Observational Equivalence in the Modeling of ... - ScienceDirect.com

World Development, Vol. 21. No. 4.. pp. 535-554. Printed in Great Britain.

1993.

0305-750x/93 $6.00 + 0.00 @ 1993 Pergamon Press Ltd

Observational Equivalence in the Modeling African Labor Markets and Urbanization CHARLES

of

M. BECKER

University of Colorado,

Boulder

and ANDREW Tulane

University,

R. MORRISON” New Orleans,

Louisiana

Summary. -

This article examines the appropriateness of neoclassical and rent-seeking models of urbanization for the African milieu and demonstrates that the reduced forms of these two models may be quite similar. The models are not observationally equivalent, however, and methods of distinguishing between them are discussed. A demographic cohort shift model of African urbanization also is presented. Its excellent predictive power suggests that migration migration models) ignore models that assume migrant homogeneity (i.e., highly aggregate information that can be useful in predicting trends in migration flows.

There is, however, also a broader purpose which transcends the African continent: to demonstrate that the estimating equations for several classes of urbanization models are quite similar. Thus, results which “confirm” the validity of one model often equally well confirm the validity of a competing model. Stated differently, many “tests” test very little, as the hypotheses they reject or fail to reject are often consistent with a very diverse set of underlying models. This problem is especially severe in macro models of developing countries (and especially for a datapoor region such as Africa), as estimable reduced forms are often but caricatures of complete, structural models. Some authors (alas, including us) have conducted tests of one of these urbanization models - typically the neoclassical model - implicitly confident that they are testing only its appropriateness. As is demonstrated below, however, “correct” results from a neoclassical formulation are generally consistent with an underlying rentseeking structure, or an explanation based on shifting demographic patterns. By carefully examining the estimating equations of the various types of models, this paper derives estimating equations that allow the competing paradigms to be distinguished from one another. This is an especially important exercise, since there is little

1. INTRODUCTION Neoclassical modeling strategies frequently have been used to explain internal migration patterns in less-developed countries (LDCs) at an aggregate level, but alternative models of urbanization are also available - rent-seeking and demographic cohort shift models are two such alternative modeling strategies. This paper presents the assumptions and theoretical underpinnings of simplified reduced forms of these three models, and provides empirical tests of their applicability to sub-Saharan Africa. In some sense, then, this paper is a test of which of these models best fits African reality. The topic is one of more than academic interest. Africa’s urban population has been growing at an annual rate of 6% or more in recent decades. The problems associated with rapid urbanization are particularly apparent in light of the continent’s economic crisis, and in the associated collapse of governments’ abilities to provide even the most basic public services. Nor is there clear evidence of a deceleration in the urbanization process even given deteriorating public sectors. Given the importance of urbanization to policy makers, then, it is also critical to understand which model (or models) offer the best explanations for past urbanization experience, and which can be used to best predict the future.

*Final revision accepted: 535

April 20, 1992.

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evidence that urban labor markets are well approximated by the paradigm of perfect competition.’ On the other hand, neoclassical models of migration and urbanization have performed remarkably well, perhaps due to strong multicollinearity between some demographic variables and economic variables. This multicollinearity may result in upwardly biased (in absolute values) coefficients for economic variables in reduced-form migration equations which do not contain these demographic variables.

2. MODELING URBANIZATION: THEORETICAL MODELS

THREE

The salient characteristic of neoclassical urbanization models is that production and demand conditions are carefully specified. While individuals migrate in search of higher wages in destination areas, the conditions which generate observed employment and wages are carefully delineated. These models can be modified to incorporate informal and service sector employment in urban areas, various assumptions about worker and job characteristics, and even foreign exchange constraints.’ The Harris-Todaro model with a sticky urban formal sector wage can be embedded in a neoclassical model to allow for open unemployment in urban areas. In short, many general equilibrium complexities can be added to this partial equilibrium model, although the possibility of estimating single-equation reduced forms quickly disappears. These complexities lead to migration models that are much too sophisticated to be estimated with the limited, highly aggregated data which are available, but in most cases the neoclassical spirit - in which agents make locational choices in order to maximize a constrained objective function - remains (see Stark. 1991). The second type of urbanization model, the rent-seeking model, is similar to the neoclassical model in the number and kind of economic sectors included in the analysis, but it adds the institutional detail of rent-seeking behavior by urban workers. Modern sector workers are assumed to be paid a wage above the opportunity cost of labor in rural areas, but the modern wage is not institutionally fixed. Instead, it varies with labor’s ability to capture firms’ economic rents. The type of labor behavior predicted by this model is clear: because workers are being paid more than the value of their marginal product, they fiercely oppose efforts to reduce employment and prefer to accept wage declines when firm profitability falls. The third type of migration model that will be

