the highest level (Class 1, Grade 1), received a salary

14. This concern has been voiced primarily, but not exclusively, in the Africancontext. See, for example, Berg (1969), Frank (1968), Knight (1975), Doctor andGallis (1966), and ILO (1972).


Table 34. Job Preference by Level of Educationfor Unemployed Urban Males Aged 15-24with No Previous Work Experience, Sri Lanka, 1968

Job preference (percent of total)Level of education Any Unskilled Clerical Other Total

Below Standard 5 59 30 4 7 100Above Standard 8 14 5 54 28 100

Note: Students above Standard 8 have either passed 0-level examinations or corn-pleted 0-level course work; the 0 level is approximately equal to the tenth grade.

Source: Richards (1973).

60 percent higher than that of a doctor-a medical officer ofhealth (MOH 1)-in 1948 and 57 percent higher in 1967. Similar-ly, assistant clerks received 40 percent more than unskilled engi-neering workers in both 1947 and 1967. At least for these com-parisons, the salary structure hardly changed in twenty years(ILO, 1971, table 21). " And yet unemployment rates in 1963were almost 17 percent for those with secondary education and23.5 percent for those with 0-level certificates (approximatelyequal to completion of the tenth grade); by 1971 the correspond-ing figures were 22 percent and 32 percent (Richards, 1977).

Perhaps the most conclusive evidence that the rigidity of publicpay scales has distorted the market for educated labor is found inthe job preferences of the unemployed. Table 34 shows that whilealmost 60 percent of those in Sri Lanka with less than Standard5 education were prepared to accept any job, the majority ofthose with more than Standard 8 (0-level) education expressecl apreference for clerical jobs. Apart from the attraction of highwages, the public sector also offers job security and regular salaryincreases. This helps to explain why even those who had alreadyexperienced extended periods of unemployment were still pre-pared to wait for clerical jobs. 16

15. Overall, however, the occupational differentials have narrowed. Similar evidenceof slowly narrowing differentials in some African and Latin American countries isreported in Berg (1969).

16. Nearly two-thirds of those surveyed in the 15-24 age group had been unemployedfor more than twelve months (Richards, 1973, p. 49). Similar evidence of a willingnessto wait is reported by Gregory (1974) for Peru,Joshi and others (1974) for the IvoryCoast, and Mulat (1975) for the Sudan.


The rigidity of public sector pay scales and the stability of jobpreferences emerge as the most likely explanation of the high ratesof unemployment among educated workers. The rapid expansionin educational output has not elicited the appropriate response inpublic pay scales, and, with the slow rate of adjustment in jobexpectations, the result has been unemployment. Since the publicsector determines both the supply of educated workers (throughits educational policy) and the demand for them (through itsrole as employer), the solution to the problem of educated un-employment is within the immediate sphere of policy influence.

Labor Heterogeneity

Enough has been said on labor heterogeneity to warrant somedemonstration of its existence and importance. Two sources ofheterogeneity are discussed here: variation in personal attributessuch as commitment and stability, and variation in ability, experi-ence, and skill.

In a classic analysis of the historical development of the Bom-bay textile industry, Mazumdar (1973) demonstrates the signifi-cance of stability and commitment for labor market analysis. Heargues that the historically observed gap between the wage ofpermanent workers and the supply price of casual labor is notinconsistent with labor market equilibrium because permanentand casual workers do not constitute a homogeneous type oflabor. On the demand side the argument is obvious: employersprefer a stable and committed labor force because it reduces turn-over costs and ensures that the benefits of on-the-job training areretained within the firm."7 Mazumdar's contribution was todemonstrate that the supply price of permanent labor exceededthat of the casual worker because the permanent workers hadmigrated to Bombay with their families. Not only did the pres-ence of families provide a degree of stability not encounteredamong individual migrants, but also those with families hadneeded a larger inducement to migrate. The demonstration thatboth the demand curve and the supply curve for permanentworkers differed from that of casual labor is sufficient to establish

17. For a fuller discussion of employer preference for a stable labor force, seeKannappan (1966).


labor heterogeneity and explain the observed wage gap (Mazum-dar, 1973)."8 In a subsequent paper Mazumdar (1979) suggeststhat the difference between the supply price of permanent andcasual migrants offers an explanation of sectoral wage differentialsthat does not imply intersectoral misallocation of labor. In theMazumdar formulation, equilibrium is achieved by standard priceadjustments in the markets for two different types of labor. 19

The other source of labor heterogeneity, variation in experienceand educational attainment, is well documented. In a typicalstudy, Psacharopoulos (1977) demonstrates that schooling andexperience explain more than 40 percent of the variance in theearnings of full-time male employees in Morocco. Mazumdar andAhmed (1978) in their study of the Malaysian labor marketdemonstrate that both formal education and experience determineearnings but that the former is more important in large firms andthe latter in small firms. Other studies in this vein include Sanyaland Versluis (1976) for the Sudan, Fong (1976) for Singapore,and Encamacion (1974) for the Philippines. This growing body ofliterature attests to the significance of labor heterogeneity as afactor in labor market analysis.

Market Disequilibrium

Market disequilibrium provides another possible explanation ofsectoral wage differentials. 2 0 Much of the analysis associated withthe theory of the dual economy has sought to explain sectoralwage differentials in the context of long-run labor market equilib-rium. Apart from transport costs, differences in the cost of living,

18. The simultaneous use of casual and permanent workers has also been noted byKannappan (197 7 a) in the Sudan and by Standing (1978b) inJamaica. Fry (1979)provides a formal model which shows that, because of training costs and a propensityon the part of rural-urban migrants to return home at some stage during their workinglife, employers will tend to hire workers with the least attractive backgrounds in theinterests of labor force stability. Fry also reviews some of the empirical literature onthese issues, which draws on the experience of the mining industry in southern andeastern Africa.

19. See chapter 5. The argument may also explain the wage differentials observedin the developed countries during their early stage of industrialization. In addition, theargument demonstrates the existence of personal attributes that may be attractive toemployers but that are not captured in observable variables. Econometric analysis ofwage variance may therefore be missing important explanatory variables.

20. This section draws on Bertrand and Squire (1980).


and variation in labor quality, the explanation of geographicalwage differentials can be sought in this framework only in factorssuch as minimum wage legislation that distort the labor market.With rapid changes in both supply and demand conditions andsome lag in labor market adjustment, it may be more appropriateto seek the explanation of persistent sectoral wage differentialsin the dynamics of disequilibrium economics. That is, wagedifferentials can be interpreted as a manifestation of the processof labor market adjustment, rather than as a characteristic of aperfectly equilibrated market. The interaction between wagedifferentials and labor migration in the context of disequilibriumis an area for potentially fruitful research.

Labor Market Adjustment

If future labor market conditions are not known with completecertainty, with labor heterogeneity there is the possibility of anadditional mechanism of adjustment, namely, changes in the jobexpectations of the unemployed. As the duration of unemploy-ment increases, the unemployed worker may reduce his incomeexpectations-that is, the minimum wage he will accept-in orderto increase his chance of obtaining some kind of job. In Kenya,for example, "Many primary school leavers who only a few yearsago constituted the major employment problem now move rapidlyinto work which a few years ago they would have shunned" (ILO,

1972, p. 67). The operation of this adjustment mechanism thusimplies a general upgrading of the educational requirements ofcertain occupations. Such upgrading is a fundamental feature ofdevelopment; nevertheless, the forced pace of this process in manydeveloping countries may cause a rapid decline in the social rate ofreturn to education. This issue is addressed in chapter 16. At thispoint, the objective is simply to explain the operation of the mar-ket for educated labor.

Table 35 provides some indication of the transformation of thelabor force in Sri Lanka by comparing the educational composi-tion of the 15-24 age group with that of the 45-54 age group.Relatively new entrants to the labor market are on average con-siderably better educated than earlier generations: in the 15-24age group more than 60 percent had reached or passed grade 6,whereas in the 45-54 age group only 40 percent had done so. If


Table 35. Non-Estate Labor Force by Educationand Age, Sri Lanka, 1969-70

Percentage of

Educational age groupattainment 15-24 45-54

No schooling 5.1 14.6Primary, grades 1-5 31.3 45.2Middle, grades 6-10 45.6 30.8Passed 0 level 16.6 8.9Passed A levela 1.5 0.6

Total number 1,009,000 529,000

a. Equivalent to graduation from secondary school.Source: ILO (1971), table 5.

the occupational structure of wages remains unchanged, it ishighly unlikely that the structure of demand will respond to thechanges in the educational composition of labor supply. As aresult, not all of the more educated entrants to the labor forcecan obtain employment in the same type of occupation as theprevious generation. 2 1

In these circumstances, the unemployed may revise theirexpectations as the duration of unemployment increases. 2 2

Unfortunately, apart from several references to this phenomenon(such as ILO, 1972, and Berry, 1975) there is little quantitativeevidence available. An exception is a study of the labor marketin Singapore, which reported that those unemployed for morethan six months aspired to lower wages than those unemployedfor less than six months, but the changes in aspirations were notgreat (Fong, 1977). Nevertheless, if high unemployment remains acharacteristic of the economic environment for any length of time,it may be expected that subsequent generations of school leaverswill continuously revise their expectations downward.

21. Knight (1979) provides a theoretical analysis of the process of filtering down indifferent types of labor market.

22. The only data on the duration of unemployment that were immediately availableare for relatively low-unemployment countries. The duration of unemployment and theunemployment rate were ten months and 5.9 percent for the Sudan in 1974 (Mulat,1975), less than six months and 6.1 percent for the Philippines in 1972 (ILO, 1974),and less than three months and 3.7 percent for Mexico in 1970 (Keesing, 1977).

9

Policy Implications

The evidence on types of market distortion and unemploymentrates described in previous sections form the basis for judging theimportance of various policy prescriptions. In this section wagepolicies for both unskilled and educated labor are examined.

Unskilled Labor

With respect to unskilled labor, the preceding analysis suggeststhat policy prescription should be based on the following:

- Unemployment rates for unskilled labor are low in mostcountries.

- Labor is highly mobile both geographically and occupa-tionally.

- Sectoral wage differentials can be explained, at least in part,by labor heterogeneity and, in the case of spatial wage dif-ferentials, by cost-of-living differences, risk premiums, theearner-dependent ratio of migrants, and the disequilibriumcharacteristic of the labor market.

- Minimum wage legislation, the main form of intervention inthe market for unskilled labor, is limited in coverage andeffectiveness.

- Nevertheless, minimum wage legislation and trade unionactivity have distorted the market for low-paid labor insome countries.

The policy inference would appear to be obvious: abolishminimum wage legislation and control the unions. This, however,is unlikely to happen. Moreover, there are good reasons for wagelegislation and trade union support, especially where oligopsonisticconditions allow employers to take advantage of unorganizedworkers. By providing a floor, minimum wage legislation serves

125


Table 36. Numerical Simulations of the Effectof Minimum Wage Legislation on the Structureof the Labor Force and on Productivity

Assumed values

Elasticity of labor demandFormal sector 0.5 1.0 2.0 3.0Informal sector 1.0 1.5 2.5 4.0

Percentage of labor supplyFormal sector 5 10 15 20Informal sector 85 80 75 70Excess supply 10 10 10 10

Elasticity of labor supply 2.0 1.0 0.5 0.2Percentage change in the

minimum wage re-quired to eliminateexcess supply -5.0 -9.6 -17.9 -42.3

Implied values

Percentage changeLabor supply -9.9 -9.6 -9.0 -8.5Total employment +0.1 +0.4 +1.1 +1.7Formal sector

employment +2.4 +9.6 +35.9 +127.0Informal sector

employment -0.05 -0.69 -5.77 -34.09Informal sector

productivity +0.05 +0.46 +2.31 +9.52

Note: The underlying model is the exact algebraic counterpart of figure 1 in chapter4. The formulas used are:

dF dw dS dw

F F jw s w

I dwI -7I- dU=dS-dF-dI

dw 2F F d wvand -= -

w e ('F + ) + rnl j

where F = formal sector employment 5F wI = informal sector employment nF Sw FS (w) total labor supply 61U = excess labor supply nl = - Sw I

wo = minimum wagew = informal sector "wage" ES w"F = F/S(i,) and =- -

F = I/Sw Sa, ~ I/S

Policy Implications 127

a useful purpose; as a standard-setting rate for a significant por-tion of the unskilled labor force, however, it serves only to createdistortions. I

For the purpose of formulating policy, the important issue isthe quantitative significance of distortions in the market forunskilled labor. Table 36 presents some simple numerical simula-tions designed to illustrate the impact of a reduction in the mini-mum wage. The underlying model is the same as that depicted in

* figure 1 of chapter 4. The table shows the assumed values for theelasticities of demand and supply and the assumed distribution oflabor supply.2 The object of the exercise is to calculate the reduc-tion in the minimum wage required to eliminate the distortion andto examine the consequences of this reduction for the structure ofthe labor force and for marginal productivity in the informalsector.3 In each simulation, the initial distortion is set equal to anexcess supply of 10 percent of the labor force.4

The results are easily summarized. First, in every case, excesssupply is eliminated primarily by a reduction in labor supply,

1. Recommendations that minimum wages be set at levels of income in the tradi-tional or agricultural sectors of the economy have been made by Turner (1965) andThormann (1970). In the United States, for example, minimum wage rates have alwaysbeen fixed at 40 to 54 percent of average earnings in manufacturing. The practice inother developed countries-Canada and Japan-has been similar (Watanabe, 1976). Thealternative approach, wage subsidies, is not considered explicitly on the grounds that itis administratively and fiscally infeasible.

2. Estimates of elasticities of demand are subject to severe problems of simul-taneous-equation bias and aggregation bias. Most studies estimate the elasticity to beclose to one. For example, Reynolds and Gregory (1965) arrived at an elasticity of0.94 for Puerto Rico, and Harris and Todaro (1969) estimated the elasticity to be 0.76in Kenya. For the public sector, if the wage bill is thought to be fixed, the elasticity ofdemand is exactly one.

Available estimates suggest an inelastic response in household labor supply to changesin the wage, but all estimates refer to rural households. Lau and others (1978) estimatean elasticity of 0.17 for Taiwan, Barnum and Squire (1979) produce an estimate of0.12 for Malaysia, and Bardhan (1979b) reports an elasticity of 0.2 to 0.3 for hired-outlabor in India.

3. The informal sector is defined as that sector not subject to minimum wage legis-lation. It may be interpreted, therefore, as aU wage and nonwage employment outsidethe public sector, large-scale manufacturing, mining, and plantation agriculture. Givenits greater labor intensity, demand for labor is assumed to be more elastic in the informalthan in the formal sector.

4. As discussed in chapter 4, statistical measures of unemployment do not fullycorrespond to the theoretical concept of excess supply because of the discouraged-worker phenomenon and because of the existence of other labor market imperfections.


rather than by an increase in employment. 5 Second, for lowelasticities of demand (less than 2.0), the transfer of labor fromthe informal to the formal sector is negligible (less than 1 percentof employment in the informal sector), but for higher elasticities itcan become significant (more than 30 percent of informal secltoremployment). And third, the increase in marginal productivityin the informal sector is only a fraction of the reduction in theminimum wage; 6 that is, given the relative size of the two sectors,marginal products are equalized mainly by reductions in productiv-ity in the high-wage sector. The essential point to emerge is that,if the demand for labor in the distorted sector is relatively inelas-tic, and the sector's share of the total labor force is small, correc-tion of the distortion produces little increase in marginal produc-tivity in the low-income sector. On the basis of this evidence, itmay be argued that the removal of distortions in the market forunskilled labor is unlikely to have a significant impact, at least inthe short term, on the incomes of those in the low-productivitysectors. If increasing these incomes is an important objective,policies other than the removal of labor market distortions will berequired. '

This is not to deny that the removal of distortions in the marketfor unskilled labor would be helpful, especially in some countries.A brief survey of wage policies in selected locations will provide

5. The force of this result decreases with decreases in the elasticity of labor supply.At the limit, when the elasticity is zero, the analysis requires modification because thenexcess supply is also zero. This is the case when everyone has to have some kind cfemployment in order to survive. The only issue then is the removal of intersectoraldifferences in marginal productivity. From the equations given in the notes to table 36,if U= O, and aI+ crF= 1, then

dw F'7 F dw

If i7F = 1.0, r1 = 1.5, aF = 0.2, and a I 0.8, a 20 percent reduction in the minimumwage results in a 3 percent increase in marginal productivity in the informal secto-r.

6. For the four cases analyzed, the fraction is 0.01, 0.07, 0.13, and 0.20.7. In a general equilibrium analysis, de Melo arrives at substantially higher estimates

of the impact on the return to labor of a removal of urban labor market distortions inColombia. As he notes, however, "Wage differentials in the industrial sector are viewedas distortionary, and to the extent that they are not, the welfare results reported belowwill overstate the gain in efficiency from equalizing wage rates" (de Melo, 1977,13. 399).Much of my discussion has stressed the importance of labor heterogeneity in explainingobserved wage differentials. Berry and Sabot (1978) also conclude that the eliminationof labor market imperfections is unlikely to increase total welfare significantly.


some indication of the scope of improvement. 8 The cases tobe considered may be divided into two broad categories-thosewith low-wage policies and those with high-wage policies-each ofwhich may be subdivided according to the degree and nature ofgovernment intervention.

The low-wage cases have either intervened to restrain wagerates or else allowed the market to function freely. India is a primeexample from the former group: since 1953 the Indian govern-ment has sought to moderate wage demands through wage boards,industrial tribunals, and labor courts. Singapore has also exercisedwage restraint by curtailing the power of the trade unions. Thelabor market has operated relatively freely in Afghanistan, how-ever, because of the almost total absence of public interventionthere, and in Thailand because of the ineffectiveness of publicintervention. Others in the low-wage group include Argentina,Brazil, Ghana, Guatemala, Indonesia, the Republic of Korea,Malaysia, Mexico, Peru, the Philippines, Sudan, and Taiwan.

Within the low-wage category there are important differencesbetween India and Brazil, on the one hand, and Korea and Taiwan,on the other. In the first two cases the low-wage policy is as-sociated with major interventions in product and capital mar-kets, whereas the second two have sought to maintain realisticexchange and interest rates. The employment consequences ofthese different strategies are discussed further in chapter 11.

In the high-wage category a distinction may be drawn betweencountries in which the public sector has actively sought to increasewages, and those in which foreign enclaves may have initiatedwage increases. The East African countries, Nigeria, Puerto Rico,Colombia, Sri Lanka, and Pakistan fall in the first group. Thesecountries have used minimum wage legislation, public sector wagescales, and support to trade unions to accelerate wage increasesin the modern sector. 9 In the other group of countries, whichincludes Zambia, Jamaica, Trinidad and Tobago, Venezuela, and

8. This survey draws heavily on Gregory (1975) and Webb (1977).9. The temporary nature of the present categorization should be kept in mind.

For example, before 1964 Pakistan would be considered a low-wage country whereasArgentina would be in the high-wage category. Collier and Lal (1980) demonstratethis point in their analysis of Kenyan labor markets. In particular, they argue that theinterventionist policies of the decade from the late 1950s to the late 1960s that resultedin an urban "wage explosion" and unemployment have since given way to a greaterreliance on market forces.


Chile, important foreign mining enclaves have allowed wageincreases that have percolated through the rest of the modernsector. Since the foreign enclaves are usually small, however,successful percolation probably requires considerable publicsector support. The distinguishing feature of these countriesis therefore the initial source of wage increases rather than themechanism that extends them to the rest of the modem sector.

Clearly, experience is varied. The East African countries andthe mineral-producing countries apparently have the most togain from a move to a policy of wage restraint. But these may bethe exception rather than the rule. As Webb (1977, p. 246)remarks, "the 'high-wage policy' that allegedly characterizesLDCs [less developed countries], and that is routinely attacked indiscussions of employment and equity, is a misrepresentation ofwage policy in LDCs."

