Embed Size (px)
Citation preview
SWP562
Capital Accumulation in Eastern and Southern AfricaA Decade of Setbacks
Ravi GulhatiGautam Datta
WORLD BANK STAFF WORKING PAPERSNumber 562
Pub
lic D
iscl
osur
e A
utho
rized
Pub
lic D
iscl
osur
e A
utho
rized
Pub
lic D
iscl
osur
e A
utho
rized
Pub
lic D
iscl
osur
e A
utho
rized
Pub
lic D
iscl
osur
e A
utho
rized
Pub
lic D
iscl
osur
e A
utho
rized
Pub
lic D
iscl
osur
e A
utho
rized
Pub
lic D
iscl
osur
e A
utho
rized
/-/-WORLD BANK STAFF WORKING PAPERS MV/5-
Number 562 57
4u J 7
Capital Accumulation in Eastern and Southern AfricaA Decade of Setbacks
Ravi GulhatiaGautam Datta
The World BankWashington, D.C., U.S.A.
Copyright © 1983The International Bank for Reconstructionand Development / THE WORLD BANK1818 H Street, N.W.Washington, D.C. 20433, U.S.A.
First printing April 1983All rights reservedManufactured in the United States of America
This is a working document published informally by the World Bank. Topresent the results of research with the least possible delay, the typescript hasnot been prepared in accordance with the procedures appropriate to formalprinted texts, and the World Bank accepts no responsibility for errors. Thepublication is supplied at a token charge to defray part of the cost ofmanufacture and distribution.
The views and interpretations in this document are those of the author(s) andshould not be attributed to the World Bank, to its affiliated organizations, or toany individual acting on their behalf. Any maps used have been preparedsolely for the convenience of the readers; the denominations used and theboundaries shown do not imply, on the part of the World Bank and its affiliates,any judgment on the legal status of any territory or any endorsement oracceptance of such boundaries.
The full range of World Bank publications is described in the Catalog of WorldBank Publications; the continuing research program of the Bank is outlined inWorld Bank Research Program: Abstracts of Current Studies. Both booklets areupdated annually; the most recent edition of each is available without chargefrom the Publications Distribution Unit of the Bank in Washington or from theEuropean Office of the Bank, 66, avenue d'Iena, 75116 Paris, France.
Ravi Gulhait is the chief economist of the Eastern Africa Regional Office ofthe World Bank; Gautam Datta is a consultant to the World Bank.
Library of Congress Cataloging in Publication Data
Gulhati, Ravi.Capital accumulation in eastern and southern Africa.
(World Bank staff working papers ; no. 562)Bibliography: p.''1. Saving and' investment--Africa, Eastern. 2. Saving
and investment--Africa, Southern. 3. Capital producti-vity--Africa, East'ern. 4. Capital productivity--Africa,Southern'. I. Datta, Gutam, 1947- . II. Title.III. Series.RC860.Z9S34 1983 332'.0415'09676 83-5899ISBN 0-8213-0169-1
ABSTRACT
The paper attempts to analyze the magnitude of the setback incapital accumulation in Eastern and Southern Africa and the proximate causesof this phenomenon. The sample consists of 16 countries and available datafor the late 1960s and 1970s are explored. Given the weakness of thestatistics, the authors rely more on expert observations than on rigorousquantitative assessments; although available data are analysed. Capitalformation increased fairly rapidly during 19 67-1974 but then slowed downconsiderably. Investment was financed to a considerable extent by externalconcessional assistance; rapid growth in such funds during the late 1970shelped offset declining national savings rates to some extent. The setback ininvestment rates was greatly accentuated by a large and widespreaddeterioration in the productivity of capital brought about by the impact ofgovernment policy, strained absorptive capacity and a variety of exogenousfactors.
-ACKNOWLEDGMENTS
We are grateful to Ram Agarwala, Rolf Gusten, Robert Armstrong and PeterHansen for valuable comments on an earlier draft of this paper.
CONTENTS
Section Page No.
I. Introduction . .................................... 1
II. First, A Look At the Record ....................... 4
III. Behavior of Investment ............................ 10
IV. Productivity of Capital ........................... 23
Capacity Utilization 24
Sector-Mix and Sectoral ICORs 28
Absorptive Capacity 30
Impact of Government Policy 31
V. Conclusion ......................................... 34
Figures
Figure 1. The Investment Ratio and GDP Per Capita ....... 13
Figure 2. The Median Ratios of Savings and Investmentto GDP, Eastern Africa ..... 16
Figure 3. The Savings Ratio and GDP Per Capita .......... 18
Figure 4. The Savings Ratio and Terms of Trade, Zambiaand Zaire ..................................... 20
Figure 5. The Savings Ratio and Terms of Trade, Ethiopiaand Uganda .................................... 21
Page No.
Annex I - Statistical Tables
Table 1 The Growth of GDP in Constant Prices, EasternAfrica and Comparator Countries, 1960-70 and1970-79 ................................................ 38
Table 2 The Growth of GDP in Constant Prices, 1967-78and Sub-Periods 1967-73 and 1973-78 ..................... 39
Table 3 The Growth of Gross Domestic Investment in ConstantPrices, Eastern Africa and Comparator Countries,1960-70 and 1970-79 ................................... 40
Table 4 The Growth of Gross Domestic Investment in ConstantPrices, 1967-78 and Sub-Periods 1967-73 and 1973-78 .... 41
Table 5 The Incremental Capital Output Ratio In The Periods1961-68, 1967-73 and 1973-79 .......................... 42
Table 6 Incremental Gross Capital Output Ratios in FiveDeveloped Countries, 1967 to 1974 ...................... 43
Table 7 Historical Incremental Capital Output Ratios InDeveloped Countries ................................... 44
Table 8 The Ratio of Gross Domestic Investment to GDP,1967-78. Three-Year Moving Averages ................... 45
Table 9 Index of Real Gross Fixed Capital Formation By theCentral Government .................................... 46
Table 10 The Ratio of Gross National Savings to GDP.Three-Year Moving Averages, 1967-78 .... ............... 47
Table 11 Terms of Trade Estimates, 1967 to 1978. Three-YearMoving Averages ........................................ 48
Table 12 Gross National Savings as a Percentage of Gross NationalInvestment. Three-Year Moving Averages, 1967-78 .... ... 49
Table 13 Net Official Development Assistance as a Percentageof External Resources Inflow ........................... 50
Table 14 Direct Investment as a Proportion of Long-Term CapitalInflows ................................................ 51
Table 15 New Private Direct Investment From DAC Sources .... ..... 52
Page No.Annex I - Statistical Tables (Cont'd)
Table 16 The Stock of Foreign Direct Investment inEastern Africa, End 1978 ............................... 53
Table 17 Gross Eurocurrency Credit to Eastern Africa .... ........ 54
Table 18 Capacity Utilization in Selected Sectors inTanzania, 1978-79 ...................................... 55
Table 19 Capacity Utilization in a Sample of Parastatal Firmsin Tanzania, 1979 ...................................... 56
Table 20 Capacity Utilization in a Single of PublicEnterprises, 1976-78, Somalia .......................... 57
Table 21 Capacity Utilization in Certain Manufacturing Firmsin Sudan, 1973 ......................................... 58
Table 22 Capacity Utilization in the Public Industrial Sectorin Sudan, 1975-76 ...................................... 59
Table 23 Frequency Distribution of Capacity Utilization inPlants/Processes of the INDECO Group, Zambia, 1981-82 .. 60
Table 24 Quantum Index of Imports, 1967 to 1978 .... ............. 61
Table 25 Petroleum Imports Into Eastern Africa. Three-YearMoving Averages ........................................ 62
Table 26 Public Current Expenditure Per Pupil in ConstantPrices At The First Level (Ages 7 to 13) .... ........... 63
Table 27 Share of Public Investment (Including ParastatalInvestment) in Total (Three-Year Moving Averages) ....... 64
Table 28 Index of Real Recurrent Expenditure on Economic ServicesIn Four Eastern African Countries ...................... 65
Annex II Interrelations between the ICOR, Growth Rate, Invest-ment Ratio and the Investment Rate ..................... 66
Annex III Limitations of National Account Data in Eastern Africa 71
References ........... ............................................ 71
I. Introduction
1. The 1970s was a disappointing decade for the economic development of
Sub-Saharan Africa and particularly of the oil-importing countries of Eastern
and Southern Africa. The aim of this paper is to study this experience in 16
countries with a special focus on capital accumulation. We try to answer the
following questions:
- What were the common characteristics of this experience and what
were the elements of diversity?
- Was the setback in development mainly the result of a slowing down
in the rate of investment or was it caused in large part by a fall
in the productivity of capital?
- To the extent that capital accumulation slowed down, was it the
result of a lag in domestic savings or a turnaround in external
capital inflow?
- What factors explain the declining productivity of capital, in cases
where this phenomenon was a prominent part of the setback in
economic development?
2. By focusing on capital accumulation, we do not intend to take part
in the debate on the role of capital in economic development. Much has been
written on this topic by those (e.g. Arthur Lewis, Rostow, Harrod, Domar) who
assign capital a strategic part, and by others (e.g. Cairncross, Frankel) who
emphasise the contribution of technology, organization, entrepreneurship,
etc. (Meier, 1964). The long run development of Eastern and Southern African
- 2 -
countries requires large doses of capital combined in appropriate ways with
the growth of human skills, the evolution and adoption of suitable innovations
and the maturation of indigenous institutions. The setback in capital
accumulation and in economic development during the 1970s might have occurred
precisely because factors of production have not been combined in the right
quantities. In any event, our emphasis on capital in this paper should not be
read to mean that we assign this factor a preeminent role.
3. Our analysis of capital productivity is cast in terms of the
incremental capital-output ratio (ICOR) which relates investment to changes in
GDP during the decades of the 1960s and 1970s. The intention is to capture
long-term changes in this coefficient and thereby to study the secular
relationship in the supply of capital and that of net production. The ICOR,
in this context, will be influenced by the pace of technical progress, the
growth of professional and managerial skills and the quality of organizations.
4. The ICOR is not narrowly concerned with new investment and its
impact on output. It is influenced not only by income attributable to new
investment but also by income generated by existing assets. And since
existing assets are generally very much larger than additions to the capital
stock, the ICOR is much more powerfully affected by the productivity of
existing assets than by the quality of new investment. For example, a decline
in capacity utilization throughout the economy caused by chronic scarcity of
foreign exchange will raise the ICOR substantially even though new investments
are highly productive.
5. An increase in the ICOR associated with the slowing down of GDP
growth is not by itself a convincing explanation. To trace the final causes
of the retardation, it is necessary to look further back into myriad factors
that determine this coefficient. Nevertheless, the ICOR is a convenient
summary statistic that allows us to decompose changes in GDP growth into those
attributable to a deterioration in capital productivity and others related to
a fall in the rate of investment.
6. The ICOR is a familiar enough coefficient with many defects (see
Reddaway, 1962). In the Eastern Africa context, these defects are compounded
by the following problems. Firstly, the proper measure of ICOR should utilize
net fixed investment. Using gross rather than net investment introduces a
bias, since the replacement component of investment is smaller at higher rates
of growth of investment. Total investment includes inventories which may be
sizable in primary-producing (and especially mineral-producing) countries in
some years. Unfortunately, neither the extent of depreciation nor the fixed
component of investment is known in many African economies and the measure of
investment used in this paper is gross, total investment 1/. Secondly, the
ICOR is not a very stable statistic. Investment is a volatile variable and so
is output. Eastern African countries generally have large agricultural
sectors, subject to the vagaries of weather. We have used three-year averages
to deal with these fluctuations but we may not have entirely eliminated them.
Thirdly, many countries in Africa undertook massive, once-for-all type of
investment projects during our period of study. Examples of these are the
Tazara Railroad (Tanzania and Zambia), and the Inga-Shaba hydroelectric
project (Zaire). In these cases a marked rise in the ICOR over several years
is inevitable, but this rise does not necessarily mean that capital
productivity is falling.
1/ This is not unprecedented in empirical, development literature. Kuznets(1961), for instance, has used this concept.
- 4 -
7. The data base for analysis is weak. Statistics on investment and
output in the non-monetized sector are particularly unreliable. National
account statistics prepared by official agencies in Eastern Africa are subject
to many other pitfalls (Annex III). We have relied mainly on data from these
sources, but it has been subjected to tests of consistency and adjusted in
some cases. Most of the statistical analysis in this paper is at the
economy-wide level. A brief enquiry into sectoral ICORs did not lead very
far. We have not attempted to establish the statistical relationship between
investment rates or ICORs and other structural or policy variables, given the
scarcity of reliable information.
8. This paper is not intended as a rigorous, quantitative analysis of
the setback in Eastern and Southern African development. Data are cited in
support of conclusions, but the statistical analysis does not generate them:
we have relied much more on expert observations of colleagues who have
followed developments in these countries over a fairly long time and who have
familiarity with field conditions in individual countries.
II. First, A Look At the Record
9. Eastern Africa passed through a disappointing decade of economic
growth in the seventies. The median growth rate in Eastern Africa, in the
1960s was above that of a group of largely Asian countries at similar, low
levels of per capita income. During the 1970s the reverse was true; growth in
comparator countries was higher than in Eastern Africa (Annex Table 1). If
the period 1968-1978, on which this paper focuses, is considered, then the
decline in growth in Eastern Africa is seen to be concentrated in the latter
half of the period (Annex Table 2). The relative position of Eastern Africa
is worse, if comparison is made with a group of oil-importing middle-income
countries in East Asia. They recorded GDP growth rates of 8.2% per year
during the 1960-1973 period and 7.5% per annum during 1973-1980, compared to
the Eastern African average which fell short of 5% per annum in both periods.
10. However, the Eastern Africa experience has been diverse. In a few
countries such as Malawi, Kenya, Botswana and Lesotho the growth rate of
output in the seventies exceeded that of China, the low-income comparator
country with the most impressive record. In over a third of the Eastern
Africa countries, the growth rate was higher than in India or Pakistan.
Counterbalancing this was the experience of Ethiopia, Zaire, Uganda,
Madagascar, Zimbabwe and Zambia. In these countries output growth was either
very low or even negative, especially in the 1973-78 period; and they greatly
lowered the Eastern Africa averages.
11. The decline in the growth of income in Eastern Africa has been
paralleled by a decline in the growth rate of investment. In real terms, the
median annual growth rate of investment fell from almost 10% in the 1960s to
less than 3% in the 1970s (Annex Table 3). At the same time, the median ICOR
rose from 4.3 in 1967-1973 to 5.2 in 1973-79 (Annex Table 5). In this area
too, however, there is considerable diversity. Overall investment growth
rates have been impressive in Burundi, Malawi, Rwanda, Lesotho, Swaziland and
Botswana (Annex Table 4). On the other hand, negative investment growth rates
characterized Ethiopia, Uganda and Zambia.
12. The rise in ICORs is observed mainly in the 1973-79 sub-period. The
ratio rose in eight countries and in another three (Zaire, TJganda and
Zimbabwe) it had turned negative. In contrast, Malawi, Somalia, Sudan and
Tanzania showed a falling ICOR in the 1973-79 period. In six
- 6 -
countries--Burundi, Malawi, Rwanda, Lesotho, Kenya and Botswana, ICORs were
relatively low (between 2.8 and 5.3), even in 1979 2/. Yet in six others the
ICORs had reached double digit or negative magnitudes.
13. These preliminary findings suggest that it is misleading to treat
the Eastern African countries as a homogenous group which suffered declining
growth of output as well as investment, accompanied by rising ICORs. While
this was true of countries with the bulk of population and GNP in the region,
there were significant exceptions. In this paper, accordingly, two
statistical groupings have been used. In the first group are countries with
relatively high rates of growth of investment and output and reasonable levels
of ICOR. In this group are included Botswana, Lesotho, Rwanda, Malawi,
Swaziland, Burundi, Kenya, Tanzania and Sudan. The second group consists of
countries with low rates of investment and output growth, accompanied by high
or even negative ICORs. In this category fall Somalia, Zaire, Uganda, Zambia,
Ethiopia, Madagascar and Zimbabwe; they account for almost 60% of the
population and only a slightly smaller fraction of GDP of the entire sample.