surveyed in this paper is a demographic cohort shift model. Ironically, while cohort structure has long received the attention of demographers and economic historians.’ it generally has not been considered by specialists in economic development or urban economics. The demographic cohort shift framework is constructed to highlight the key role that increasing education levels and declining mortality rates have played in Africa’s urban explosion. Since it is a stylized fact of the migration literature that younger and more highly educated individuals are more likely to migrate than older and less well-educated individuals, the broadening in the base of the age pyramid and increasing education levels characteristic of African countries during the lY5Os, 1960s and 1970s increased, with some lag, the number of individuals who were prime candidates to migrate to urban areas.” The use of a demographic cohort shift model permits estimation of the effects on urbanization of this larger cohort of migration-prone individuals. Equally important, it allows us to predict the effects of economic crisis - as reflected in falling educational levels and rising mortality rates on urbanization in coming years.’ Section 3 turns to a more detailed presentation of a neoclassical migration and urbanization model. Section 4 then develops a formal model of rent-seeking behavior in urban labor markets, discusses the issue of observational equivalence, and suggests modeling and estimating strategies which will avoid this pitfall. Finally, section 5 presents a demographic cohort shift model, examines the importance of cohort shift in Kenya since 1960. and returns to the theme of observational equivalence.

3. A NEOCLASSICAL MODEL OF URBANIZATION FOR SUB-SAHARAN AFRICA (a) The model and its empirical results Becker and Morrison (lY88a) developed a neoclassical model of urbanization for the African milieu, and provided a detailed discussion of the restrictions that must be imposed to obtain a reduced form estimating equation. The model, by specifying production (and hence labor demand) conditions in three economic sectors, integrates the “push” and “pull” factors that simpler migration models (e.g., gravity models) treat as separable.h The logic of the standard neoclassical model is straightforward. Two types of firms - modern and traditional - produce output in urban areas.

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Output in the urban modern sector is produced using inputs from the urban traditional sector and from abroad, as well as capital and labor. Labor inputs are modeled as being available at a fixed minimum wage, reflecting the ubiquitous presence of minimum wage legislation in African modern sectors.7 From this production function, modern sector labor demand can be derived using standard constrained maximization techniques. Similarly, urban traditional labor demand can be derived from that sector’s production function, which uses only labor and capital. The lack of imported inputs to production in this sector captures the stylized fact that traditional firms generally have limited access to foreign exchange or formal credit institutions which would permit them to purchase imported capital or intermediate goods. The next step in constructing the neoclassical model of urbanization is to specify production conditions in rural areas. and then derive rural labor demand from this production function. The model’s rural economy is quite simple, largely due to data restrictions. Our specification follows Hansen’s (1979) stylized model for an African economy characterized by scarce high-quality but copious “marginal” land. If this is the case, the marginal product of peasant land is zero, and labor’s average and marginal products are identical. In principle, rural output will depend on several factor inputs, including capital, labor, and intermediate goods such as fertilizer and pesticides. Since data for nonlabor inputs are unavailable, these factors are lumped into the technology term. Rural labor demand is then derived from this simple productive structure. Labor demand in all three productive sectors added to unemployment in urban areas to yield a national labor force identity (zero unemployment is assumed in rural areas). Finally, a HarrisTodaro closure is imposed on the model: migration to urban areas is a function of the difference between the agricultural wage and the expected urban wage, where the expected wage depends on the level of the urban modern sector minimum wage, the unemployment rate, and the wage in the urban traditional sector. If free entry is assumed into the urban traditional sector, there will be no unemployment in this sector. Further, zero migration equilibrium requires that the urban traditional sector wage be equal to the rural wage. Once the national labor force is derived and expressed in terms of exogenous variables, it is straightforward to obtain the reduced form estimating equation for urbanization. Given a fixed (in the short run) national labor force, urban labor force growth is simply the mirror image