Educated Labor

The argument with respect to educated unemployment is bothdifferent and more complex. The basic premises are:

- Unemployment rates for educated labor are high in manycountries.

- The supply of labor with primary and secondary educationhas increased extremely rapidly.

- Public legislation and long-established pay scales have re-sulted in inflexible salary structures.

- In the absence of wage flexibility, the revision of job expecta-tions has been too slow to prevent the emergence of unem-ployment.

Once again the policy conclusion seems obvious: increase theflexibility of pay scales."0 In the short run (that is, when the stockof educated labor is given), this would have two consequences.First, the occupational structure of employment would change

10. Specific recommendations are made in, for example, ILO (1971 and 1972).For Kenya, ILO (1972) suggests an incomes policy with differential rates of increasefor low- and high-wage jobs. ILO also recommends a 25 percent cut in public salaliesfor new recruits.


in accordance with the supply and demand elasticities at eachoccupational level; this, in turn, would imply a change in theaverage educational attainment of labor within occupationalgroups in line with the relevant elasticities of substitution betweeneducational levels within any given occupational group. Andsecond, provided the supply curve of the existing educated laborforce is not perfectly inelastic, and that on average the wage foreducated labor falls, some labor would be withdrawn from themarket.

Although there is very little evidence on demand elasticitiesfor labor in general"1 and none on elasticities for labor at partic-ular educational levels or for labor in the public sector, thepresumption must be in favor of at least some elasticity. Never-theless, provided the demand for educated labor is not highlyelastic, and there is some elasticity on the supply side, someproportion of the unemployed will withdraw from the laborforce, and the investment resources embodied in them will belost to the economy. The main effect, however, will be a lowerreturn to any given level of education as the educational qualityof any particular job is upgraded. This obviously has implicationsfor educational investment.

In the long run the focus of attention switches from the marketfor educated labor to the market for education. As long as thepublic sector continues to subsidize education, private demandfor education will exceed public supply even if salary scales areflexible. It follows that other policy modifications will be requiredto prevent, or else cope with, the emergence of excess demand forpublicly provided and subsidized education. 12

In both the short and the long runs, changes in the expectationsof recent and prospective graduates may prove significant. In arapidly changing world, unemployment may reflect inadequateflows of information or a failure to adjust labor supply decisionsappropriately on the basis of the available information. Given therapid expansion in educational output and the equally rapidchanges in industrial organizations in most developing countries,labor supply decisions are almost certainly ill informed and pos-sibly ill conceived. Information services, labor exchanges, and

11. See note 2 above.12. Education policy is discussed in chapter 16.


job-placement agencies can therefore play a vital role in securinglabor market equilibrium by advancing the rate of adjustment injob expectations. 13

Conclusion

The above analysis of labor markets yields two policy con-clusions. The more important is that the removal of distortions inthe market for unskilled labor is unlikely to increase significantlythe incomes of low-productivity labor in the short run. If thealleviation of poverty is a primary goal of economic policy, themain concern should be the factors influencing labor demandand supply, and not the operation of the labor market itself.Obviously, removing distortions improves short-run allocationalefficiency and should therefore be encouraged; it also has poten-tially significant dynamic repercussions on capital accumulationwhich warrant consideration. 14 Nevertheless, the present analysissuggests that the removal of labor market distortions will be oflimited significance in many countries unless supported by othermeasures.

The second conclusion is that the high rates of educated un-employment signify not only a failure in the labor market butalso the possibility that investment in education has been over-expanded. A discussion of this possibility, however, is deferreduntil chapter 16.

13. Employment services are discussed in ILO (1971 and 1972). Both studies com-ment on the weaknesses of existing employment services and suggest country-specificimprovements.

14. This particular aspect is addressed in chapter 13.

PART III

Policies Affecting Labor Demand

If increasing the efficiency of the unskilled labor market is unlike-ly to have a major impact on labor productivity, factors whichproduce outward shifts in the demand curve for labor assumegreater importance. Because the demand for labor derives from thedemand for output and the conditions of production, any policythat affects production can also affect labor demand. Clearly,some factors will prove more influential than others. In this sec-tion three of the more important factors-industrial trade policy,the growth of agriculture, and improvements in the efficiency ofcapital markets-are examined. This is preceded by a discussion ofthe role of the tertiary (service) and informal sectors in laborabsorption, and of the implications for policy of the distinctionbetween sectors producing tradable and nontradable goods.

133

to

I

10

Labor Absorption in Servicesand Informal Activities

The rapid expansion in the tertiary sector of many developingcountries was documented in chapters 2 and 3. In particular,it was shown that from 1900 to 1960 three-quarters of the reduc-tion in the share of the labor force in agriculture was absorbedinto services.' Of itself, this need not cause concern. The highrates of rural-urban migration, however, made the absorption oflabor in low-productivity service and manufacturing activitiesa highly visible feature of most cities in developing countriesand led to the concern that "rural unemployment is being ex-ported to the urban informal sector." 2 Policy advice then stressedthe means of increasing the productivity and incomes of thoseemployed in the informal sector. The intention here is to placein perspective the "over-distension" of the tertiary sector (Bairoch,

1973, p. 74) and the role of the informal sector and to pave theway for the subsequent analysis of policy measures.

The output of most service and informal activities is not traded

internationally-a feature of great significance. First, unliketradable commodities, for which demand can often be assumedinfinitely elastic, nontradable commodities face a downward-sloping demand schedule. As a result, measures designed to in-crease nontradable productivity or output also affect productprice. Second, the demand for nontradable output depends ondevelopments in the rest of the economy-the tradable sector

1. From table l it can be seen that the reduction in the share of the labor forcein agriculture between 1900 and 1960 was approximately 7 percent; during the sameperiod the share in services increased by more than 5 percent and that in industry byless than 2 percent.

2. Bairoch (1973), for example, presents the problem as a choice between urban"over-unemployment" and rural underemployment.

135

136 Policies Affecting Labor Demand

will demand intermediate products and services, and consumerswill require final products and services. And third, nontradableproduction is not subject to the type of policy intervention-tradetariffs and subsidies-most frequently used to influence tradableproduction. Of course, trade policy ultimately affects non-tradables, but only through the restructuring of tradable produc-tion and of final consumption as a result of the original change intrade policy. Direct intervention in the output market for non-tradables usually takes the form of public production. Publicintervention can also occur in the markets for factors of produLc-tion and tradable inputs used by the nontradable sector.

This discussion suggests that before analyzing policy measuresit is appropriate to investigate further the sources of demand forservices and to examine the levels and rates of change of produc-tivity in the service and informal sectors. The underlying objectiveis to demonstrate that the observed expansion of the tertiarysector is an expected consequence of developments elsewhere inthe economy and that productivity in the service and informalsectors is not generally lower than that in other sectors.

Demand for Services

The tertiary sector is frequently treated as a source of residualemployment for the rapidly expanding population. This view,however, neglects the very obvious point that there must be acorresponding demand for the services or else they would notbe purchased; more important, it neglects the growth in demandfor services, which can be expected as the economy develops.In this respect, three different types of services are identifiedhere: "new" and "old" consumption services and intermediateservices.3

New services are those for which the income elasticity of de-mand is positive; education, health, tourism, entertainment, andleisure-time activities fall into this category. Old services have anegative income elasticity of demand and include such activitiesas petty trading and domestic services. Table 37 presents esti-mates of employment in old and new services for selected de-veloping and developed countries. The unweighted means are

3. This section draws heavily on Sabolo (1975a).

Labor Absorption in Services 137

Table 37. Employment in New and Old Servicesin Developed and Developing Countries

Percentage oftotal employment

New OldCountry Year services services

Developed countriesAustria 1961 4.4 3.4Belgium 1961 9.0 6.7Canada 1961 13.1 2.7Denmark 1960 9.6 7.9Finland 1960 7.8 3.4France 1962 8.8 4.8Japan 1960 5.4 15.2Netherlands 1960 10.0 2.0New Zealand 1961 11.1 2.3Norway 1960 8.0 5.5Switzerland 1960 13.1 10.6United States 1960 7.9 1.6

Unweighted mean 9.0 5.5

Developing countriesEgypt 1960 3.0 10.0El Salvador 1961 1.9 11.5Ghana 1960 1.2 3.1India 1951 1.3 9.7Iran 1966 3.6 7.1Mexico 1960 1.2 9.3Morocco 1960 3.7 2.0Panama 1960 10.0 9.4Portugal 1960 2.7 10.0Puerto Rico 1960 10.1 6.2Thailand 1960 1.9 2.8Turkey 1965 2.7 7.9Venezuela 1961 5.4 15.2

Unweighted mean 3.7 8.0

Source: Sabolo (1975a), tables 12 and 13. Sabolo cites national censuses as his datasources but does not describe the method used to derive his employment estimates. Seealso table 38 following.

* revealing: old services account for 8.0 percent of employmentin developing countries compared with 5.5 percent in developedcountries, whereas new services account for only 3.7 percent indeveloping countries and 9.0 percent in developed countries.

The relation between employment in services and GDP percapita can also be explored statistically. Sabolo (1975a) reportsan elasticity of 0.55 between the share of employment in new


services and income per capita, compared with an elasticity of0.35 between the share of total tertiary sector employment andincome per capita. This indicates that as incomes rise an increas-ing proportion of total tertiary employment is accounted for bynew services. In contrast, the elasticity of the share of employ-ment in old services with respect to income is reported to be-0.32; that is, as income rises, the share of employment in oldservices declines. 4

Intermediate services are demanded by other producing sectors,the government, and households. They include transport andcommunications, commerce (the net of petty traders who provideold services), banking and finance, professional services, andgovernment services. Employment in intermediate services for aselection of countries is shown in table 38. In developing countriesit accounts for almost 60 percent of total tertiary employment;that is, most of the employment in the tertiary sector is inducedby other activities.

Sabolo (1975a) shows that the share of employment in inter-mediate services is positively related to the growth of nontertiaryproduction, the elasticity being 0.2.5 This indicates that the de-velopment of agriculture and industry has an important effect onemployment in services. Other evidence, however, suggests that,by itself, the growth of industrial output does not have a signili-cant impact on employment in the tertiary sector until fairly

4. These statements are based on cross-sectional, and not intertemporal, evidence.The estimated equations are:

In EN= - 0.797 + 0.545 In Y R 0.805(0.077)

InE 0 =2.119-0.319InY R=0.552(0.093)

where EN and E 0 are the percentage of total employment in new and old servicesrespectively, Y is income per capita in 1968 U.S. dollars, and standard errorsare reported in parentheses (Sabolo, 1975a, app. 2).

5. The estimated equation is:

InE=0.794+0.2031ng R=0.911(0.008)

where E is the share of total employment in intermediate services, and g is the per-centage change in nontertiary GDP (Sabolo, 197 5a, app. 2).


Table 38. Employment in Intermediate Servicesin Developed and Developing Countries

Intermediate services

Percentage oftotal tertiary Percentage ofsector total

Country Year employment employment

Developed countriesAustria 1961 74.4 23.9Belgium 1961 63.3 27.2Canada 1961 68.4 34.3Denmark 1960 60.5 26.8Finland 1960 65.8 21.5France 1962 64.6 25.0Japan 1960 71.1 26.5Netherlands 1960 67.7 31.6New Zealand 1961 73.0 35.4Norway 1960 69.0 30.1Switzerland 1960 66.4 25.4United States 1960 62.4 57.3

Unweighted mean 67.2 30.4Developing countries

Egypt 1960 54.2 16.2El Salvador 1961 41.3 9.3Ghana 1960 81.2 18.9India 1951 40.0 7.3Iran 1966 59.0 28.7Mexico 1960 60.7 16.3Morocco 1960 71.0 14.0Panama 1960 52.1 20.6Portugal 1960 55.1 15.6Puerto Rico 1960 66.4 32.3Thailand 1960 65.4 8.8Turkey 1965 39.9 7.0Venezuela 1961 56.0 26.2

Unweightedmean 57.1 17.0

Source: Sabolo (1975a), table 20. Sabolo cites national censuses as hisdata source but does not describe the method used to derive these employ-ment estimates. Presumably, new and old services plus intermediate servicesconstitute total services.

late in the development process. For his groups of countries,Sabolo reports that the elasticity of the growth of service em-ployment with respect to the growth of industrial production ispositive and significant (0.71) in the developed countries but


positive and insignificant (0.17) in developing countries.6 Heattributes this result to the relatively immature development ofinterindustry linkages in developing countries.7 Although notconclusive, this evidence suggests that in the early stages ofdevelopment the demand for intermediate services generated byagriculture is more important than that generated by industry.

Productivity in Services

The above evidence is not entirely convincing because theincreases in employment may reflect decreases in productivity.According to the Chenery-Syrquin (1975) analysis of patternsof development, productivity in the tertiary sector declines inrelation to average productivity. Nevertheless, as shown in table39, the tertiary sector remains the most productive sector forlevels of development ranging from US$100 to US$1,000 percapita GNP at 1964 prices. Far from being a low-productivitysector, services are seen to have the highest level of sectoralproductivity. This evidence, however, must be interpreted withcare because the measurement of productivity in the servicesector, especially for government services, is problematical. Never-theless, the data do indicate that total income generated in theservice sector divided by the total labor force in services exceedsthe corresponding figures for industry and agriculture.

Informal Sector

High average levels of productivity are, of course, perfectlyconsistent with very low levels for certain groups within the ser-vice sector. Although evidence is not generally available on thenumber of people in low-productivity occupations in services,

6. The estimated equations are:

InAEL=0.116+0.168lnAX R=0.227(0.175)

andInAED=-0.030+0.7061nAX R=0.717(0.149)

where the subscripts L and D denote less developed and developed countries respective-ly, A denotes percentage change, X is secondary GDP, and standard errors arereported in parentheses (Sabolo, 1975a, app. 2).

7. Stem (1977) arrives at a similar conclusion.


Table 39. Variation in Sectoral Productivitywith Level of Development

Level of Sectoral productivitydevelopment in relation to(per capita relatonutoGNP in 1964 average productivityU.S. dollars) Primary Secondary Tertiary

Less than 100 0.73 1.60 1.68100 0.69 1.64 1.59200 0.59 1.31 1.64300 0.54 1.22 1.59400 0.52 1.17 1.52500 0.51 1.14 1.45800 0.52 1.09 1.301,000 0.55 1.07 1.22More than 1,000 0.80 1.03 1.05

Source: Derived from Chenery and Syrquin (1975), table 3 and figure 9.

considerable research has been undertaken on productivity andincome levels in the urban informal sector. As noted in chapter4, the informal sector is defined in a variety of ways, but inempirical exercises it is usually limited to own-account workersand establishments employing fewer than five workers. Thepresumption is that minimum wage legislation and other institu-tional factors have little influence on labor earnings in this sector,and that labor incomes will therefore be uniformly low becauseof the pressure of excessive labor supplies. In fact, labor incomesvary considerably, many of the self-employed express no desirefor wage employment in the formal sector, training and appren-ticeship schemes are common, and many entrepreneurs activelyseek ways to expand their operations. Much of the evidence forthese statements has emerged from the ILO's World Employ-ment Program, part of which involved a consistent analysis of theurban informal sector in selected countries. Some of the resultsare reported below.

With regard to productivity and incomes, there is ample evi-dence that many in the informal sector do at least as well as, ifnot better than, those in the formal sector. For example, theself-employed in Kumasi, Ghana, are reported to have higherincomes than those in wage employment (Aryee, 1977). Ap-proximately 65 percent of those in commerce and 75 percentof those in transport in greater Sao Paulo, Brazil, had incomes


in excess of the minimum wage. In personal services, however,only 20 percent eamed more than the minimum (Schaefer,1975). In the retail trade in Freetown, Sierra Leone, "the meanmonthly net revenue .. . exceeded the mean monthly wage ofmost semi-skilled and clerical grades within the formal wagesector" (Fowler, 1978, p. 35). The average family income ofthose in Calcutta's informal industry and trade sector in 1974was above the officially established poverty line (Bose, 1974).Average family income in the informal sector of Abidjan wasreported to be "close to or above the legal minimum wage"(Joshi and others, 1974, p. 7.11). After the deduction of alloperating costs, more than 90 percent of those in the informalmanufacturing sector of Nouakchott, Mauritania, enjoyed profitsequal to or greater than the wages received by a skilled worker inthe modem sector (Nihan andJourdain, 1978). This evidencenot only indicates the eaming capacity of those in the informalsector, but also confirms the earlier contention that the existenceof minimum wage legislation does not necessarily imply sharpeamings differentials between sectors.

Other characteristics of the informal sector attest to its dyna-mism. For example, various training activities and apprenticeshipschemes exist in the informal sectors of Abidjan (Joshi and others,1974), Freetown (Fowler, 1978), Nouakchott (Nihan andJour-dain, 1978), and Kumasi (Aryee, 1977). Expressed job preferencesare also revealing: more than 86 percent of the informal sectorparticipants sampled in Jakarta expressed a preference for self-employment (Moir, 1978); only 25 percent of those sampledin Freetown wanted wage employment rather than self-employ-ment (Fowler, 1978).

Perhaps the single most important piece of evidence to emergefrom these studies is that entrepreneurs in the informal sectorwere frequently seeking means to expand their activities butinvariably cited the high cost of capital as the main constraint. i

In summarizing the results of the African studies, Sethuraman(1977, p. 345) comments: "As a rule informal sector enterprisesfind the banks unhelpful and unsympathetic to their needs since,unlike their formal sector counterparts, they cannot provide thenecessary collateral. In Freetown, for example, banks provide

8. See Fowler (1978), Moir (1978), and Sethuraman (1977).


only 2% of investment funds in the informal sector, while inKumasi only 9 out of 298 enterprises had ever obtained a loan ofany kind from a formal credit institution." Similarly, only 1.5percent of entrepreneurs in the informal sector of Nouakchotthad started their business with a bank loan, while more than80 percent had relied on personal savings (Nihan and Jourdain,1978). Of course, if formal sector credit were available only atcompetitive rather than subsidized rates, excess demand in theinformal sector would be correspondingly curtailed. Moreover,as noted above, given the nontradable characteristic of informalsector production, expansion of output requires price reductions.For these reasons, the expressed demand for formal sector creditmust be interpreted with some reservation.

Conclusion

The above analysis of the service and informal sectors was notintended to convey the impression that all is well. On the con-trary, incomes remain appallingly low. It was intended, however,to demonstrate that (1) services and informal activities can helpgenerate employment and increase output; (2) the appropriateway to stimulate demand for the output of these sectors is toencourage the growth of output in the tradable sectors of theeconomy-especially in agriculture, at least in the early stages ofdevelopment; and (3) with respect to factor markets, the lack ofaccess to formal credit constrains expansion in the informal sector.

11

The Employment Effectsof Industrial Trade Policy

There are at least two ways of analyzing the employment impactof industrial trade policy. The first relies on intercountry orintertemporal comparisons to identify broad relationships be-tween employment generation and trade policy. The secondcompares the labor intensity of import-substituting and exportindustries without necessarily identifying the policy measuresrequired to switch production from one sector to the other.Evidence from both approaches is reviewed here.

Intercountry Comparisons

Evidence is first presented on the relation between the sectoralstructure of the labor force and the pattern of development asdefined by the Chenery-Syrquin trade and production orientationindexes (Chenery and Syrquin, 1975).1 Table 40 reveals that,both at low levels of GDP per capita (less than US$240 at 1964prices) and at higher levels, the share of the labor force in in-dustry is related to the pattern of development. The transform a-tion of the sectoral structure of the labor force has naturallyproceeded considerably further in the industrial countries thanin the primary specialization countries; it has also proceededfurther in the industrial countries than in either the balancedcountries or the import-substituting countries, at least in termsof the unweighted means. The employment elasticities, however,fail to reveal any obvious pattern.

