Austral. 1. Statist.. 26 (I), 1984, 45-57

REGIONAL ECONOMIC-DEMOGRAPHIC MODELLING AND PROJECTION: REVIEW O F A N INTERNATIONAL CONFERENCE'

PAMELA WfiSIAMS

IMPACT Research Centre, The University of Melbourne

s-w The state-of-the-art in economic-demographic modelling of reg-

ional populations was presented at the International Conference on Forecasting Regional Population Change and its Economic Determinants and Consequences held at Airlie House, Virginia, U.S.A. over May 26 to 29, 1982. This review of papers presented at the Conference concludes that such modelling is at an early stage of development and currently provides only an adjunct to more conven- tional methods of regional forecasting. Given expected future improve- ments in the theory, data and techniques of economic-demographic modelling, such models could soon provide a worthwhile alternative.

1. Introduction

Forecasts of population change are an important input to the framing of regional economic and social policies. Traditionally, such forecasts have been made using cohort-component techniques, which assume constancy or simple time-trends in the components of demo- graphic change and refer only indirectly to the determinants and conse- quences of regional population change. Recently, however, population forecasting models which incorporate the linkage between regional economies and their populations are being developed; for an early example, see Adams et al. (1975). These economic-demographic mod- els have the potential to improve substantially the policy advice derived from regional population forecasts by improving our under- standing of regional economic and demographic behaviour and its consequences.

The state-of-the-art for such economic-demographic modelling was recently recorded at the International Conference on Forecasting Regional Population Change and its Economic Determinants and

Manuscript received January 5 , 1983.

46 PAMELA WILLIAMS

Consequences. The Conference, sponsored by the American Statistical Association and the US. Bureau of the Census, brought together a wealth of knowledge on approaches to forecasting regional popula- tions, with attendance by over 100 practitioners from ten countries. Whilst the Conference provided interesting examples of operational economic-demographic models, it also provided ample evidence of the dominance of traditional forecasting techniques. Forecasting models which fully incorporate the linkages between regional economy and demography appear to be an ideal seldom achieved.

The limited use of econometric models in regional population forecasting can be attributed to three factors: first, the lack of a theory which can fully capture and explain the complex interrelationships between economy and demography, and the resultant difficulties in specifying economic-demographic models; second, the lack of ade- quate data to implement such models, especially those to explain regional migration; and, third, the lack of necessary technical, financial and manpower resources to build and implement such models in those agencies involved in forecasting. Consequently, economic- demographic models of regional population are still in the early stages of development and tend to be used as an adjunct to more conven- tional methods of forecasting.

In this review of paperg presented at the Conference, I have chosen to consider, in the following section, the approaches taken by Conferees to the modelling and projection of the components of regional demographic change. Then, in Section 3, I consider how these approaches to modelling demographic change were combined with models of economic change in single region and multi-regional economic-demographic models. Section 4 contains concluding re- marks.

2. Approaches to Modelling and Projecting the Components of Regional Population Change

The first step towards incorporating econornic-demographic mod- els into population projection facilities is to develop models of the components of population change: fertility, mortality, marital status change, and regional migration. The models presented at the Confer- ence focussed heavily on regional migration, which, in the current climate of declining fertility and mortality, is seen as the most impor- tant component of regional population change. Certainly, the model- ling of mortality in terms of causes of death was not attempted in any of the papers presented. Also, despite agreement that the marital status distribution of the population was an important factor in analys- ing changing fertility, labour force participation, housing demand and the like, only two papers (Ahlburg, 1982; and Rogers Rr Williams,

REGIONAL ECONOMIC-DEMOGRAPHIC MODELLING AND PROJECTION 47

1982) made any explicit attempt to consider the effects, or determin- ants, of marriage and divorce. Both papers presented economic models of fertility, marriage, divorce and female labour force participation, the specification of which incorporated relationships suggested in the liter- ature of the “new home economics” school, foIlowing such authors as Becker (1960 and 1974), Becker, Landes & Michael (1977), Easterlin (1973), Lancaster (1966), Butz &Ward (1979), and Keeley (1977 and 1979). Further, Rogers & Williams used their model to project popula- tion disaggregated by marital status. By attempting to incorporate the simultaneity between important demographic events at a level of disaggregation not normally available, such models could be extremely useful for policy-makers. However, both models were estimated at the national level, and their application at the regional level may be limited by lack of data.