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(with opposite sign) of rural labor force change; both depend on variables that affect the relative attractiveness of urban and rural locations. The reduced form equation for urbanization contains the minimum wage, the domestic price (thus including the effects of tariffs and quantitative restrictions) of imported intermediate and capital goods, gross domestic product, government expenditure, traditional and modern sector capital stocks, the price of rural output, and the rate of technological change in the rural sector (see equation 13 in Appendix A). All variables are expressed as growth rates. When this neoclassical model is tested against a crosscountry sample of sub-Saharan African nations for 1970430, it does a reasonably good job of identifying probable causes of Africa’s recent urbanization experience.x Table 1 presents a summary of the effects of key variables in the neoclassical model of urbanization. Factors determining the demand for urban modern output consistently are found to be important determinants of urban population growth. GDP contributes strongly to urbanization, supporting the hypothesis of an “urbanizing bias” in the demand structure: as incomes increase, a larger share of income is spent on urban modern goods. Estimates suggest that a doubling of GDP growth rates would elicit a 1421% increase in the urban growth rate. Government expenditures, while not as important as GDP, do play a role in urbanization. The small estimated coefficients, however, indicate that government spending has not been a direct, major cause of Africa’s rapid urban growth. It is important to note that this result refers to the average impact of government spending, and particular types of spending may have far more potent impacts. The price of imported products is the only demand-side variable not found to be a determinant of urbanization. This is not surprising, given that an increase in the price of imported products has two conflicting effects. The first effect is import substitution: demand for now relatively less expensive domestic products increases. At the same time, however, the increase in the price of imports raises the cost of production to modern-sector urban firms that use imported inputs, thus depressing modern sector output and labor demand. Increases in the rate of capital accumulation in the urban modern sector also spur urbanization by increasing the productivity of labor and hence stimulating labor demand. The size of this effect is quite small, perhaps due to empirical problems in the measurement of urban investment, but also possibly reflecting a tenuous link between

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Table Independent variable” Constant “%AGDP % AGOVEXP %AK,, “%ALFPR URBL ‘%ACAL

I. Ordinary

Least Squares (OLS)

(1H 0.0225 (1.134)yj 0.1662$ (1.5X2) 0.0223 (1.058) 0.0061$ (1.718) 0.37281 ( 1.485) -0.0123 (-0.303) -9.4729% (-1.373)

(2)10.016X (1.058) 0.1854~~ (1.877) O.O273!i (1.486) 0.0058~ (1.661) 0.33931 (1.421)

-0.601X*’ (-2.178)

DEVELOPMENT Estimates of Urban Populalion

(3)-i0.0085 (0.560)

0.2155*‘(2.173) 0.03x7** (2.269) O.OOS3~ (1.494)

(4)? 0.023 14-2 3 (1.432) 0.13881 (1.399) 0.0362/j (1.96.5)

Grow!h

(5)i

(h)t

0.0153

0.0204 (0.X50) O.lX31# (1.562) 0.0240 (O.XY6) O.OOhl~ ( 1.442) 0.3433 (0.889) -0.007Y (-0.158) -0.5683# (-1.354) 0.0065 (0.224) -0.0003 (-0.01) 0.0030~ (1.711)

(1.018)

O.lXlJil (1 .X52) 0.0451 (2.63X)

*

0.3026 (1.215)

-0.5305*” ( - 1.899)

-0.4869~~ (- 1.737)

-0.4561% (- 1.606)

‘%AK, ‘%AP*, SIZE

0.0030/1 (2.007)

0.0330** (2.364)

0.003x** (2.789)

0.0033** (2.27)

0.0037~ ’ (2.60)

F R? R’

2.957** 0.564 0.373 0.0107 24

3.573*0.55x 0.402 0.0104 24

3.675** 0.505 0.368 0.0107 24

3.403** 0.486 0.343 0.0109 24

3.662 0.435 0.316 0.01 12 24

SEE No. obs

Rurrs Erpuriorr

1.YX4 0.561 0.27x 0.01 1s 24

(7)$ 0.0014 (-0.064) 0.21431 ( 1.562) -0.0012 (-0.054) 0.0058 (0.9X0)

- 0.9026.~ (-2.1X3)

0.0056*‘ (2.614) .3 164 +* 0.513 0.35 1 0.0141 21

*‘%AGDP = annual growth rate of GDP: %AGOVEXP = annual growth rate of government expenditures; %, AK,, = annual growth rate of urban modern-sector capital stock; %ALFPR = annual growth rate of labor force participation rate; URBL = percentage of population living in urban areas (1970); “/“ACAL = annual growth rate of percentage of minimum caloric intake received; %AK, = annual growth rate of urban intermediate sector capital stock: %AP*, = annual growth rate of “full price” of imports; SIZE = natural logarithm of habitable land area. iDependent variable: annual urban population growth rates, 197&X0. iDependent variable: annual growth rate of nation’s largest city, 197&X0. iistatistically significant at 20% level. JJStatistically significant at 10% level. **Statistically significant at 5% level. It-statistics are in parentheses.

capital formation and employment growth in urban Africa. Nor does capital accumulation in the urban traditional sector appear to increase urban growth rates, although measurement problems again may well account for this result. The most potent determinant of African urbanization in the neoclassical model is the rate of change in per capita caloric intake, our proxy for the change in rural real incomes. The estimates suggest that a 1% increase in the rate of caloric intake growth will lead to a 0.5% decrease in the urban growth rate. Thus, if a country such as Chad experienced a rise in caloric intake, to take an extreme example, to the Congo’s level (roughly a 53% increase in 1986), Chad’s urban popula-

tion growth rate would be expected to decline by over 25%. Thus, the neoclassical urbanization model supports the policy prescription of rural development to stem rural-urban migration. In a separate regression employing the growth rate of a nation’s largest city as the dependent variable, the dampening effect on urbanization of improvements in caloric intake was even stronger, almost reaching 1: 1.