14. The criterion chosen to distinguish the two groups is whether the
rate of GDP growth for the 1967-1978 period exceeded or fell short of 4% per
annum 3/. Too much should not be read into the classification; it is purely
statistical. While there are similarities between the growth and investment
experience of countries in each category, their ranking by the investment
2/ Kuznets (1960) and Kuznets (1961) found gross ICORs lying between 4 and 6in many countries. Carrington and Edwards (1979) estimated gross ICORs tobe between 4 and 8 in the mid-seventies in several major OECD countries.See Annex Tables 6 and 7 for details.
3/ In terms of growth of per capita GDP, this would mean a growth rate ofapproximately 1 to 1.5% for most of the same countries.
rate, ICOR, growth rate of GDP or other relevant series is not always
congruent. The Sudan and Tanzania deserve special mention in this context;
while we have put them in the first group on the basis of the chosen growth in
GDP criterion, they could just as well be assigned to the second group, if
emphasis was given to the behavior of savings or capacity utilization.
15. The timing of the setback in investment and output also shows
considerable inter-country variability. The first oil price increase of
1973-74 is often taken as a watershed in the recent growth history of oil
importing developing countries. This event was clearly of importance in the
region, but it was far from decisive. Very specific influences were at work
in each country. In 1972, Idi Amin came to power in Uganda and initiated
major changes in policy. In 1974, Ethiopia underwent a revolutionary change
in government. In 1975 the civil conflict in Zimbabwe escalated. The same
year also saw a decline in copper prices which severly affected Zambia and
Zaire. Drought affected several countries during the mid-seventies. Many
countries reaped the benefits of the coffee boom of 1976-77 to variable
degrees. The East African Common Market collapsed in 1977. Thus, while the
oil price rise of 1973 was, undoubtedly, a major factor in the economy of each
country, it was not the only and perhaps not even the predominant shock in all
of them. For presentational purposes, the three-year average centered on 1973
has been taken as a rough dividing line to separate the data for the period
under study 4/.
16. No country experienced a fall in GDP in the 1967-1973 sub-period,
but four countries suffered an absolute reverse during the 1973-78
sub-period. Moreover, during 1973-78 growth rates in output were lower in 10
4/ All growth rates are calculated using three-year averages as the base andterminal period.
- 8 -
countries, relative to the earlier sub-period. In 11 countries the growth
rate of investment was lower in 1973-78 compared to 1967-73. In six countries
real investment declined in the latter sub-period, while this was the case in
only three countries in the 1967-73 period. The ICOR remained at a
satisfactory level in 1967-1973. ICORs were higher (ignoring very small
variations) in six countries and lower in eight, compared to the 1961-68
period. Except for Madagascar, no country had an unusually high ICOR in the
period upto 1973. The 1973-79 experience was much more unidirectional; in 12
countries the ICOR rose relative to the earlier sub-period.
17. We recognize that splitting the sample of 16 countries into two
groups, on the basis of a purely statistical criterion, is useful, but hardly
sufficient. A great deal of diversity remains in each group. For example,
Group I could be subdivided into (i) the BLS countries, i.e. Botswana, Lesotho
and Swaziland; (ii) countries facing acute demographic pressures, i.e.,
Malawi, Kenya, Rwanda and Burundi; (iii) the rest, i.e., Tanzania and Sudan.
The BLS countries are not typical. Their distinguishing characteristics are
the following: (a) Each has a population of less than 1 million; (b) Given
their geographical position and land-locked nature, they have very intensive
economic relations with the Republic of South Africa (RSA). These include
trade, a large flow of migrant-worker remittances from RSA to BLS countries,
private investment from RSA into mining, tourism and commercial agriculture in
BLS countries and fiscal arrangements under the Southern African Customs
Union. The seeming economic success of BLS countries, at least in terms of
macro-economic variables, must be related in large part to the prosperity of
RSA.
_ 9 -
18. Demographic pressure is present in all 16 countries. In fact, this
is a characteristic of the entire Sub-Saharan African region (see Faruqee and
Gulhati, 1983). However, in Malawi, Kenya, Rwanda and Burundi, the
demographic problem exists in a much more acute phase because the margin of
cultivable, but not yet cultivated, land has narrowed considerably or
disappeared altogether. This subset of countries also has policy frames which
share several common characteristics, i.e., openness to foreign private
investment, encouragement of indigenous private enterprise, tolerance for
large numbers of expatriates and relative emphasis on the economic growth
objective as against equity.
19. Tanzania and Sudan fall in a residual category, but they are very
different from one another. Tanzania is distinguished by its plentiful
physical potential and its sharp change of course symbolized by the Arusha
Declaration which rejected the private sector, outward-oriented, capitalist
strategy. Sudan also had its wave of nationalizations in 1970, but this
socialistic doctrine was reversed later on. It is a very large country in
physical size, but it is not richly endowed with infrastructure or natural
resources.
20. Countries in Group II are also a diverse lot in terms of
institutional and policy frames as well as per capita income levels (Ethiopia
$120 and Zambia $540 in 1979). Ethiopia, Uganda and Zimbabwe have been
victims of civil strife to a much larger extent than the rest. Zambia and
Zaire share a heavy dependence on copper and the sharp fluctuation in its
international price. Ethiopia, Madagascar and Zambia have assigned a
commanding role to the public sector and placed a heavy emphasis on the equity
objective.
- 10 -
21. These brief, descriptive notes bring out the complex nature of
social, political and economic reality in Eastern Africa. The aim of
explaining the setback in capital accumulation in terms of some easily
identifiable factors is not at all easy.
III. Behavior of Investment
22. The slowing down in GDP growth could be the result of rising ICORs
or of declining investment ratios or of some combination of these factors. We
will examine the detailed evidence, first by focusing on the behavior of
investment and its ratio to GDP and later by studying ICORs.
23. The investment ratio in the mid-sixties (see text table page 11)
was very low in Burundi and Rwanda and already on the high side in five
countries. During 1967-1973, the volume of investment expanded briskly, i.e.,
at double-digit growth rates in Malawi, Zaire and Lesotho (Annex Table 4).
The investment ratio rose rapidly in these countries and also in some other
cases.
- 11 -
RELATIVE GROWTH OF INVESTMENT AND GDP IN EASTERN AFRICA, 1968-1973 a!
Rate of Investment GrowthInvestment/GDP Less than Equal to More thanratio in 1966/68 Negative GDP Growth GDP Growth GDP Growth
Less than 10% Burundi Rwanda-------------------------------------------------------------- __-----------
Between 10% & 15% Sudan Madagascar SomaliaLesotho
Between 15% & 20% Uganda Ethiopia ZaireMalawiTanzania
------------------------------------------------------------- __------------
Above 20% Kenya BotswanaZambia ZimbabweSwaziland
a/ All growth rates use three-year averages for the base and terminal period.source: Data files, The World Bank.
24. A comparison of investment rates in the mid-seventies between
Eastern Africa and other LDCs suggests that the former was not much
handicapped. We generated a sample of 24 low-income countries, 15 from the
region and 9 non-African low-income countries. A regression equation was
fitted for the pooled sample of countries, relating the investment ratio to
per capita GDP in 1974-76. The estimated equation was:
_2I/Y = 8.4202 + 0.0516 (y) (R = 0.51)
Where I = gross national investmentY = GDP at factor cost
and y = GDP per capita in US dollars.
- 12 -
In Ethiopia, Sudan, Burundi, Madagascar and Zimbabwe the actual ratio lay
below the regression line (see Figure 1). The actual investment ratio was
above the regression line in Malawi, Tanzania, Lesotho, Botswana, Somalia,
Zaire and Zambia. Malawi, Lesotho and Zaire stand out in having an investment
ratio far higher than warranted by their level of per capita GDP. In Kenya
the actual and predicted ratios were approximately equal. We also calculated
a regression equation of 15 East African countries separately 5/. The East
African regression line remains above the regression line for the pooled
sample, but the distance between the two tends to diminish at higher levels of
per capita income.
25. From this favorable position in the mid-seventies, the pace of
capital accumulation has slowed down considerably. The median growth rate in
the volume of investment slackened from a brisk 6.4% per annum during
1967-1973 to only 2.4% per annum in 1973-78. The text table on page 14 shows
that the volume of investment declined in absolute terms in six countries. It
is surprising to note, therefore, that in this period of widespread slowing
down, a number of countries experienced large increases in investment. There
was a dramatic turnaround in Burundi and Sudan who had experienced an
investment decline in the early 1970s, but who now saw a sharp rise (Annex
Table 4). Lesotho, Swaziland and Somalia maintained a substantial expansior.
in investment.
5/ The regression equation for 15 East African countries separately was
2I/Y = 11.6 + 0.0454(y) (R= 0.44)
FIG. 1 THE INVESTMENT RATIO AND GDP PER CAPITA, 1974-7645 , , , , , , , _ , ,
BOTSMAM
40LOSOTMW
REGRESSION LINE,
*ZA3REp RE0GRESS ION L INE,I- // _ 5 COMBINED SAMPLE
w
> 20zH
e .. .. II I I IB 5Q t 0Q 15Q 20e 2SQ 300 350 4B0 450 500 558
GDP PER CAPITA (u.s DOLLARS)
- 14 -
a/RELATIVE GROWTH OF INVESTMENT AND GDP IN EASTERN AFRICA, 1973-1978
Rate of Investment GrowthInvestment/GDP Less than Equal to More thanRatio in 1973 Negative GDP Growth GDP Growth GDP Growth
Less than 10% Burundi----------------------------------------------------------------- __--------
Between 10% & 15% Ethiopia Rwanda SudanMadagascarUqanda
Between 15% & 20% Lesotho
Above 20% Zambia Tanzania Somalia ZaireZimbabwe Kenya SwazilandBotswana Malawi Somalia
a/ All growth rates are based on three year averages for the base and terminalperiod.
Source: Data files, the World Bank.
26. Looking at the situation at the end of the 1970s, the investment
picture is particularly stark in two countries. In Uganda, the investment
ratio has dropped from a respectable 16% to 17 % of GDP in the late 1960s to
an abysmally low level of 3% to 4% now. This is catastrophic. In Ethiopia,
the drop is not as precipitous, i.e., from 15% to 9% in the same period, but
it is a cause for concern (Annex Table 8).
27. The setback in investment is largely an African phenomenon. Out of
63 non-African low-and middle-income countries listed in the World Development
Report, 1981, only 8% of the sample had negative investment growth rates in
the seventies. In Eastern Africa this was the case in 40% of the sample. All
the countries in Group II with the exception of Somalia had declining real
investment rates in this period.
- 15 -
28. The slowing down of investment activity in Eastern Africa could be
the result of a relative scarcity of investable funds or strains on absorptive
capacity (reflected in lack of projects, shortages of trained personnel,
emergence of bottlenecks and delays in decision making (see Gulhati, 1967) or
some combination of these two factors). Given that at least eight countries
have experienced an expansion of investment at a rate of 6% per year or more
over the whole period 1967-1978, we should not discount the impact of strained
absorptive capacity in reining in investment. Central government investment
outlays in real terms doubled in Zaire in the early 1970s and trebled in
Malawi, Lesotho and Botswana during 1972-79 (Annex Table 9). Lack of projects
has been an issue in several instances. Availability of project managers,
engineers and accountants has been a chronic problem in most of these
countries. Bottlenecks, such as limited construction capacity and congestion
in ports have delayed project implementation in many places. Finally,
slowness of government decision making has been a pervasive phenomena
affecting all aspects of economic activity. These strains have not only
influenced the trend of capital accumulation but also its quality; a topic we
will discuss in the context of ICORs.
29. Meanwhile, we will focus on the availability of savings--internal
and external--as a factor bearing on capital accumulation. Figure 2 shows
that while the median investment ratio for the whole sample rose from 16.5% to
24.1% between 1966/68 and 1973/75, the national savings ratio was fairly
flat. Subsequently, the average investment ratio dropped by about 3 points
and the savings ratio by almost 4 points. The proportionate contribution of
external savings in financing capital accumulation has tended to rise during
the period as a whole.
-16 -
FIGURE 2: THE MEDIAN RATIOS OF SAVINGS ANDINVESTMENT TO GDP,EASTERN AFRICA
sB-
-THE INVESTIENT RATIO
(PERCENT)' THE SAVINGS RATIO
24-
s-I
12-
|~~~~~~~~~~~~~~~~~~~~~ %
19;7 1198 1888 t878 t871 1872 1873 1874 1879 1878 1977 19;8
YEARS
- 17 -
30. National savings during the late 1960s were very low or negative in
more than one-third of the sample, as the table below shows. Burundi, Lesotho
and Botswana had negative savings at that time. Only Zambia had a high
savings coefficient. The record shows a substantial rise in savings till
about the middle of the 1970s. This was particularly the case in Malawi,
Swaziland, Botswana and Zimbabwe (see Annex Table 10).
RATIO OF SAVINGS TO GDP
(Number of countries)1966/68 1972/74 1976/78
Low Ratios (less than 5%) 6 3 3Middle Ratios (5% up to 20%) 9 9 8High Ratios (above 20%) 1 4 5
31. The savings ratios of African countries were not atypical when
compared with a broad sample of low-income countries. A regression of the
savings ratio in 1974-76 against per capita GDP for a sample of 9 comparator
low-income countries and 15 Eastern Africa countries indicated that actual
savings in Malawi, Tanzania, Kenya, Swaziland, Ethiopia and Somalia were above
the predicted level (see Figure 3). Actual savings lay below the predicted
level in Lesotho, Sudan, Botswana, Zaire and Madagascar. We also calculated a
FIG 3. THE SAVINGS RATIO AND GDP PER CAPITA, 1974-7645 . a -s
40
35
30
2.5H 2 5 REGRESSION LINE, '
<< ~~~~~~~~~~~~~~COMBINEDDSAMPLE20
U) ~~~~~~~~~~~~~~~~~~REGRESSION LINE,z l X#XU E. AFRICA_
z iS - / _
0 H A
35
-5
-10LEBHOW
0 50 801 1 5Q 200 250 300 35Q 488 458 58a8 550
QDP PER CAPITA(u.S. DOLLARS)
- 19 -
regression equation for 15 Eastern African countries separately 6/. The
regression line for Eastern Africa remained below the pooled regression line
for a substantial range of per capita incomes.
32. During the second half of the 1970s, the trend was distinctively
towards lower domestic saving ratios, particularly in Group II and in Tanzania
and Sudan from Group I. In the case of copper exporting economies, declining
saving ratios went hand in hand with a serious deterioration in the terms of
trade (Figure 4) but this relation did not hold in many other instances. The
collapse of savings in Ethiopia and Uganda took place despite the rise of
coffee prices and substantial improvement in terms of trade (Figure 5; also
see Annex Table 11).
33. The reliance of Eastern Africa on external savings to finance its
investment program has always been high and this has increased (Annex Table
12). The median ratio of gross national savings to gross national investment
exceeded 700% only once during this period. In seven out of fourteen countries
for which data are available for 1977-79, this ratio was below 50%. In Group
I countries, domestic savings financed only approximately a quarter of total
investment at the beginning of the period. This proportion had risen to over
a half by 1973, but it has shown no sustained increase threafter. In Group II
countries the reliance on domestic resources for investment was much higher at
6/ It should be stressed that the data base for this exercise is quite weak.Apart from the data problems in Africa, savings data on economies such asNepal or Afghanistan are largely conjectural. Even in Bangladesh or Indiasavings estimates are not felt to be very accurate. The regressionequation for the pooled sample was:
2S/Y = 1.06 + 0.0549 y (R = 0.41) where S = savings, Y = GDP and y =
per capita GDP. For 15 Eastern Africa countries the equation was:2
S/Y = 4.15 + 0.0609 y (R = 0.43)
- 20 -
FIGURE 4: THE SAVINGS RATIO AND TERMS OFTRADE<,ZAMBIA AND ZAIRE
-_TERMS OF TRAD. ZAMBIA- TERMS OF TRADE ZAIRE
-- - SAVINGS RATIO, ZAMBIA---- SAVINGS RATIO ZAIRE
_ I
4%
IL -zfi;:e . . . . -11
%~~~~~~~~~~~~~~~~~~~4
NC
023-
1867 1888 sass 1870 1871 1872 1873 1974 1975 1876 -1977 1878YEARS
*~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The terms of trade is an index with the value for the year1975 = 10. The plotted points are three-year averages.