1. On the basis of indexes of trade and production orientation, Chenery andSyrquin define four mutually exclusive development patterns: (I) primary specializationas in Malaysia and Venezuela; (2) balanced as in the Philippines and Peru; (3) importsubstituting as in India and Brazil; and (4) industrial as in Korea and Taiwan.

144

Effects of Industrial Trade Policy 145

The above confirms the expectation that trade policy influ-ences the sectoral structure of the labor force. A further ques-tion of interest is the extent to which exports themselves in-fluence the composition of the labor force. In a study of eighteendeveloping and twenty-five developed countries, Oberai (1978)demonstrates that the elasticity of modern sector employment 2

with respect to the share of exports in GDP is approximately0.2 for all countries and almost 0.5 for the subsample of develop-ing countries. 3 The composition of exports, however, did notexert an independent influence on modern sector employment:the percentage of nonprimary exports in total exports was notsignificant in almost all the reported regressions, especially whenconsidered together with the other independent variables. 4 Thissuggests that primary and nonprimary exports increase the de-mand for modem sector employment to a similar degree, theformer presumably through an increased demand for distributionand transport and also through multiplier effects.

Change in the composition of the labor force, however, doesnot necessarily imply an overall increase in the demand for labor.Information on movements in wage and unemployment ratesconstitutes important additional evidence. Such data, however,are extremely difficult to assemble for an international compari-son. Evidence is presented in table 41 for only four countries:Sri Lanka (primary specialization), Philippines (balanced), Mexico(import substitution), and Korea (industrial). The table high-

2. Defined as all professional, administrative, technical, executive, managerial, andclerical workers and all salaried employees and wage earners except those in agriculture(Oberai, 1978, p. 38).

3. The estimated equations are:

ln MA = 0.015 + 0.46 In y + 0.235 In E - 0.012 InS R2 =0 743

(7.69) (3.45) (0.17)

In ML = -0.442 + 0.528 In y + 0.484 In E R2 = 0.607(2.76) (2.33)

where M is the percentage of total employment in the modem sector, y is GDP percapita, E is the percentage of exports in GDP, S is the share of nonprimary exportsin total exports, the subscripts A and L denote all countries and less developed countriesrespectively, and t coefficients are reported in parentheses (Oberai, 1978, table 9).

4. Oberai reports essentially the same results when the dependent variable is definedas the share of wage employment in total employment. The elasticity of wage employ-ment with respect to the share of exports in GDP is 0.2 for all countries and 0.3 fordeveloping countries. The share of nonprimary exports in total exports is not signifi-cant.

Table 40: Share of Industry in Total Labor Force by Development Patternand GDP per Capita for Selected Countries, 1970

GDP per capita less than US$240 GDP per capita more than US$240

Percentage Percentageof labor Employment of labor Employmentforce in elasticity, force in elasticity,

Country industry 1960-70 Country industry 1960-70

Primary specialization

Ivory Coast 0.03 0.53 Malaysia 0.15 n.a.Sierra Leone 0.15 n.a. Iraq 0.22 1.05Sudan 0.08 n.a. Nicaragua 0.15 0.21Zambia 0.09 n.a. Venezuela 0.25 0.85Sri Lanka 0.14 0.42 Saudi Arabia 0.12 n.a.Tanzania 0.05 n.a.Uganda 0.05 n.a.


Balanced

Morocco 0.18 0.98 Guatemala 0.17 0.65Ghana 0.17 n.a. Peru 0.20 0.40Philippines 0.16 0.45 Costa Rica 0.20 n.a.Syria 0.21 0.61 Greece 0.24 0.20El Salvador 0.13 0.29 Jaaica .0.26 0.1 1

Unweighted Ireland 0.31 0.38mean 0.17 0.23

Import substitution

Bolivia 0.21 0.64 Mexico 0.23 0.45India 0.11 0.25 Chile 0.28 0.14Brazil 0.18 n.a. Uruguay 0.31 1.33Colombia 0.21 0.63 Argentina 0.32 0.02Ecuador 0.22 n.a.Turkey 0.12 0.34


Industrial

Egypt 0.19 1.24 Yugoslavia 0.29 0.55Pakistan 0.19 0.23 Portugal 0.33 0.18Korea, Puerto Rico 0.35 n.a.

Rep. of 0.20 0.67 Israel 0.36 n.a.Tunisia 0.21 0.25 Lebanon 0.25 0.69

Unweighted Singapore 0.30 0.45mean 0.23 0.31

n.a. Not available.Note: Iran, Hong Kong, Thailand, Kenya, and Taiwan were included in the Chenery-Syrquin analysis but have been omitted because their

share of the labor force in industry departed substantially from group norms. In addition, South Africa and Spain were excluded from thepresent analysis.

Source: Chenery and Syrquin (1975), table 16; ILO (1977); World Bank (1979a), table 2; and World Bank data.

Table 41. Wage Rates, Unemployment, and the Sectoral Structure of the Labor Force in Four Countries, 1950-70

Sri Lanka Philippines Mexico Korea

Year Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services

Percentage of labor force1950 57.8 12.4 29.9 66.9 11.8 21.3 61.2 16.7 22.1 74.1 6.4 19.5

1960 56.3 13.5 30.2 61.1 15.2 23.8 55.1 19.5 25.4 66.4 9.3 24.4

1970 55.1 14.4 30.5 53.2 15.8 31.0 45.2 22.9 31.9 51.0 20.1 28.9

Change,1950-70 -2.6 +2.0 +0.6 -13.7 +4.0 +9.7 -16.0 +6.1 +9.8 -23.0 +13.7 +9.4

Employmentelasticity,1960-70 0.42 0.45 0.45 0.67

Annual percentage growth in real manufacturing wages1956-60 9.9 0.5 2.4 4.4

1960-64 -0.8 -4.5 8.6 -3.7

1965-68 1.4 0.3 2.3 10.1

°° 1968-72 1.4 -1.7 1.6 6.6

1956-72 3.1 - 1.4 3.8 4.2

Unemployment rates (percent)1960 n.a. 6.3 n.a. 9.0

1970 14.0 7.6 3.7 4.5

Annual percentage growth ratesExports,

1960-70 0.5 2.9 3.2 35.7

Labor force,1960-70 2.1 2.3 2.8 2.9

GNP percapita,1960-76 2.0 2.4 3.0 7.3

n.a. Not available.Sources: ILO (1977); Webb (1977), table 2 and app. table I; ILO (1971); Keesing (1977); World Bank (1978a); and World Bank, World

Economic and Social Indicators (quarterly).


lights the difference in the transformation of the sectoral structureof the labor force and confirms the earlier results; that is, thetransformation has proceeded much more rapidly in Korea than inany of the other countries. In fact, the composition of the laborforce in Sri Lanka has hardly changed in twenty years.

Moreover, Korea has enjoyed the fastest growth in real wages,a decline in the unemployment rate, and a very rapid increase inGDP per capita. 5 Sri Lanka has experienced the highest rates ofunemployment and, at least since 1960, low rates of increase inreal wages. The Philippines has suffered a decline in real wages,and rates of unemployment between 6 and 8 percent. Mexico has

matched Korea's performance in unemployment and real wageincreases from 1956 to 1972. Since 1965, however, Mexican realwage increases have not maintained parity with those in Korea,and none of the countries has approached Korea's growth rate inGDP per capita.6

Labor Intensity of Manufactured Tradables

The disadvantage of international comparative studies is thatseveral changes usually occur at once so that convincing demon-strations of causality- are rare. As an alternative, some authorshave sought to compare the labor intensity of exports and import

substitutes. As late as 1973, however, Hsieh (1973, p. 2) com-mented that "in spite of the importance of the subject not a singlestudy has been found that devotes itself to a thorough and sys-tematic analysis of the direct and indirect effects of export

expansion on employment in developing countries." Subsequentstudies focused on the employment generated by exports withoutconsidering the possibility that employment elsewhere was cur-tailed as a result of switching nonlabor factors of production toexports. 7

In the short run, it is appropriate to treat the capital stock asgiven and investigate the employment effect of transferring aunit of capital from one sector to the other. Using this approach,Westphal (1978) reports that the labor-capital ratio for manu-

5. Additional discussion may be found in Rao (1978).6. For further evidence on the impact of export promotion, see Balassa (1977).7. Lydall (1975), Tyler (1976), and Watanabe (1972), for example, fail to exam-

ine the possibility of forgone employment elsewhere in the economy.


Table 42. Ratio of Labor Coefficients in Exportablesand Import Substitutes in Selected Countries

Direct To talCountry requirements requirements

Brazil 1.07 2.67Chile 0.81 1.07Colombia 1.93 n.a.Indonesia 2.09 1.92Kenya 0.72 n.a.Korea, Rep. of 1.25 1.23Thailand 2.21 1.70

n.a. Not available.Note: The labor coefficient is the labor content of one unit of domestic value

added.Source: Krueger (1978), table 1.

factured exports in Korea in 1966 was 3.24 compared with2.67 for domestic production and 1.98 for import substitution. 8

In a similar analysis, Krueger (1978) calculates the ratio of laborper unit of domestic value added in export and import-competingindustries in selected countries. Her results, reported in table 4-2,reveal that exportables are in general more labor intensive thanimport substitutes.

Differences in labor intensity of the magnitude reported forKorea by both Westphal and Krueger hardly seem sufficient toaccount for the substantial increase in industrial employmentrecorded in table 41. To proceed further, it is necessary to aban-don the short-run assumption of a fixed capital stock. The elirai-nation of the policy bias against exports can be expected to causea quantum increase in the marginal rate of profit in the exportsector and an increase in GDP. If the supply of capital is nothighly inelastic, two consequences may be expected. First, re-sources will be switched from import-substitution to exportindustries. And second, because of the higher overall rate ofreturn to investment in the economy and the larger GDP, therate and level of investment will also be increased. Employmentthus benefits from both a switch to a more labor-intensive modeof production and from an expansion in the capital stock. In thespecific case of Korea, for example, the capital stock in manu-

8. The figures reported are for direct factor requirements, but the analysis rermainsunchanged even if total factor requirements are considered.


facturingis reported to have increased fourfold between 1960and 1973 (Westphal, 1978, table 15). Moreover, gross investmentexpanded from 11 percent of GDP in 1960 to 27 percent in 1975(Westphal, 1978, table 1). The data attest to both the elasticityof the supply of capital and the efficiency of the capital marketand suggest that the relative factor intensities of exports and im-port substitutes may be a less interesting consideration than themagnitude of the savings response. 9

Moreover, industrial trade policy is not concerned solely withthe balance between exports and import substitutes. The effi-ciency of an industry producing exclusively for the domesticmarket can similarly be impaired by inappropriate tariff structuresor heavy reliance on quantitative import restrictions. Improve-ments in this area, therefore, can also be expected to have favor-able and dynamic effects on employment.

Conclusion

The significance of industrial trade policy in the present contextrests on its contribution to employment creation. In this respect,it appears that two conditions are necessary if a move toward freetrade is to have a quantitatively significant impact on the demandfor labor: (1) existing policies must constrain the expansion ofexports in particular or reduce the efficiency of domestic in-dustry in general; and (2) complementary factors of production-human and physical capital-must be in elastic supply.

For low-income countries existing policies may not be an ef-fective constraint on exports. The significance of industrial tradepolicy for these countries therefore lies mainly in its impact onproduction for the domestic market. The resulting increase inemployment growth, however, is likely to be small in relation tothe annual increment in the labor force. For example, if the rateof growth in industrial employment in low-income Africa and Asiawere suddenly doubled (an unlikely event), the industrial sector

9. Compared with Mexico, for example, Korea's high rate of industrial employ-ment growth (11.1 percent) is attributed primarily to its higher growth rate of industrialoutput and not to its higher employment elasticity (see table 41). In Korea output grewat 17.2 percent and the employment elasticity was 0.67; in Mexico the rate of increasein employment of 4.2 percent reflects output growth of 9.3 percent and an employmentelasticity of 0.45.


would still absorb only less than half the projected growth inthe labor force.10 Nevertheless, a rationalization of industrialtrade policy does yield an unambiguous increase in labor demaLndand should be encouraged. Moreover, apart from quantitativeconsiderations, an increase in industrial employment yields thebenefit of improved labor quality (and hence higher wages) as aresult of skill acquisition through on-the-job training.

In the middle-income countries that are still embracing import-substitution policies, a more rational trade policy will have, andin several cases has already had, a substantial effect on employ-ment."1 For these countries, the significance of industrial tradepolicy lies more clearly in its impact on production for exportand is also likely to yield more indirect employment than in low-income countries because industrial linkages are better developed.

10. The industrial sector accounts for approximately 10 percent of the labor forceand has been growing at 4 percent annually. Projected rates of annual growth for thelabor force are above 2 percent. Thus a rate of growth in industrial employment oi 8percent times the share of industry in the total labor force (0.10) equals 0.8 percent,which is less than half the growth rate of the labor force.

11. For a review of experience in fifteen countries, see Donges (1976).

12

Employment in Agriculture

Much of the literature on the transformation in the structure ofthe labor force concerns the movement of labor out of the pri-mary (agricultural) sector. This is consistent with Clark's view onchanges in the pattern of demand and intersectoral differences inproductivity growth as discussed in chapter 2. This approach,however, does not treat the time dimension explicitly and hencedoes not specify the optimal rate of transformation. It was arguedin chapter 2 that, at least in relation to the annual increment inthe labor force, the industrial sector in today's developing coun-tries has not been as successful in absorbing labor as that in thedeveloped countries of the nineteenth century. It is now arguedthat given the observed increments in the labor force some of theefforts intended to increase industrial labor absorption may haveeffectively constrained the demand for agricultural labor. Ab-stracting from labor market imperfections, this argument assertsthat the intersectoral equalization of labor's marginal productoccurs at a lower level of demand for agricultural labor than wouldotherwise be the case, because of policy discrimination againstagriculture in general and agricultural labor in particular.

Internal Terms of Trade

The import-substitution policies adopted by many developingcountries in the 1950s and 1960s have had significant implicationsfor the development of agriculture. Protection acts as a tax onagriculture because it raises the price of manufactured goods inrelation to agricultural goods in the domestic market. Moreover,import restrictions maintain the exchange rate at a higher levelthan would be the case under free trade, so that the agriculturalexporter receives less domestic currency for a given quantity ofexports.

153


Table 43. Contribution of Agriculture and Manufacturingto GDP and GDP Growth under Different Assump tionsabout Protection in Selected Economies

Ratio of value added Ratio of growth rate in valuewithout protection to added without protectionthat with protection to that with protectiona

Manu- Manu-Economy Year Agriculture facturing Agriculture facturing

Argentina 1958 1.48 0.72 1.50 0.71Brazil 1966 1.26 0.76 1.25 0.75Mexico 1960 1.08 0.91 1.13 0.89Pakistan 1963-64 1.14 0 .06 b 1.08 0 .0 0 bPhilippines 1965 1.10 0.80 1.09 0.75Taiwan 1965 1.09 0.86 1.06 0.87

Note: Value added without protection is measured by valuing tradables at worldprices and then multiplying by a factor equal to the value at domestic prices of a unitof foreign exchange. Nontradables are measured conventionally. See Little and others(1970), pp. 410-18.

a. For 1950-53 to 1964-66.b. Large-scale manufacturing only.Source: Little and others (1970), tables 2-12 and 2-13.

As an approximate measure of the bias against agriculture,table 43 shows sectoral contributions to GDP and GDP growthwith and without allowance for protection. That is, if valueadded is measured at world prices and allowance is made for anovervalued exchange rate, GDP originating in agriculture is in-creased in the Philippines, for example, by 10 percent and GDP

in manufacturing is reduced by 20 percent. Similarly, the growthrate of agricultural GDP is increased by half in the Philippineswhen measured at world prices, whereas the manufacturing growthrate is reduced by almost one-third.

The implications for labor demand of the sectoral misallocationof resources suggested by the above estimates are identical tothose discussed in the case of exports. That is, for a given capitalstock, labor demand is increased if the marginal capital-labor r atiois lower in agriculture than in manufacturing, and in the long runthe removal of the distortion in the product market will increasetotal GDP and the economy-wide rate of profit, which in turn willinduce mnore saving. Empirical evidence on sectoral capital-laborratios, however, is nonexistent. Comparisons which allow fullyfor the investment cost of increasing the availability of water andother agricultural inputs are not generally available. And, as noted

Employment in Agriculture 155

Table 44. Relative Yields and Labor Intensityby Farm Size in Colombia and Pakistan, 1960

Colombia Pakistan

Farm Relative Relative Farm Relative Relativesize value labor size value labor(hectares) addeda intensity b (acres) addeda intensity b

0-3 4.7 10.3 0-1.0 3.2 19.53-5 3.0 5.1 1.0-2.5 1.7 4.45-10 2.5 2.4 2.5-5.0 1.2 1.810-50 1.5 1.5 5.0-7.5 1.1 1.350-500 0.8 0.5 7.5-12.5 1.0 0.9500+ 0.4 0.1 12.5-25.0 1.0 0.8

25.0-50.0 0.9 0.750.0-150.0 0.8 0.6150.0+ 0.7 0.8

a. Value added per areal unit in relation to the mean.b. Labor input per areal unit in relation to the mean.Source: Berry and Cline (1979), tables 4-8 and 4-26.

in the discussion of exports, the long-run argument requires anefficiently operating capital market and an elastic supply of saving.Nevertheless, the presumption should generally be that a move-ment to restore the industry-agriculture balance will shift theeconomy-wide demand curve for labor to the right.

Farm Size

One of the most persistent findings of empirical research isthat labor intensity and yield decrease as farm size increases. Twoillustrations of this tendency are provided in table 44.1 Valueadded per unit of area on small farms (less than three hectares) inColombia is almost five times larger than the average for all farms.The corresponding figure for Pakistani small farms (less than oneacre) is 3.2. Farms of more than 500 hectares in Colombia use10 percent and farms of more than 150 acres in Pakistan use 80percent of the labor input applied per areal unit on the averagefarm.

These and similar results have attracted great attention in theliterature because they suggest the possibility of simultaneously

1. The most comprehensive compilation of evidence on this issue is contained inBerry and Cline (1979).


Table 45. Average Farm Size and Farm Size Distributionin Selected Economies, 1960

Average Gini Average Ginifarm coefficient farm coefficientsize of farm size size of farmn size

Economy (hectares) distribution Economy (hectares) distribution

Japan 1.2 0.41 DominicanIndonesia 1.2 0.55 Rep. 5.1 0.80Taiwan 1.3 0.40 Guatemala 8.3 0.83Egypt 1.6 0.60 Panama 18.8 0.74Sri Lanka 1.6 0.67 Peru 20.4 0.94Korea, Colombia 22.6 0.87

Rep. of 2.1 0.20 Nicaragua 37.4 0.B0Pakistan 2.4 0.63 Costa Rica 41.1 0.78India 2.7 0.63 Brazil 74.9 0.83Uganda 3.3 0.49 Venezuela 81.2 0.93Thailand 3.5 0.46 Paraguay 108.5 0.94Philippines 3.6 0.51 Chile 118.3 0.93Senegal 3.6 0.40 Mexico 123.9 0.75Morocco 9.8 0.64 Uruguay 195.3 0.82Kenya 11.7 0.82 Argentina 371.1 0.84Tunisia 15.4 0.65

Unweightedmean 4.3 0.53 87.6 0.84

Source: Berry and Cline (1979), table 3-3.

increasing output and improving the distribution of that outputby an appropriate land reform. Cline (1977, p. 281), for example,claims that "The single most powerful policy instrument for thecombined objectives of rural equity and output growth is landreform." The argument has been made most forcefully in theLatin American context, where the distribution of farms by sizeis highly skewed and average farm size is much larger than ineither Asia or Africa. These points emerge very clearly fromtable 45. According to the unweighted means, the Gini coefficientfor the size distribution of farms exceeds 0.8 in Latin Americabut is close to 0.5 for Asia and Africa; differences in average farmsize are even more marked, the average Latin American farmbeing twenty times larger than its Asian or African counterpart.