Fertility

Conferees felt that, ideally, regional fertility behaviour should be analysed in the context of a behavioural model. However, lack of regional fertility data currently prevents the direct modelling of reg- ional age-specific fertility rates. Conferees opted to use econometric models of national fertility to provide projections of national fertility which could be disaggregated for each region, on the basis of its own peculiarities.

Operational models of national fertility ranged from models of the crude birth rate (Ahlburg, 1982), the total fertility rate (Greenberg & Renfro, 1982), fertility rates by race and quinquennial age group (Redwood, 1982), and the parameters of a distribution of completed family size (from Brooks, Sams & Williams, 1982, and discussed in Rogers & Williams, 1982). To produce projections of age specific fertility rates, models with no age disaggregation assumed a constant age distribution of age-specific fertility rates. However, direct model- ling of race and age-specific fertility rates (Redwood, 1982) occasion- ally led to inconsistencies in the age distribution of the projected fertility rates. The explanatory variables used to model these measures of fertility derived from the “new home economics” literature and included female wage rates, income (both current and relative to aspirations), female labour force participation rates, indicators of labour market pressure (including unemployment rates, and relative generation size), measures of the opportunity cost of having children, the number of children already born per married woman, variables measuring the effect of recent marriages (including the marriage rate, the median age at rnamage and the total stock of marriages) and variables to measure the effects of war and the introduction of con- traception. Rogers & Williams (1982) presented the only model which

48 PAMELA WILLIAMS

attempted to incorporate the effects upon fertility of decisions with respect to family size and of the role of children as security for their parents (via variables such as the infant mortaility rate and the old age pension). The choice of the particular explanatory variables used in each of these models appeared to reflect more closely the availability of data than the dictates of theory; the correct model to determine national fertility is by no means clear.

Using this approach, once a national fertility projection has been derived, by modelling or some other method, it must be disaggregated according to some ratio of regional to national fertility. A constant ratio between the regional and national age profile was assumed by Joun & Conway (1982), Greenberg & Renfro (1982) and Redwood (1982), whilst PIaut (1982) and Ahlburg (1982) attempted simple models of the ratios of regional to national crude birth rates or births, with age-specific birth rates being determined by a constant schedule of age-specific rates. None of these approaches is successful in provid- ing a methodology for the analysis of causes of differential regional fertility, or, in incorporating these causal influences in the projection of regional fertility.

Regional Migration

Analysis of the determinants of regional migration and attempts to model it were the subject of many of the papers presented at the Conference. Several studies (Plane & Rogerson, 1982; Isserman, 1982; Rogers & Williams, 1982; Rosenman, 1982; Black, 1982; Warnes, 1982; and Herzog & Schlottmann, 1982) analysed the deter- minants of regional migration, pointing to the importance of economic and job-related factors (such as regional differentials in wages, security of employment, living costs, housing costs and housing availability) and non-economic factors (such as regional differentials in climate and living environment). However, Conferees (Wetrogan & Engels, 1982; Bilsborrow & Akin, 1982; and Noms, 1982) lamented the lack of data to measure regional migration, let alone to explore its relationship to other variables. Census data are untimely, ask questions retrospec- tively (increasing likelihood of loss of memory) and are unable to capture multiple movers. However, they do provide fine geographic detail and a large sample size, which are lacking from more timely survey data. Panel data are usually severely limited by their cost, the size of the sample (and its tendency to contract over time) and reporting errors. Alternatively, determining net migration from a re- sidual technique, where (net migration = population change - natural increase), is limited by the lack of faith in population estimates and the high probability of compounding errors. Also, this technique provides only net migration, as opposed to the more useful gross flows.