(b) But is African

reality neoclassical?

For those who believe the proof of an economic model resides in its power of prediction (or in

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the case, replication), the neoclassical model is quite acceptable. Yet parts of the neoclassical model may not accurately describe African reality. If a model of urbanization is required not only to predict well, but must also accurately describe economic and social structures, alternative models may need to be devised. One criticism of the neoclassical urbanization model is that it suffers from aggregation bias. Labor is treated as completely homogeneous, and distinctions between workers of different age, skill and education classes are ignored. Thus, any change in the composition of the population at risk to migrate with respect to these characteristics can change the magnitude of migration flows. The neoclassical migration model, by focusing on a “typical” individual, misses these important effects. More precisely, aggregation becomes a problem if: (i) different groups have different propensities to migrate, and (ii) the relative weights of these groups in total population change over time. An aggregation bias also emerges if the weight changes are correlated with economic variables in the neoclassical model. The aggregation bias inherent in both neoclassical and rent-seeking models is the principal motivation for a demographic cohort shift model of migration presented in section 6. A second contestable assumption of the neoclassical model is that urban firms minimize costs. Since the model’s labor demand equations are derived under the assumption of costminimizing behavior, noncost minimizing behavior by managers or entrepreneurs makes neoclassical factor demand functions difficult to defend. While some alternative managerial strategies are effectively equivalent to cost minimization, or are at least highly correlated with it, hardly all alternatives imply cost minimization especially if government-induced distortions are acknowledged. In fact, there has been significant discussion in the economic development literature about whether the private modern sector in African countries attempts to maximize profits or even minimize costs (to our knowledge, no one has argued either case for African public sectors). The consensus has been that, especially in the manufacturing sector, tariff protection has fostered a legacy of high cost, low-quality production. If entrepreneurs (usually a misnomer, since the term implies a willingness to take risks, and producers protected by high tariff barriers may be content to “satisfize” profits rather than assume risk) can sell their output at cost without fear of price competition from foreign producers, rational firms will not behave as a price-taking competitor; cost minimization also disappears if

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managers expect tariff protection to be varied inversely with the firm’s efficiency. If costs are not minimized for a given level of output, profit clearly cannot be maximized. There is ample evidence of protectionism across Africa. While comparable crosscountry estimates of effective rates of protection are not available for the sub-Saharan countries, indirect evidence of protectionism is given by the large share of government revenues that is generated by import duties. The average share for all subSaharan countries was over 26% in 1986. The Gambia, Lesotho, Sudan and Swaziland all raised over 50% of government revenues through import taxation. Large countries tend to have lower percentages, but a considerable number of countries obtain over 40% of revenues from import duties.’ Noting that a very high proportion of African modern sector firms operate as domestic monopolies or near-monopolies, and demonstrating that high tariff barriers exist are not conclusive evidence that entrepreneurs do not minimize costs, such data are nonetheless suggestive. If private firms do not minimize costs, what then of publicly owned firms? Clearly this in an important issue given the large contribution of public enterprises to GDP. Although data are not available for a complete cross-section of African countries, the partial data that exist highlight the key role public enterprises play. For reporting countries, the smallest share of GDP generated by public enterprises in 1986 was 4.5% in the Central African Republic; even this percentage is considerable. Almost 15% of Nigeria’s GDP was produced by public enterprises. The highest percentage reported for 1986 was Sudan, ublic enterprises accounted for 47.5% of where R GDP. ’ Determining conclusively whether these enterprises minimixe costs is difficult, given existing data. If one excludes short-run adverse supply or demand shocks, persistent losses are evidence that public enterprises are pursuing some objective other than cost minimization, and that their budget constraints are “soft” in the sense that central governments can be relied on to bail out consistent loss-makers. For 1985-86, the public enterprises of six of 11 reporting countries posted net losses for both years.” These countries were The Gambia, Malawi, Senegal, Ivory Coast and Mauritius. While in typical countries such as Senegal structural adjustment programs have caused aggregate demand to contract, and the consequent reduced demand for public enterprises’ output can be blamed for their financial losses, Senegalese public enterprises have reported losses for all years (1982-86) for which