Before concurring with Cline's view, however, it is importantto consider the causes of the observed differences in factor use.Dynamic considerations, such as the adoption of new technolo-gies, also require attention. Moreover, apart from assessing thedesirability of land reform, it is equally essential to considerquestions of implementation. The historical experience of pastland reforms is therefore pertinent.


Distortions in Factor and Input Markets

The yields and factor usage of large farms may differ from thoseof small farms for three reasons: (1) they use different production

* technologies; (2) they face different configurations of factorand product prices; and (3) they are operated according to dif-ferent principles. 2 To treat them in reverse order, reason (3)is based on the distinction between subsistence, or utility-maximizing, farms and commercial, or profit-maximizing, farms.If for subsistence farmers the supply price of labor to off-farmemployment lies below that to on-farm employment, more laborwill be applied per areal unit, and hence yields will be higher onutility-maximizing farms (usually thought to be small) than onprofit-maximizing farms (usually thought to be large). 3 As demon-strated in chapter 6, however, the available evidence from produc-tion function analysis on this type of labor market dualism is notconvincing. Moreover, some tests of profit-maximizing behavior,based on both profit and production functions, have confirmedthat small and large farms are operated in an equally efficientmanner. 4

Reason (2) is perhaps the most frequently cited. Labor marketsare characterized as monopsonistic and capital markets as seg-mented. Monopsonistic labor markets serve to reduce the overalldemand for labor, while segmented capital markets provide asource of cheap capital for large farms. Of the two, the latterhas received more attention. Several studies, for example, haveproduced evidence of the labor-displacing effect of mechaniza-tion. In a review of the literature, Yudelman and others (1971,p. 100) conclude: "Using comparative data for owners and non-owners (of tractors) and intertemporal data for the same groupof cultivators (before and after purchasing tractor equipment),it was clearly established that the introduction of large-scalemachinery resulted in substantial reduction in the labor require-ment within the range 12-27% man-days per hectare." The authorsqualify their conclusion with the remark that "selective mechani-

2. This section draws on Barnum and Squire (1978).3. This argument is advanced by, among others, Cline (1977), Mazumdar (1965),

and Berry and Cline (1979).4. See, for example, Sidhu (1974) and Barnum and Squire (1978).


Table 46. Sources of Agricultural Loans in Selected Economies

Percentage PercentagePercentage of institu- of publicoffarmers tional loans loans inreceiving in total totalinstitutional agricultural institu tio nal

Economy loans credit loans

AfricaEthiopia 1 7 n.a.Ghana 1 n.a. 75Kenya 12 n.a. 60Morocco 10 n.a. 23Sudan 1 n.a. n.a.Tunisia 5 n.a. 90Zambia 0 0 0

Unweightedmean 4.3 - -

AsiaBangladesh 15 14 100India 20 30 87Jordan 8 n.a. 90Malaysia 2 n.a. 54Pakistan 5 14 100Philippines 28 42 38Korea, Rep.

of 40 34 100Vietnam 21 23 100Sri Lanka 14 20 100Taiwan 95 65 18Thailand 7 8 87Turkey 23 40 95

Unweightedmean 23.2 - 80.8

Latin AmericaBolivia 5 n.a. n.a.Brazil 15 83 80Chile 15 85 86Colombia 30 96 28Ecuador 18 90 26Guatemala 2 n.a. n.a.Honduras 10 n.a. 23Mexico 15 n.a. 72Nicaragua 20 n.a. 83Panama 4 n.a. n.a.Paraguay 6 n.a. n.a.Peru 17 27 85

Unweightedmean 13.1 - -

n.a. Not available.Source: Donald (1976), table 3.


zation may relieve seasonal shortages without unduly displacinglabor. However, it should be sttessed that purposive studies,considering all the aspects of selective mechanization, are lacking."Similar conclusions are reached by Bardhan (1977) in her surveyof the Indian literature, by Abercrombie (1972) in his review ofLatin American experience, and by Bartsch (1977) in his surveyof Asian experience.

Of itself, mechanization does not indicate a misallocation ofresources. Most authors writing on the issue, however, point tothe importance of interest and exchange rate policies in deter-mining the rate of mechanization. Barker and others (1972), forexample, report that, although the stated objective of the Filipinogovernment was to provide credit at favorable interest rates formechanization on small farms, the program actually served tofinance the purchase of tractors on large farms. When the pesowas allowed to float in 1970, however, the demand for loansslackened noticeably.

As shown in tables 46, 47, and 48, unequal access to creditand other subsidized inputs is a general finding. With the notableexceptions of Taiwan and Korea, institutional credit usuallyreaches less than a quarter of the farm population (table 46).Moreover, even in the case of public institutions designed to pro-vide credit to small farms, large and medium farms often receivemost of the available funds: of the fifteen such programs docu-mented in table 47, thirteen channeled less than a quarter oftheir funds to small farms. Small farms receive very few loansfrom other institutions and are forced to rely on informal sources,which charge very high rates of interest. The disparity betweenformal and informal interest rates is very apparent from table 48.Real interest rates charged by agricultural credit institutions areoften very low or even negative, whereas real rates in excess of50 percent are not unusual in the informal market.5

As a result, mechanization is concentrated on large farms. InChile in 1963, for example, farms of more than fifty hectares had93 percent of all tractors; in Colombia in 1960 they had 66 per-cent of all tractors; and in Mexico in 1960 they had 75 percentof all farm machinery (Abercrombie, 1972). The evidence is fairlyconvincing, therefore, that factor price distortions, especially

5. The real cost of providing institutional credit is estimated to range from 15 to20 percent (World Bank, 1975b).


Table 47. Percentage Distribution of Institutional Creditby Farm Size in Selected Economies

Number of loans (percent) Value of loans (percent)

Economy Small Medium Large Small Medium Large

AfricaKenya 98 n.a. 2 41 n.a. 59

AsiaBangladesh 23 50 27 18 31 51India 16 35 49 16 25 59Korea,

Rep. of 36 35 29 n.a. n.a. n.a.Malaysia 36 48 16 18 51 31Pakistan 40 45 15 23 46 31Taiwan n.a. n.a. n.a. 26 47 27

Latin ArhericaBrazil 17 45 38 1 13 86Bolivia 38 n.a. 62 6 n.a. 94Colombia 93 6 1 62 21 17Costa Rica n.a. n.a. n.a. 10 n.a. 90Ecuador n.a. n.a. n.a. 24 41 34El Salvador 85 n.a. 15 7 n.a. 93Honduras 91 n.a. 9 19 n.a. 81Nicaragua 90 n.a. 10 10 n.a. 90Peru 49 n.a. 51 21 n.a. 79

n.a. Not available.Note: The definition of "small," "medium," and "large" farms varies

among countries.Source: Donald (1976), table 4.

segmentation in the capital market, have advanced the rate ofmechanization on large farms.6

Reason (1), which asserts that large and small farms use dif-ferent technologies, is also related to the issue of unequal access tosubsidized inputs and to the rate of adoption of new techniques.High-yielding varieties of seed, inorganic fertilizers, and chem:icalpest and weed controls have frequently been adopted first on largefarms. This may reflect unequal access: large farms have moredirect contact with government programs offering seed, credit,

6. Most authors writing on rural credit programs criticize the provision of cheapcredit to large farmers. See, for example, Yudelman and others (1971), Berry andCline (1979), Cline (1977), Abercrombie (1972), Bartsch (1977), and Barker andothers (1972).


Table 48. Formal and Informal Rural InterestRates in Selected Economies

Nominal interest rates RnfZateofn

(Percent) 1967- 70

Economy Informal Formala (percent)

AfricaEthiopia 70 12 4Ghana 70 6 6Ivory Coast 150 10 4Kenya n.a. 7 0Morocco n.a. 5 2Nigeria 200 6 8Sudan 120 7 0Tunisia n.a. 6 3Uganda n.a. 12 11

AsiaAfghanistan 33 9 n.a.Bangladesh n.a. 12 3India 25 9 10Indonesia 40 14 11Iran n.a. 6 2Jordan 20 7 5Malaysia 60 18 2Pakistan 30 7 3Philippines 30 12 6Korea,

Rep. of 60 16 11Sri Lanka n.a. 12 6Taiwan n.a. 10 7Thailand 30 11 2Vietnam 48 30 28

Latin AmericaBolivia 100 9 4Brazil 60 15 22Chile 82 14 30Colombia n.a. 12 8Costa Rica 24 8 4Ecuador n.a. 10 3El Salvador 25 10 2Honduras 40 9 3Mexico 60 10 3Nicaragua n a. 10 2Peru n.a. 10 7

n.a. Not available.a. Rates charged by agricultural credit institutions.Source: Donald (1976), tables 6 and 7.


Table 49. Recent Agricultural Developmentin Japan, Taiwan, and Mexico(annual percentage rate of change)

Japan, Taiwan, Mexico,Item 1952-67 1952-67 1950-68

Labor productivity 5.8 3.3 1.8Yield 2.9 4.1 1.8Land-labor ratio 2.9 -0.8 0.0Labor force -2.8 1.0 2.2Output 3.0 4.3 4.0Area 0.1 0.2 2.2

Source: Yudelman and others (1971), table 1 and related text.

and subsidized fertilizers. It may also reflect the imperfect flowof information and differences in risk-taking behavior. Eitherway, large farms have adopted the seed-fertilizer-irrigation packagemore quickly than small farms. 7 This is of considerable signifi-cance because the package is universally considered to be land-augmenting (that is, other things being equal, more labor can beapplied efficiently to a given amount of land to achieve a largeroutput). Cline (1977), however, suggests that adoption willgradually spread to smaller farms, especially if credit and inputscan be effectively channeled to them.

Recent Evidence

The recent experience of Japan, Taiwan, and Mexico illustratesthe interactions of land distribution, the availability and spreaclof technological innovations, and productivity in agriculture. 8 Therelevant data are reported in table 49. In all three places agri-cultural output has increased by at least 3 percent. In Japan andTaiwan the increase in output is accounted for almost entirely byincreases in yield, since land area remains virtually constant. Thissuggests that technological change has been land-augmenting inboth countries. The 5.8 percent growth rate of labor productivityin Japan, however, is much higher than that recorded in Taiwan(3.3 percent). This, in turn, suggests that at least in Japan technol-ogy has also been labor-saving. Yudelman and others (1971)

7. Evidence on this point is provided in Yudelman and others (1971), Bardhan(1977), and Cline (1977).

8. This section is based on Yudelman and others (1971).


document changes in inputs which support these inferences. Theyconclude: "the technology of Japanese agriculture has beenadapted to circumstances that are similar to those in many labor-scarce developed countries. A decline in the labor force in agri-culture has been accompanied by the introduction of labor-savingtechnology, along with the continued use of high-yielding tech-nology. In Taiwan, though, a continuing increase in the number ofpeople engaged in agricultural production has tended to obviatethe need for the introduction of a labor-saving technology"(Yudelman and others, 1971, p. 108).

The development of agriculture in Mexico has been quitedifferent. Over half the increase in output is attributed to an ex-pansion in the area cultivated. Both labor productivity and yieldshave increased at rates considerably lower than those recorded inJapan and Taiwan. For the present purpose, the most importantinference to be drawn from table 49 is that, in terms of theaggregate growth rates of labor productivity and yields, therehas been no labor-saving technological change and little that island-augmenting. The available data on input use, however, belieboth these assertions: between 1950 and 1960 the agriculturaluse of tractors per worker increased twofold, and between 1948and 1968 the total consumption of fertilizers increased at anannual average rate of 15.6 percent (Yudelman and others, 1971).

The discrepancy between the evidence on increases in inputsand the observed changes in the aggregate growth rates of laborproductivity and yields is resolved by an examination of thestructure of Mexican agriculture. Unlike that in Japan and Taiwan,agriculture in Mexico consists of a small modern sector and a largetraditional sector. The modem sector supports market-orientedfarms with an average holding in 1960 of 27.3 hectares. Thetraditional sector contains small private farms of less than fivehectares and most of the communal lands, or ejidos, and it oc-cupies 70 percent of the agricultural labor force. Mechanizationand the use of fertilizers have been concentrated in the modernsector, where the yields of the principal crops-wheat and cotton-have increased noticeably. In the traditional sector, output growthfor such crops as corn and beans was induced primarily by an ex-pansion of acreage. Thus, despite an increased use of both land-augmenting and labor-saving technologies in the modem sector,economy-wide yields and labor productivity failed to show anymarked improvement.


An important difference between the Japanese and Taiwaneseexperience, on the one hand, and the Mexican experience, on theother hand, lies in the diffusion of technical knowledge and thedistribution of inputs. The size distribution of landholdings isclearly one possible explanation of this difference. In Japanand Taiwan land reform conferred rights of ownership within anexisting, fairly even distribution of agricultural units, and thecharacteristic family farms were retained. In Mexico, however,land reform involved expropriation and redistribution of onlypart of the total land area, and ownership of expropriated landwas entrusted to the communal tenure of ejidos.

Other factors, however, were also important. For example,while irrigation facilities cover a substantial part of the total culti-vated area in Japan and Taiwan, in Mexico they are confined lto

the regions where large commercial farms predominate. Similarly,the use of fertilizer is widespread in Japan and Taiwan but is con-fined to the irrigated areas, and hence the modem sector, inMexico. Moreover, information on fertilizer and other inputs iseffectively disseminated to all farmers in Japan and Taiwanthrough farmers' associations, which also organize the distributionof inputs, market the output, and provide credit. Similar institu-tions do not exist to the same extent in the traditional sector ofMexico. The modem sector, however, has access to government-subsidized credit for the purchases of farm machinery.

Policy Inference

For policies affecting labor demand, the evidence clearly pointsto the virtues of land-augmenting technological change and ofselective, but not general, mechanization. The outstanding ques-tion is which policies are appropriate for ensuring that the desiredtechnological developments actually occur.

Some authors view the evidence on farm size, yields, and laborintensity as a clear indication of the desirability of land reform.In their discussions, however, the same authors point to the un-equal access to credit, fertilizer, and seed as an important factorunderlying the observed variation in yield and labor input. Thissuggests the possibility that the efficiency gains claimed by landreform can be achieved by improvements in market operationwithout reformation of the landownership system. It is important


to recognize, however, that in some countries land reform may bea necessary precondition for the successful implementation ofefficiency-increasing policies. Wherever possible, considerationshould be given to the removal of incentives-such as subsidizedcredit, subsidized fuel, and overvalued exchange rates-favoringmechanization; the diffusion of public sector investment in irri-gation, transport and communications, and extension servicesthroughout the agricultural sector; the provision of equal accessto credit regardless of farm size;9 and increased support for agri-cultural research at both the national and international levels.

Improvements in product and capital markets of the typesuggested here may perhaps be the only way to increase employ-ment substantially in the short run, especially in low-incomecountries where agriculture's share of the labor force still exceeds70 percent. Agriculture offers considerable scope for factor sub-stitution both within and between crops. Indirect employmenteffects are also likely to be important in these countries, moreas a result of agricultural than industrial expansion.

In the event that land reform is still considered desirable, itscosts and benefits should be assessed primarily in terms of itsimplications for income distribution. Short-run costs of implemen-tation have been high in some cases, and the commitment to re-form has sometimes been less than complete.1 0 The pursuit oftenurial stability and security may be politically more acceptableand can be expected to confer the benefits of dynamic effi-ciency.' 1 It is essential, however, that reforms of both land andtenure be accompanied by the widespread provision of inputs,credit, services, and information as described above, if productiv-ity is to be increased.

9. Reviews of agricultural credit systems are provided in World Bank (1975b) andDonald (1976).

10. Land reform experience in several countries is reviewed in World Bank (1975a).11. Bamum and Squire (1978) show that tenant farmners in Malaysia are as efficient

as owner-operators in a static sense.

13

Capital Markets

At various points in Part III reference has been made to the signif-icance of an efficiently operating capital market. The discussionof the urban informal sector, for example, pointed out the de-mand by small-scale entrepreneurs for access to formal channelsof subsidized credit. Precisely the same point arose in the dis-cussion of agricultural development, where it was argued thatsegmented capital markets have had significant implications forlabor demand: the availability of cheap credit to large farmshas encouraged labor-displacing mechanization, while the highcost of informal credit has generally retarded the adoption of theland-augmenting water-seed-fertilizer technology. In addition,it was suggested that export-led growth in, for example, Korea wasfacilitated by the operational efficiency of the capital market: theresponse of saving and investment to higher levels of GDP andincreased possibilities for profit was in part the result of a well-developed capital market.

The existence of highly localized and fragmented capital rnar-kets clearly points to the possibility of gains in the efficiency ofresource allocation from market unification. 1 This is analogous tothe argument in chapter 4 concerning the removal of policy-induced distortions in the labor market. There the objective wasto remove intersectoral wage differentials resulting from, forexample, labor legislation. Here the objective is to remove dif-ferentials caused by interest rate ceilings and the like. Fragmentedcapital (and labor) markets also result from transport and informa-tion costs. In this event, market unification may still yield thebenefits of efficiency but only at a cost.

The manner in which improvements in the capital marketimpinge on the demand for labor is complicated. Four effects,however, seem potentially important. First, for a given level of

1. This is the central theme in McKinnon (19773).

166

Capital Markets 167

institutionally provided credit, assume that allocation by ration-ing in a market restricted to preferred customers is replaced byprice allocation in a market open to all entrepreneurs. In thisevent, the impact on the demand for labor will depend on thetechnological characteristics of production of the previouslypreferred and the newly accepted customers and on the realloca-tion of investable resources between the two groups. Second,assume that the increase in the lending rate of interest impliedby the first effect leads to an increase in the deposit rate. Assumefurther that the economy-wide rate of saving (including self-investment) remains unchanged. Again an improvement in re-source allocation will occur because financial saving will now makeup a larger share of total saving. The resulting decline in low-yielding self-financed investment will allow a correspondingexpansion in higher-yielding market-financed investment. 2 Theultimate impact on labor demand will depend on the productiontechnologies involved as before.

Third, the improvement in static resource allocation impliedby the previous two effects may affect the economy-wide rate ofsaving, including self-investment. If this rate is assumed to in-crease, as a result of the higher level of GDP, labor demand wouldbe affected favorably. And fourth, the capital market may befurther improved by expanding the array of financial assets avail-able to the potential saver and reducing transaction costs. Thisshould unequivocally increase the overall level of saving and hencethe demand for labor. 3

The above suggests that improvements in the operational effi-ciency of the capital market will have a static impact on labordemand (the first and second effects) that depends crucially onthe technology of production in different sectors of the economy.The dynamic impact (the third and fourth effects), however,depends on the determinants of savings behavior. Some of theavailable empirical evidence on these issues is reviewed below.

Capital-Labor Ratios

Within manufacturing the available evidence, albeit scant,indicates that investment per job increases with the scale of in-

2. This particular effect is examined in terms of a two-sector model by Galbis(1977).

3. See, for example, Bhatt (1978).


Table 50. Fixed Assets per Job in Direct Employmentfor Four Countries(U.S. dollars)

Size of India, Colombia, Mexico, Philippines,enterprise 1965-73 1974 1970 1970

Small 278 3,000 3,700 1,020Medium 557 n.a. 9,500 2,850Large 2,450 13,400 14,500 8,000

n.a. Not available.Note: The data reflect investment decisions made five to twenty years previously.

Allowance for depreciation and inflation would change the absolute numbers but nottheir relative size. Rough estimates suggest that at 1976 prices average fixed assets perjob would lie in the range of US$1,000 to US$3,000 for small enterprises and betweenUS$10,000 and US$20,000 for medium and large enterprises.