REGIONAL ECONOMIC-DEMOGRAPHIC MODELLING AND PROJECTION 49

Certainly lack of data represents an important hindrance to regional migration analysis and modelling. Ideally, data on the personal and employment related characteristics of the migrant and the ecomonic and environmental characteristics of his origin and destination regions is required. The data should be sufficiently disaggregated to allow the analysis of small regions, preferably defined according to “market”, rather than political, boundaries. The analysis of sequential and return migration requires panel data which tracks the migration behaviour of particular individuals or households over time. Few data sets are available which incorporate all these factors adequately.

The models of regional migration presented at the Conference varied enormously in quality, in complexity, and in the migration variables they sought to explain. The migration variables modelled were generally highly aggregated. Whilst different factors were recog- nised as influencing in- and out-migration, lack of data and the possibility of compounding errors led many modellers to use net migration variables. It was generally agreed that the determinants of migration would vary with the demographic characteristics (age and sex, in particular) of the migrants and that the disaggregation of migration flows by these characteristics would provide useful informa- tion. However, few authors attempted to model migration at a dis- aggregated level. The migration variables which were actually model- led ranged from total net migration (Joun & Conway, 1982; and Plaut, 1982), net migration by age group (Greenberg & Renfro , 1982), total migration inflow and outflow (Fukuchi, et al. 1982; Van der Veen & Evers, 1982; and Ledent, 1982) and migration inflow and outflow by sex and age group (Beaumont et al. 1982). Plaut (1982) also disaggre- gated his net migration projections by sex and age group using a simple ratio technique.

The underlying theory behind all the migration models was simi- lar: migrants respond according to the relative attractiveness of a region, which is closely related to its labour market and environmental conditions. Models of single regions related migration to and from that region to its conditions relative to those of the nation (Greenberg & Renfro, 1982; and Plaut, 1982), whilst multi-regional models related migration to conditions in the source and destination regions (Van der Veen & Evers, 1982) or to conditions in all other regions (Beaumont et al., 1982; and Ledent, 1982). Joun & Conway (1982), derived total net migration residually: national labour markets were assumed to be sufficiently flexible for labour demand and supply within a region to be equated by net migration to or from that region. For models of smaller regions (Van der Veen & Evers for the Netherlands and Fukuchi, et al. for Tokyo), the relationship between locational choices and employ- ment opportunities, land prices, housing availability, and commuting possibilities was explored. In the two models disaggregated by age

50 PAMELA WILLIAMS

(Beaumont et al., and Greenberg & Renfro), economic conditions were directly relevant for the migration of adults of labour force age, and indirectly for children (whose migration was related to that of persons of labour force age, their parents). Neither of these studies attempted to explain the migration of older persons in a behavioural model.

The variables used to measure regional attractiveness were similar in all of the models; they included unemployment rates, employment levels, employment separations, per capita incomes, expected income (which was measured using real wages rates and the probability of finding employment), relative prices (of goods and services and of land), housing availability, quality of natural environment, past levels of migration and of population, and distance between regions. In general, these variables entered the models in simple linear form, although Ledent (1982) and Beaumont et al. (1982) presented models where multiregional consistency was ensured.

The ability of the models to describe their chosen migration variable ranged from poor to adequate. Despite the presence of in-sample errors ranging from 10 to over 100 per cent, all model- builders felt that their models provided some advance over the common assumption of constant migration rates. The poor quality of migration data and their inherent volatility were felt to frustrate modelling attempts. Some authors proposed improvements to the explanatory variables of their models, especially those variables which were determined simultaneously within economic-demographic mod- els. Despite these suggestions, there appears to be an optimism regard- ing migration modelling which results cannot support. The study and modelling' of regional migration is an area of research still in its infancy.

3. EconomicDemographic Models of Regional Economic and Demographic Growth

Whilst regional economic conditions will affect the level and composition of the components of population change, population growth will simultaneously affect the regional economy via its impact on the level and composition of consumer demand, housing demand and labour supply. Thus, models should recognise the two way links between regional population change and the regional economy. The specification of such models at the Conference varied according to the size of the region being considered and the scope of the model (that is, single region versus multi-region).