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data are available. Short-term adjustments cannot be the entire or even a significant explanation peristent for African public enterprises’ losses. Another legitimate excuse for short-run losses is a fall in the international price or export volume of an important export marketed by a public enterprise. This could be the case, for example, in The Gambia, where the volume of groundnut exports fell an average of 3% a year during lY8(&85 before rising 5.2% in 1986.” But real farm gate ground nut prices fell in both 1985 and 1986.13 Public sector enterprises in The Gambia reported losses for every year during 1981-86. and this period contains years of increasing and decreasing export volumes. as well increasing and decreasing farm gate as prices. While consistent financial losses cast doubt on the cost-minimizing hypothesis, financial profits do not necessarily confirm it. Public enterprises in Sierra Leone, Somalia, Zaire, the Congo and Nigeria reported profits during 1985-86. Enterprises in these countries may make profits despite not minimizing costs, due to a privileged position in the domestic market or control of an export for which world demand is relatively price inelastic. Not surprisingly, the countries with profitable public enterprises are mostly mineral exporters with heavy parastatal representation in those industries. To summarize, African modern sectors are heavily influenced and often dominated by public enterprises. Typically. half of all modern sector employment is accounted for by the public sector. ” Public firms are often charged with many social objectives in addition to the goal of earning profits. Parastatal managers are rarely rewarded for extraordinary financial results or penalized for unjustifiable losses. In fact, though, managerial autonomy is also severely limited.” The result appears to be a situation in which much of the modern sector is at best slowly responsive to market forces. Noncost-minimizing behavior may have important implications for labor market behavior and, consequently for migration modeling. If public enterprises do not face a hard budget constraint and are permitted to run recurrent deficits, workers’ wage demands are unlikely to meet stiff resistance from management. Workers may be quite successful in obtaining a share of public sector rents, and the possibility of obtaining rents in the urban modern sector may be a powerful lure to potential migrants. This possibility motivates the development of a rent-seeking model of migration.

4. A RENT-SEEKING MODEL AFRICAN URBANIZATION (a) The stylized facts of rent-seeking Suhuran

OF

in sub-

Africa

Any model purporting to describe Africa’s modern sector must explain why employment has remained remarkably stable (and typically grown slightly) in the face of continuing economic decline. Labor productivity (measured as output per worker) and real wages in the modern sector have fallen in many African countries between the mid-lY7Os and the-mid 198Os, yet employment has continued to grow in most countries (Table 2). In fact, during lY7S-1985, modern sector employment declined in only three of the 24 countries for which data are available: Ghana, The Gambia, and the Central African Republic. In contrast, nine experienced declining manufacturing labor productivity during the period. The largest declines were registered in Ghana, Somalia and Botswana, where the average product per worker fell at the astounding annual rates of 9.4, 7.X and 6.8X.‘” On the other hand, impressive productivity gains of 13.2, 12.1 and 9.6% per year were recorded in Togo, Cameroon and Lesotho, respectively. Employment growth rates for the countries with impressive productivity growth (an unweighted average annual employment growth rate of 1.6%) differ significantly from those from countries with productivity declines (with an unweighted average annual employment growth rates of 5.3X), but in a perhaps unexpected direction. Generally speaking, though with significant exceptions, countries with rapid productivity improvement had slower employment growth. Why did employment not expand if workers were becoming more productive? The simple answer is that this question almost certainly has the causality reversed. These countries had more rapid productivity growth because they were shedding redundant labor more quickly than other African nations. ” Neoclassical labor market models suggest that employment and productivity should be positively related if expansions in employment are the result of increasing labor demand. Since labor demand is a derived demand (i.e., it depends on the level of desired production), and since modern sector output was largely stagnant during this period, the negative relationship between employment and productivity should not be surprising, even within a neoclassical framework. The obvious neoclassical hypothesis is that the negative relationship between productivity and employment is caused by supply shifts. In other

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Table

2. African

Country

Year

Empl

Benin Botswana Burkina Faso Burundi Cameroon CAR CBte d’Ivoire Ethiopia Gambia Ghana Kenya Lesotho Madagascar Malawi Mali Mauritius Nigeria Senegal Somalia Swaziland Tanzania Togo Zambia Zimbabwe

1974 1974 1974 1974 1974 1974 1974 1974 1975 1974 1974 1974 1974 1974 1974 1974 1974 1974 1974 1973 1974 1974 1974 1974

95 60 92 72 84 235 64 75 164 92 75 97 114 66 56 64 43 69 71 60 69 93 92 92

unweighted Source:

LABOR

manufacturing Real earnings /Empl 102 85 56 190 69 61 106 152 45 363 117 68 103 103 161 91 91 134 170 94 175 135 93

MARKETS employment,

Real output /Empl 96 137 84 97 61 77 76

75

184 70 55 X7 121 90 157 79 133 166 132 45 124 99

Year 1985 1984 1985 1983 1985 1985 1982 1985 1985 1983 1985 1985 1984 1983 1981 1985 1983 1985 1985 1983 1985 1982 1985 1985

Bank.