-21 -
FIGURE S:THE SAVINGS RATIO AND TERMS OFTRADE*ETHIOPIA AND UGANDA
-fi TERMS OF TRADE ETHIOPIA- - TERMS OF TRADE UGANDA-- -- SAVIN6S RATIO UGANDA---- SAVINGS RATIO ETHIOPIA
20- ~ ~ ~ ~ ~ ~ ~ ~ ~ 7
i- /
le-~~~~~-
19B7 19B8 18B8 1870 1871 1272 1973 1874 1975 1876 1977 1978
YEARS
The terms of trade is an index with the value for the year1975 = 10. The plotted points are three-year averages.
- 22 -
the beginning of the period, approximately 90%. By 1978 this ratio had fallen
to almost 55%. Five cases of striking increase in the domestic financing of
investment can be identified: these are Burundi, Malawi, Rwanda, Swaziland
and Botswana. However, all these countries started the period with very low
or even negative savings rates so that with the exception of Swaziland they
are still heavily dependent on external capital flows. In Tanzania, Sudan,
Zaire and Ethiopia the ratio of gross domestic savings to investment has
declined; the drop is precipitous in the case of the first three countries.
34. Most of the external savings in Eastern Africa take the form of
official development assistance or ODA. Annex Table 13 shows that ODA
exceeded 50% of external resources inflow in all countries and exceeded 75% in
11 of them. In earlier years, non-concessional capital flows constituted an
important source of external capital in Zambia, Zaire, Sudan and Kenya. This
resulted in a rapid buildup of debt service payments, and in Zaire and Sudan
it was necessary to negotiate postponement in scheduled debt service
payments. The role of direct investment has not been of much importance in
the Eastern African countries, with the exception of Zaire and the countries
of the Southern African Customs Union. On the basis of the IMF figures,
direct investment accounted for only 5% to 9% of long-term capital flows to
Sub-Saharan Africa 7/ (Annex Table 14). Even in countries such as Kenya or
Malawi which have been very receptive to foreign equity capital, net private
7/ There are major statistical gaps in this area. The two sources of primarydata, the OECD and the IMF, each suffer from crucial deficiences. TheOECD data omit South African investment since it is concerned only withthe DAC group. The IMF data do not cover Zaire, an important recipientcountry. IMF data also include flows between South Africa and its customsunion partners originating in the customs union payments provisions. Datafor the BLS countries are, therefore, not comparable to that of othercountries.
- 23 -
direct investments have been only 10% to 15% of total long-term capital
inflows. Moreover, much of the investment is in the form of reinvestment of
profits by established foreign companies. Besides the mineral producers, only
Kenya has any substantial stock of foreign capital (Annex Table 16).
35. To conclude this section, the supply of investable funds has had a
considerble influence on the tempo and pattern of capital accumulation.
Declining national saving rates during the late 1970s affected investment
adversely and this tendency would have been more pronounced had it not been
for some offsetting changes in the flow of external funds. ODA from all
sources to the sample of 16 countries expanded by 7% per annum in real terms
during 1976-79. Heavy reliance on ODA also emphasizes the vulnerability of
Eastern Africa in that future investment prospects are intimately tied up with
what happens to official aid. It is clear that the region is not of
particular interest to private foreign investors and that considerations of
creditworthiness will stand in the way of external borrowing on commercial
terms, except on a limited scale.
IV. Productivity of Capital
36. The deterioration in ICORs has been a widespread phenomena. In
trying to understand why this has happened, we will look at the following
factors:
- extent of capacity utilization;
- changes in sectoral-mix of investment and output, and in sectoral
ICORs;
- strains on absorptive capacity; and
- impact of government policy.
- 24 -
Capacity Utilization
37. Our hypothesis regarding utilization is that it has fallen sharply,
partly because of a scarcity of imports. The emergence of idle capacity
raised ICORs sharply, but this decline in capital productivity is caused not
so much by the quality of new investment projects as by the economy-wide
constraint on imports. It follows that ICORs will fall as soon as extra
foreign exchange is available to purchase critical production inputs.
38. Direct evidence to support this hypothesis is scant. Measurements
of capacity utilizations are crude and observations over time are seldom
available. Some statistics are available for Tanzania, Somalia, Sudan, and
Zambia (Annex Tables 18-23). The Tanzanian figures related to the late 1970s
and showed capacity utilization varying from a low of 12% in motorcycles and
bicycles to a high of 94% in tobacco manufactures. There was some tendency
for utilization to vary inversely with the degree of dependence of the
activity on imports. In Somalia, however, utilization was low even in
industries relying on domnestic materials, e.g. meat. Plant capacity had been
designed with exports in view, but these failed to materialize. In Sudan,
Zambia and Zaire the import constraint had been much more severe and this had
affected local farm production; thereby reducing supplies of local and
imported raw materials to manufacturers.
39. No capacity utilization data was available for agriculture, but
there was no doubt that mechanized agricultural production was severely
reduced, partly because of the unavailability of imported spare parts or fuel
for tractors and fertilizers, etc. Events in the Geizera Scheme in the Sudan
are pertinent in this context. The sharp decline in Geizera cotton should not
all be attributed to the foreign exchange constraint; there were many other
- 25 -
factors involved, but unavailability of critical imports was an important part
of the picture. In Tanzania, the shortage of foreign exchange was partly
responsible for the collapse of agriculture. Many crops such as wheat, rice,
sugar, tea, tobacco, sisal and mild coffee rely heavily on imported inputs.
Even maize grown for the urban market uses a large amount of inputs purchased
abroad. In addition, transportation of farm output in a country as
geographically dispersed as Tanzania is very demanding of foreign exchange for
vehicle parts and fuel.
40. We can also cite some evidence at the macro-level on this issue.
Ideally one would study the relation between the flow of intermediate good
imports and ICORs but data for this exercise is not available. Instead, we
have examined the connection between ICORs, total imports and petroleum
imports. Overall there is some correlation between rising ICORs and declining
imports. Group II countries have experienced both phenomena in a more
intensive form than Group I. However, there are cases such as Kenya, and to a
lesser extent, Malawi, where declines in import coefficients allowed GDP
growth with a less than proportionate expansion in imports and without a
sacrifice of productivity. There are also cases such as Somalia and Sudan,
where capacity utilization problems were evident even in a period when the
volume of imports was rising significantly. It was difficult in these
countries to divert foreign exchange earnings to the import of intermediate
goods, since a sizeable part of these earnings accrued to migrants and did not
pass through official channels. Remittances from migrant workers typically
came in the form of non-essential consumer good imports which could be sold in
local markets at premium prices. Furthermore, a large part of imports were
financed by external aid tied to capital goods required by new projects and
not available for purchasing intermediates required for using already
installed capacity.
- 26 -
THE RELATION BETWEEN CHANGE IN ICORS, CHANGE IN IMPORTS
AND THE CHANGE IN PETROLEUM IMPORTS
PercentagePercentage Percentage Change in
Change in Change in Volume of
ICOR between Import Petroleum
1967-73 and Volume Imports
1973-79 1973-77 a/ 1973-77 a/
Group I
1. Burundi 47 45 6
2. Malawi -12 14 8
3. Rwanda 174 1164 462
4. Tanzania 13 -4 42
5. Lesotho 93 89 --
6. Sudan c/ 47 --
7. Kenya 71 -8
8. Swaziland 197 41 --
9. Botswana 73 49 __
Median 25 38 8
Group II
10. Ethiopia 112 14 -10
11. Somalia c/ 27 200
12. Zaire b/ -50 --
13. Madagascar -17 -6 -11
14. Uganda b/ -23 -6
15. Zimbabwe b/ -31 11
16. Zambia 247 -29 23
Median 326 -8 1
Eastern AfricaMedian 21 12 4
a/ These changes are calculated on the basis of three-year averages for the
base and the terminal.
b/ ICOR was negative in latter period implying severe deterioration in the
productivity of investment.
c/ Available data show reduction in ICOR but this is inconsistent with expert
observations.
Source: Annex Table 5, 24 & 25.
- 27 -
41. Also significant was the sluggishness or decline in the volume of
petroleum imports in recent years in several countries. Typically, petroleum
imports increased much more rapidly than GDP in the late 1960s and early
1970s. The subsequent slowing down was a major impediment in the efficient
functioning of the transport network which was the major end-user of oil
imports. This generated a major setback for many economic activities,
especially agricultural marketing, in many countries.
42. Capacity utilization has also fallen because governments have not
provided sufficient funds in the recurrent budget to purchase inputs required
for maintenance and operation of schools, health clinics, roads, agricultural
research and extension services, etc. Although this generalization was
supported by field observations of economic and technical analysts familiar
with Eastern Africa, it was not possible to cite systematic statistical
evidence for all countries. Faced with budgetary difficulties, governments
responded by a series of actions during the late 1970s which cumulatively led
to an anomalous situation, namely underfunding of already completed economic
assets in the public sector while new projects were being launched.
43. Conditions regarding road maintenance are a source of concern in
most countries, particularly with respect to secondary and feeder roads.
Underfunding was not the only difficulty but it was a major impediment in
securing the full benefits of past investments in the road network.
Similarly, very large capital outlays on primary schools during the 1970s were
not producing the expected benefits because of inadequate recurrent budget
provisions. Annex Table 26 shows that real recurrent provisions per primary
school student declined during 1970-75 by 42% in Uganda, by 41% in Malawi, by
38% in Madagascar and by 37% in Lesotho.
- 28 -
44. We were able to find data on real recurrent budget outlays on
economic services for only four countries, and even this information is
subject to many qualifications (Annex Table 28). In the Sudan, the peak was
reached in 1974; since then recurrent outlays for economic services have been
falling. In 1979 the index of these outlays had declined by 53 points.
Similarly, these outlays in Zambia peaked in 1975 and by 1978 they had
declined by 80 points. Kenyan and Tanzanian data show rising indices, but we
are not able to determine whether or not these increases were adequate. We do
know that Tanzanian agriculture has been deprived adequate recurrent budget
funds, impeding the mobility of research and extension staff and creating
shortages of needed materials and provisions.
Sector-Mix and Sectoral ICORs
45. The economy-wide ICOR is a weighted average of sectoral ICORs.
Typically, agriculture has the lowest ratio and this situation persists until
a rather advanced state of development when agriculture gets increasingly
mechanized (Kuznets, 1960 and 1961). In Eastern Africa, agricultural ICORs
are particularly low, reflecting the very low technology and the general
absence of draft animals and irrigation.
46. The upward shift in ICORs can be attributed to some extent to the
decline in the share of agriculture in investment and output. Available data
are summarized in the table on page 29. They show a substantial contraction
in agriculture's share in total capital formation in Burundi, Tanzania and
Kenya, although many gaps in the statistical series limit their usefulness.
The contribution of agriculture to GNP also fell in these cases as well as in
Malawi, Ethiopia, Somalia and Zimbabwe.
- 29 -
CHANGES IN SHARE OF AGRICULTURE IN OUTPUT AND INVESTMENT
(in percent)
Output Investment1967 1973 1978 1967 1973 1978
Burundi 66 67 62 - 35 20Malawi 54 49 44 - - -Tanzania 44 39 41 11 6 -
Kenya 37 32 32 13 9 9Ethiopia 56 50 48 6 8 -Somalia 90 53 55 23/a 16/b 25
Zimbabwe - 17 14 - 10 11/cZaire - 16 18 - - -
Zambia - 11 12 7 5/d -
a/ 1963-66b/ 1975c*/ 1977d-/ 1971
Source: Data Files: The World Bank
47. Time series data on sectoral investment and output are not available
for most countries. We have, nevertheless, tried in two cases to break down
each sector's contribution to the change in the economy-wide ICOR, using
Martin Wolf's formula (see Annex II). In the Tanzanian case, the
decomposition exercise reveals the impact of countervailing sectoral trends
which more or less offset each other, thereby making for an almost stable
economy-wide ICOR. The agricultural ICOR declined but this was counteracted
by a sharp increase in the industrial ICOR. The role of the services sector
remained unchanged.
- 30 -
48. The second decomposition exercise for Kenya was based on data which
is not consistent with that used in this paper. We cite the results,
nevertheless, simply to illustrate the nature of the calculations.
Accordingly, ICORs rose in all sectors; the services sector was responsible
for 64% of the rise in the overall ratio; industry contributed 33% and
agriculture only 3%.
Absorptive Capacity
49. We have mentioned, earlier (para. 28) that rapid expansion in the
volume of investment during the late 1960s and 1970s created a number of
bottlenecks, particularly in the public sector. The supply of skills for
example, did not keep pace with the growing number of projects started.
Although a concerted attempt was made to expand enrollment and train available
personnel, the demand for project staff could not be satisfied in a timely
fashion. The period witnessed an outflow of colonial officers as part of the
indigenization drive and after 1973, there was another migration of Somalis
and Sudanese (including professionals) to the Gulf countries in search of
attractive salaries. The local supply of middle- and high-level skills was
supplemented to some extent by expatriates financed by technical assistance or
on direct hire. Nevertheless, vacancies persisted and available staff was
moved from post to post in a desperate attempt to fill gaps. All this was
well understood among development practitioners familiar with Eastern Africa,
even though we have not found systematic evidence to buttress these
impressions.
50. In this context it is instructive to examine the experience of the
World Bank in project implementation during the 1970s. Our focus is on 32
agricultural projects. In one-fifth of these cases, actual costs were higher
- 31 -
than estimated costs. In no less than half the sample, actual unit costs were
higher than estimated. In one-third of the sample, the planned project size
had to be reduced. The reasons for this varied, but stringency of budget
funds, inability on the part of the governments to set up implementation units
in time as well as the failure to mobilize project beneficiaries figured
prominently. In about one-third of the projects, the actual completion time
substantially exceeded the estimated time. Furthermore, in almost all these
cases problems relating to administration and staff were partly responsible
for delays. There were relatively few instances where purely technical or
natural factors were responsible for the delay in project completion.
Impact of Government Policy
51. It can be argued that a number of structural factors in Eastern and
Southern Africa countries tend to raise capital costs, compared to say those
prevailing in the Indian sub-continent. Many Eastern and Southern African
countries are landlocked and this makes for higher transportation costs.
Also, they are of small economic size and thereby unable to exploit economies
of scale and agglomeration. They face a large element of uncertainty, making
it necessary to hold substantial inventories. Labor, including unskilled
labor, is relatively more expensive (Gulhati and Sekhar, 1981). And the acute
scarcity of skills and experience tends to reduce productivity all around. To
these structural factors should be added the impact of government policy on
the efficiency of investment. This impact is visible at macro, sectoral and
project levels, particularly during the latter 1970s, when these economies had
to confront a substantial deterioration in the international economic climate.
- 32 -
52. The sharp fall in capacity utilization related to the import squeeze
in many Eastern and Southern African countries was the result not only of
declining terms of trade but also of the policy-induced bias against exports
reflected in the price and exchange rate regimes. In the event, the volume of
exports declined during 1970-79 in Tanzania, Kenya and Sudan (Group I) as well
as in Ethiopia, Zaire, Zambia, Madagascar and Uganda (Group II) (see World
Bank, 1981). Their marketing was frequently the sole responsibility of
parastatals which tended to absorb a growing part of the border price, thereby
undermining farm incentives. Furthermore, many of these governments opted to
deal with the pressure on the balance of payments by import restrictions
rather than by pursuing an active exchange rate policy (Gulhati and
Autokorala, forthcoming). The scarcity value of foreign exchange was not
reflected in the payment made to exporters. Those who earned foreign exchange
by exportation were not rewarded suitably, leading in time to the accentuation'
of the import constraint, fall in the utilization of capacity and the
corresponding rise in ICORs.