Source: World Bank (1978b), table 1-2.

vestment. The data in table 50, for example, suggest that small-scale manufacturing enterprises use four to ten times more laborper unit of fixed investment than their larger counterparts. Verymuch lower figures than those shown in table 50 have beenreported for manufacturing enterprises operating in the urbaninformal sector. According to Fowler (1978), for example, capitalper worker in the manufacturing enterprises of Freetown's in-formal sector averages less than US$60. 4 Other estimates for Indiaand Ghana reveal equally low figures (Bose, 1974, and Aryee,1977).

Apart from lower capital-labor ratios, there is also some evi-dence that value added per unit of capital is higher in small-scale manufacturing units. The relevant data are reported intable 51. For India, Malaysia, and Mexico an inverse relationbetween establishment size and capital productivity is confirmed,but the relation is much less clear in Pakistan and is reversed in thePhilippines.

Neither capital productivity nor labor intensity, however, is asatisfactory measure of overall efficiency. The most that can beestablished from the available data is that small firms are laborintensive and that there is no reason to suppose that they areinefficient. Nor is there any reason to suppose that large-scaleenterprises are necessarily inefficient. Nevertheless, if access tocredit is extended to all enterprises at competitive rates, the

4. This figure does not include working capital or the value of land and buildings.

Table 51. Capital Productivity by Size of Enterprise for Five Countries

India Malaysia Mexico Pakistan Philippines

Ratio Ratio Ratio Ratio Ratioof of of of ofvalue value value value value

Number added Number added Number added Number added Number addedof to of to of to of to of toworkers capital workers capital workers capital workers capital workers capital

Small 1.6 1-9 2.01 1-5 1.34 1-9 2.15 5-19 0.96Medium 0.95 10-19 1.30 6-15 0.76 10-19 0.75 20-49 0.98Large 0.29 20-29 1.32 16-25 0.65 20-49 0.97 50-99 1.24

30-49 1.05 26-50 0.64 50-99 1.46 100-199 1.2550-99 1.41 51-75 0.64 100-249 1.16 200-499 1.18100-199 1.02 76-100 0.66 250-499 0.81 500+ 1.11200-499 0.77 101-250 0.62 500-999 0.65500+ 1.13 251-500 0.61 1,000+ 1.20

500+ 0.61Average 1.03 1.07 0.64 0.99 1.13

Note: The table reports the ratio of value added to fixed capital. For Malaysia the book value of fixed assets excludes land. For Mexico,Pakistan, and the Philippines the book value of fixed assets includes land.

Source: World Bank (1978b), table 1-5.


small-scale sector can be expected to expand in relation to thelarge-scale sector because the previous differential access tosubsidized credit clearly favored larger enterprises. 5

The resulting gain in employment, however, cannot be de-rived immediately from a comparison of labor intensities be-cause, if the wage-rental ratio is changed, some impact on factorproportions can be expected. Small-scale enterprises will curtailtheir use of labor and large-scale enterprises will expand it. De-pending on the relative magnitudes of the sectoral elasticities ofsubstitution, returns to scale, and the initial distribution of em-ployment between large and small enterprises, the overall effecton labor demand could be strengthened or weakened. The ulti-mate impact on labor demand thus remains ambiguous. 6

The case for capital market unification in agriculture is stronger.The evidence on the labor-displacing effects of mechanization andthe land-augmnenting effect of the water-seed-fertilizer packagehas already been described. If credit is made available to all farmsat competitive rates, it may be expected that the rate of mechani-zation will be reduced and that more farms will be able to adoptthe water-seed-fertilizer technology. The realization of eitherexpectation will have a favorable impact on labor demand.

Determinants of Saving

The determinants of saving in developing countries, especiallyin rural areas, remain unclear. In a recent survey of the econo-metric literature, Saito (1977) reports that a positive relationbetween saving and income is confirmed and that, in poorercountries at least, the marginal propensity to save is an increasing

function of household income. The relevance of the permanentincome hypothesis (that consumption expenditure is not undulyinfluenced by temporary fluctuations in income) for developingcountries is also supported, since the marginal propensity to savefrom transitory income exceeds that from permanent income.

5. An extreme example is reported in Guisinger (1978). He claims that between1960 and 1972 smal investors faced user costs of capital more than twice those of theirlarge-scale counterparts.

6. Available evidence on factor substitution possibilities is discussed in recent re-views by White (1978) and Pack (1978). Programs providing technical and other typesof assistance to small-scale enterprises are described in Neck (1977).

Capital Markets 1 71

The available evidence on the relation between interest ratesand household saving is contradictory and inconclusive. The fewempirical studies that investigate this relation are open to method-ological criticisms and subject to data deficiencies, especiallywith respect to the interest rate variable. A recent study in ruralIndia represents one of the more careful attempts at identifyingthe determinants of saving. Among the findings of this study are:First, the marginal propensity to save is an increasing function ofincome within a certain range of income levels. Second, thepropensity is related positively to the expected rate of return onfarm investment. And third, subsidized credit for rich farmersdepresses their propensity to save (Bhalla, 1976).

Although confirming a positive and increasing marginal propen-sity to save, available studies provide no indication of the relationbetween the overall adequacy of the financial system and saving,where "adequacy" denotes a variety of qualitative characteristics,such as range and availability of services, as well as the structureof interest rates. Several case studies, however, illustrate the possi-bilities of mobilizing saving. Saito (1977), for example, reports thesuccess of the Post Office Savings Scheme in mobilizing saving inSri Lanka despite negative real rates of interest. Nonprice attri-butes, such as low risk and accessibility, were thought to haveattracted savers in this instance.

The Syndicate Bank in India provides a striking example of adetermined effort to reduce the transaction costs associated withthe provision of banking services to small-scale farms and enter-prises. 7 In 1968, 30 percent of its loans were to agriculture andsmall enterprises and 90 percent of its deposit accounts were foramounts under Rsl,500. The Syndicate Bank was able to providethese services and earn a profit because its costs for lending toagriculture and small enterprises were less than a third of thoseincurred by the city banks, and its administrative costs for mo-bilizing deposits were also much lower than those of the citybanks.

Bhatt (1978, p. 11) attributes the efficiency of the SyndicateBank to "the creative adaptation of the banking tec]hnology tosuit local conditions." In particular, he cites the socioeconomicbackground of the original promoters of the bank, the bank's

7. This description is based on Bhatt (1978).

1 72 Policies Affecting Labor Demand

recruitment and promotion policies, the provision of technicalservices to farmers and industrialists, the emphasis on decen-tralized decisionmaking, and innovations such as the Farmers'Protection Deposit Scheme and the Pigmy Deposit Scheme.

These deposit schemes are worth describing in more detailbecause of the possibility of duplicating them elsewhere. Theguiding principle for the Farmers' Protection Deposit Scheme wasthe recognition of a particular motive for saving: crop insurance.The deposit pays interest at the annual rate of only 5 percent, butthe depositor was granted the right to borrow up to twice theoutstanding deposit at a rate of 9 percent in the event of cropfailure. The scheme demonstrated that operators of small farmsare prepared to save, even at low rates of interest, in order toeliminate, or at least reduce, a major cause of concern.

The Pigmy Deposit Scheme illustrates the importance ofreducing transaction costs for the potential depositor. Door-to-door agents collected a given amount at stated intervals, so thatsmall amounts could be saved on a daily, weekly, or monthly biasiswithout the need for frequent visits to the bank. The cost to thebank proved lower than the cost of other types of deposit, andPigmy Deposits soon became an important part of total deposits.

Other successful programs have been based on cooperativeassociations. The National Agricultural Cooperative Federation inKorea and the Farmers' Associations in Taiwan are cases in point.Both institutions have pursued a policy of high interest ratesto attract savings and have provided a variety of complementaiyservices to borrowers to ensure full productive use of investableresources.

Conclusion

The analysis suggests that the short-run impact on the demandfor industrial labor of eliminating nonprice rationing in the formalcapital market cannot be discerned from the available evidence.The impact on agricultural labor demand, however, will be posi-tive. In the long run, the elimination of nonprice rationing or thereduction in transaction costs will have a potentially significan-timpact because saving is responsive to both increases in GDP andimprovements in financial services.

14

Synthesis

Much of Part III has stressed the dynamic consequences of im-provements in resource allocation. Except in the case of agricul-ture, it is argued that a more efficient allocation of resources willincrease employment, not because of changes in the sectoraldistribution of a given quantity of investable resources, butbecause of the dynamic ramifications of the resulting increasedrate of capital accumulation.' The concentration on allocationalefficiency follows immediately from the delimitation of the pres-ent exercise; 2 the importance attached to dynamic consequences,however, is a judgment based on the preceding analysis. 3

As a partial test, this judgment can be confronted with theavailable evidence on the relation between sectoral output andemployment growth. By definition, the employment elasticityequals the ratio of the rate of growth in employment to that ofoutput. If dynamic considerations prevail, the intercouantry correla-tion between employment and output growth will be high, whilethat between employment growth and the employment elasticitywill be low. If all countries had the same employment elasticityand employment growth were determined solely by outputgrowth, the correlation coefficient relating employment and out-put growth would be unity, while that relating employmentgrowth and the employment elasticity would be zero.

The significance of this test is increased if it is confined toeconomies at relatively similar stages of development, which have

1. This echoes the conclusion on improvements in the efficiency of labor marketsadvanced in chapter 9.

2. See chapter 1.3. This judgment is apparently shared by the ILO. Although one of the premises

of the World Employment Program is that high growth rates have not necessarily yieldedcorrespondingly high rates of employment growth, three of the recent comprehensivecountry reports have recommended strategies which entail higher GDP growth ratesthan those observed in the recent past (Thorbecke, 1973).

173

1 74 Policies Affecting Labor Demand

adopted different development strategies usually thought to havesignificantly different implications for factor usage. Accordingly,fourteen semi-industrialized economies were selected.4 Althoughall are in the middle-income range, they have used a variety ofindustrial strategies ranging from import substitution in Colombiaand Mexico to export promotion in Korea and Taiwan. The sarnegroup also offers a wide range of agricultural strategies embracingthe bimodal approach of Colombia and Mexico as well as theunimodal approach of Korea and Taiwan.

The results are easily summarized. For industry the correlationcoefficient between employment and output growth is 0.79 whilethat between employment growth and the employment elastic-ity is 0.24. For agriculture, however, the results are reversed, thecorresponding coefficients being 0.06 and 0.82. Although notconclusive, the results are consistent with the argument thatdynamic considerations prevail in the industrial sector, whereasin agriculture variations in factor proportions associated withstatic resource allocation predominate. 5

4. They are Argentina, Colombia, Greece, Republic of Korea, Mexico, Philippines,Portugal, Singapore, Spain, Taiwan, Tunisia, Turkey, Uruguay, and Yugoslavia.

5. The test focuses on the relation between employment and output and excludesother factor inputs. Nevertheless, if the relation between employment and output issimilar among economies and yet their production is characterized by different factorintensities, the difference must reflect variations in technical efficiency (that is, the useof less of one or more inputs for a given level of output) rather than variations in alloca-tive efficiency or factor price ratios.

PART IV

Policies Affecting Labor Supply

The historical and cross-sectional analyses of chapters 2 and 3demonstrated the marked differences in population growth rates,levels of education, and rates of expansion in educational facili-ties. The high rate of unemployment among the educated wasreviewed in chapter 4. In the present section, the role of popula-tion and education policies in determining the quantity andquality of the labor supply is assessed.

175

S * . v~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

15

Population Growthin Economic Development

It was demonstrated in chapter 2 that population growth in thedeveloping countries today exceeds by a considerable margin therates of growth experienced by the developed countries through-out the nineteenth century. It was shown in chapter 3 that growthrates in the 1960s varied among regions: Latin America experi-enced the highest rates followed by Africa, Asia, and, at a con-siderable distance, the developed countries of Europe and NorthAmerica.

Consequences of Rapid Population Growth

The high fertility rates in most developing countries mean thatage structures bulge disproportionately at the younger ages andsuccessive age cohorts increase in size.' These characteristics inturn imply that: (1) a greater proportion of resources is requiredto feed, clothe, and educate the young, thereby reducing the avail-ability of resources for productive investment; (2) a greater pro-portion of investment is required to equip new entrants to thelabor force, thereby limiting the extent to which capital perworker can be increased; 2 and (3) a larger stock of labor is ap-plied to fixed factors, such as land, resulting in diminishingreturns.

Tables 52 through 54 substantiate these points by providinginformation on the age structure of the population by region for1975 (table 52), gross domestic investment per new labor marketentrant for selected countries in 1975 (table 53), and the growth

1. This section draws on King (1978); see also Enke (1971).2. Growth of the labor force is essentially determined by the growth and age struc-

ture of the population. See chapter 3 and Stolnitz (1974).

177

178 Policies Affecting Labor Supply

Table 52. Estimated Age Structureof the Population by Region, 1975(percent)

Region 0-4 5-14 15-64 65+

Eastern Africa 18.5 26.4 52.4 2.7Middle Africaa 17.0 25.6 54.5 2.9West Africa 18.4 26.4 52.7 2.5Southern Africa 17.5 23.5 55.1 3.9North Africa 17.1 27.2 52.5 3.3Middle East (including

Turkey) 17.1 26.0 53.0 3.9South Asia (including

Iran) 16.5 26.4 54.1 2.9Southeast Asia (including

Burma, Philippines) 17.0 26.6 53.4 3.0East Asia (excluding

China, Taiwan, Japan) 13.3 24.8 58.3 3.6Caribbean 14.5 26.2 54.2 5.1Central America

(including Mexico) 17.9 27.9 50.9 3.4Tropical South America 16.5 26.6 53.8 3.1Temperate South America 10.6 19.8 62.3 7.3North America 7.9 17.6 64.3 10.2Europe 7.7 16.2 63.8 12.9Japan 9.1 15.4 67.7 7.8

a. Includes Angola, Central African Empire, Chad, Congo, Equatorial Guinea, Gabon,Cameroon, and Zaire.

Source: United Nations, Selected World Demographic Indicators by Countries, 1950-2000 (New York, May 1974); as reported in King (1978), table 3.

rates in crop area and agricultural population for selected coun-tries from 1970 to 1975 (table 54). As expected, table 52 revealssharp differences between the age structures of the developed andthe developing regions, but within the latter group differences arenot marked. Table 53 provides some indication of the variation ingross domestic investment per new entrant to the labor market:a rich country with a slowly growing population such as Franceis able to invest rhore than US$250,000 in each new labor marketentrant, whereas a poor country with a faster growing population,such as Ethiopia, has little more than US$1,000 available for eachnew worker. Much of this difference, however, must be attributedto variations in national income rather than in population growth.The effect of rapid population growth on social investment may

Population Growth 179

Table 53. Gross Domestic Investmentper New Labor Market Entrant in Selected Countries, 1975

Grossdomestic

Gross Rate of investmentdomestic labor Increase per labor

Gross investment force in labor forcedomestic (millions growth, force, entrantinvestment/ of U.S. 1974-75 1974-75 (U.S. dol-

Country GDP dollars) (percent) (thousands) lars)

Ethiopia 10.5 278 2.0 234 1,190Bangladesh 6.1 563 1.6 402 1,400Burma 10.5 376 1.6 203 1,850Tanzania 21.3 543 2.4 152 3,570Pakistan 15.6 1,718 2.5 479 3,590Zaire 33.9 745 1.9 199 3,740Sri Lanka 16.4 434 2.5 116 3,740India 22.0 18,352 2.0 4,619 3,970Kenya 19.6 617 2.6 132 4,680Indonesia 19.0 6,756 2.2 1,003 6,740Thailand 26.8 3,837 2.9 536 7,160Ghana 10.6 556 2.1 76 7,320Korea,

Rep. of 26.8 5,121 3.0 562 9,110El Salvador 20.1 370 3.3 40 9,250Colombia 17.3 2,325 3.2 237 9,810Senegal 15.5 316 1.7 32 9,900Cameroon 21.4 467 1.4 43 10,850Philippines 31.1 4,908 2.7 410 11,970Egypt 27.3 3,394 2.5 257 13,210Morocco 23.6 1,875 2.8 125 15,000Nigeria 28.9 7,766 2.1 507 15,320Peru 18.6 2,617 3.0 132 19,820Turkey 22.7 8,049 1.8 302 26,650Brazil 25.4 31,194 2.9 966 32,300Syria 31.4 1,654 2.6 48 34,460Mexico 28.8 22,764 3.3 550 41,390Iran 29.8 16,266 2.6 237 68,630Algeria 57.4 7,809 2.8 102 76,560Yugoslavia 33.0 10,214 1.3 125 81,720Argentina 21.4 10,589 1.2 118 89,740United

States 15.4 231,800 1.7 1,555 149,070Japan 32.5 158,457 1.4 796 199,070France 22.5 75,588 1.3 287 263,370

Source: World Bank data reported in King (1978), table 2.


Table 54. Average Annual Growth Rates of Crop Areaand Agricultural Population for Selected Countries, 19 70-75

Average annual growth rate (percent)

Agriculturalpopulationper square

Total Agricultural kilometerCountry population Crop area population of crop area

Pakistan 3.0 0.1 2.2 2.1Sri Lanka 1.7 0.0 2.0 2.0Nepal 2.1 0.2 2.1 1.9Egypt 2.2 0.1 1.8 1.7Dominican

Republic 2.9 0.6 2.4 1.8India 2.1 0.2 1.7 1.5El Salvador 3.1 0.9 2.2 1.3Burundi 2.1 0.9 1.9 1.0Indonesia 2.4 0.5 1.4 0.9Bangladesh 2.0 0.9 1.5 0.6Mauritius n.a. 0.2 -0.1 -0.3Vietnam 2.6 2.0 1.6 -0.4Philippines 2.8 2.5 1.9 -0.6Haiti 1.6 1.2 0.4 -0.8Thailand 2.9 3.7 2.8 -0.9Korea,

Rep. of 1.8 0.7 -0.6 -1.3Barbados n.a. 0.0 -1.4 -1.4Jamaica 1.8 0.8 -1.9 -2.7Rwanda 2.3 5.5 2.4 -3.1Trinidad and

Tobago 1.1 3.1 -0.4 -3.5Netherlands 0.9 -0.6 -3.3 -3.9Japan 1.4 -0.6 -4.4 -5.0Lebanon 3.0 1.4 - 3.7 - 5.1

n.a. Not available.Sources: Land use: Food and Agriculture Organization (FAO), Production Year-

book, voL 30 (1976). Projections of agricultural population: FAO, based on U.N.medium variant projections. As reported in King (1978), table 6; and World Bank(19 7 8a).

be more important. For example, Zymelman (1976b) showsthat although a "typical" developing country spends the sameproportion of GDP on primary education as a "typical" OECDcountry, its enrollment rate is only half that of the OECD coun-try. Unit costs expressed as a percentage of GNP per capita are notdifferent, but the proportion of school-age children is twice aslarge in developing countries as in the OECD countries. Finally,


table 54 shows that the increasing pressure of population on landis apparent only in countries such as Pakistan where the popula-tion is growing rapidly and agriculture remains the dominantsector.

Population Growth and GNP per Capita

It is generally concluded from the above arguments that higherrates of population growth result in lower rates of growth in GNP

per capita than would otherwise be the case. For example,between 1965 and 1975 annual growth in GNP in low-incomeAfrica, low-income Asia, Western and Northern Europe, and NorthAmerica and Oceania was in the range 3.5 to 3.9 percent. Growthin GNP per capita in the former two regions, however, was halfthat achieved in the latter two regions because of differing popu-lation growth rates. 3 Despite this demonstration, however, moststudies indicate no obvious relation between the growth rates ofpopulation and of income per capita. Easterlin (1967), Kuznets(1965), and Chesnais and Sauvy (1973) failed to find any statisti-cally significant relation, whether positive or negative, in varioussamples of developing countries, while Conlisk and Huddle (1969),Hanson (1973), and Thirlwall (1972) demonstrate a slight posi-tive relation.