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earnings and output growth (1980 = 100)

Empl 124 177 107 139 111 176 94 11x 108 74 123 105 122 92 98 134 75 114 150 105 107 104 107 103

Real earnings /Empl 81 107 133 197 103 105 79 137 4X 76 161 62 105 9X 112 X6 101 69 95 45 95 142

Real output /Empl 134 6X 106 135 215 80 92 113 76 90 151 56 92 126 104 112 102 6X 74 121 103 113

Annual growth rates Ern out Emp 2.S’Y” 11.4 -0.5% 1.4 6.1 7.6 -3.9 2.6 10.0 -2.6 4.9 4.9 -0.1 4.2 -.5.X -4.1 11.8 -2.4 -20.1 4.6 -3.8 0.7 x.2 0.7 -4.9 3.X 0.2 x.3 -6.X 6.9 1.9 6.4 -0.6 4.7 -2.5 7.0 -f9 5.8 0. I 4.1 -11.6 1.4 1.4 -3.1 1.0 3.9 3.4

averages

World

AND

World Tables 1988-W

- 1.2

3.1% -6.8 2.1 3.7 12.1 0.3 2.4 3.x -9.4 2.3 9.6 -4.3 -3.0 4.9 -3.7 4.0 -2.4 -7.X -5.1 13.2 - 1.7 1.2 0.8

(1989).

words, the arrival of more workers to urban areas increased the supply of labor to the urban modern sector, simultaneously increasing employment and (if the marginal product of labor diminishes, as is conventionally assumed) lowering average productivity. If this neoclassical scenario is accurate, wages in the urban modern sector should be driven down by the increased labor supply, and wages and productivity should fall in tandem. Indeed, the countries with the three largest productivity declines between the mid-1970s and the mid1980s all had falling wages (Table 2). Overall, of the nine countries with productivity declines, seven had falling wages. But six countries (Burundi, Ivory Coast, Ethiopia, Kenya, Mali and Nigeria) had falling wages without productivity declines. This could be explained by a decrease in labor demand, were it not for the fact that employment increased all these countries. The neoclassical paradigm is simply unable to explain the observed movements in wages, productivity and employment in many African countries without recourse to complex and untestable hypotheses (for example, regarding the nature of

technological change). This is particularly true for countries such as Ethiopia, Ghana, Kenya, Mali, Madagascar, Somalia, Tanzania and Zambia, which experienced average annual declines in earnings per manufacturing worker in excess of 3%. Neoclassical manufacturing labor supply curves are linked to productivity in other sectors, and there is nothing to suggest rural declines in most of these countries of a magnitude that would give rise to these sorts of supply shifts.‘” An alternative model is needed. One interpretation of these data is that African unskilled and semi-skilled modern sector workers are able - at least during some periods - to obtain a wage above their opportunity cost. This wage is obviously not institutionally fixed (note the declines in wages in Table 2), but rather varies with labor’s ability to capture rents. This paradigm is known as the rent-seeking model.” Because it receives a noncompetitive wage, modern sector labor fiercely combats efforts to reduce employment; labor has a weaker motive to increase employment, although the presence of extended families with amply underemployed labor in African cities means that already-

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employed workers are likely to have at least a general interest in further employment expansion. Furthermore, the intensity of lobbying for higher wages and creation of additional modern sector jobs is plausibly related to the size of the economic rent generated by an enterprise.2” Consequently, modern sector managers face something closer to a quantity rather than a wage constraint, and there is little employment fluctuation even in severe economic downturns.

(b) The model and its empirical results The focus in this section is on the development of a rent-seeking model of migration and urbanization.2’ The heart of the rent-seeking model is the assumption that workers are able to capture a share of modern sector value added greater than the share they would obtain as competitive price takers. In other words, workers capture a share of modern sector firms’ economic profits. If, for example, domestic prices of imported intermediate goods fall or if the value of gross output increases. potential rents and hence labor earnings also will rise. The share of value added going to labor can be treated either as a societally or culturally determined (and hence exogenous) parameter, or it can be endogenized. The latter option is pursued in this paper. As discussed above, a stylized fact of African labor markets is that modern sector employment has not fallen significantly, despite an extended period of economic crisis. Labor’s share in modern sector value added, in contrast, has not been nearly as stable: the share seems to fluctuate procyclically in most African countries. In particular, we hypothesize that for the modern sector in aggregate, labor’s ability to raise its share of value added depends on forces related to labor market pressures and factor and product market structure. Two such determinants are government’s size (i.e., the value of publicly produced goods and services relative to private production) and government’s capacity to pay higher wages. These are important variables because of the large role of parastatals in Africa, and because government enterprises face particularly soft budget constraints and are particularly susceptible to political pressure. A second important determinant of labor’s ability to extract rents is the country’s capacity to import food, other key consumption goods, and intermediates used to produce these goods domestically. As long as foreign exchange is available to finance cheap food and consumer goods imports, labor’s share demands will be