53. The decline in the share of agriculture in investment and output and
the parallel emphasis on industrialization and urban infrastructure were also
policy induced to a large extent. While farm prices were regulated at low
levels, manufactured goods' production was stimulated by raising their prices
to levels far above those prevailing internationally. For some time this
strategy produced rapid growth of the manufacturing sector, but this advance
could not be sustained (Gulhati and Sekhar, 1981). The incentive system was
tilted in favor of both import and capital-intensive industrialization
oriented mainly to the home market. The new manufacturers became the victim
of the economy-wide foreign exchange constraint. Their high costs prevented
them from selling abroad in order to finance their import needs.
- 33 -
54. Investment activity in the public sector rose at a faster rate than
in the private sector in many Eastern and Southern African countries (Annex
Table 27). This was true not only of Ethiopia and Zambia, i.e. socialist
economies, but also of Burundi and Malawi who remain capitalistic in their
ideology. At the end of the 1970s, there was scarcely any country in our
sample in which the share of public investment fell short of 40% of total
investment in the formal or monetized sector and in several this share was
much higher. In principle, this public investment was subject to scrutiny via
the planning, project appraisal and budgeting processes. Since a substantial
part of public investment was financed with ODA, many of the bigger projects
were scrutinized by technical and economic staffs of aid agencies. The
deterioration in the productivity of investment took place despite all these
ex-ante analyses and supervision missions during the course of project
implementation.
55. An examination of 21 agricultural projects in Eastern and Southern
Africa, financed partly by the World Bank Group, is instructive in this
context. The weighted average economic rate of return ex-ante was nearly 20%:
a re-evaluation of these same projects (after construction was completed and
the flow of benefits had started) resulted in a weighted rate of return
ex-post of only 12%. Of course, even the latter was an estimate since an
actual rate of return could be calculated only at the end of the project's
life. The substantial deterioration in capital productivity captured by these
ex-ante and ex-post estimates was the result of some combination of
cost overruns, time delays and scaling down of project benefits.
- 34 -
V. Conclusion
56. Now we will try to answer some of the questions listed in the
introduction:
- the relative roles of the investment rate and investment
productivity in bringing about a retardation in GDP growth;
- factors responsible for the declining productivity of investment.
57. Nine out of 16 countries in our sample experienced a retardation in
the growth of GDP. The extent of the setback was relatively minor in Rwanda
but very large in Botswana, Zimbabwe, Zaire and Zambia (see table on page
35). In Swaziland and Rwanda the setback in GDP growth took place despite a
large rise in the investment rate: it was entirely due to a decline in the
return to capital. In Zimbabwe, the investment rate remained more or less
unchanged and the slowing down in the expansion of GDP was attributable to a
fall in capital productivity. The last column shows that GDP growth would
have increased very slightly, if the ICOR had remained constant during the
1970s. Deterioration in capital productivity was also the dominant factor in
Zambia, Zaire, Botswana and Uganda. Zambia's GDP growth rate declined by
seven percentage points, despite a substantial rise in the investment rate.
In Zaire, Botswana and Uganda the setback was the combined result of falling
investment and deteriorating capital productivity, but the latter clearly
played the dominant role. For example, in Zaire, GDP expansion was reduced by
8.6 percentage points; of this less than one percentage point could be
explained by the fall in the investment rate (see last column), and the rest
was attributable to a deterioration in capital productivity. In contrast, the
decline in the investment rate was exclusively responsible for the setback in
GDP in Madagascar (which experienced an improvement in capital productivity),
and it was the major culprit in Ethiopia.
- 35 -
Analysis of Setback in Growth Rate of GDP1967-73 Compared to 1973-78
(percentage points)
Change inthe Rate of Change in GDP
Extent of Investment Growth RateSetback in GDP & Savings* Assuming(percent p.a.) I S Change in ICOR Constant ICOR
Swaziland - 4.9 14.2 23.4 197 +0.9Rwanda - 0.8 13.8 9.5 174 +1.6Zimbabwe - 9.1 - 0.5 1.5 x +0.6Zambia - 7.0 4.0 -12.2 247 -0.6Zaire - 8.6 - 1.3 -18.8 x -0.7Botswana -13.1 - 1.8 21.7 73 -3.2Uganda - 4.5 -11.8 - 9.9 x -1.7Madagascar - 1.4 - 3.4 0.0 - 17 -0.9Ethiopia - 2.9 - 3.4 - 5.1 112 -1.4
* 1976-78 compared to 1969-71.
x ICOR was negative in latter period implying severe deteriorationin the return to existing capital and new investment.
Source: Annex Tables 2, 5, 8 and 10.
58. We cannot assess quantitatively the role of various factors
contributing to a decline in the productivity of investment. The attempt by
many countries to raise rapidly the level of overall investment, to
industrialize and modernize their economies at the expense of agriculture and
to expand the public sector at a rate which far exceeded the availability of
relevant professional skills has led to a massive deterioration in the quality
of projects and the effectiveness of their implementation. Superimposed on
these factors was the deterioration in the international economic climate
- 36 -
which made it even more difficult to manage the public finances and the
foreign exchange budgets, thereby compounding the problems of project
execution and causing capacity utilization to decline drastically.
59. The analysis in this paper is based on data up to 1979. Systematic
information is not available for the subsequent period but it is clear that
economic difficulties facing these countries have multiplied. The retardation
in GDP growth became even more pronounced in 1980 and 1981. The constraint on
foreign exchange for the import of intermediate goods remained acute.
Budgetary pressures made it very difficult to fund recurrent economic needs
adequately, and so on.
60. Economic recovery will necessitate a reconsideration of major
elements of the economic and institutional policy frame. First, the emphasis
will have to be on consolidation and rehabilitation rather than on starting
many new projects. The aim of obtaining a reasonable pay off from already
completed investments must take precedence over starting new schemes. The
efficiency of the existing capital stock must be increased before launching
the next round of capital accumulation. Secondly, the emphasis will have to
be on reviving traditional agriculture (food plus cash crops), thereby
securing some relaxation of the constraint on foreign exchange through volume
increases of exports and reduction of the need for food imports. Once this
phase is over, attention can be given to the promotion of new crops and
technological changes to raise yields. A prosperous and dynamic agriculture
is a good foundation for industrialization, since it provides many inputs for
manufacturing and since it is also a major consumer of industrial goods. The
plea to revive and strengthen agriculture should not be viewed as a step
- 37 -
detrimental to the industrialization drive of African countries. Finally, the
recovery program requires institutional adjustments aimed at improving the
efficiency of the public sector and at expanding its capacity to manage the
economy.
ANNEX I
Statistical Tables
- 38 -ANNEX
Table 1: THE GROWTH OF GDP IN CONSTANT PRICES,EASTERN AFRICA AND COMPARATOR COUNTRIES,
1960-70 AND 1970-79
Average annual growth rate1960-70 1970-79
Group I12.Burundi 4.4 3.02. Malawi 4.9 6.33. Rwanda 2.7 4.14. Tanzania 6.0 4.95. Lesotho 4.6 7.06. Sudan 1.3 4.3
-7. Kenya 6.0 6.58. Swaziland 8.6 4.69. Botswana 5.7 13.5
Median 4.9 7.0
Group II1UT Ethiopia 4.4 1.911. Somalia 1.0 3.112. Zaire 3.6 -0.713. Madagascar 2.7 0.314. Uganda 5.9 -0.415. Zimbabwe 4.3 1.616. Zambia 5.0 1.5
Median 4.3 1.5
Eastern Africa median 4.5 3.6
Comparator countriesMedian /a 3.5 4.2
/a Consists of nine low income Asian countriesand Haiti.
Source: 1. Accelerated Development in Sub-SaharanAfrica: An Agenda for Action, WorldBank, 1981.
2. World Development Report, 1981, WorldBank.
- 39 -
ANNEX
Table 2: THE GROWTH OF GDP IN CONSTANT PRICES,1967-78 AND SUB-PERIODS 1967-73 AND 1973-78
Average annual growth rate /a1967-78 1967-73 1973-78
Group I1. Burundi 4.1 4.1 4.12. Malawi * 5.7 5.4 6.03. Rwanda 5.2 5.6 4.84. Tanzania 4.7 4.4 5.15. Lesotho 5.2 3.7 6.96. Sudan * 4.3 4.3 4.37. Kenya 6.3 6.7 5.88. Swaziland 5.8 7.8 2.99. Botswana * 13.8 22.0 8.9
Median 5.2 5.4 5.1
Group II10. Ethiopia 2.7 4.0 1.111. Somalia * 3.4 1.8 5.312. Zaire 3.1 7.1 -1.513. Madagascar 1.1 1.7 0.314. Uganda * 1.2 3.3 -1.215. Zimbabwe 3.9 8.2 -1.116. Zambia 2.4 5.8 -1.4
Median 2.7 4.0 -1.1
Eastern Africa median 4.2 4.9 4.2
/a Compound rate of growth of GDP at factor costbased on three year end point averages.
* = For countries marked with an asterisk, GDP atmarket prices was used for lack of data.
Source: Data Files, World Bank.
- 40 -
ANNEX
Table 3: THE GROWTH OF GROSS DOMESTIC INVESTMENT IN CONSTANT PRICES,EASTERN AFRICA AND COMPARATOR COUNTRIES, 1960-70 AND 1970-79 /a
Average annual growth rate /a1960-70 1970-79
Group I1. Burundi 4.3 16.52. Malawi 15.4 2.33. Rwanda 3.5 18.94. Tanzania 9.8 3.05. Lesotho 18.5 24.46. Sudan -1.3 8.07. Kenya 7.0 1.28. Swaziland 10.6 13.39. Botswana 25.3 5.6
Median 9.8 8.0
Group II
10. Ethiopia 5.7 - 1.811. Somalia 4.3 8.512. Zaire 9.6 - 5.013. Madagascar 5.4 - 1.814. Uganda 9.8 -13.115. Zimbabwe -- - 2.116. Zambia 10.6 - 5.6
Median 7.7 - 2.1
Eastern Africa median 9.6 2.7
Comparator countries median 5.5 6.7
-- = Not available.
/a Least squares growth rates.
Source: Accelerated Development in Sub-Saharan Africa: An Agenda forAction, World Bank, 1981.
- 41 -
ANNEX
Table 4: THE GROWTH OF GROSS DOMESTIC INVESTMENT IN CONSTANT PRICES,1967-78 AND SUB-PERIODS 1967-73 AND 1973-78 /a
Average annual growth rate /a1967-78 1967-73 1973-78
Group I1. Burundi 8.9 -1.0 22.02. Malawi 9.3 13.9 4.13. Rwanda 15.2 9.4 23.04. Tanzania 6.0 7.3 4.55. Lesotho 17.3 11.5 25.06. Sudan 3.5 -2.2 10.67. Kenya 4.9 6.9 2.58. Swaziland 9.1 7.4 9.39. Botswana 18.1 36.0 - 4.3
Median 9.1 7.3 4.5
Group II10. Ethiopia -1.8 0.2 - 4.011. Somalia 6.2 5.5 7.212. Zaire 2.9 13.0 0.413. Madagascar 0.4 1.9 - 1.314. Uganda -8.0 -4.4 -12.415. Zimbabwe 0.4 9.1 - 9.116. Zambia -2.4 5.8 -11.4
Median 0.4 5.5 - 4.0
Eastern Africa median 6.0 6.4 2.4
/a Compound rates of growth based on three-yearaverages.
Source: Data Files, Warld Bank.
- 42 -
ANNEX
Table 5: THE INCREMENTAL CAPITAL OUTPUT RATIOIN THE PERIODS 1961-68, 1967-73 AND 1973-79 /a
ICOR1961-68 1967-73 1973-79
Group IIIi-Ftundi 1.8 1.9 2.82. Malawi 2.8 4.3 3.83. Rwanda 4.5 1.9 5.24. Tanzania 2.7 5.3 4.65. Lesotho 2.0 2.7 5.26. Sudan 16.5 5.7 3.67. Kenya 4.1 4.2 4.58. Swaziland 3.9 3.6 10.79. Botswana 3.3 2.6 4.5
Median 3.3 3.6 4.5
Group II10. Ethiopia 3.6 4.2 8.911. Somalia 6.0 8.0 4.212. Zaire 6.2 4.5 neg.13. Madagascar 8.6 17.5 14.514. Uganda 2.5 5.7 neg.15. Zimbabwe 6.8 3.2 neg.16. Zambia 9.2 7.0 24.3
Median 6.2 5.7 24.3
Eastern Africa median 4.0 4.3 5.2
neg. = Negative.
/a The years 1961-68 were chosen rather than 1960-67because of data constraints. The method used forcomputing ICORs is described in Annex 2.
Source: Data Files, World Bank.
- 43 -
ANNEX
Table 6: INCREMENTAL GROSS CAPITAL OUTPUT RATIOSIN FIVE DEVELOPED COUNTRIES, 1967 TO 1974
1967 1968 1969 1970 1971 1972 1973 1974
1. France 6.5 5.1 3.4 3.5 4.7 4.4 4.8 8.62. Japan 2.6 2.7 3.5 - 3.6 5.2 4.4 4.2 --3. West Germany 7.3 -- 3.3 4.7 9.5 8.2 5.3 --
4. UK 7.2 5.6 14.0 8.2 7.6 7.4 3.3 --
5. USA 6.9 4.3 7.2 6.3 -- 4.3 3.6 --
-- = Not available.
Source: John C. Carrington and George T. Edwards Financing IndustrialInvestment, The Macmillan Press, 1979.
- 44 -ANNEX
Table 7: HISTORICAL INCREMENTAL CAPITAL OUTPUT RATIOSIN DEVELOPED COUNTRIES /a
ICOR
1. UK 6.32. Germany 6.13. Italy 5.7
4. Denmark 4.45. Norway 7.36. Sweden 5.5
7. USA 6.58. Canada 5.69. Australia 6.9
10. Japan 4.311. Argentina 7.612. Union of South Africa 4.9
/a Based on a varying number of years from the late19th to the mid 20th century.
Source: Simon Kuznets "Quantitative Aspects of theEconomic Growth of Nations" in Economic Devel-opment and Cultural Change, Vol. IX, No. 4,Part II, July 1961.
Table 8: THE RATIO OF GROSS DOMESTIC INVESTMENT TO GDP, 1967-78
Three-Year Moving Averages /a
(Percentages)
1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978
Group I1. Burundi 7.8 8.3 7.5 7.3 5.5 5.8 6.2 7.8 9.1 10.2 12.7 14.0
2. Malawi 16.7 17.1 21.6 22.8 25.1 23.8 25.4 26.7 24.3 23.6 26.2 31.5
3. Rwanda 8.8 7.7 7.7 8.1 9.3 10.5 11.2 12.8 13.7 15.9 21.9 24.0
4. Tanzania 18.6 18.7 20.6 23.9 26.3 25.9 24.5 24.2 23.9 22.8 22.2 22.3
5. Lesotho 11.2 11.4 11.5 12.2 12.9 15.9 17.0 24.0 30.8 37.5 40.2 39.0
6. Sudan 10.8 10.3 10.5 10.1 9.1 8.6 11.9 15.7 18.9 17.9 17.3 16.5
7. Kenya 21.4 21.7 23.3 24.9 25.9 24.5 26.4 25.1 25.3 23.5 28.0 28.9
8. Swaziland 25.2 22.7 20.3 19.8 20.7 22.8 24.6 27.7 31.2 33.3 34.0 --
9. Botswana 23.0 28.1 34.4 41.2 47.5 50.0 52.3 51.2 49.0 41.8 39.4 --UL
Median 16.7 17.1 20.3 19.8 20.7 22.8 24.5 24.2 24.3 23.5 26.2 24.0
Group II10. Ethiopia 15.1 14.8 13.8 13.0 12.9 12.9 12.2 11.5 10.9 10.6 9.6 9.4
11. Somalia 13.3 13.7 13.6 13.6 14.0 15.1 21.2 23.0 24.5 22.1 21.4 20.8
12. Zaire 17.7 20.8 22.9 27.3 30.8 32.1 31.2 30.3 28.8 30.8 26.0 21.0
13. Madagascar 14.7 15.9 16.3 16.7 15.7 15.3 14.2 13.8 13.3 12.9 13.3 16.4
14. Uganda 16.2 17.6 16.9 17.1 14.8 12.9 11.1 9.8 8.9 6.6 5.3 4.7
15. Zimbabwe 22.6 23.4 22.7 22.0 22.7 24.1 26.4 29.2 28.1 25.6 21.5 20.0
16. Zambia 32.7 28.9 27.4 28.3 - 33.6 33.9 33.7 35.4 36.5 35.8 32.3 26.5
Median 16.2 17.6 16.9 17.1 15.7 15.3 21.2 23.0 24.5 22.1 21.4 16.4
Eastern Africa median 16.5 17.9 18.6 18.5 18.2 19.4 22.9 24.1 24.4 23.2 22.1 20.9
-- = Not available.