Small Area Models

Two papers (Van der Veen & Evers, 1982; and Fukuchi, et al., 1982) provided models of the joint determination of economic and

REGIONAL ECONOMIC-DEMOGRAPHIC MODELLING ANJ3 PROJECTION 5 1

population growth within regions smaller than States. These models emphasized the interactions between labour markets, and migration and commuting decisions. Unfortunately, lack of data forced these models to be highly aggregated and somewhat simplistically specified. Whilst both models fitted the data tolerably well, their lack of dis- aggregation by demographic characteristics, the simplistic specification of the unemployment rate (for Van der Veen & Evers) and the excessive reliance on lagged dependent variables (for Fukuchi, et al.) would limit their usefulness for small area forecasting. Despite these problems, the models provided instructive attempts to incorporate the effects of regional income, employment opportunities, housing prices, housing availability and commuting possibilities o n locational deci- sions.

Single Region Models

Several State-level models, which explained the economic and demographic growth of a single region, were presented. These models tended to ignore the interaction between regions, relating changes in a given region to changes in the national economy. Whilst these single- region models allow us to directly analyse the impact of national policy on the region, they tend to ignore spatial interaction and may not be particularly useful for regions where development does not closely mirror the national economy (see Taylor, 1982). These models attemp- ted to explain interrelationships between labour markets, product markets, housing markets, and population growth.

Joun & Conway (1982) relate national economic growth to in- creases in regional production, using an input-output framework. Subsequent increases in income, employment, consumption and reg- ional migration provide second-round effects upon output, residential construction, private investment and government expenditures. Leak- ages from the regional economy also occur via savings, taxes and imports. The labour market equations are specified such that regional employment and labour force participation rates tend towards the national average, a convenient control. The two-way feedbacks incor- porated in this model enhance its usefulness for policy simulation, although many of the linkages are poorly specified; for instance, the effect of population change on economic variables is generally incorpo- rated by estimating the variables in per capita terms.

Plaut’s model of Texas (Plaut, 1981 and 1982) also incorporates the effects of national economic growth upon that region, under the assumption that the relative attractiveness of Texas to people and to business will determine its long run growth via inducing migration and investment (in particular, manufacturing investment). Migration is a major determinant of population change and, therefore. of labour supply. Investment prompts changes in capital stocks and, via a CES

52 PAMELA WILLIAMS

production function, increases in labour demand and output in manu- facturing, whilst non-manufacturing production is determined sepa- rately. Labour supply and demand interact within the labour market to determine employment and income by industry and sector, with the major linking variables being the wage rate and the level of job availability. Variables then feed back into the relative attractiveness variable to determine second-round effects. The model fits tolerably well in sample and its strength in simulation lies in its relatively precise specification of the relationships between economic growth, invest- ment, capital accumulation and regional output. This supply-side ap- proach is particularly useful in modelling a region undergoing indus- trialization (compared with the demand-orientated approach stressing the role of government expenditures used by Joun & Conway for Washington (Conway, 1981)).

Greenberg & Renfro (1982) provide a demand-orientated ap- proach to modelling New York, using a model whose central core is the determination of personal income levels (via employment, wages, wage and salary income and non-wage personal income). As in Plaut, the national economy has its greatest impact on the manufacturing sector, although less emphasis is placed upon the role of investment and capital accumulation and industries have been divided according to whether they sell products in the national market (and are therefore dependent on national economic conditions) or are local in orientation (and therefore depend upon domestic demand). In Greenberg & Renfro, taxation and the financial sector have been extensively model- led, allowing for the analysis of the implications of policy changes in these areas. Population plays an important role in determining the growth of the government, services and transportation sectors and, indirectly via housing starts, and housing sector. The unemployment rate is used to link demand for, and supply of, labour (by comparison, Plaut uses a measure of job opportunities, the vacancy-to- unemployment ratio). Whilst this linkage is quoted as a strength of the model, the poor specification of the unemployment rate equation can lead to a negative unemployment rate in some simulations, so it may be acting to compound errors rather than increase simultaneity. Taylor (1982) provides several examples of such increases in interactive error with the introduction of partial and poorly specified simultaneity in regional models.