The absence of any simple negative correlation between popu-lation and income per capita growth rates, however, is not al-together surprising. Population growth is only one of manyfactors affecting the rate of increase of income per capita. 4

Clearly, a more complex model, incorporating both demographicand economic factors, is required. Several such models exist andconsistently demonstrate that moderate population growth rates(less than 1.5 percent) produce higher rates of growth in per capitaincome than high population growth rates (more than 2.5 per-cent). 5 The same conclusion is reached by Simon, who explicitlyconsiders several arguments that imply a positive relation betweenpopulation growth and the growth of GNP per capita. In partic-

3. King (1978), table 1.4. For an exchange on the role of population growth in the determination of the

growth of income per capita see Hanson (1973) and Enke (1973). Cassen (1976) pro-vides a well-balanced account of the arguments on both sides of this debate.

5. See, for example, Enke (1971 and 1974), and Blandy (1972).


ular, Simon allows for increased effort on the part of those withlarge families, economies of scale associated with larger popula-tions, an industrial investment function responsive to changes indemand, and an agricultural savings function responsive to changesin the capital-output ratio in agriculture. These factors notwith-standing, Simon (1976, p. 335) concludes that "positive popula-tion growth produces considerably better economic performancein the long run (120 to 180 years) than does a stationary popu-lation, though in the short run (60 years), the stationary popula-tion performs slightly better" and that "moderate populationgrowth (doubling over 50 years [that is, an average annual growthrate of 1.4 percent] ) performs better in the long run than eitherfast population growth (doubling over 35 years [2.0 percent ayear] ) or slow population growth (doubling over 200 years [lessthan 0.4 percent a year] )." He suggests that "the 'best' rate ofgrowth in terms of long-run output per worker (or income perconsumer equivalent) is relatively slow growth under somereasonable set of conditions-a doubling in perhaps 90 years [thatis, an average annual growth rate of 0.7 percent] -whereas withsome other sets of conditions the doubling time for the besteconomic performance is considerably shorter" (Simon, 1976,p. 333).

Since the models discussed in the previous paragraph focus onGNP per capita (or some equivalent measure) in constant dollars,no allowance is made for society's preference for current overfuture consumption. On the assumption that society does con-sider a dollar in the future to be worth less than a dollar in thepresent (if only because society will be richer in the future), itmay be concluded that the population growth rates which havethe most favorable effect on GNP per capita in the immediatefuture will look better if future consumption is discounted thanif it is not.6 In the context of these models this would tend toincrease the attraction of the low and moderate growth rates ofpopulation in relation to the high ones.

An alternative approach uses standard cost-benefit techniquesto estimate the social net worth of family planning programs. Theconceptual difficulties of measuring the social benefit of one less

6. For example, with an annual discount rate of 5 percent, a dollar's worth ofconsumption thirty, fifty, and a hundred years in the future is only equal to 23 percent,9 percent, and 1 percent, respectively, of a dollar's worth of consumption in the present.


birth, as well as the empirical difficulties of predicting the reduc-tion in births effected by any given program, have limited theapplication of this approach. The available studies, however, sug-gest acceptable rates of return.7

Family planning programs may also be justified on the groundsthat they reduce market imperfections and offset divergencesbetween the private and social costs of children. Available evi-dence indicates that couples in developing countries are frequentlyunaware of alternative contraceptives and consequently chooseinferior methods. The high incidence of abortion in some coun-tries also suggests that family planning programs could improvethe efficiency of the "market" by increasing the flow of contra-ceptive information. Other considerations may also arise if, forexample, lifetime public sector expenditure on health, education,and other social services exceeds the taxes paid by an additionalchild and his immediate family. Imperfect information anddivergences between the private and social costs of childrentherefore provide a rationale for the public provision of familyplanning services.

Population Growth, Structureof the Labor F'orce, and Wage Rates

It is also possible to obtain some indication of the effect ofpopulation growth on selected labor market variables, such as therate of transformation in the sectoral structure of the labor forceand the rate of change in real wages. Unfortunately, because ofdata inadequacies, the statistical models used for this purpose havenot always been based on a complete specification of the labormarket. For example, if the market is competitive the appropriatereduced-form equation has the wage rate as the dependentvariable. Serious weaknesses in wage-rate data have led mostresearchers to estimate employment rather than wage functions.On some occasions this is justified by reference to institutionallydetermined wages in the modern sector, so that employment is

7. "Suggest" is used rather than "show" or "demonstrate" because most studies arehypothetical; that is, they calculate the maximum quantity of resources which couldbe allocated to family planning and at the same time leave welfare (GNP or GNP percapita) unchanged despite a given reduction in fertility. See Simon (1970) and Demeny(1965).


determined by demand. In this event, however, the wage shouldappear as an independent variable, but again this is not usuallyattempted. In addition, most available studies focus on the rela-tive size of the manufacturing labor force as a function of theabsolute size of the total population, rather than on growthrates, and are therefore not directly relevant.8

The most useful study (Oberai, 1978) for the present purposeregresses the percentage change in the share of modem sectoremployment 9 between 1960 and 1970 on the period rate ofgrowth of GDP between 1960 and 1970, the share of modernsector employment in 1960, and the period rate of growth of thelabor force between 1960 and 1970. The results have a very simpleinterpretation: if the labor force increases at 3 percent, the shareof modem sector employment in the total labor force decreasesby 1 percent, and the share of the labor force in other sectorsand in unemployment increases by 4 percent. 1 0 It may be con-cluded that rapid population growth retards the transformation ofthe sectoral structure of the labor force.

A similar study (Gregory and Lal, 1977) demonstrates thedampening influence of labor force growth on the rate of in-crease of real wages. It shows that for a sample of twenty-twocountries the elasticity of the rate of growth in real wages withrespect to labor force growth is approximately minus one.

The available evidence indicates quite clearly that populationgrowth has significant implications for employment and wagerates. It is often pointed out, however, that even a major reductionin fertility cannot be expected to have any impact on the growthof the labor force for at least fifteen years. For short-term policy-making, the labor force can be treated as independent of popula-tion growth. For example, Stolnitz (1974) notes that even if

8. See, for example, Chenery and Syrquin (1975), Blandy (1972), and Sabolo(1975b).

9. Defined as all professional, administrative, technical, and clerical workers and allsalaried employees and wage earners in the nonagricultural sectors (Oberai, 1978, p. 38).

10. The estimated equation is:

M= 38.22 + 0.061Y- 0.658S - 0.257L R2= 0.59(1.76) (4.93) (2.20)

where M = percentage change in modern sector employment; Y growth rate of GDP;S = initial share of modern sector employment; L = growth rate of labor force; and tcoefficients are reported in parentheses (Oberai, 1978, table 8).


fertility rates in developing countries had been halved in 1975, themale labor force would have been only one-eighth smaller in 2000than it otherwise would have been. The same reduction in fertility,however, would have halved the male work force under age 25by 2000, and it is precisely this group that has suffered mostfrom unemployment. Although it is true that changes in fertilitydo not affect the short-run labor supply to any significant ex-tent," family planning programs should remain a crucial elementof long-term policymaking.

Scope for Policy Intervention

The next step is to investigate the scope for policy intervention.First, the significance of family planning programs in reducingfertility is assessed, using the results of international econometricstudies. Second, a more detailed assessment of different types ofprograms is undertaken for a selection of areas.

Most of the available econometric studies confirm the im-portance of a variety of social, developmental, and cultural factorsin determining fertility; generally, however, some measure of thestrength of the family planning program is also found to besignificant.12 The results of only one study (Mauldin and Berel-son, 1977) are reported here, but it is representative of the morecomprehensive and qualitatively superior exercises.

With a sample of ninety-four developing economies, Mauldinand Berelson attempt to explain the change in crude birthrates 13

between 1965 and 1975 in terms of the demand for family limita-tion and the supply of family planning methods. On the demandside, the authors consider measures of the "social setting" andcultural factors. The social measures, which include adult literacy,primary and secondary school enrollment, life expectancy, infantmortality, the share of the male labor force in nonagriculturalactivities, GDP per capita, and the degree of urbanization, may be

11. A reduction in fertility may in fact increase female labor force participation inthe short run (Standing, 1978a).

12. For reviews of the literature see Mauldin and Berelson (1977) and Faruqee(1978).

13. According to Mauldin and Berelson the use of the superior total fertility rate asa measure of fertility would not change their results because of the very high correlation(0.97) between the crude birthrates and the total fertility rates.

Table 55. Percentage Decline in Crude Birthrate by Social Setting and Program Effort, 1965-75

Program effort

Strong Moderate Weak None

cn) Economy Percent Economy Percent Economy Percent Economy Percent Total

High social settinge

Korea,Singapore 40 Cuba 40 Venezuela 11 Dem. Rep. of 5Hong Kong 36 Chile 29 Brazil 10 Kuwait 5Korea, Trinidad and Mexico 9 Peru 2

Rep. of 32 Tobago 29 Paraguay 6 Lebanon 2Argentina 31 Colombia 25 Jordan 1Taiwan 30 Panama 22 Libya -1Mauritius 29Costa Rica 29Fiji 22Jamaica 21

Mean 30 Mean 29 Mean 9 Mean 3 19Median 30 Median 29 Median 9.5 Median 2 22

Upper-middle social settinga

China 24 Malaysia 26 Egypt 17 Mongolia 9Tunisia 24 Turkey 16 Syria 4Thailand 23 Honduras 7 Zambia - 2Dominican Nicaragua 7 Congo - 2

Republic 21 Zaire 6Philippines 19 Algeria 4Sri Lanka 18 Guatemala 4El Salvador 13 Morocco 2Iran 2 Ghana 2

Ecuador 0Iraq 0

Mean 24 Mean 18 Mean 6 Mean 2 10Median 24 Median 20 Median 4 Median 1 7

0(N ~~~~~~~~~~~~~~~~~~~~~~~~~~~~(Table continues on the following pages).

TABLE 55 (continued)

Program effort

Strong Moderate Weak None

Economy Percent Economy Percent Economy Percent Economy Percent Total

Lower-middle social settinga

Vietnam, PapuaDem. Rep. of 23 India 16 New Guinea 5 Angola 4

°° Indonesia 13 Pakistan 1 Cameroon 3Bolivia 1 Burma 3Nigeria 1 Yeman, People'sKenya 0 Dem. Rep. 3Liberia 0 Mozambique 2Haiti 0 Khmer Rep. 2Uganda -4 Ivory Coast 1

Senegal 0Saudi Arabia 0Vietnam,

Rep. of 0Madagascar 0Lesotho -4

Mean 23 Mean 14 Mean 1 Mean 1 3Median 23 Median 14.5 Median 0.5 Median 1.5 1

Low social settinga

Tanzania 5 Laos 5Dahomey 3 Central AfricanBangladesh 2 Rep. 5Sudan 0 Malawi 5Nepal -1 Bhutan 3Mali -1 Ethiopia 2Afghanistan - 2 Guinea 2

Chad 2Togo 2Upper Volta 1Yeman Arab

Rep. 1Niger 1Burundi 1Sierra Leone 0Mauritania 0Rwanda 0Somalia 0

Mean 1 Mean 2 2

Median 0 Median 1.5

All social settings

Mean 29 21 4 2 9

Median 29 22 2 2 3

a. Degree of modernization.Source: Mauldin and Berelson (1977), table 12.


viewed as an index of modernization. The cultural factors includethe position of women in society and the dominant religo-culturaltradition (such as Catholic, black African, Chinese). On the supplyside, an index of program effort is devised on the basis of policystatements (interpreted as an indication of commitment), theavailability and quality of family planning services and advice,the use of mass media, the budget support from the government,and so on.

The results are easily recorded. The explained variance in thedecline in the crude birthrate is increased by 26 percent if theindex of program effort is added to the social-setting variables,and by 12 percent if it is added to the social-setting variables andthe cultural factors. Program effort is thus seen to be an importantadditional factor in reducing fertility.' 4

Mauldin and Berelson also provide a useful cross-tabulation ofthe social setting or degree of modernization against the programeffort. Their results are reported in table 55. The tabulation re-veals very clearly that large declines in the crude birthrate (CBR)

are strongly associated with a substantial program effort, whereasa "high social setting" (a high degree of modernization) isassociated with only modest declines unless linked to a strongprogram effort.

Countries with both significant program effort and high socialsetting enjoyed a CBR decline of some 30%, those with onlysignificant program effort a decline of about 20%, those withhigh social setting alone a drop of 5%, and those with neithersaw no change in their CBR during the ten-year period. If thepast record can be extrapolated to the future, a country whichwished to reduce its CBR substantially would be well advisedto institute a family planning program of at least moderatestrength. Given the existence of a moderate program effort,improving social setting takes precedence, but planning to relyonly on enhancing social setting would appear to result in arelatively slow decrease in CBR. (Mauldin and Berelson, 1977,p. 75.)

The geographical dispersion of family planning efforts emerges

14. Multicolinearity poses a severe problem for the interpretation of results invirtually all the studies investigating fertility decline.


Table 56. Total and per Capita Fundsfor Family Planning Programs in Selected Areas

Total funds(thousands of Per capita fundsU.S. dollars) (U.S. cents)

Area Year Government Totala Government Totala

Mauritius FY1972 673 888 81 107Iran 1972 9,000 10,696 29 35Tunisia 1973 278 1,640 5 30Fiji 1971 157 157 29 29Pakistan FY1969 n.a. 22,405 n.a. 17Laos 1972 n.a. 534 n.a. 17Korea, Rep. of 1972 3,470 5,582 10 17Philippines 1972 1,331 5,991 3 16Thailand 1973 1,900 5,000 5 14Guatemala 1973 34 656 1 12HongKong 1972 249 455 6 11Taiwan 1973 1,012 1,237 7 8Indonesia FY1972 5,663 9,663 5 8Ghana FY1972 391 562 4 7Bangladesh FY1972 3,200 4,000 4 5Turkey 1972 n.a. 1,797 n.a. 5Dominican

Republic 1972 80 178 2 4Jamaica 1971 1,090 n.a. 56 n.a.India 1972 86,590 n.a. 15 n.a.Malaysia 1973 1,060 n.a. 11 n.a.Morocco 1972 347 n.a. 2 n.a.

n.a. Not available.a. Includes intemational, foreign, and private sources where available.Source: As reported in Boulier (1977), table 6.

very clearly from table 55. Africa, for example, offers little in the

way of family planning services; with the important exceptionsof India and Sri Lanka, the same is true of South Asia. LatinAmerica exhibits considerable variation, ranging from very strongprograms in countries such as Jamaica and Costa Rica to relativelyweak ones in Mexico and Venezuela. Throughout most of South-east Asia, however, programs are characterized as strong ormoderate.

Family planning programs can take a variety of forms, rangingfrom policies of persuasion (for example, the promotion of smallfamilies), through price policies (for example, subsidized contra-ceptive supplies), to policies of coercion (such as raising the


minimum legal age for marriage). 15 Most programs concentrate onproviding information about contraception and supplying contra-ceptive services, including sterilization, at or below market cost.The allocation of funds to family planning programs for selectedlocations is shown in table 56. Annual expenditure per capitaexceeds US$1 only in Mauritius and is generally less than 20 U.S.cents. Government expenditure on family planning is usually lessthan 0.2 percent of total government expenditure (India, In-donesia, and the Philippines are notable exceptions) and less than5.0 percent of expenditure on health (Indonesia, the Philippines,Taiwan, Iran, and Korea being some of the important exceptions).1 6

Few programs have relied on coercive measures or tax incen-tives. In China and India attempts have been made to increase theminimum age of marriage, but the effectiveness of these policies,especially in rural areas, and their ultimate impact on fertilityremain uncertain. The most important coercive policy, theprohibition of abortion, serves to increase fertility; liberalizinglaws, however, have been enacted during the late 1960s and early1970s in India, Korea, Singapore, Tunisia, Turkey, and Zambia.With regard to tax incentives, Singapore and the Philippines haveeliminated or reduced benefits accruing to larger families, Indiahas sterilization and nonpregnancy bonuses, and Taiwan has ex-perimented with educational benefits for smaller families. Apartfrom the Indian sterilization campaign in Gujarat and Ernakulam,which was highly successful, it is too early to evaluate the pro-grams. Perhaps the most significant achievement, however, belongsto Indonesia. Besides demonstrating that low-income, under-developed countries can successfully reduce fertility, the Indone-sian example illustrates the importance of community involvementat the village level.

Evidence on both the potential benefits and the feasibility ofreducing fertility favors extending and improving family planningprograms, especially in the low-income countries which are ex-periencing high rates of population growth. Failure to do so wouldconstitute a major error of policy formulation, with significantconsequences for long-run development. This conclusion is partic-

15. For a survey of family planning programs, see Cuca (1979).16. Reported in Boulier (1977), p. 182.


ularly relevant to the low-income countries of Africa, wherefertility rates have not yet started to decline, and to some middle-income Latin American countries, where population growth ratesexceed 3 percent (see chapter 3). Few countries in either grouphave yet introduced population policies to any significant extent.

16

Education Policy

The discussion in this chapter is confined to the central issuesof overexpansion of educational facilities and educated unemploy-ment. A variety of other issues, such as the content of curric-ulums, are discussed in World Bank (1980).

Role of Education in Economic Growth

Numerous studies have documented the statistical relationbetween some measure of educational attainment and nationalincome per capita. For example, Harbison and Myers (1964)report a high correlation (0.89) between their composite indexof human resource development and GDP per capita.' These andsimilar exercises, however, fail to prove causality; educationalexpansion may be a result of economic growth rather than viceversa. Nevertheless, such exercises cannot be completely dis-missed: Peaslee (1967), for example, draws on historical andcontemporary data to show that sustained economic growth wasnot achieved in his sample of countries until 10 percent of thepopulation was enrolled in primary school. Similarly, in a de-tailed study of Latin American development, Ramos (1970)demonstrates that the rapid growth in manufacturing outputfrom 1960 to 1970, although not associated with a rapid growthin manufacturing employment, was based on significant improve-ments in the quality of the labor force. In particular, he showsan absolute fall in employment in manufacturing based on tradi-tional skills, a relative fall in those sectors relying mainly on un-skilled labor, and a strong relative and absolute rise in employ-ment in the skill-intensive subsectors of modem manufacturing.

1. The composite index is the weighted sum of enrollment rates at the secondaryand tertiary levels.

194

Education Policy 195

His argument is completed by reference to the rapid improve-ments in the educational attainments of the Latin American laborforce during that and earlier periods.

Apart from such macro analysis, the significance of educationcan be demonstrated at the micro level by an examination ofearnings differentials. 2 Table 57 reveals that discounted lifetimeearnings increase rapidly with educational attainment, especiallyin the developing countries. The differentials reported here arecalculated on the basis of contemporary cross-sectional data andtherefore do not adequately measure potential or expected earn-ings unless it is assumed that labor market conditions remain un-changed. Nevertheless, for current purposes the data are adequate:earnings of the educated exceed those of the uneducated. 3

Measures of earnings differentials, however, are only part of thestory; costs of education are also relevant. It is more appropriate,therefore, to focus on the social rate of return to education. Table58 summarizes the evidence on rates of return by educationallevel for a selection of countries. The individual studies on whichthis table is based vary in quality and method so that the reportedfigures should be interpreted only as crude indications of thesocial net worth of education. 4 Nevertheless, it is probably safe toconclude that rates of return in the developing countries declinewith the level of education' but exceed those reported forsecondary and higher education in developed countries.

Educational Expansion and Its Implications

Recognition of the link between education and economicgrowth led to the rapid expansion in educational facilities and out-put described in chapter 3. An unforeseen consequence, however,

2. Whether these differentials reflect the role of schooling in selecting or "screen-ing" more able individuals or whether they represent schooling's direct impact on produc-tivity is not easy to determine. In either event, earnings differentials may be regarded asa measure of the private benefits from schooling.

3. This is the almost universal conclusion emerging from estimates of earningsfunctions. See, for example, Mazumdar and Ahmed (1978) and Psacharopoulos (1977).