/a Average of share of investment in current prices. For Ethiopia from 1971 onwards and for Burundi
from 1977, only fixed investment data are available.
Source: Data Files,World Bank.
Table 9: INDEX OF REAL GROSS FIXED CAPITAL FORMATION BY THE CENTRAL GOVERNMENT /a
(1972 = 100)
1972 1973 1974 1975 1976 1977 1978 1979
Group II. Burundi -- -- -- -- -- -- -- --2. Malawi 100.0 128.7 183.6 264.8 186.7 242.4 253.6 341.2
3. Rwanda /b -- 100.0 133.0 279.9 571.1 571.9 154.5 --4. Tanzania 100.0 85.6 120.2 136.7 150.2 162.2 175.9 --
5. Lesotho 100.0 86.5 169.9 -- -- -- -- --
6. Sudan 100.0 78.4 111.3 215.1 236.1 411.4 300.3 --7. Kenya 100.0 96.0 81.3 82.0 91.4 108.3 119.7 126.28. Swaziland 100.0 243.0 171.9 185.1 185.1 261.1 -- --9. Botswana 100.0 140.8 164.2 155.7 190.5 239.8 308.0 315.2
Group II
10. Ethiopia 100.0 82.6 59.7 71.4 102.1 127.9 -- --
11. Somalia -- -- -- -- -- -- -- --
12. Zaire 100.0 203.8 273.1 113.0 233.4 217.8 194.1 --
13. Madagascar 100.0 69.3 -- -- -- -- -- --
14. Uganda -- -- -- -- -- -- -- --
15. Zimbabwe -- __ __-- -- -- -- _ 16. Zambia 100.0 - 34.1 63.1 -- -- 60.3 48.2 --
-- = Not available.
/a Gross fixed capital formation deflated by the unit value index of manufacturedexports of developed countries (MUV Index) from U.N. Monthly Bulletin ofStatistics.
/b 1973 = 100 instead of 1972.
Source: 1. IMF (1981) Government Finance Statistics Yearbook.2. U.N. Monthly Bulletin of Statistics.
Table 10: THE RATIO OF GROSS NATIONAL SAVINGS TO GDP
Three-Year Moving Averages, 1967-78
(Percentages)
1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978
Group I1. Burundi - 1.4 - 1.2 -0.8 -0.6 - 2.1 - 2.2 - 1.4 2.2 3.4 6.6 5.9 5.32. Malawi 0.6 1.3 4.9 8.0 10.9 11.9 14.7 14.8 12.6 12.0 14.9 16.43. Rwanda 2.6 2.1 1.9 1.4 0.9 1.4 2.2 3.3 4.6 7.7 10.9 12.34. Tanzania 17.0 17.2 17.7 18.6 19.0 17.6 14.4 11.4 12.7 14.2 14.2 10.55. Lesotho -10.3 - 8.7 -6.4 -6.9 -13.1 -10.2 -12.4 -6.9 -14.6 -14.1 -9.4 -2.96. Sudan 7.8 7.9 9.1 9.2 8.2 6.6 6.1 4.3 3.5 2.1 2.2 1.57. Kenya 17.7 17.8 19.3 19.0 18.8 16.5 17.5 15.0 16.2 18.4 20.7 19.48. Swaziland 12.0 5.7 3.5 8.9 15.5 21.1 25.5 33.4 42.8 44.9 32.3 --
9. Botswana -11.5 -12.1 -8.4 -0.7 6.4 11.2 20.3 25.9 30.6 25.1 21.0 --
Median 2.6 2.1 3.5 8.0 8.2 11.2 14.4 11.4 12.6 12.0 14.2 10.5
Group II10. Ethiopia 11.9 12.0 11.7 11.0 10.8 11.4 12.6 11.2 9.8 7.4 5.9 4.011. Somalia 4.5 4.8 6.1 6.1 7.8. 9.0 8.9 7.1 6.8 9.1 8.1 6.412. Zaire 16.2 20.7 21.8 21.1 18.8 18.0 17.7 15.2 8.5 2.7 2.3 4.913. Madagascar 6.9 8.9 9.8 9.6 8.8 8.1 8.0 7.8 8.4 8.9 9.6 9.014. Uganda 15.1 17.0 17.4 15.6 13.9 12.2 12.1 9.4 8.2 6.8 5.7 4.615. Zimbabwe 19.7 20.9 20.7 20.6 21.0 22.6 25.2 26.2 25.7 24.2 22.1 19.316. Zambia 36.0 38.9 41.0 38.1 31.8 30.6 34.3 29.5 27.1 23.2 25.9 22.8
Median 15.1 17.0 17.4 15.6 13.9 12.2 12.6 11.2 8.5 8.9 8.1 6.4
Eastern Africa median 9.9 8.4 9.5 9.4 10.9 11.7 11.7 11.3 9.2 9.0 10.3 7.7 x
-- = Not available.
Source: Data Files, World Bank.
Table 11: TERMS OF TRADE ESTIMATES, 1967 TO 1978
Three-Year Moving Averages
1975 = 100 /a
1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978
Group Ii. Burundi -- -- -- -- -- -- -- -- -- -- -- --
2. Malawi 87 83 89 98 106 106 101 98 97 101 102 993. Rwanda 114 108 113 116 118 115 115 110 120 156 182 1824. Tanzania 98 96 99 99 100 101 106 107 111 120 127 122
5. Lesotho -- -- -- -- -- -- -- -- -- -- -- --
6. Sudan 77 76 79 82 83 94 94 99 101 100 95 907. Kenya 115 108 112 113 119 119 115 109 109 130 146 1438. Swaziland -- __ __ __ __ __ __ __ __ __ __ __
9. Botswana -- -- -- -- -- -- -- -- 4- -- -- --
Median 98 96 99 99 106 106 106 107 109 120 127 122
Group II
10. Ethiopia 131 128 136 136 138 133 128 116 122 155 175 171
11. Somalia 138 134 133 135 136 132 123 110 102 102 105 104
12. Zaire 164 175 190 183 160 149 151 140 121 107 103 97
13. Madagascar 112 111 113 117 121 123 118 110 106 119 124 122
14. Uganda 117 117 122 125 126 121 112 106 112 152 168 168
15. Zimbabwe -- -- -- -- -- -- -- -- -- -- -- --
16. Zambia 183 197 217 204 172 160 169 157 130 102 96 93
Median 135 131 135 136 137 133 126 113 117 113 115 113
Eastern Africa median 115 111 113 117 121 121 115 110 111 119 124 122 x
-- = Not available.
/a The index for the year 1975 rather than the three-year moving average for that year was equal to 100.
Source: UN (1980) UNCTAD Handbook of International Trade and Development Statistics.
Table 12: GROSS NATIONAL SAVINGS AS A PERCENTAGE OF GROSS NATIONAL INVESTMENT
Three-Year Moving Averages, 1967-78
1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978
Group I1. Burundi -17.9 -14.5 -10.7 - 8.2 - 38.2 -37.9 -22.6 28.2 37.4 64.7 46.5 37.92. Malawi 3.6 7.6 22.7 35.1 43.4 50.0 57.9 55.4 51.9 50.8 56.9 52.13. Rwanda 29.5 27.3 24.7 17.3 9.7 13.3 19.6 25.8 33.6 48.4 49.8 51.34. Tanzania 91.4 92.0 85.9 77.8 72.2 68.0 58.8 47.1 53.1 62.3 64.0 47.15. Lesotho -92.0 -76.3 -55.7 -56.6 -101.6 -64.2 -72.9 -28.8 -47.4 -37.6 -23.4 -7.46. Sudan 72.2 76.7 86.7 91.1 90.1 76.7 51.3 27.4 18.5 11.7 12.7 9.17. Kenya 82.7 82.0 82.8 76.3 72.6 67.3 66.3 59.8 64.0 78.3 73.9 67.18. Swaziland 47.6 25.1 17.2 44.9 74.9 92.5 104.9 120.6 137.2 134.8 95.0 --9. Botswana -50.0 -43.1 -24.4 - 1.7 13.5 22.4 38.8 50.6 62.4 60.0 53.3 --
Median 29.5 25.1 22.7 35.1 43.4 50.0 51.3 47.1 51.9 60.0 53.3 47.1Group II10. Ethiopia 78.8 81.1 84.8 84.6 83.7 88.4 103.3 97.4 89.9 69.8 61.5 42.611. Somalia 33.8 35.0 44.9 44.9 55.7 59.6 42.0 30.9 27.8 41.2 37.9 30.812. Zaire 91.5 99.5 95.2 77.3 61.0 56.1 56.7 50.2 29.5 8.8 8.8 23.313. Madagascar 46.9 56.0 60.1 57.5 56.1 52.9 56.3 56.5 63.2 69.0 72.2 54.914. Uganda 93.2 96.6 103.0 91.2 93.9 94.6 109.0 95.9 92.1 103.0 107.5 97.915. Zimbabwe 87.2 89.3 91.2 93.6 92.5 93.8 95.5 89.7 91.5 94.5 102.8 96.516. Zambia 110.1 134.6 149.6 134.6 94.6 90.3 101.8 83.3 74.2 64.8 80.2 86.0
Median 87.2 89.3 91.2 84.6 83.7 88.4 95.5 83.3 74.2 69.0 72.2 54.9Eastern Africa median 59.9 66.4 71.5 66.9 66.6 63.5 57.3 53.0 57.8 63.5 59.2 49.2
-- = Not available.
3ource: Data Files, World Bank.
- 50 -ANNEX
Table 13: NET OFFICIAL DEVELOPMENT ASSISTANCEAS A PERCENTAGE OF EXTERNAL RESOURCES INFLOW /a
Average1976 1977 1978 1979 1977-79
Group I
1. Burundi 100.0 89.4 99.1 100.7 96.42. Malawi 78.7 83.0 80.8 76.3 80.03. Rwanda 98.4 100.4 101.2 99.7 100.44. Tanzania 79.3 80.9 82.1 79.9 81.95. Lesotho 100.0 99.2 96.5 102.4 99.46. Sudan 57.9 54.6 63.5 87.2 68.47. Kenya 39.8 32.1 60.6 77.2 56.68. Swaziland 74.4 77.4 88.6 66.7 77.69. Botswana 83.4 112.9 392.0 70.4 191.8
Median 79.3 83.0 88.6 79.9 81.9
Group II
10. Ethiopia 102.6 108.0 106.8 78.9 97.911. Somalia 88.9 71.1 91.8 70.3 77.712. Zaire 39.6 51.0 45.1 55.5 50.513. Madagascar 102.4 113.1 76.7 57.0 82.314. Uganda 50.1 73.3 -- 104.3 88.815. Zimbabwe 21.4 446.7 161.4 145.3 251.116. Zambia 46.9 64.5 58.5 84.1 69.0
Median 50.1 73.3 84.3 78.9 82.3
Eastern Africa median 79.0 82.0 88.6 79.4 82.1
-- = Not available.
/a Net Official Development Assistance refers to disbursements ofconcessional loans or grants. External Resource Flows include,in addition, private grants, transactions on commercialterms, direct investment and purchases of securities of inter-national development organizations. All defense related trans-actions are excluded.
Source: OECD (1980) Development Co-operation, 1980 Review.
- 51 -
ANNEX
Table 14: DIRECT INVESTMENT AS A PROPORTION OF LONG-TERM CAPITAL INFLOWS /a
(Percentages)
Average1974 1975 1976 1977 1978 1979 1977-79
Group I1. Burundi -- -- -- -- -- -- --2. Malawi 32.6 15.1 20.7 7.4 10.9 11.2 9.83. Rwanda 23.4 17.5 25.2 16.0 18.5 55.4 30.04. Tanzania 0.0 0.0 0.0 0.0 0.0 0.0 0.05. Lesotho - -- -- -- -- --
6. Sudan 0.0 0.0 0.0 0.0 0.0 0.0 0.07. Kenya -- 10.1 19.4 26.3 13.9 14.0 18.18. Swaziland -60.0 6.3 36.7 59.8 44.4 74.7 59.69. Botswana /b -- -54.3 236.6 -54.8 78.1 122.3 48.5
Group II10. Ethiopia 56.7 27.7 6.5 16.0 0.0 0.0 5.311. Somalia 1.2 12.9 3.2 12.1 0.3 -- 6.212. Zaire -- -- -- -- -- -- --13. Madagascar 57.1 13.6 15.4 -16.7 -25.0 -2.9 -14.914. Uganda 12.2 35.4 -7.2 - 6.9 - 2.5 -4.8 - 4.715. Zimbabwe -- -- -- -- -- --
.16. Zambia 50.8 10.2 25.0 88.2 -- -- --
__ e Not available.
/a Both direct investment and long-term capital inflow are from the IMFsource listed below. OECD estimates of direct investment are differ-ent.
/b The entries for Botswana, Lesotho and Swaziland cover imputed pay-ments to South Africa under the Customs Union Agreement. In someyears Botswana is a net creditor.
Source: Balance of Payments Yearbook, Vol 31, December 1980, IMF.
- 52 -
ANNEX
Table 15: NET PRIVATE DIRECT INVESTMENT FROM DAC SOURCES /a
(In US$ millions) /b
1976 1977 1978 1979
Group I1. Burundi -0.6 ( --) -0.3 ( --) 0.9 ( --) -0.3 ( --)2. Malawi 5.3 ( 9.7) 0.2 ( 5.7) -7.9 (10.1) -- ( 13.7)3. Rwanda 0.1 ( 5.9) 0.1 ( 5.2) -0.7 ( 4.9) 0.4 ( 12.9)4. Tanzania 6.5 ( 0.0) 2.9 ( 0.0) 6.2 ( 0.0) 2.0 ( 0.0)5. Lesotho -- ( --) 0.4 ( --) -- ( --) -- ( --)6. Sudan 5.9 ( 0.0) 4.8 ( 0.0) 4.1 ( 0.0) -4.7 ( 0.0)7. Kenya 20.5 (75.4) 6.1 (75.0) -0.6 (63.7) 1.4 ( 17.2)8. Swaziland 2.0 ( 4.6) 1.7 (12.2) 0.3 (16.1) 1.3 ( 62.3)9. Botswana 3.2 (11.3) 0.3 (12.5) -0.3 (42.1) -- (154.2)
Group II10. Ethiopia 0.2 ( 4.3) -1.2 ( 5.9) -- ( 0.0) -- ( 0.0)11. Somalia 1.3 ( 2.2) 56.6 ( 8.1) -0.1 ( 0.3) -- ( --)12. Zaire 245.2 ( --) 16.4 ( --) 93.8 ( --) 143.9 ( --)13. Madagascar -0.4 ( 2.3) -5.5 (-3.5) 0.6 (-3.8) -0.6 ( -6.5)14. Uganda 2.2 ( 1.2) -- ( 0.8) 0.1 ( 1.0) -- ( 1.5)15. Zimbabwe 27.5 ( --) -1.7 t --) -0.6 ( --) -0.9 ( --)16. Zambia 26.7 (31.1) 2.8 (17.7) 25.9 ( --) 0.8 ( --)
-- = Not available.