A further paper (Batey & Madden, 1982) presented a model of Merseyside, U.K., using an input-output framework which specifically incorporated demographic as well as economic variables. The relation- ship between these variables is predominantly captured via changes in employment levels. This approach has the advantage of enabling the identification of the main causal factors (economic, demographic or the interaction of both) of changes in the simulation scenario. However, as

REGIONAL ECONOMIC-DEMOGRAPHIC MODELLING AND PROJECTION 5 3

with all input-output frameworks, it is highly data intensive, does not face the problem of how to vary coefficients over time and does not have the flexibility of econometric methods.

Multi - regional Models

Multi-regional models attempt to allow for the feedback of the effects of economic and demographic change in each region upon every other region. Unfortunately such models are inherently data intensive, a factor which tends to limit their sophistication. Two such models were presented at the Conference; the ECESIS model (as documented in Beaumont et al., 1982; Isserman, 1982; and Plane & Rogerson, 1982) for the States of the U.S. was operational, whilst the model of Isard & Smith (1982), for the States of Australia, was not yet im- plemented.

ECESIS is an impressive attempt at multi-regional modelling, where care has been taken to ensure that results are consistent both within and between regions and are soundly based on economic and demographic theories. It employs a bottoms-up approach, where indi- vidual regions are modelled without reference to a national “control” model, although some national variables are used as exogenous input to the regional models. This zpproach has the disadvantage that the sum of the regional results may not necessarily be consistent with expected national results. The economic-demographic linkages in ECESIS accord well with theory; population change affects labour supply and the demand for output and changes in employment and unemployment will affect migration and, therefore, population change. These linkages occur both within and between regions.

The demographic sectors of the ECESIS regional models are specified such that consistency between flows and the resultant stocks at a relatively high level of disaggregation by age and sex of the demographic variables is achieved. Unfortunately, the demographic sector models only regional migration in terms of its economic deter- minants; attempts to model fertility were not successful. In the economic sector, each regional model was constrained to be as small as possible and a common structure was used for all regions. As far as possible, changes in one region are related to the changes in all other regions. Each region has three industries, manufacturing (which is modelled in greatest detail), non-manufacturing (which is modelled using a simple reduced-form employment equation), and farming (which is exogenous). Supply and demand factors interact in determin- ing manufacturing output, with increasing capacity utilization and rising costs providing a check on growth. Demand for manufacturing output is related to wage rates, income and a trade matrix, whilst supply is determined using a Cobb-Douglas production function and

54 PAMELA WILLIAMS

related factor demand equations (which incorporate partial adjust- ments to desired levels of factor inputs). The demand for labour derived in this manner is used in an identity with labour supply (which is derived from labour force participation rate equations) to determine the unemployment rate. Manufacturing wages are determined by vari- ables reflecting local labour market conditions, the industry’s ability to substitute for alternative factors, and a wage transmission variable, which allows all regions to have some impact upon a given region’s manufacturing wage. The non-manufacturing wage rate is a simple function of manufacturing wages and the regional unemployment rate. Incomes are then calculated from wages, proprietor’s income and transfer payments, where the latter is determined partly by population.

The simple specification of equations in ECESIS, necessitated by data constraints, can lead to the compounding of errors. For instance, the labour force participation rate equations perform poorly and the errors feed through to the unemployment rate, to wages and incomes, to the relative attractiveness of the region and then to migration. Given this, ECESIS may be more useful for carrying out empirical tests of the importance of economic-demographic linkages than for forecasting. In contrast, Isard & Smith (1982) presented a complex multi-regional model with theoretically more acceptable equation specifications. However, as this model is still at a very early stage of development, it is difficult to assess its worth. Certainly, as data become available and computing capabilities improve, models such as that suggested by Isard & Smith will become useful for policy simula- tion, if not forecasting.