moderated; if the prices of these key goods begin to rise, however, labor will demand compensating increases in its share of value added in order to maintain real wages at their previous level. Capital account conditions may also affect the ability to extract rents. Capital as well as current - account conditions may affect labor’s ability to extract rents; capital inflows in the form of expanded foreign credit (and hence import capacity) loosen the government budget constraint, thereby inviting pressure by the bureaucracy and organized labor for higher real wages. Related to the above factors is the availability of rents to be extracted. One would expect formal sector labor to press for tariffs and other measures that create rents by raising domestic prices relative to world prices (i.e., support of import-substituting manufacturing). In addition, some sectors (notably mining in the African context) have “true” rents to be extracted even when output is valued at world prices. The fifth determinant of labor’s income share is the level of unemployment. Higher unemployment should discourage labor from pressuring for increases in its share of value added, since workers may fear being fired or laid off as a result of aggressive bargaining. It is clear that a nation’s general ideological and trade orientation, plus the political position of the planning and labor ministries also matter. Finally, an important determinant of interfirm or interindustry differences in labor’s share is the elasticity of the demand curve a firm or industry faces. The more inelastic the demand curve, the better able is the firm or the industry to pass along higher labor costs. Conversely, firms in competitive industries must behave as price takers, and hence cannot pass on wage increases. As in the neoclassical model described in section 3, the rent-seeking model divides the stereotypical African economy into three distinct productive sectors. Production in the urban modern sector is assumed to use labor, capital, inputs from the traditional sector, and imported intermediates. But because of rent-seeking behavior by labor, factor demands are no longer as simple as those resulting from the neoclassical framework of the preceding section. In particular, firms take into account the additional costs of training a new hire, and the labor “discipline” effect, i.e., that creating an additional position will affect the unemployment rate (the direction of the effect is uncertain a priori and will depend on the elasticity of migration response), which in turn will affect labor’s ability to extract rents (see equation 4a of Appendix B). Nor are the demands for other factors of production unaffected by rent-seeking behavior.

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The use of more inputs from the urban traditional sector lowers the amount of rents available for labor to extract (this is the effect rcr in equation 4b of Appendix B), and firms will consequently use more of this input than they would in a neoclassical world. The demand for imported intermediates is similarly affected, but the above-mentioned trade balance effect (increased domestic price of imported goods met by demands for a higher labor share) is also relevant. Thus, the net effect on demand for imported intermediates of the introduction of rent-seeking behavior into the model is uncertain. The strategy for solving the rent-seeking model is the same as in the neoclassical model. Production and labor demand conditions in the urban traditional and rural sectors are specified, a national labor force identity is employed to derive a measure of the urban population, and a Harris-Todaro expected wage equilibrium condition is used to close the model. The reduced form equation derived from this model contains the domestic price of imported intermediate and capital goods, gross domestic product, government expenditure, traditional and modern sector capital stock, the price of rural output, the rate of technological change in the rural sector, and the labor share term, if it is treated as exogenous (see equation 5 of Appendix B).” All variables are expressed as growth rates. Several econometric problems were encountered in estimating the rent-seeking model. The price of rural output was dropped from the estimating equation because of lack of data.*s Another problem is that the sample of countries used to estimate the rent-seeking model is smaller than the sample used for the neoclassical model: 22 versus 27, to be exact. The smaller sample size occurs because data on wages as a share of manufacturing value added are not available for five of the countries (Chad, Liberia, Mauritania, Uganda and Zaire) that were included in the neoclassical analysis. The loss in degrees of freedom in estimation may cause the insignificance of some coefficients, while other coefficients may take different values because the small sample has different characteristics than the larger one. The results from the full rent-seeking model are reported in Table 3. Unlike in the neoclassical model, demand-side variables are not very significant. GDP is a statistically significant determinant of urban growth in only one of the specifications (and only marginally significant at that), and government current expenditure is never an important factor. A change in the average rate of tariff protection on net neither