/a The figures in parentheses are from the IMF. They also refer to all direct in-vestment. Both sets of data include reinvestments by non-resident entities.Portfolio investment and export credits are excluded. The Development AssistanceCommittee (DAC) forms part of the Organization for Economic Co-operation andDevelopment (OECD).
lb The IMF figures are in SDRs in the source publication. They have been con-verted to dollars at the period average exchange rates.
Source: 1. OECD (1981) Geographical Distribution of Financial Flows to Develop-ing Countries.
2. IMF (1980) Balance of Payments Yearbook.
- 53 -ANNEX
Table 16: THE STOCK OF FOREIGN DIRECT INVESTMENTIN EASTERN AFRICA, END 1978 /a
(In US$ million)
Stock
Group I1. Burundi 262. Malawi 1003. Rwanda 254. Tanzania 1705. Lesotho 46. Sudan 607. Kenya 5208. Swaziland 509. Botswana 57
Group II10. Ethiopia 10011. Somalia 10012. Zaire 1,25013. Madagascar 19014. Uganda 1015. Zimbabwe 40016. Zambia 330
/a Stock figures represent estimated bookvalues. The data refer only to DAC countries'investments in Eastern Africa, and excludeSouth African investments.
Source: OECD (1980) Development Co-operation1980 Review.
- 54 -
ANNEX
Table 17: GROSS EUROCURRENCY CREDITS TO EASTERN AFRICA /a
(US$ million)
1973 1974 1975 1976 1977 1978 1979
Group I1. Burundi -- -- -- -- -- -- --2. Malawi 5.3 - - - 50.0 - 50.03. Rwanda -- -- -- -- -- -- --
4. Tanzania - - - - - 12.05. Lesotho - - - - - - 10.06. Sudan 3.4 220.0 36.8 19.0 - 9.5 -7. Kenya 4.5 - - - - - 212.08. Swaziland - - - - - 28.0 -9. Botswana - - - - - 45.0 -
Group II10. Ethiopia - - - - - - 14.011. Somalia -- -- -- -- -- -- --12. Zaire 223.0 71.3 27.0 - - - -13. Madagascar - - - - 3.0 29.6 26.314. Uganda -- -- -- -- -- -- --15. Zimbabwe -- -- -- -- -- -- --
16. Zambia 150.0 - 160.0 - - - 12.8
-- = Not available.
- = Nil or negligible.
/a Eurocurrency credits are credits with a maturity of more than oneyear made by private banks using funds deposited or borrowed bythem in external currencies.
Source: World Bank, Borrowing in International Capital Markets.
- 55 -
ANNEX
Table 18: CAPACITY.UTILIZATION IN SELECTED SECTORS IN TANZANIA, 1978 and 1979
Industry Production as a pe-rcentage of capacity1978 1979
Sugar 39 39Distilled spirits and liquors 102 89Tobacco manufacturing 92 94
Spinning and weaving 64 63Madeup textiles 49 66Footwear 68 56
Fertilizers and pesticides 42 52Plastic 46 24Glass 23 15
Cement, lime, plaster 80 88Iron, steel and metals 55 62Structural metal products 47 47
Fabricated metal products 42 37Electrical machinery 74 66Motor vehicles 42 33Motorcycles and bicycles 30 12
Source: Data Files, The World Bank
- 56 -ANNEX
Table 19: CAPACITY UTILIZATION IN A SAMPLEOF PARASTATAL FIRMS IN TANZANIA, 1979
Productionas a percentage of
Parastatal capacity
1. Tanzania Fertilizer Co. 522. Steel Rolling Mills 623. ALUCO (Aluminum Sheets) 45
4. PIPECO (Pipes) 715. ALAF Steel Cast 546. GALCO (Iron Sheets) 74
7. ALAF Steel Co. 258. National Bicycle Co. 259. Ubungo Farm Implements 67
10. Tanzania Gables 3911. Tanzania Breweries 8912. Tanzania Cigarette Co. 94
13. Tanzania Shoe Co. 5614. Legy Plastics 3415. Metal Box Co. 2716. Friendship Textile Mill 82
Soiurce: nsta wiles, The World Rpnk
- 57 -
ANNEX
Table 20: CAPACITY UTILIZATION IN A SAMPLEOF PUBLIC ENTERPRISES, 1976-78, SOMALIA
Production as a percentage of capacityParastatal 1976 1977 1978
1. ITOP Fruit Cannery 36 29 222. Mogadishu Meat Factory 51 53 463. Kismayo Meat Factory 61 37 --
4. Flour and Pasta Factory 58 64 615. INCAs Box Factory 36 27 256. SOMALTEX -- 65 75
Source: Data Files, The World Bank
- 58 -
ANNEX
Table 21: CAPACITY UTILIZATION IN CERTAIN MANUFACTURINGFIRMS IN SUDAN, 1973
(Percentages)
Percent ofFirm and/or Department Product capacity utilized
1. Sudan Knitwear Knitwear 67
2. Khartoum Tannery Leather(i) Beam House
Cow hides 92Sheep skins 38
(ii) Chrome SectionCow hides 52
(iii) Finish SectionDa side leather 57Vegetable process 100Pickles process 100
3. Sudan Soap Factory Oils & oilproducts 46
4. Blue Nile Plastic Co. Plastics(i) Plastic crates 67
(ii) Polyethelene filters 51(iii) Printing 67
5. Karima Canning Factory Foodcanning 15
6. The Flour Mill Corp. Flour 80
7. Coldair Engineering Co. Electricalappliances
(i) Refrigerators 54(ii) Water coolers 18
(iii) Air conditioners 16(iv) Commercial refrigerators 8(v) Air coolers 20
8. Bata Corp. Shoes 42
9. Blue Nile Brewery Beer 99
10. Guneid Sugar Sugar 70
11. Girba Sugar Sugar 118
Source: Public Corporations in Sudan, 1977, bvernment of Sudan.
- 59 -ANNEX
Table 22: CAPACITY UTILIZATION IN THE PUBLICINDUSTRIAL SECTOR IN SUDAN, 1975/76
Total numberBelow 35% 35 to 65% Above 65% of firms
Food 6 1 2 9
Sugar and beverages 0 1 2 3
Oil mills 1 2 1 4
Leather 1 3 0 4
Mining 1 1 0 2
Building materials 1 2 0 3
Spinning and weaving 0 2 0 2
10 12 5 27
Source: Public Corporations in Sudan, 1977, Qbvernment of Sudan.
- 60 -
ANNEX
Table 23: FREQUENCY DISTRIBUTION OF CAPACITY UTILIZATIONIN PLANTS/PROCESSES OF THE INDECO GROUP, ZAMBIA,
1981-82
Number ofPercent of plants/ Percentage 1/
capacity utilized processes of total Industries-
0 to 10 percent 5 9 Oils and fats, car assembly, batteries,engineering.
10 to 30 percent 12 21 Tires, jute, glass, engineering, batteries,fertilizer, canning, detergents, woodproducts, tiles.
30 to 50 percent 8 14 Milling, glass, cooking oil, coffee, sawmilling.
50 to 70 percent 20 35 Cement, stone, pharmaceuticals, polyprope-lene, explosives, engineering, beer,milling, bakery, sugar, gases, wood.
70 to 90 percent 9 16 Lime, explosives, spinning, milling, bakery,beer, sugar.
Above 90 percent 3 5 Textile weaving, explosives.
Total 57
1/ There may be overlaps because different processes or plants in an industry havedifferent percentages of capacity utilized.
Source: INDECO Group Financial Review, 1981-82, mimeo.
Table 24: QUANTUM INDEX OF IMPORTS, 1967 TO 1978
Three-Year Moving Averages
1975 = 100
1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978
Group I1. Burundi -- 65 70 76 84 86 84 92 100- 113 122 139
2. Malawi 67 64 69 77 87 92 92 98 100 101 105 1513. Rwanda 49 51 57 63 68 62 62 77 100 116 134 1464. Tanzania 75 74 82 92 102 104 105 105 100 94 101 1015. Lesotho /a -- 28 28 29 37 48 64 81 100 114 121 1236. Sudan 54 57 65 69 71 69 72 88 100 108 106 947. Kenya 89 90 98 111 119 120 114 108 100 100 115 1168. Swaziland /a -- 81 86 90 88 87 88 93 100 110 124 --
9. Botswana /a- 36 44 48 55 65 78 87 100 106 116 --
Median -- 64 69 76 84 86 84 92 100 108 116
Group II10. Ethiopia 114 111 117 116 116 111 103 98 100 104 117 119
11. Somalia 60 64 66 70 76 89 95 100 100 112 121 130
12. Zaire 71 78 98 111 125 126 128 112 100 80 64 50
13. Madagascar 113 122 127 133 130 123 107 103 100 101 101 113
14. Uganda 176 176 178 201 188 169 128 113 100 90 98 92
15. Zimbabwe /b -- 82 89 96 105 109 109 109 100 89 75 7516. Zambia 102 109 112 115 119 112 103 103 100 91 73 64
Median 108 109 112 115 119 112 107 103 100 91 98 92
Eastern Africa Median _ 76 84 91 95 98 99 99 100 103 111 -i
/a Data for these countries are from Data Files, EPD.
/b Data for Zimbabwe is derived from IFM (1981) International Financial Statistics Yearbook.
Source: UN (1980) UNCTAD Handbook of International Trade and Development Statistics.
Table 25: PETROLEUM IMPORTS INTO EASTERN AFRICA
(In '000 barrels per day of oil equivalent)
Three-Year Moving Averages
1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977
Group I1. Burundi 0.57 0.6 0.6 0.5 0.4 0.4 0.47 0.47 0.5 0.47 0.52. Malawi 1.7 1.8 2.0 2.2 2.4 2.6 2.6 2.7 2.8 2.8 2.83. Rwanda 0.3 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.6 0.7 0.84. Tanzania 18.1 21.2 22.7 25.1 27.6 32.6 34.8 31.2 26.0 20.2 20.25. Lesotho -- -- -- -- -- -- -- -- -- -- --6. Sudan -- -- -- -- -- -- -- -- -- -- --7. Kenya 41.6 43.4 45.5 48.9 51.9 54.9 57.3 58.4 56.7 53.9 52.7 c8. Swaziland -- -- -- -- -- -- -- -- -- -- --9. Botswana -- -- -- -- -- -- -- -- -- --
Median 1.7 1.8 2.0 2.2 2.4 2.6 2.6 2.7 2.8 2.8 2.8
Group II10U7EtiTopia 8.8 10.4 12.1 12.4 13.2 13.9 13.8 13.3 12.5 12.0 12.411. Somalia 1.2 1.2 1.2 1.3 1.4 1.4 1.5 2.1 2.7 3.8 4.512. Zaire -- -- -- -- -- -- -- -- -- -- --13. Madagascar 7.2 8.6 10.2 11.2 12.2 12.7 12.9 13.8 13.2 12.9 11.514. Uganda 5.5 6.4 7.7 8.8 9.2 8.9 8.4 8.0 7.7 7.9 7.915. Zimbabwe 8.4 9.4 9.7 10.1 10.5 10.9 11.1 11.1 11.4 11.8 12.316. Zambia 5.9 7.5 8.1 8.7 9.2 12.4 15.0 19.8 20.0 20.5 18.5
Median 6.6 8.1 8.9 9.5 9.9 11.7 12.0 12.2 12.0 11.9 11.9 t
Eastern Africa Median 5.9 7.5 8.1 8.8 9.2 10.9 11.1 11.1 11.4 11.8 11.5
-- = Not available.
Source: Data Files, The World Bank.
- 63 -
ANNEX
Table 26: PUBLIC CURRENT EXPENDITURE PER PUPILIN CONSTANT PRICES AT THE FIRST LEVEL (AGES 7 TO 13) /a
Currencyunit 1970 1975
1. Botswana Pula 28.1 34.72. Ethiopia Birr 42.3 43.63. Kenya Shilling 163.0 216.44. Lesotho Rand 0.73 0.465. Madagascar Franc 9022.0 5613.06. Malawi Kwacha 11.0 6.57. Uganda Shilling 141.3 81.48. Zambia Kwacha 28.2 35.6
/a Both teaching and non-teaching expenditures are in-cluded. The GDP deflator has been used to deflateexpenditures at current prices.
Sources: 1. UNESCO (1980) Statistical Yearbook.
2. Data Files, The World Bank.
Table 27: SHARE OF PUBLIC INVESTMENT (INCLUDING PARASTATAL INVESTMENT) IN TOTAL (THREE-YEAR MOVING AVERAGES)
(Percentages)
Average d/1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1977-79
Group I1. Burundi 64.1 66.0 66.4 64.8 65.3 69.7 75.4 80.1 84.6 87.5 90.4 -- -- 90.42. Malawi 52.1 50.1 54.0 57.3 59.9 58.3 60.3 61.7 61.3 61.4 61.5 62.8 62.3 62.23. Rwanda -- -- 47.8 51.9 54.2 -- -- -- -- -- -- -- -- --4. Tanzania 47.7 51.6 55.5 62.5 69.3 70.7 69.9 66.7 59.9 52.8 46.8 45.8 -- 46.35. Lesotho -- -- -- -- -- -- ---- -- -- -- -- -- --6. Sudan /a -- -- -- 28.2 26.4 28.5 34.2 36.3 42.9 41.6 42.0 -- -- 42.07. Kenya -- -- -- -- -- -- 42.2 -- -- 44.7 44.78. Swaziland -- -- -- -- -- -- -- -- -- -- -- -- -- --9. Botswana /b -- -- -- -- -- -- -- -- -- -- 56.5 58.2 60.7 58.5
Group II10. Ethiopia -- -- -- -- -- -- -- -- -- 47.7 56.7 62.6 68.0 62.411. Somalia -- -- -- -- -- -- -- -- -- -- -- -- --12. Zaire -- -- -- -- -- -- -- -- -- -- -- -- -- __13. Madagascar -- -- -- -- -- 39.6 -- -- -- -- -- -- -- --14. Uganda 18.1 21.5 27.2 34.0 37.5 -- -- -- -- -- -- -- -- --15. Zimbabwe -- -- -- 29.0 -- -- -- 33.0 -- -- -- 40.0 -- 40.016. Zambia -- -- -- -- -- -- -- -- -- -- -- -- 93.0/c 93.0
-- = Not available
/a Estimates of the Bank of Sudan. The Ministry of Planning has alternative estimates.
/b The estimates for Botswana refer to the percentage of total investment financed by public funds (domesticand foreign).
/c Figure for 1980.
/d Where data for some of the period is missing, the average relates to years for which data is available.
Note: This table has been compiled from a variety of national sources. Concepts are not comparable betweencountries and coverage may not be comprehensive or accurate. Total investment refers in almost all casesto the monetized or formal sector.
Source: Data Files, The World Bank.
- 65 -
ANNEX
Table 28: INDEX OF REAL RECURRENT EXPENDITURE ON ECONOMICSERVICES IN FOUR EASTERN AFRICAN COUNTRIES
1970 1971 1972 1973 1974 1975 1976 1977 1978 1979
Kenya 100 113 111 114 118 147La 153 134 171 181
Sudan 100 110 122 118 164 155 158 139 130 111
Tanzania 100 104 115 154 186 -- la 291 265 342 --
Zambia 100 140 111 99 97 171 134 127 91 --
-- = Not available.
a/ Series broken in this year.
Note: The GDP deflator was used to convert series into constant prices.