4. Concluding Remarks

The forecasting of regional population change and its economic determinants and consequences is by no means a well-developed science or, for that matter, art. Theories and their empirical implemen- tations are often crude and much remains to be studied. Theoretically, the determinants of regional population change, especially regional migration, are not well understood. Micro level studies, as described by Caldwell (1982), are needed to improve our understanding of what induces people to move and what determines their choice of location. Such studies provide a focus for analysis and indicate the important aspects of migration phenomena which should be incorporated in economic-demographic models. Nor are the consequences of regional population change well understood. Further research is needed to determine relationships with employment and output, and also to spec* more clearly the adjustment mechanisms which take place. Migrants bring human, physical and financial capital and demand to a

REGIONAL ECONOMIC-DEMOGRAPHIC MODELLING AND PROECI'ION 5 5

region. They influence investment (via demands for infrastructure and housing) and prices and, through population growth, they may contri- bute to the achievement of economies of scale within a region. As such they can increase demand for labour, setting in motion further regional growth. These complex interrelationships require further study.

With a basis of underdeveloped theory and poor data, it is not surprising that empirical models of regional population change require much improvement. It is not clear that increasing the linkages between economic and demographic change will improve regional forecasting models if the data on which they are based are poor and limit the specification of the interrelationships. The use of aggregate variables may reduce data requirements, but it may also hide important relation- ships and reduce the usefulness of the projections. The disaggregation of such aggregate variables is not a trivial problem. Using national variables and disaggregating to the regional level also introduces problems. The specification of economicdemographic models must be continually improved as the theory underlying the relationships is developed. This does not necessarily imply that the models will be improved simply by the addition of more explanatory variables. Care- ful attention must be paid to developing specifications which protect models from providing ridiculous results. In situations where data are poor, it is not possible, as most Conferees have done, to rely solely on empiricism; where priors are suggested by theory (for example, the unemployment rate should lie between zero and unity), they should be incorporated directly into the specification.

The theory and techniques for forecasting regional population change and its economic determinants and consequences are changing rapidly. Those involved in these changes are optimistic that multi- regional economic-demographic modelling provides the most suitable forecasting methodology as well as providing a framework for analys- ing the nature and implications of economic and demographic change. Currently, however, such models provide at most an adjunct to more conventional methods of regional forecasting. Their current rate of improvement suggests that in time they will provide an alternative.

References

I n the following list ICFFWC Paper stands for: Paper presented to the International Conference on Forecasting Regional Population Change and its Economic Determinants and Consequences, Airlie House, Virginia, U.S.A.

ADAMS, F. G., BROOKING, C. G. & G u m , N. J. (1975). On the Specification and Simulation of a Regional Econometric Model: A Model of Mississippi. Review of Economics and Statistics 57, 286-298.

56 PAMELA WILLLAMS

AHLBURG, D. (1982). Forecasting Regional Births from National Birth Forecasts. ICFRPC Paper.

BATEY, P. W. J. & MADDEN, M. (1982). The Modeling of Demographic-Economic Change Within the Context of Regional Decline: Analytical Procedures and Empiri- cal Results. ICFRPC Paper.

BEAUMONT, P., IS-, A., MCMILLEN, D., PLANE, D. & ROGERSON, P. (1982). The ECESIS Economic-Demographic Interregional Model of the United States. ICFRPC Paper.

BECKER, G. S. (1960). An Economic Analysis of Fertility. NATIONAL BUREAU OF ECONOMIC RESEARCH. Demographic and Economic Change in Developed

Countries. Princeton University.Press, 209-240. BECKER, G. S. (1974). A Theory of Marriage. T. W. SCHULTZ (ed). Bonornics of the

Family. Chicago: University of Chicago Press, 299-344. BECKER, G. S . , LANDS, E. M. & MI-, R. T. (1977). An Economic Analysis of

Martial Instability. Journal of Political Economy 85 (6), 1141-1187. BILSBORROW, R. E. & AKJN, J. S . (1982). Data Availability Versus Data Needs for

Analyzing the Determinants and Consequences of Internal Migration: An Evalua- tion of U.S. Survey Data. ICFRPC Paper.

BLACK, M. (1982). Migration of Young Labour Force Entrants. ICFRF'C Paper. BROOKS, C., SAMS, D. & WILLIAMS, L. S. (1982). A n Economerric Model of Fertility,

Marriage, Divorce and Labour Force Participation for Australian Women, 1921/22 to 1975/76. IMPAm Preliminary Working Paper No. BP-29, University of Mel- bourne.