4. The studies are described in detail in Psacharopoulos (1973).5. For this and other reasons, it is often argued that primary education should be

expanded in relation to secondary and higher education. See Blaug (1973). This maywell be the case for certain countries, but, as argued below, past rate-of-return calcula-tions are not appropriate indicators of the future social profitability of education.

Table 57. Comparison of Gross Discounted Lifetime Earningsamong Educational Levels in Selected Countries

Compared educational levels

Discount Primary! Secondary! Higher! Higher! HigherlCountry rate None Primary Secondary Primary None

United States 5 - 1.53 1.56 2.3810 - 1.68 1.65 2.76 -

Canada 5 - 1.57 1.76 2.7610 - 1.59 1.81 2.89 -

Israel 5 1.59 1.56 1.42 2.20 3.5210 1.56 1.83 1.42 2.61 4.07

Mexico 5 2.94 1.46 2.39 3.49 10.2610 3.08 1.39 2.71 3.78 11.65

Colombia 5 3.29 2.74 1.77 4.86 16.0010 3.45 2.46 2.12 5.21 17.99

Philippines 5 2.34 1.54 1.45 2.23 5.2110 2.56 1.71 1.52 2.60 6.64

Ghana 5 2.25 1.92 4.77 9.19 20.6610 2.53 2.03 4.48 9.08 22.97

Kenya 5 1.70 2.32 2.63 6.12 10.4310 1.72 2.48 3.04 7.55 12.97

Nigeria 5 2.72 2.21 4.25 9.40 25.5810 2.32 2.30 4.45 10.25 23.77

India 5 2.77 1.48 3.56 5.26 14.5710 3.38 1.60 3.54 5.65 19.11

- Not applicable.Source: As reportedin Hinchliffe (1975), table 1.


Table 58. Average Social Rates of Return by Educational Levelin Developed and Developing Countrzes

Rate of Standard Number ofEducational level return (percent) deviation observations

Developed countriesPrimary - - -Secondary 9.0 5.3 9Higher 9.1 2.6 11

Developing countriesPrimary 18.8 9.2 15Secondary 15.9 6.1 18Higher 12.6 5.0 19

- Not applicable.Source: Psacharopoulos (1973), table 4-1.

was the emergence of high rates of unemployment among thosewith primary and secondary education, indicating a situation ofexcess supply. A rough measure of the imbalance between thedemand and supply of educated labor is the ratio of modemsector job vacancies to labor market entrants with secondary orhigher education, as shown in table 59. The table may be inter-preted as follows: if modem sector employment grows at 5percent, job vacancies, including those arising from deaths andretirement, would amount to, for example, 50 percent of the newlabor market entrants with secondary or higher education in thePhilippines, 142 percent in Senegal, and 446 percent in Kuwait. Ofcourse, not all secondary school leavers will necessarily seekmodem sector jobs, while primary school leavers can be expectedto fill some modem sector vacancies. The ratio should be inter-preted, therefore, as only roughly indicative of the gap betweenjob aspirations and opportunities.

The crucial determinants of this gap are the size of the modemsector and its rate of growth, population growth (which deter-mines age structure), and the rate of school enrollment. The highrates of unemployment for secondary school leavers in Sri Lankaand the Philippines reported in table 21 are not surprising in viewof the relative imbalance between demand and supply suggestedby the very low values of the ratio shown in table 59. In contrast,countries such as Kuwait can be expected to experience shortagesof educated workers because of the exceptional growth of themodem sector at a time when the educational sector is still rela-


Table 59. Comparison of Modern Sectorjob Vacanciesand Educated Labor Market Entrants in Selected Countries, 1973

Accommodation ratio at growthrates of modern sector employmenta

Country 2 percent 5 percent 8 percent

Philippines 0.29 0.50 0.72Sri Lanka 0.38 0.66 0.94Sudan 0.41 0.73 1.04India 0.42 0.74 1.05Venezuela 0.58 1.01 1.44Korea, Rep. of 0;60 1.06 1.51Peru 0.61 1.06 1.52Algeria 0.61 1.07 1.52Singapore 0.67 1.17 1.68Thailand 0.69 1.21 1.74Kenya 0.72 1.26 1.80Zambia 0.77 1.35 1.93Senegal 0.81 1.42 2.03Ivory Coast 0.85 1.49 2.12Chile 0.89 1.56 2.23Malaysia 0.93 1.63 2.32Syria 0.95 1.66 2.37Botswana 0.95 1.67 2.38Guatemala 1.29 2.25 3.22Ghana 1.33 2.31 3.31Costa Rica 1.33 2.33 3.33Mexico 1.63 2.86 4.08Brazil 1.83 3.21 4.58Panama 2.39 4.19 5.98Kuwait 2.55 4.46 6.37

a. The accommodation ratio is the number of modem sectorjob vacancies expressedas a proportion of the number of labor market entrants with secondary or higher educa-tion. The modern sector includes all professional, technical, administrative, and mrana-gerial workers, all salaried employees and wage earners in nonagriculture, and 50 percentof employers and workers on own account in clerical jobs. Vacancies depend on deathsand retirement rates and economic growth assumed to be at a rate of 2, 5, or 8 percent.

Source: Dore and others (1976).

tively underdeveloped. Although not so extreme, Brazil faces asimilar situation. Intermediate values of the ratio are recorded forKorea, where modem sector employment is growing rapidly andthe educational system is well developed.

The analysis suggests that the problem of educated unemploy-ment may be attributed at least in part to the recent high popu-lation growth rates and the simultaneous desire to increase erLroll-ment rates. As a result, the educational structure of the labor force


has undergone a very rapid transformation. Labor markets haveadjusted-with a narrowing of wage differentials and some revisionof expectations-but not sufficiently. This suggests that neithertable 58 nor table 59 is an adequate base from which to drawpolicy conclusions. The appropriate procedure is to recognize thatadjustments are occurring, albeit slowly, in the labor market andto reconsider the estimation of social rates of return to education.

As noted earlier, rate-of-return calculations which fail to allowfor changing labor market conditions may prove seriously mis-leading. Equating expected earnings differentials with existingdifferentials, and then proceeding to recommend nonmarginalexpansions in educational facilities is not legitimate. 6 Illegitimateanalysis, however, does not necessarily lead to incorrect policyconclusions: realized social rates of return may well be lower thanexpected, but still higher than any reasonable measure of theopportunity cost of capital. Unfortunately, the lack of informa-tion on realized rates of return prevents a judgment on the extentof overexpansion, if any, in education.

Nevertheless, the policy advice is clear: future calculations ofrates of return should allow for the narrowing of wage differentialsusually associated with economic development 7 and for thepossibility of unemployment. The advice points to the need forcareful and continuous review of labor market developments andtendencies, and may well imply some reduction in the rate ofexpansion of educational facilities, especially at the secondarylevel.

Social and Private Rates of Return

Because education is usually highly subsidized, private rates ofreturn generally exceed the corresponding social rates. Psacharo-

6. Allowances for unemployment and segmented labor markets have been madein a number of studies. See, for example, Selowsky ( 1973) and Piiiera and Selowsky(1978).

7. Evidence on this point is documented in Gunter (1964) and Taira (1966). Thisphenomenon often manifests itself in the form of credentialism, a situation in whichemployers select overqualified applicants simply because educational achievement offersa simple means of rationing vacancies. As noted in chapter 3, however, the educationalstatus of the work force normally increases during economic development. See alsochapter 8. Knight (1979) provides a theoretical framework for the analysis of "filteringdown" based on the concept of an occupational production function.


poulos (1973, table 4.1) shows that the private rate of return forprimary education is 8 percentage points higher than its socialrate in developing countries; for secondary education, 4 percent-age points higher; and for higher education, 10 percentage pointshigher. It follows that if educational facilities are expanded at asocially optimal rate, and the social and private opportunity costsof capital are similar, the private demand for education will exceedpublic supply even if education is not regarded as a consumptiongood.

Of course, some of the demand will be satisfied by privateinstitutions, but as long as the private rate of return exceeds thesocial rate in public schools, excess demand for public schoolplaces will continue. A solution frequently recommended is tomake students or their parents bear a higher proportion of thecosts of education by charging tuition or other fees in order toreduce, if not eliminate, the gap between private and social ratesof return.8 A gradual increase in tuition fees, or the introductionof a system of student loans to be repaid after graduation, wouldseem particularly appropriate at secondary and higher levels,where the cost of education is many times higher than at the pri-mary level (see table 60).9 Moreover, in the past those proceedingto secondary and higher education have come mainly from thericher groups in society; a system of tuition fees, rather than heavysubsidies from general taxation, would benefit both incomedistribution and resource allocation. The pursuit of equity wouldbe further served by the provision of free education or evenscholarships for able students from low-income families, and byimprovements in both the quality and coverage of primaryeducation.

The above recommendations, however, may encounter diffi-culties. Tuition fees are unpopular; student loan schemes have notproved successful in practice; social and private rates of returncan still diverge because of externalities and imperfect informa-tion; and full-cost pricing may fail to eliminate excess demand ifeducation is perceived as a consumption good. It may be expected,

8. A more extreme solution allows for the private provision of education. In fact,in most countries some part of the educational system is privately organized. In thePhilippines, for example, higher education is primarily private.

9. Similar recommendations have been made by, among others, Blaug (1973),Fields (1974), Harbison (1977), Emmerij (1973), and Edwards and Todaro (1974).


Table 60. Educational Expenditure by Region

Educational Unit costRegion expenditure as aand as a percentageeducational percentage of GNP Enrollment Demographiclevel of GNP per capita ratio burdena

Eastern AfricaPrimrary 2.04 20 46.00 21Secondary 1.13 124 5.94 15Higher 0.59 927 0.51 12

Western AfricaPrimary 1.64 24 37.85 18Secondary 1.20 142 4.99 17Higher 0.49 1,405 0.33 10

AsiaPrimary 1.33 11 53.66 21Secondary 0.93 27 25.14 13Higher 0.56 205 2.15 13

Middle EastbPrimary 1.71 15 57.99 19Secondary 1.54 47 20.18 16Higher 0.84 306 2.20 12

Latin AmericaPrimary 1.63 11 67.81 22Secondary 0.84 22 24.18 15Higher 0.84 121 5.34 8

OECD countriesPrimary 1.68 16 97.50 10Secondary 1.79 21 70.34 12Higher 0.71 55 11.82 11

a. Proportion of school-age children in the population.b. Indudes Afghanistan, Algeria, Egypt, Jordan, Morocco, Syria, Turkey, and

Tunisia.Source: Zymelman (1976b), tables VIII-2, VIII-3, VIII-4, XII-3, XXI-2, and XXI-4.

therefore, that even if tuition fees are adopted to some extentin some countries, most will still experience conditions of excessdemand for secondary education. Consequently, nonprice ration-ing will remain an important feature of educational systems formany years to come.

Vocational and On-the-Job Training

Educated unemployment may also reflect an inappropriatecombination of academic and vocational instruction; the skillssupplied by the education system may not match the skills de-


manded by industry." 0 The appropriate role of vocational train-ing, however, is a controversial issue. Although the acquisition ofindustrial skills is an essential component in the transformationand upgrading of the labor force, the most useful institutionalarrangement for imparting these skills remains unclear. Neverthe-less, experience in several countries provides some useful guidingprinciples. Blaug (1973, p. 71), for example, argues that given thedifficulty, if not impossibility, of predicting the future demand forhighly specific skills, vocational training in formal institutions"makes little sense on either educational or on economicgrounds." But after a review of establishments that offer informaltraining, Zymelman (1976a) concludes that in some circum-stances such training may be socially beneficial.

The most important feature of a successful training progranais a direct link with the labor market. Unless vocational trainingestablishments are responsive to changing labor market conditions,their graduates will encounter difficulty in finding employmentand the investment in training will prove socially unproductive.In the apprenticeship schemes of West and East Africa, for ex-ample, the link between the labor market and the training facilitiesis provided by the master craftsmen. Nigeria, for instance, hasmore than 2 million adolescents and young workers apprenticedto traditional and modem craftsmen such as weavers, black-smiths, carpenters, printers, and mechanics. This system provesuseful in imparting certain types of skills but is clearly limitedby the existing knowledge of the master craftsmen. When theeconomy is in the throes of a rapid transformation, the indigenousapprenticeship system is unlikely to be an adequate means ofteaching skills.

The alleged divergence between private and social benefitsof training and the economies of scale associated with traininghave sometimes led the public sector to provide vocational instruc-tion through the formal education system. The Secondary Techni-cal Schools in Kenya, for example, offer courses in English,mathematics, science, geography, technical drawing, and eitherbasic engineering or basic building technology and applications.Approximately equal time is devoted to academic and technical

10. This section draws on Zymelman (1978).


subjects. A follow-up study of the 1974 graduates, however,indicated that in mid-1975 almost 60 percent were unemployed.

A similar situation is observed in Thailand, where the Compre-hensive Schools offer a mixture of academic and vocational train-ing at the secondary level. The academic course is designed toequip students for further education, while the vocational trainingprovides skills for those seeking immediate employment. Fewstudents (about 15 percent), however, select the vocational sub-jects, and the equipment and facilities remain seriously under-utilized. The Trade and Industry Schools are more explicitlyconcerned with the training of skilled workers for industry butalso provide some general education. As a result, the schools areoften used as a device by students either to return to the academicstream or to obtain a white-collar job. The ability of graduatesto obtain industrial employment is also questionable; only a smallpercentage work in the private sector.

In both Kenya and Thailand, skills are acquired primarilythrough on-the-job training in private industry. The failure of thevocational schools is generally attributed to their inability toadapt to changing labor market conditions, which, in turn, is aconsequence of the inflexible administration usually associatedwith formal education. 1 1

Other countries have deliberately sought to encourage on-the-job training and make vocational training institutions responsiveto the labor market. The Industrial Training Board (ITB) in Singa-pore, for example, was established outside the formal educationsystem with the express purpose of promoting and coordinatingindustrial training within a highly flexible and responsive frame-work. The ITB is an autonomous body with members drawn fromgovernment, the trade unions, and industry. The board relies onthe advice of eight trade-specific committees and offers a varietyof training courses. The needs of employers are of central con-cern. For example, the Day Release Course accepts only nomineesof employers, and part-time trainees in the skill-upgrading programmust also have the endorsement of their employers. Employers

11. This is not a necessary characteristic of formal education. The World Bank-supported technical schools in Korea have proved highly successful in establishingstrong links with the labor market.


can choose from a selection of schemes which combine formalinstruction and on-the-job training in different proportions. TheITB also supervises the Joint Government-Industrial TrainingScheme and the Industrial Training Grants Scheme, both of whichare designed to encourage industry's participation in trainingprograms, either in conjunction with the government or in-dependently through the provision of grants.

Responsiveness to the needs of private industry is also apparentin Brazil's National Service for Industrial Apprenticeship (SENAI).

Established by the government in 1964, SENAI is a private non-profit organization. It is administered by the National Confedera-tion of Industry and provides a variety of training programs. Ofinterest, however, is its reliance on periodic surveys of the labormarket to provide a basis for forecasting the quantitative andqualitative needs of business. This is followed by careful jobanalyses to identify the technical requirements of specific jobs.In this manner, the supply of skilled labor is tailored to thefuture needs of industry. The 1 percent payroll tax used to financethe scheme also serves as an incentive to employers to undertaketheir own on-the-job training programs, since those who do so areexempt from the tax.

Generalizing on the basis of such a small sample is alwayshazardous. Nevertheless, the available evidence suggests thatvocational training can be successful, provided it is not embeddedin the inflexible administration usually found in the formaleducation system. The two successful programs-ITB in Singa-pore and SENAI in Brazil-differ in specifics but are similar intheir determination to involve the business community in thetraining process and in their efforts to monitor and respond tochanging labor market conditions.

Conclusion

Much of the discussion in Part IV has dealt with the implica.-tions for the labor force of two major developments of the lasttwenty years: rapid population growth and a major expansionin educational facilities. The former has retarded the rate oftransformation in the sectoral structure of the labor force, whilethe latter has advanced that in the educational structure of thelabor force. Whether the rates of transformation are too slow in


the one case or too fast in the other will remain a matter ofcontroversy. The consequences of the underlying developmentsare nevertheless highly visible in the developing countries: largenumbers of workers remaining in low-productivity agricultureand high rates of educated unemployment. Although such out-comes are obviously dependent on the interaction of demandand supply within an imperfectly operating labor market, itmight be argued that factors operating on the supply side of theequation must shoulder a major portion of the blame for theemployment problems encountered in most developing countries.

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I

Index

Abercrombie, K. C., 159 Berelson, Bemard, 185, 190Abidjan (Ivory Coast), 142 Berg, Elliot J., 114, 116 n.10Abortion, 192 Berry, Albert R., 28Afghanistan, 129 Bertrand, TrentJ., 79 n.1Africa, 117, 118, 142, 181, 193; agri- Bhatt, Vinayak V., 171

cultural labor in, 85; apprenticeships Birthrates, 185-90in, 202; farm size in, 156; migration Blaug, Mark, 202and, 101; population growth and, 42, Blomqvist, A. G., 106 n.843, 46, 47; time-budget studies for, Blue-coUar workers, 114-15; in Latin84; trade policy and, 151; under- America and United States compared,employment and, 74 21-22

Age: education and, 123; migration and, Bombay, 121101; structure of population and, 17- Bonded rural labor, 95-9618, 177-78; unemployment and, 120 Brazil, 129, 141, 198, 204; migration in,n.16 98

Age distribution, unemployment and, Bruton, Henry J., 6668 n.11, 69 n.12

Agriculture, 29, 133; bimodal and uni- Calcutta, 142modal approaches to, 174; in de- Cambodia, 98veloped and developing countries Canada, 117(1880-1960), 11-12, 13; employment Capital accumulation, labor force growthin, 153-65; GDP and, 27; low-income and, 8-9, 28-29, 33-35countries and, 8, 9; migration and, Capital costs in informal sector, 142-43102-03; productivity growth and, 53, Capital-labor ratios, 167-7055; rural wages and, 90-97; sectoral Capital markets, 133, 160, 165; agricul-structure of labor force and, 47-48; tural employment and, 155; laborstructure of labor force model and, demand and, 8-9; manufactured31-41; surplus labor and, 63-64; tradables and, 151;policy and, 172;transfer of labor from, 79, 153;utili- synthesis, 166-72zation of labor and, 82-90; wage em- Caribbean area, population growth in, 47ployment and, 85 Casual labor, 121-22

Ahmed, Masood, 114, 115, 122 Chenery, HoUlis, 47, 140, 144Apprenticeship schemes, 202, 204 Chesnais,Jean-Claude, 181Argentina, 129 Cheung, Steven, 94, 95Asia, 117, 118, 181; agricultural labor in, Children, participation rate and, 16

85; farm size in, 156; migration and, Chile, 115, 117101; population growth and, 42, 43, China, 19246; trade policy and, 151; under- Clark, Colin, 11, 26, 153employment and, 74 Cline, WiUiam R., 156

Australia, 103, 117 Collier, Paul, 106 n.8Colombia, 73, 117, 155, 159, 174

Bairoch, P., 11 n.1, 26, 28 Comprehensive Schools (Thailand), 203Banks, 142-43, 171-72 Conlisk, John, 181Bardhan, Pranab Kalpana, 91, 93, 95, Connel,John, 107

103 n.4, 159 Contraceptives, 183, 192Barker, Randolf, 159 Corporations. See FirmsBamum, Howard N., 100 Cost of living, 122

223

224 Index

Credit, 142-43; agriculture and, 159, 160, Employment, 57, 80; in agriculture,164, 165, 170, 171; capital markets 153-65; education and, 197; industrialand, 166, 167, 170 trade policy and, 144-52; informal

Crop insurance, 172 sector and, 143; modem sector and,184; public sector and, 118-21; re-