Sources: Data Files, World Bank
- 66 -ANNEX II
INTERRELATIONS BETWEEN THE ICOR, GROWTH RATE,INVESTMENT RATIO AND THE INVESTMENT RATE
The ICOR for the period i to ; is defined as the ratio of invest-
ment summed over the period i-1 to j-1 to output in period j minus output ir
period i.The ICOR, the rate of growth of output, the investment ratio and
the rate of investment in Eastern Africa are related to each other.
It is worthwhile examining some identities.
Let K = capital stock
Y = output
I = investment
and the operator indicate changes in each variable.
Then AK = ICOR
Also & = I I/. i
,Ay 'A!!Y = Y/ y ............ -- -- -... .......................... iY y
This identity states that
ICOR = investment ratio/growth rate of output
AlsoAK AK K
y
or taking logarithms
log ~K- = logi~K_ log +Y log K/ .Mi8AY = o-KlgS + lgKy ................................ (i
K
Or log (ICOR) = log (growth rate of capital) - log (growth rate of output)
+ log (average capital output ratio)!/.
Thus the ICOR is inversely related to the growth rates of output
and capital and directly related to the investment ratio. Kuznets (1960),
1/ See A.A. Walters (1966) and Kazuo Sato (1971) for analysis along similarlines.
- 67 -
ANNEX II
Kuznets (1961), K. Sato (1971) and J. Vanek and A.H. Studenmund (1968)
among others have estimated these relations and also other behavioral ones.
Some of these exercises cannot be replicated for the Eastern Africa sample
since they involve a knowledge of the rate of depreciation of capital stock
and net investment magnitudes. Kuznets (op. cit.) found the gross ICOR to
be significantly related to the growth rate of output as well as per capita
income. The latter association may be due to the relation between sectoral
shares in output and income. As incomes rise, the economy generally shifts
towards a non-agricultural composition of output and ICORs in the non-agri-
cultural sectors are typically higher than in agriculture. There is, how-
ever, also capital deepening with development, so that at significantly
higher levels of income, the ICOR in all sectors may be higher. Sato also
found in some of his regressions that the share of exports in goods and
services is related positively to the ICOR. Export items generally require
more capital in production, processing and transport than goods intended
for domestic consumption, especially if they are minerals. Overall, how-
ever, Sato concluded that the relation between various behavioral variables
and the ICOR was weak in samples consisting exclusively of low income
countries.
In the case of the Eastern African countries we are more inter-
ested in why growth rates of output decreased and the ICOR rose between
periods rather than in an explanation of the ICOR at a point in time.
However cross section regressions do reveal some interesting patterns.
The inverse relation between the ICOR and growth rate, was, we
have seen valid for Eastern Africa on an intertemporal basis. Output
growth was lower in the 1973-79 sub-period relative to the 1967-73 one and
- 68 -
ANNEX II
ICORs were on the average higher. The same relation holds cross section-
ally. The correlation coefficients between ICOR and the growth rate of
output were -0.35 and -0.82 in the two sub-periods respectively, both
significant on the basis of the 't' test at the 90 percent level of
significance.
The correlation coefficient between ICOR for the 1967-73 sub-
period and the investment ratio in 1973 was positive and equal to 0.61.
This was significantly different from zero at the 90 percent level. For
the sub-period 1973-79 however this coefficient was not significantly dif-
ferent from zero. This may have been due to the omission of several coun-
tries from the data set due to their ICORs taking negative values.-/
Besides the above relations, however, another statistical as-
sociation was noticed in the data for Eastern Africa. This was an inverse
association between the ICOR and the growth rate of investment. In the
1967-73 period this correlation was not significant, though close to it.
In the 1973-79 period, the correlation coefficient was -0.58 and signifi-
cant. This relation does not follow from an accounting identity. Evi-
dently in countries where the ICOR is high, the growth rate of investment
is low. This may indicate that the high ICORs characterizing the Eastern
African economies are not merely a transient phenomenon due to the lumpi-
ness of investment and gestation lags. If that was the case, it is more
likely that high ICOR levels would be associated positively with the rate
of growth of investment. However the evidence is too limited to draw any
strong conclusions.
1/ A negative ICOR is inadmissible in statistical manipulations as the lowerthe ICOR the more productive is investment, yet a negative ICOR is anextreme example of inefficiency of investment.
- 69 -ANNEX II
The contribution of each sector to the change in overall ICOR can
be identified according to the following breakdown given in "Capital
and Growth in India, 1950-71" by Martin Wolf in World Bank Staff Working
Paper No. 279. The symbols are from the original.
Let I = aggregate ICOR
I = ICOR in sector i
Ci = Share of sector i in the increment in output IAYiAtYJ
Then the change in ICOR or Al is given by
Al=EAI Ci +EACT Ii+EACiAI I/i ii i ii i i
Now the second term on the R.HS. is
EACiI + ECi (I - I)
But EACiI IEACi and
ZAC = 0 as the incremental shares in output of the sectors
must cancel each other out and sum to zero.
Then AI = EAIiCi + EACi (Ii - I) + EACi i
Al C + AC (I - I) + AC AI gives the i sectors contribution to the overallii i i i i
ICOR change. The first term gives the contribution of the ith sectoral ICOR.
The second term measures the contribution of the sectoral output increase.-t
The last is a cross product term. The details of the exercise for Tanzania
and Kenya are summarised below. The change in the ICOR from 1967-73 to
1973-79 was analysed as follows:
1/ The last term is of the second order of smallness, but its inclusion isrequired as A is a finite rather than an infinitesimal operator.
2/ This contribution is positive or negative depending on whether the ithsectoral ICOR is higher or lower than the overall ICOR.
- 70 - ANNEX 11
(1) (2) (3) (4) (5) (6) (7)
PercentageSum of distribution
Country and sector Is &jCj aCiAIi ACj(I-I) 3, 4 & 5 of column 6
KenyaAgriculture 1.7 0.204 0.1990 0.0710 -0.1120 0.1580 3.6Industry 2.4 0.330 1.4560 -0.0180 0.0030 1.4410 32.7Services 4.5 0.465 3.3950 -0.5020 -0.0860 2.8070 63.7
TanzaniaAgriculture 1.5 0.250 -0.1900 -0.1290 -0.5600 -0.870 1/Industry 10.0 0.190 10.2600 -8.6400 -0.8300 0.790 1/Services 4.4 0.560 0.0056 -0.0001 -0.0004 0.0059 1/
1/ Agriculture accounted for the entire decrease of 0.07 in the overall ICOR.
Source: Data Files, World Bank
- 71 -
ANNEX III
Limitations of National Account Data in Eastern Africa
I. General
In this Annex a number of issues relating to data on the Eastern
African countries are discussed. An appreciation of these issues will help
in evaluating the quantitative information presented in this paper as well
as aid the reader in interpreting data from standard sources on Africa.
It is generally acknowledged that economic data for Africa are poor.
It may be well worth supplementing usual national accounts and macro data
for this region by data generated in response to special surveys over whose
design and organization the researcher has greater control. Specifically,
farm management surveys, special sample surveys, small industry survey, etc.,
spring to mind. The veracity of the data from these sources should compen-
sate for their lack of economy-wide coverage. Currently there is a paucity
of such information and reliance has to be placed on national accounts sources
which are often estimates based on limited evidence. Some improvements have
been effected but if the goal is to obtain reliable information for research and
policy design, then a much heavier emphasis on data upgrading is required.
Currently, published African data seem to suffer from the following
drawbacks.
(a) Many estimates are derived from a few verifiable indi-
cators. For instance overall investment is sometimes derived from
imports of capital goods. Price indices may be obtained from the
prices of a handful of commodities in the capital city using very
- 72 -
ANNEX III
outdated weights. Import or export statistics may omit any ad-
justment for smuggling when this is recognized to be a major
phenomenon. Consequently though a mass of statistics may be avail-
able in the standard UN format, there is no guarantee that this
information represents the real world or is comparable across
countries. In the shakiest of cases the information simply does
not accord with qualitative evidence or the experience of observers
on the scene.
(b) The presence of overvalued exchange rates, multiple
exchange rate practices and unreliable price indices makes constant
price comparisons as well as cross country comparisons in terms of,
say, United States dollars dubious. Trend analysis fares better than
any comparison of absolute magnitudes.
(c) Data are often volatile from year to year to an extent
which casts doubt on their reliability. The procedure adopted in this
paper has been to take three year averages centered around the re-
porting year whenever possible in order to minimize this effect.-/
Data are also reported at short intervals so as not to miss
cycles. We have tried not to draw any inference unless data
for several years confirmed an event.
1/ If the period to be analyzed was very short then this procedure has notbeen followed. Use of a moving average results in the omission of anumber of years at the end palats and Ie "et practic&l for short series.
- 73 -
ANNEX III
II. Country Specific Notes
While national accounts data for most African countries suffer
from deficiencies, the series for Sudan, Tanzania and Somalia are even more
suspect than others. In the case of Sudan the national authorities claim
that the series for the seventies and the sixties are not comparable. They
have also stopped releasing national income estimates in constant prices.
In the case of Tanzania, the national accounts estimate of a growth rate
of 8.8 percent per annum for subsistence production in the seventies is
considered implausible. The aggregate growth estimates in this paper as-
sume that the subsistence sector has only grown at a rate of 4.3 percent
per annum. For Somalia, while World Bank data files show a growth rate of
7.4 percent per annum in the 1973-78 Deriod. lntpr information esti-
mates the growth rate to have been only about 2.5 percent between 1972 and
1978. There are no official national accounts and virtually no primary
data base, but the economy appears to be in general stagnation.
- 74 -
REFERENCES
Carrington, John C. and Edwards, George T., Financing Industrial Investment,MacMillan Press, London, 1979.
Faruqee, Rashid and Gulhati, Ravi, Rapid Population Growth in Sub-SaharanAfrica, World Bank Staff Working Paper, No. 559, 1983.
Gulhati, Ravi I., "The Need for Foreign Resources, Absorptive Capacity andDebt Servicing Capacity", Capital Movements and Economic Development, Editedby Adler, John H., St. Martin's Press, 1967.
Gulhati, Ravi and Sekhar, Uday, "The Industrial Strategy for Late Starters:The Experience of Kenya, Tanzania and Zambia, World Bank Staff WorkingPaper No. 457.
Gulhati, Ravi and Autokorala, Vimal, "Behaviour of Import and the Nature ofRelated Policies" (Forthcoming).
Kim, Kwan S., "Enterprise Performances in the Public and Private Sectors:Tanzanian Experience, 1970-75", The Journal of Developing Areas, 15, April1981.
Kuznets, S., "Enterprise Performances in the Public and Private Sectors:Capital Formation Proportions, International Comparison for Recent Years",Economic Development and Cultural Change, Vol. 8, P&2, July 1960.
Kuznets, S., "Quantitative Aspects of the Economic Growth of Nations, VI,Long-Term Trends in Capital Formation Proportions", Economic Development andCultural Change, Vol. 1, P&2, July 1961.
Meier, G.M., Leading Issues in Development Economics, Oxford University,1964.
Reddaway, W.B., The Development of the Indian Economy, George Allen andUnwin Ltd., London, 1962.
Sato, Kazuo, "International Variations in the Incremental Capital-OutputRatio", Economic Development and Cultural Change, Vol. 19, No. 4, July 1971.
Scott, M.F.G., "The Contributlon of Investment to Growth", Scottish Journalof Political Economy, Vol. 28, November 1981, No. 3.
Vanek, J. and Studenmund, A.H., "Towards a Better Understanding of theIncremental Capital-Output Ratio, , The Quarterly Journal of Economics,Vol. LXXXII, No. 3, August 1968.
Walters, A.A., "Incremental Capital Output Ratios", Economic Journal, 76,December 1966.
Wolf, Martin, "Capital and Growth in India: 1950-71", India OccasionalPapers World Bank Staff Working Paper No. 279, November 1978.
World Bank; Accelerated Development in Sub-Saharan Africa; An Agenda forAction, 1981.
World Bank Aggregate Demand and Capital Market Imperfec-Macroeconomic Imbalances tions and Economic
Publications In Thailand: Simulations Developmentof Related with the SIAM 1 Model Vinayak V. Bhatt and
of Related Wafik Grais Alan R. RoeInterest Focuses on the demand-side adjust- World Bank Staff Working Paper
ments of the Thai economy to lower No. 338. July 1979. 87 pagesagricultural growth and to higher (including footnotes).energy prices. Discusses policymeasures and structural changes that Stock No. WP-0338. $3.00.might enable the economy to over-come these problems and continue tomaintain high GDP rates of growth. The Changing Nature ofWorld Bank Staff Working Paper No. Export Finance and ItsWord ankStff oringPaer o. Implications for Developing448. April 1981. 70 pages (including Countries2 appendLxes). onre2 appendixes). ~Albert C. Cizausk~asStock No. WP-0448. $3.00.
World Bank Staff Working Paper No.409. July 1980. 43 pages (including
An Analysis of 3 annexes).Developing Country Stock No. WP-0409. S3.00.
Adjustment Experience and Adjustment Experiences inGrowth Prospects of the the 1970s: Low-income AsiaSemi-Industrial Countries Christine Wallich Compounding and Dis-Frederick Jaspersen This background study for World counting Tables forThis background study for World Development Report 1981 examines Project EvaluationDevelopment Report 1981 examines low-income South Asia's adjustment J. Price Gittinger, editorthe successful process of adjustment to the extemal shocks of the 1970s, Easily comprehensible, convenientto extemal 'shocks" of the 1970s especially those factors that helped tables for project preparation and(rising prices of oil imports, reduced make the effects of these external analysis.demand for exports, slower economic developments less severe in thegrowth in the OECD countries) in the region than in other parts of the The Johns Hopkins University Press,semi-industrial developing countries. developing world. 1973; 7th printing, 1982. 143 pages.Presents an analytical framework for World Bank Staff Working Paper No. LC 75-186503. ISBN 0-8018-1604-1.quantifying the effects of demand 487. August 1981. iv + 39 pages $6.00 paperback.management and structural adjust- (including references).ment in forty-two countries, with par- Arabic: WorldBank 1973. (Auailableticular reference to Uruguay, Brazil, Stock No. WP-0487. $3.00. from ILS 1715 Connecticut Avenue,Republic of Korea, and Turkey. N.W., Washington, D.C. 20009, U.S.A.)
World Bank Staff Working Paper No. Aspects of Development $4.00 paperback.477. August 1981. 132 pages (including Bank Management French: Tables d'interets composes et3 appendixes). William Diamond and d'actualisation. Economica, 4th print-Stock No. WP-0477. $5.00. V. S. Raghavan ing, 1979.
Deals exclusively with the manage- ISBN 2- 71 78-0205-3, 36 francs.A4|ustment in ment of development banks. The Spanish: Tablas de interes compuesto yLow-income Africa book is divided into eight sections, de descuento para evaluaci6n de proyec-Robert Liebenthal each dealing with one aspect of tos. Editorial Tecnos 1973; 4th print-This background study for World of the various ways of dealing ing, 1980.Deuelopment Report981 analyzes with them. ISBN 84-309-0716-5, 380 pesetas.the adJustment to external shocksduring the 1970s made by a group EDI Series in Economic Deuelopment.of middle-income and low-income The Johns Hopkins University Press, A Conceptual Approach toAfrican countries, with particular 1982. 311 pages. the Analysis of External Debtreference to Kenya, Tanzania, LC 81-48174. ISBN 0-8018-2571-7 of the Developing Countries
$29.95 hardcover, ISBN 0-8018-2572-5, Robert Z. AliberWorld Bank Staff Working Paper No. $12.95 paperback. World Bank Staff Working Paper No.486.(Aug b io+r56page 421. October 1980. 25 pages (including(Including bibi3ography). appendix, references).Stock (10. WP-0486. $3.00. Stock No. WP-0421. $3.00.