BUTZ, W. P. & WARD, M. P. (1979). The Emergence of Countercyclical U.S. Fertility. American Economic Reuiew 69, 318-328.

CALDWELL, S. B. (1982). Modeling Deomgraphic-Economic Interactions: Micro, Macro and Micro/Macro Strategies. ICFRPC Paper.

CONWAY, R. S. JR. (1981). Washington Projection and Simulation Model II. Seattle: Washington Department of Commerce and Economic Development.

EASTERLIN, R. A. (1973). Relative Economic Status and the American Fertility Swing. SHELDON, E. B. (ed.) Family Economic Behauiour: Problems and Prospects. Philadelphia: J. B. Lippincott, 170-233.

FIJKUCHI, T., CHvMn, M. & YWGUCXI, M. (1982). Interregional Economic- Demographic Model of the Tokyo Region. ICFRPC Paper.

GWNBERG, C. & -0, C. (1982). An Econometric-Demographic Model of New York State. ICFRPC Paper.

HERZOG, H. W. JR. & SCHLOTTMANN, A. M. (1982). Labour Force Mobility in the United States: The Migration Decision, R e - and Post-Move Unemployment, and Implications for Re-migration. ICFRfC Paper.

ISARD, W. & SMITH, C. (1982). Remarks on Procedures for Estimating Specific Linkages in an Integrated Multipolicy Multiregion Model. ICFRPC Paper.

Is-, A. M. (1982). Multiregional Demoecononic Modeling with Endogenously Determined Birth and Migration Rates: Theory and Prospects. ICFRPC Paper.

JOUN, R. Y. P. & CONWAY, R. S. JR. (1982). Regional Economic-Demographic Forecasting Models: A Case Study of the Washington and Hawaii Models. ICFRPC Paper.

KEELEY, M. C. (1979). An Analysis of the Age Pattern of First Marriage. International Economic Review 20(2), 527-544.

KEELEY, M. C. (1977). The Economics of Family Formation. Economic Inquiry 15, 238-250.

LANCASTER, K. J. (1966). A New Approach to Consumer Theory. Journal of Political Economy 74, 132-157.

LEDWT, J. (1982). The Migration Component in hlultiregional Economic-Demographic Forecasting Models Using Alonso's Theory of Movement. ICFRF'C Paper.

REGIONAL ECONOMIC-DEMOGRAPHIC MODELLING AND PROJEE<JI?ON 57

NORRIS, D. (1982). New Sources of Canadian Small Area Migration Data. ICFRPC

FLUE, D. A. & ROGERSON, P. A. (1982). Spatial Economic/Demographic Modeling of

b u r , T. R. (1981). An Econometric Model for Forecasting Regional Population

PLALT, T. R. (1982). Economic-Demographic Interactions in an Econometric Model of

REDWOOD, A. L. (1982). Forecasting Subnational Birth Rates. ICFRPC Paper. ROGERS, A. & WILLIAMS, P. J. (1982). A Framework for Multistate Demoeconomic

Modeling and Projection, with an Illustrative Application. ICFRPC Paper. ROSE", C. C. (1982). Labor Force Migration, Non-labor Force Migration and

Non-economic Reasons for Migration. ICFRPC Paper. TAYLOR, C. A. (1982). The Effects of Refining Demographic/Economic Interactions in

Regional Econometric Models. I G " C Paper. VAN DER VFEN, A. & EVERS, G. H. M. (1982). Labor Force Participation, Migration,

Commuting and the Regional Labor Market. A Simultaneous Approach. ICFRPC Paper.

WARNES, A. M. (1982). Longer Distance Migations in Older Ages: Some Implications for Local Population Projections. ICFRPC Paper.

WETROGAN, S. & ENGELS, R. (1982). Evaluation of Census and Administrative Data Sources for Migration Data. ICFRPC Paper.

Paper.

Interregional Migration with Limited Data. ICFRPC Paper.

Growth. International Regional Science Reuiew 6, 53-70.

Texas. ICFRPC Paper.