Desai, Meghnad, 91 source allocation and, 173-74; rural,Developed countries: compared with 82-90; sectoral, 55; in service sector,

developing countries (1880-1960), 136-40. See also Employment policy11- 14; employment in, 136-37; in- study; Industrial employment; Self-dustrial labor absorption and, 23-25; employment; Underemployment;industry's share of labor force and, 26- Unemployment; Wage employment31; historical labor supply in, 15-20 Employment policy study: labor market

Developing countries: analysis of employ- policy conclusions and, 6-10; majorment in, 59-66; compared with de- issues in, 3-5; organization of, 5veloped countries (1880-1960), 11-14; Encamacion,Jose, 122employment in, 136-37; industrial Entrepreneurs, 141; cost of capital and,employment increase in, 3; industrial 142-43labor absorption and, 23-25; industry's Ethiopia, 178share of labor force and, 26-31; his- Expectations: income, 123-24; job, 10;torical labor supply in, 15-20; rural market adjustments and, 123, 124;employment in, 83-97 reality and, 82

Dominican Republic, 73 Exports, 7, 27, 30, 106, 114, 174; agri-Dualism: sectoral analysis of, 79-81; culture and, 153; labor intensity and,

supply-and-demand theories and, 91- 149-5 1; policy and, 145. See also92 Trade

Durand, John D., 43-46

Earnings: distribution of, 65; informal Family: migration and, 121; off-farmsector and, 141-42; underemployment work and, 91; size and farm size,and, 73, 74. See also Wages 86-87

Eamings differentials, 81; education and, Family enterprises, income sharing and,195, 199; migration and, 101-02. See Family panning 9, 182-83, 185-92

Easterlin Richarde 181 Farmers'Association (Taiwan), 172.at 'n R.car, 181 Farmers' Protection Deposit Scheme, 172Economic development: education and, Farm.si croecitnd 159; Semoent

194-95; industry's share of labor and, Farm s1ze: credt and, 159; employment26-28; labor market operation in, 77- and, 155-56, 157; family size a70d,78; marginal product of labor and, 79; 86-87 mechanization and, 157-60pattems of, 144 n.1; process of, terhnology and, 160-62historical perspective on, 11-14; Fert4ity, 9, 16; population growth and,structure of labor force and, 31-41 and, 1859 3

Education, 77, 92; economic growth and, anF , 16, , 194-95; implications of expansion in, Fertilizer, 160, 163, 164, 170195-99; labor force growth rate Firms: hiring practices of modern sector18-19; labor heterogeneity and, 122; 114-16; wage rate changes and, 62labor market and, 31; market adjust- Fong, Pang Eng, 122ments and, 123-24; migration and, Formal sector, 81; m1i2um wage 8nd,101; policy and labor supply, 10; 126public sector employment and, 120-21; Fowler, D. A., 16rates of return and, 199-201; structure France, 178of labor force and, 49-51, 56; un- Freetown (Sierra Leone), 142, 168employment and, 19, 69, 75, 130, 132,197-98, 201;wage policies and, 130- Ghana, 55, 129, 14132. See also On-the-job training; Glytsos, Nicholas F., 55Vocational training Gregory, Peter, 67, 110, 111

Efficiency, 115, 168; allocational, 173; Gross domestic product (GDP), 7; agri-of unskilled labormarkets, 77 culture and, 27; education and, :180;

Egypt, 86, 90 gross capital formation and, 29 ril0;

Index 225

industry's labor force share and, 26- of, 26-31; migration and, 102-03;29; resource allocation and, 8; sectoral productivity growth and, 53, 56;employment and, 55-56; services and, sectoral structure of labor force and,28 47-48; services and, 140; structure of

Gross national product (GNP): popula- labor force model and, 31-41; tradetion growth and, 181-83; urban growth policy and, 149-51, 152; wage ratesand, 98 and, 79, 80. See also Manufacturing

Guatemala, 129 sectorInformal sector, 77, 166; defined, 81,

Hansen, Bent, 90 127 n.3, 141; dualism in, 80-81;Hanson, John R., 181 minimum wage and, 127-28; servicesHarbison, Frederick, 194 and, 135, 136, 140-43Harris, John R., 100-01, 103, 106 n.8 Information, 59 n.2; contraceptives and,Hiring practices: of modern sector firms, 183, 192; failure of, 6, 60; improving,

114-16; in public sector, 118-21 66; imperfect, 61; migration policyHisadrut (Jewish labor movement), 112- and, 105; services and, 131

13 Input, agricultural, 154, 157-62, 163Hsieh, C., 149 International Labour Office (ILO), 141,Huddle, Donald, 181 173 n.3; measure of underemployment

and, 65-66IlUiteracy, 69 Investment, 166; agricultural, 154; farm,Imports, 7, 27 171; manufacturing sector and, 167-Import substitution, 7, 30, 106, 174; 68; labor market, 177-78; manu-

agriculture and, 153; labor intensity factured tradables and, 150-51; popula-and, 149-51, 152. See also Trade tion growth and, 178-80

Income, 39; expectations, 123-24; infor- Iran, 68mal, 77; migration model and, 101-02,107; savings and, 170; services and, Jakarta, 142141-42, 143 Jamaica, 129

Income distribution, land reform and, Japan, 85, 103, 162-64165 Jobs: preference and, 142; secondary

Income per capita: in developed and education and, 10developing countries, 26; education Job search, 66, 69, 77; discouragedand, 194; manufacture and, 1 1; popu- workers and, 62; statistical unemploy-lation and, 181 ment definition and, 61

Income sharing, family enterprises and,63-64, 67; rural households and, 79 Kenya, 55, 69, 202, 203

India, 91, 129, 168, 192; interdistrict Kilby, Peter, 113 n.4wage differences in, 92-93; landlords Korea, 55, 129, 145, 149, 159, 172, 174,in, 95, 96; migration and, 107; open 192, 198unemployment in, 57; savings in, Krueger, Anne O., 150171-72 Kumasi (Ghana), 141, 142, 143

Indonesia, 129, 192 Kuwait, 197Industrial employment: determining, Kuznets, Simon, 181

26-31; developed countries' increasein, 3. See also Employment Labor demand, 5, 145, 154, 164; adjust-

Industrial trade policy. See Policy (in- ment costs and, 62; capital marketsdustrial trade) and, 166-67, 170; in developed and

Industrial Training Board (ITB, Singa- developing countries, 20-22; policiespore), 203 affecting, 133;policy analysis and, 7-9;

Industry: capital markets and, 167-70; rural wage rates and, 91-92; tradedeveloped countries' employment policy and, 152increase and, 3; in developed and Labor force participation, 96; agriculturaldeveloping countries (1880-1960), households and, 85-88; population12-14, 22; employment and output growth and, 15-16, 43-46; supplygrowth in, 174; labor absorption factors and, 92(1960s) and, 23-25; labor force share Laborheterogeneity, 81-82, 121-22, 125

226 Index

Labor intensity: capital markets and, 168, Malaysia, 86, 89, 93, 114, 117, 122, 129,170; of manufactured tradables, 149- 168; unemployment rate in, 6251 Mandatory Palestine, 110, 111, 112-13

Labor legislation, 59 n.3, 65, 66, 80, Manufacturing sector, 11, 56; capiital114 n.5,115 n.7, 125; labor market markets and, 167-70; education and,distortion and, 109-13, 127-30; unem- 194; migration and, 102-03; wages in,ployed and, 57, 74; wages and, 77 56. See also Industry

Labor market: absorption, 23-25, 30, Mauldin, W. Parker, 185, 190135-43, 153; adjustment in, 123-24; Mauritius, 192agriculture and, 153-65; bonded labor Mazumdar, Dipak, 81, 91, 94, 114-15,in rural, 95-96; casual labor in, 121-22; 121-22in developed and developing countries, Mechanization (farm), 157-60, 163, 164,11-14; disequilibrium in, 122-23; 165, 166, 170dualism of, 79-82; economic develop- Men, 122, 185; labor force participationment and, 77-78; growth in, 33-35; of, 43-46; migration of, 101; in ruralhistorical comparisons and, 11-31; work force, 83-84; unemployment of,industrial trade policy and, 144-52; 69, 111 n.2misallocation of, 58, 61, 66; partici- Mexico, 55, 114 n.5, 117, 129, 145,pation of agricultural households in, 149, 159, 163, 164, 168, 17485-88; population growth and, 42-47, Middle-income countries, 174; family56, 183-85; rural wages and, 90-97; planning in, 9; labor force structure in,share of industry in, 26-3 1; sectoral 47-48; real wage rates in, 53; tradestructure of, 47-48; surplus labor in, policy and, 152; wage employment in,58, 60, 63-64, 84-85; urban, 109-24; 57utilization of rural, 82-90. See also Migration: permanent workers and, 121-Policy (labor market) 22; rural-urban, 6-7, 77, 78, 98-108,

Labor supply, 5; in developed and de- 135; services and, 106-07veloping countries, 15-20; education Minimum wage: informal sector and, 141-and, 10; population programs and, 9; 42; labor market operation and, 109-rural wage rates and, 91-92; surplus, 13; legislation, 59, 60 n.6, 65, 66,84-85 74, 80, 114n.5, 115 n.7;policy con-

Labor supply price: casual workers and, clusions and, 6; theoretical concepts121-22; dualism in traditional sector and, 59, 65; wage policy and, 125-and, 79, 80 30. See also Wages

Land distribution, 93, 97 Mining, pay scales and, 115-16, 130Landlords (rural), 93-96 Mobility: labor, 6, 77, 105, 125; oc-Land reform, 156, 164, 165 cupational, 96Latin America, 28, 30, 117, 118, 193; Models: for analysis of unemployment and

agricultural labor force in, 85; educa- underemployment, 59-61; dual labortion and, 194; farm size in, 156; market, 79-82; of income-sharingmigration and, 101; occupational family enterprises, 64; of migration,structure in, 21-22; population growth 100-01, 103, 106 n.8; minimum wageand, 42, 43, 46, 47; population pro- reduction, 127-30; of population andgrams and, 9; underemployment and, income growth, 181; of three-sector74 economy, 31-41; of wage-rate deter-

Lewis, W. Arthur, 63, 92 mination, 55Limbor,J-M., 11 n.l Modern sector: defined, 79 n.2; dualismLiuch, Constantino, 34 of, 79; employment in, 145, 184, 197;Low-income countries: agricultural hiring practices in, 114-16

growth in, 8, 9; labor force structure Monopolies: labor markets and, 157;in, 47-48; population growth in, wages and, 11443, 46, 181; population policy and, Morawetz, David, 36 n.15192-931 real wage rates in, 53; trade Morocco, 122policy and, 151-52; wage employment Mortality rates, 16; population growthin, 57 and, 42

Myers, Charles A., 194Mabro, Robert, 92

Index 227

National Agricultural Cooperative Federa- Powell, Alan A., 34tion, 172 Prices, 8;labor supply, 79, 80, 121-22

National Service for Industrial Apprentice- Productivity, 40; capital, 168; in de-ship (SENAI, Brazil), 204 veloped and developing countries,

Nepal, 98 29; demand and growth of, 20-21;Newberry, David M. G., 94 labor absorption by industry and,Nigeria, 113 n.4, 202 25; minimum wage and, 115 n.7;realNouakchott (Mauritania), 142, 143 wage rates and, 53-56; services and,

135-36, 140-41; worker's educationOccupations, 82; labor force structure and, 49-51

and, 21-22, 51-53, 56, 130-31 and, 49-51On-the-job training, 142, 203-04 Protection, agriculture and, 153-54Output: agricultural, 162; composition of, Psacharopoulos, George, 122, 199-200

26-27, 28, 29-31; employment rate Public sector, 28, 109; education and,growth and, 20-21, 173, 174;labor 131;hiringpracticesin, 118-21;absorption and industrial, 24; popula- salary structure in, 6, 77, 116, 119-tion growth and, 182; services and, 21, 129135-36, 143; surplus labor and agri- Puerto Rico, 110-11, 112, 113, 115 n.7

cultural, 63-64 Ramos, Joseph R., 194

Pakistan, 155, 168 Rates of retum, education and, 199-201Palestine. See Mandatory Palestine Ravenstein, E. G., 100Pay scales: high-wage, 114; inflexibility Republic of Korea. See Korea

of, 77; mining industry and, 115-16, Resource allocation, 3, 77, 154; capital130; public sector, 118-21. See also markets and, 166, 167; employmentWages and, 173; industrial output and, 30-

Peaslee, Alexander L., 194 3 1; labor demand and, 8-9; misaloca-Permanent labor, 121-22 tion of labor and, 58, 61, 66; trans-Peru, 98, 129 fer of labor from agriculture and,Philippines, 73, 83, 84, 118, 129, 145, 79

149, 154, 159, 168, 197 Reynolds, Lloyd G., 110, 111Pigmy Deposit Scheme, 172 Rosenzweig, Mark R., 87, 92-93Policy (industrial trade), 7, 133; employ- Rudra, Ashok, 95

ment effects of, 144-52; services and, Rural sector: female workers in, 46;135-36, 143. See also Trade migration policy and, 107; unemploy-

Policy (labormarket): agriculture and, ment in, 68; utilization of labor in,164-65; capital markets and, 172; 82-90; wage determinations for, 90-97education and, 194-205; high-wage,114; migration and, 105-08; popula- Sabolo, Yves, 137, 138, 139tion growth and, 185-93; rural sector Sabot, Richard H., 62, 66, 100and, 96-97; rural-urban migration and, Saito, Katrine W., 171105-08; services and, 135-36, 143; Sanyal, Bikas C., 122study conclusions and, 6-10; under- Sao Paulo, 141employment, 74; unemployment, Savings, 8, 155, 166, 167; determinants75; wage differentials and, 66; wages of, 170-72and, 125-32. See also Labor market Sauvy, Alfred, 181

Population, 75, 77; capital formation and, School fees, 10, 200-0129; consequences of rapid growth in, School leavers, 6, 123, 124, 197177-81; GDP and growth in, 28 n.9; Seasonality, farm labor and, 89-90

v GNP per capita and, 181-83; labor Self-employment, 57, 141, 142; theoreti-force growth and, 18, 19, 42-47, cal concepts and, 59-60. See also183-85; migration and urban, 98; Employmentpolicy, 185-93; labor supply and Sen, Amartya K., 66growth in, 9, 15-18. See also Fertility. Senegal, 197

Post Office Savings Scheme, 171 Services, 29; demand for, 136-40; inPoverty: migration and, 107-08; policy developed and developing countries,

and, 132; underemployment and, 4, 11, 12, 13; expansion in, 135; GDP65-66, 69 and, 28; informal sector and, 140-43;

228 Index

Time-budget studies, 83-85migration policy and, 106-07, 135; Tobago, 129policy and, 135-36, 143; productivity Todaro, Michael P., 100-01, 103, 1.06 n.8and, 135-36, 140-41; productivity Trade, international, 26-28. See also Ex-growth and, 53; rural-urban migration ports; Imports; Import substitution;and, 7; sectoral structure of labor Policy (industrial trade); Terms offorce and, 47-48; structure of labor tradeforce model and, 31-41 Trade unions. See Unions

Sethuraman, S. V., 142 Traditional sector, dualism in, 79-80Sharecropping, 93-96, 165 Transportation, 122, 141, 145; migrationSierra Leone, 142 policy and, 105Simon, Julian L, 181-82 Trinidad, 129Singapore, 129, 192, 203 Tuition fees, 10, 200-01Sjaastad, L. A., 100 Tunisia, 192Smith, Anthony, 55 n.8 Turkey, 192Social security: labor market distortion Turner, H. A., 127 n.l

and, 117-18; unemployed and, 57, Turnham, David, 62, 7374

Squire, Lyn, 79 n.1 Underemployment, 58; defined, 4; esti-Sri Lanka, 55, 117, 123, 145, 149, 197; mates of, 69-74; invisible, 64-65, 69;

pay scales in, 119-21; rural unemploy- policy and, 74; theoretical conceptsment in, 68; savings and, 171 and, 58-66; visible, 62, 69-73. S'ee

Stexilization, 192 also Employment; UnemploymentStewart, Frances, 66 Unemployment, 57, 77, 125, 129 n.9,Stolnitz, George J., 184 135; assumptions concerning, 82;Subsidies, 136; agriculture and, 165, defined for statistical purposes, 61;

171; education, 131, 199-200; of pub- discouraged workers and, 62; disguised,lic services, 7 63; duration of, 123, 124;education

Subsistence, hypothesis of, 90-91 and, 6, 19, 69, 75, 130, 132, 197-98,Sudan, 129 201; estimates of, 66-69; formatSussman, Zvi, 112-13 modelingand, 81;male labor fcrceSweden, 117 and, 185; measuring, 65, 66; migrationSyndicate Bank (India), 171-72 policy and, 106; modern sectorSyrquin, Moises, 47, 140, 144 dualism and, 80; open, 57, 66, 67,

69-74, 96; policy and, 66; publicTaiwan, 83, 129, 159, 162-64, 172, 174, sector and, 120-21;solution to, 75;

192 theoretical concepts of, 58-66; urban,Tanzania, 115 n.8; discouraged worker 13-14, 68, 73, 80. See also Employ-

study in, 62; open unemployment in, ment; Underemployment57; underemployed in, 73 Unemployment rates, 3-4, 145, 149;

Tariffs, 136 migration and, 103-05Taxes, payroll, 11 7-18 Unions, 74, 80; labor market operationTax incentives: fertility and, 192; on-the- and, 112-14; minimum wage and,

job trainingand, 204 125, 129; wages and, 77, 116 n.11Technical Schools (Kenya), 202 United Kingdom, 117Technology, 167; agricultural, 8, 157-60, United States, 110; minimum wage in,

162-64, 166, 170; in developed coun- 127 n.ltries, 21; development and progress Unskilled workers, 29, 30, 77, 114-15;in, 29-30; labor force growth and, wage policies for, 125-30, 13235-41; occupational structure of Urban sector: female workers in, 46;labor force and, 51-53 migration and, 6-7, 77-78, 98-108;

Tenants (farm), 93-96 population increase in, 17; unemploy-Terms of trade: agriculture and, 8; barter, ment in, 68, 73

27-28; agricultural employment and Uruguay, 55intemal, 153-55. See also Trade

Thailand, 90, 101-02, 110, 111-12, 129, Value added: manufacturing and, 158;203 sectoral composition of, 26

Thormann, Peter 1., 127 n.l Venezuela, 115, 117, 129

Index 229

Versluis, Jan, 122 interdistrict differences in (India),Vocational training, 10, 201-03 92-93. See also Earnings; Earnings

differentials; Pay scales; MinimumWage differentials, 110, 114, 125; formal wage; Salaries; Wage differentials;

modeling and, 81; geographical, 122- Wage rates23; migration and, 102; mining and, Webb, Richard C, 130115-16; policy and, 66; for unskilled Westphal, Larry E., 149, 150and uneducated workers, 4. See also White-collar workers, 51, 114-15, 203;Earnings differentials; Wages in Latin America and the United

Wage employment, 57, 142; agriculture States, 22and, 85; theoretical concepts and, 59. WiUiams, Ross A., 34See also Employment Women, 112; labor force participation

Wage policies: for educated labor, 130-32; and, 46; in rural work force, 83-84;for unskilled labor, 125-30 unemployment and, 69-70, 111 n.2

Wage rates, 62, 79; adjustment, 80; Work hours, 83-85education policy and, 10; industrial,79, 80; migration and agricultural, Yields, 157103; population growth and, 183- Youth, 18, 69, 77; apprenticeship schemes85; productivity and, 53-56; rural, and, 202; population growth and, 17790-9 7; urban, 77. See also Wage Yudelman, Montague, 157, 162differentials; Wages

Wages, 145; determinants of rural, 83- Zambia, 115, 117, 129, 19297; institutional determinants and, 4; Zymelman, Manuel, 180, 202

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