Development Banks Developments in and Food Policy Issues inWilliam Diamond Prospects fogr the External Low-income CountriesOperating experiences that serve as a Debt of the Developing Edward Clay and otherspractical guide for developing coun- Countries: 1970-80 A background study for Worldtries, with a selected list and and Beyond Development Report 1981. Discussessummary description of some Nicholas C. Hope food distribution-especially Itsdevelopment banks. , d 'd insecurity in the face of external
The Johns Hopkins University Prss, Development Report 1981 analyzes conflict withintemrn production1957; 5th printing, 1969. 141 pages the debt situation and its implica- conflcrswinh genteral anoducwith(including 2 appendixes, index). tions for future borrowing. reference to Bangladesh, Zambia,
LC 5 7-13429. ISBN 0-8018-0708-5, World Bank Staff Working Paper No. and India.$5.00 (S3.50) paperback. 488. August 1981. 70 pages (including World Bank Staff Working Paper No.
2 annexes, references). 473. August1981. uli + 715 pages.
Development Finance Com- Stock No. WP-0488. $3.00. Stock No. WP-04 73. $5.00.panies: Aspects of Policyand Operation Energy Prices, Substitution, A General EquilibriumWilliam Diamond, editor; and Optimal Borrowing in Analysis of Foreignessays by E. T. Kuiper, the Short Run: An Analysis Exchange Shortages In aDouglas Gustafson, and of Adjustment in Oil- Developing EconomyP M. Mathew Importing Developing Kemal Dervis, Jaime de Melo,
The Johns Hopkins University Press, Countries and Sherman Robinson1968.130 pages (including appendix, Ricardo Martin and Examines the consequences of alter-index). Marcelo Selowsky native adjustment mechanisms to
LC-68-27738. ISBN 0-8018-0166-4, Develops a short-term model for foreign exchange.shortages in semi-$5.00 (43.25) paperback. evaluating the adjustment (par- industrial economies. Compares
French: Les societes flnancieres de ticularly, extemal borrowing) of oil- devaluation to two forms of Importdeveloppement: quelques aspects de importing developing countries to the rationing and flnds that adjusting byleur politique et de leurs activits. increases in oil prices during the rationing is much more costly in(Available free from the World Bank 1970s. Discusses the borrowing terms of lost gross domestic product.Washington, D. C) strategies that can be exdpected in the World Bank Staff Working Paper No.
Spansh:Las ompiifa flanciras future and the demands that will be 445. January 1981. 52 pages (includ-Spanish: Las companiias financieras made on multilateral institutions. 44ng reernces)198.32pgs(nldde desarrollo: algunos aspectos de su ing refernces).politica y de sus actividades. Editorial World Bank Staff Working Paper No. Stock No. WP-0443. $3.00.Tecnos, 1969. 466. July 1981. 77 pages (including
300 pesetas. footnotes, references).Stock No. WP-0466. $3.00. NEW
Development Prospects Growth and Structuralof Capital Surplus Oil- Exchange Rate Adjustment Adjutm in EastAsaExporting Countries: Iraq, under Generalized Currency Adjustment in East AsiaKuwait, Libya, Qatar, Floating: Comparative arvez HasanSaudi Arabia, UAE Analysis among Developing Analyzes the economic performanceRudolf Hablultzel Countries of the five large market economies of
Rudolf liabiutzeRomolM ButitaEast Asia-Korea, Thailand, theThis background study for World Romeo . utista Philippines, Malaysia, andDevelopment Report 1981 Examines the experiences of twenty- Indonesia-during the last twodiscusses the production strategies two developing countries in adapting decades; focuses on the key factorsand the development policies of the to the generalized floating of the explaining their remarkable economiccapital-surplus oil-exporting world's major currencies since 1973 and social progress; and identifles thecountries. and discusses the implications that main economic issues for the 1980s.
World Bank Staff Working Paper No. currency floating has on policymaking World Bank Staff Working Paper No.483. August 1981. 53 pages (including tions for further research. 529.1982. 42 pages.statistical tables). World Bank Staff Working Paper No. ISBN 0-8213-0102-0. $3.00.
Stock No. WP-0483. $3.00. 436. October 1980. 99 pages (including
appendix).
Stock No. WP-0436. $3.00.
International A4justment in a t c icS of ect appraisal. To give substance to
the 1980s _1 t the applied and policy dimensions,many of the readings are drawn fromVijay Joshi Ben t ELKing the experience of development prac-
A backgound study for World A pratical rwAm l to explore the way titioners and relate to such important
Development Report 1981. Analyzes In which capitl Inflow from abroad sectors as agriculture, industry
the macroeconomics of intemational affects economic growth. power, urban services, foreign trade,
adjustment. Highlights potential and employment. The principlesmarket failures and areas for The Johns Hopkins Uniuers~ity Pr~ess, outlined are therefore relevant to aintervention. 1968. 69 pages (including 4 annexes). host of development problems.
World Bank Staff Working Paper No. LC 68-8701. ISBN 0-8018-0338-1, $5.00 The Johns Hopkins University Press.
485. August 1982. 57 pages. (X3.00) paperback. February 1983. About 304 pages.
ISBN 0-8213-0062-8. $3.00. LC 82-7716. ISBN 0-8018-2803-1,The PAW E xVlcure e of $35.00 hardcover; ISBN 0-8018-2804-X,
Tweli1 law D.Pe $12.95 paperback.
NEW CA _1II W75-31BBeis a Private Bank Lending to
The Niature of Credit Uses the methodology applied In the Developing CountriesMarkets in Developing author's -The Newly Industrializing Richard O'BrienCountries: A Framework Developing Countries after the Oil
for Policy Analysis Crisis" (World Bank Staff Working A background study for WorldArvind Vircnani Faper No. 473. October 1980) to Development Report 1981.
examine the policy experience of Describes the evolution of relation-
The central purpose of the paper is to twelve less developed countries in ships between private banks andanalyze various forms of government the period following the quadrupling developing countries.
intervention in the loan market in of oil prices In 1973-74 and the World Bank Staff Working Paper No.terms of their effect on efflciency world recessLon of. 1974-75. 482. August 1981. vi + 54 pages
World Bank Staff Working Paper N'o. Wo,id 5r SW Working Paper No. (including appendix. bibliography).524. 1982. 204 pages. 449. Apdl 1. 36 pages (Including Stock No. WP-0482. $3.00.
ISBN 0-8213-0019-9. $5.00. appedI.Stock No. WP-Ct449. $3.00. Private Capital Flows to
The Newly Industrializing Developing Countries andDeveloping Countries after The Political Structure of Their Determinations:the Oil Crisis the New Protectionism Historical Perspective,Bela Balassa Douglas R. Nelson Recent Experience, and
World Bank Staff Working Paper No. This background study for World Future Prospects43 7. 5 ctober 1980. 5 7 pages (including Development Report 1981 Alex Flemingappendix). apresns a polilc c-econofftic A backgound study for World
Stock No. WP-043 7. $3.00. iw Development Report 1981.Discusses the nature and determina-
World Bank SW Ubrking Paper No. tion of recent private capital flows to
rNotes on the Analysis of 471. Juty 1W. 57 pages (Including developing countries. Focuses on
Capital Flows to Developing references). those flows passing through theNations and the Stock No0. WP-04 71. $5.00. international banks and examines the
prospects for and constraints on"Recycling" Problem developing countries' continuing
Ralph C. Bryant access to the international capital
A backgound study for World NEW markets.Development Report 1981. World Bank Staff Working Paper No.Summarizes and criticizes the con- Pcing PHcy for Develop- 484. August 1981. 41 pages.ventional analysis of the interrela- ment lanagement Stock No. WP-0484. $.00.tions between flnancial markets In ewald M. Meierthe Industrialized countries and capi-tal flows to the developing nations. pfn t h e Private Direct Foreign
World Bank Staff Working Paper No. e _meA of a price system, the Investment in Developing4 76. August 1981. 67 pages. funcions of Prbm& the various CountriesStock No. WP-04A76. $3.00. policies that a govenmnent mighit Ki. Billerbeck and Y. Yasugi
Stock No. WP-4 76. $5~00 ~pursue In cases of market failure,and the principles of public pricing of World Bank Staff Working Paper No.goods and services provided by 348. July 1979. io + 97 pages (includ-govemment enterprises. It also pro- ing 2 annexes).vides the would-be practitioner withan appreciation of the underlying Stock No. WP-0348. $5.00.logical structure of cost-benefit proj-
NEW Structural Adjustment implications in terms of incomePolicies in Developing generation, extemal deficit, and
Short-Run Macro-Economic Economies inflation.Adjustment Policies in Bela Balassa World Bank Staff Working Paper No.South Korea: A Quantitative Examines structural adjustment 513. June 1982. 93 pages (includingAnalysis policies (policy responses to external appendix).Sweder van Wijnbergen shocks, such as the quadrupling of lSBN 0-8213-0023-7. $3.00.
oil prices and the world recession ofAn analysis of the startling reversal of the 1970s) of developing countries.performance of the South Korean Considers reforms in production World Debt Tableseconomy in 1979 and 1980 compared incentives, incentives to save and towith the preceding fifteen years, and invest, public investments, sectoralof data on the extemalan exploration of the short-run policies, and monetary policies, and public and publicly-guaranteed debtmacro-economic policy options comments on the interdependence of of 101 developing countries plusavailable to liorea in 1981. Highlights the various policy measures and on eighteen additional tables of privatethe role of commercial banks, foreign the intrnaionaplc menvironment in and nonguaranteed debt from thecapital inflows, and money markets the international environment in World Bank Debtor Reportingand the use of credit obtained from Y P System. Describes the nature, con-these sources to finance fixed and World Bank Staff Working Paper No. tent, and coverage of the data;working capital. 464. July 1981. 36 pages. reviews the external debt of 101
countries through 1981; containsWorld Bank Staff Working Paper No. Stock No. WP-0464. $3.00. tables on external public debt out-510. November 1981. iv + 178 pages standing commitments, disburse-(Including 3 appendixes). ments. service payments, and netISBN 0-8213-0000-8. $5.00. NEW borrowings of 101 developing coun-
tries, by country, 1972-1981.Structural Aspects of (EC-167/81). December 1982. Annual.
NEW Turkish Inflation: About 300 pages._ J950-1979 1SSN 0253-2859. $75.00.
State Finances in India M. Ataman Aksoy Computer tapes containing the dataA three-volume set of papers that Inflation has been one of the major bases for the World Debt Tables areexplores a range of issues relating to problems of the Turkish economy available from the Publicationsthe nature of intergovernmental flscal during the postwar period. This paper Distribution Unit World Bank. Therelations in India. develops alternative inflation models tapes are available to international
and analyzes their performance in agencies and official nonprofit agen-Vol 1: Revenue Sharilg light of the Turkish experience in cies of member governments at a
Vol. 1: Revenue Sharing order to provide a framework on nominal fee. For information concem-in India which a more realistic macro model ing fees for other organizations,Christine Wallich can be developed. please write to the addressee listedDeals specifically with the principles World Bank Staff Working Paper No. above.of revenue sharing in India. 540. 1982. 118 pages. Supplements to World Debt Tables are
lSBN 0-8213-0098-9. $5.00. issued periodically as informationVol. II: India-Studies in becomes available; the currentState Finances updates are included with orders forChristine Wallich NEW World Debt Tables.Examines in detail the implications ofrevenue sharing for project finance. Thailand: An Analysis of lE RINTh
Structural and Non- The Impact of Contractual Savings onResource Mobilization and Allocation:Vol. III: The Measurement of Structural Adjustments The Experience of Malaysia
Tax Effort of State Govern- Arne Drud, Wafik Grais, and Social Security Funds in Singaporements, 1973-1976 Dusan Vujovic and the Philippines: Ramiflcations ofRaja J. Chelliah and This study was prepared as a Investment PoliciesNiarain Sinha background paper for the preparation Investments of Social Security Funds
of a structural-adjustment loan to In India and Sri Lanka: LegislationAttempts to evaluate the tax perfor- Talnadisaflo-ptapr- and Experiencemance of particular states in terms of Thailand and is a follow-up to a pre- Parthasarathi Shome andthe average tax effort of all states. vious paper entitled "Aggregate Katrine Anderson Saito
Demand and Macroeconomic World Bank Reprint Series: Number 144.World Bank Working Paper No. 523. Imbalances in Thailand:' Comparative Reprinted from The Malayan Economic Review, vol.September 1982. uol. 1, 85 pages, vol. II, statistics are used, within the frame- 23, no. I (April 1978):54-72; Labour and Society,186 pages. vol. III, 85 pages. work of a four-sector macroeconomic vol. 5, no. I (January 1980):19-30: and The Indian
ISB082303Xuo , 300o model, to assess alternative ways of Journal of Economics, uol. 60, part 3, no. 238ISBlY 0-8213-0013-X. vol. I, $5.00, vol. II macroeconomic adjustment in the (January 1980).349-60.$5.00, vol. II, $3.00. Thai economy. Discusses specifically Stock No. RP-0144. Free of charge.
fiscal policy interventions, manipula-tions of the exchange rate, and pro-ductivity improvements and their
PolHcy Responses to External Shocks InSelected Latin American CountriesBela BalassaWorld Bank Reprint Series: Nlumber 221.Reprinted from Quarterly Review of Economics and
Business. vol. 21, no. 2 (Summer 1981):131-64.
Stock tNo. RP-0221. Free of charge.
Restructuring the World Economy:Round 11Hlollis Chenery
World Bank Reprint Series: 11umber 204.
Reprinted from Foreign Affairs
(Summer 1981).1102-1120.
Stock Nlo. RP-0204. Free of charge.
Risk Assessments and Risk PremiumsIn the Eurodoflar MarketGershon Feder and Knud Ross
World Bank Reprint Series: 11umber 220.
Reprinted from The Journal of Finance, vol. 37,
no. 3 (June 1982):679-91.
Stock Nlo. RP-0220. Free of charge.
WORLD BANK PUBLICATIONSORDER FORM
SEND TO:WORLD BANK PUBLICATIONS WORLD BANK PUBLICATIONSRO. BOX 37525 or 66, AVENUE D'IENAWASHINGTON, D.C. 20013 75116 PARIS, FRANCEU.S.A.
Name:
Address:
Stock or ISBN # Author, Title Qty. Price Total
Sub-Total Cost:
Postage & handling fee for more than two free items ($1.00 each):
Total copies: _ _ Air mail surcharge ($2.00 each):
TOTAL PAYMENT ENCLOSED:
Make checks payable: WORLD BANK PUBLICATIONS
Prepayment on orders from individuals is requested. Purchase orders are accepted from booksellers, library suppliers, libraries, and institutions.All prices include cost of postage by the least expensive means. The prices and publication dates quoted in this Catalog are subject to changewithout notice.
No refunds will be given for items that cannot be filled. Credit will be applied towards future orders.No more than two free publications will be provided without charge. Requests for additional copies will be filled at a charge of US $1.00 per
copy to cover handling and postage costs.Airmail delivery will require a prepayment of US $2.00 per copy.Mail-order payment to the World Bank need not be in U.S. dollars, but the amount remitted must be at the rate of exchange on the day the
order is placed. The World Bank will also accept Unesco coupons.
II
I
HG 3881.5 .W57 W67 NO.562C.3
GULHATI, RAVI.
CAPITAL ACCUMULATION INEASTERN AND SOUTHERN AFRICA
-7~~~~~~~~~~~~~~~~~~N
DATE NAME AND EXTENSION ROOMNUMBER
1~ F JeePIeLkYQJuly 2 -O
The World Bank . F
Headquarters:1818 H Street, N.W. I
Washington, D.C. 20433, U.S.A.
Telephone: (202) 477-1234Telex: WUI 64145 WORLDBANK
RCA 248423 WORLDBK
Cable address: INTBAFRADWASHINGTONDC
European Office:66, avenue d'1ena75116 Paris, France
Telephone: (1) 723-54.21Telex: 842-620628
Tokyo Office:Kokusai Building1-1, Marunouchi 3-chome 0
Chiyoda-ku, Tokyo 100, Japan
Telephone: (03) 214-5001Telex: 781-26838
0
ISSN 0253-2115/ISBN 0-8213-0169-1