AND

URBANIZATION

543

stimulates urban growth (via increased production of import substitutes) or decreases urbanization (via an increase in the cost of imported intermediate and capital goods) when urban population growth rate is used as the dependent variable. When employment in manufacturing is the dependent variable, however, an increase in tariff rates is found to lead to a decrease in manufacturing employment. This suggests that while manufacturing employment is affected by tariff policy, the link between manufacturing employment losses and a slowdown in urban growth is sufficiently weak that tariffs have no direct effect on urban population growth. This result is supported by two-stage least squares results (reported elsewhere) that show only a weak link between urban modern sector growth and urbanization.24 The only consistently significant neoclassical determinant of urbanization is modern sector investment, and it has differing effects depending on the dependent variables used. With urban population growth as the dependent variable, an increase in government capital expenditures stimulates urban growth. When manufacturing employment is used as the dependent variable, however, government capital expenditures reduce modern sector employment. A possible explanation for these seemingly contradictory results is straightforward: given the large role that parastatals play in modern sector production, increased capital expenditures by governments often induce (to the extent possible) substitution of capital for labor. To the extent that government capital expenditure improves general urban infrastructure, however, this will serve to attract more migrants to urban areas and increase urban population. The rural wage, measured by per capita caloric intake, is not an important determinant of urbanization. This contrasts sharply with the result in the neoclassical model, where the rural wage was the most potent determinant of urbanization rates. In sum, the neoclassical “portion” of the rent-seeking model does not perform very well. In the empirical estimation of the neoclassical and rent-seeking models, only one variable distinguishes between the two: labor’s share in value added, our measure of the labor share parameter (see Appendices A and B). This comparison of the reduced form estimating equations is sobering; the two models are close to being observationally equivalent. The crux of the observational equivalence problem is that first, the data do not permit estimation of different structural models and, second, reduced form results seemingly supportive of the neoclassical

544

WORLD

Independent variable*

Equation

Constant GNP Govcrnmcnt current cxpcnditures Government capital expenditures Average rate of protection

(lH

(2)t

-0.01 (O.l3)r/ 0.0 (0.46) 0.01 (Oslh) 0.34j/ (1.73) -0.12

-0.06 (0.70) 0.55~~ (1.52) -0.15 (0.X2) 0.33* (2.03) -0.15

(0.80) Import

price

Per capita

DEVELOPMENT

caloric

intake

Labor’s avcragc share in MVA Labor’s average share in MVA (stock)

054 (0.6’)) -0.20 (0.35) 0.09 (0.69)

O.Ohii (11.46)

(1.06) I .Ol (l-2.5) 0.09 (0.11) -0.07 (0.72)

O.YY 0.33 0.0

(S):]:

0.07

(1. IO) 0.0 I (0.80) -0.0’) (0.6’)) -0.26. (1.7’)) -0.23 (2.07) -0.16 (0.20) 0.30 (0.47) -0.21 (2.0X)

-0.01 (1.17) 0.66 0.25 -0. I3

F R? R’

(3) 0 implies 11 > -1. Since n is the inverse of the price elasticity of demand, r( > 0 implies that the long-run demand for UM goods is price elastic. This is not obvious, but neither is it too unreasonable given the competition from imports and small-scale producers. If urban traditional sector production can be represented by the Cobb-Douglas technology:

W,=-...--=

PRQR LR

PR4R(LK)~ (I’ to

(A7)

where W, = rural wage. L, = rural employment, and QH = rural output. If free entry is assumed into the urban traditional sector, there will be no unemployment in this sector. Further, zero migration equilibrium requires that W, = WR. If n is defined to be the probability of obtaining a c/M sector job, labor market equilibrium requires nw,,,,, = W,. We follow Harris and Todaro (1970) in assuming that n is a function of the ratio of currently unemployed to currently employed workers:

AFRICAN

LABOR

MARKETS

u ,071 8 @

n=

(As)

To solve the model and reduce it to an estimable form, the labor force “adding-up” constraint is needed: L = LW,, f fJW,, + LTn+ L, where i. the exogeneously Finally, we cl[(L,)] takes q(L,)

= A,L;

Collecting

AND

Although (Al 1) cannot be solved analytically for LR. it can be differentiated to solve for dLH. Urban labor force growth is then obtained residually:

dL”KHn,v = di

h< 0

Hansen’s assumption of abundant marginal land (b = 0) allows a single equation solution for (All). Letting primes denote percentage changes and defining cij to be the elasticity of i with respect to j and hR to be the share of group k in the urban labor force:

(AIf.

terms yields a single equation

solution

for

(All)

Lo’

=

The estimation of this equation reported in Table I.

APPENDIX B: THE DERIVATION THE RENT-SEEKING MODEL Production and output demand conditions in the rent-seeking model are identical to those in the neoclassical model (see Appendix A, equations Al and A2). but labor demand is not. Labor demand is no longer found by simple constrained maximization. In particular, we model the rent-seeking behavior of labor as follows:

f’f,W,m - P,T,,J.

PI)

Equation (Bl) says that workers are able to capture a portion (0) of modern sector value added. The ability of labor to extract rents is not treated as exogenous in this model; rather the percentage of value added captured by labor is given by: 0 = g(GIY, BDIY, TB, KF, PROT, U). g, > 0, g2 < 0, g7 > 0. g-4> 0, ‘75 > 0, g, < 0 032) G/Y is the share of government-produced

goods

produces

the results

OF

and services in GDP, BDIY is the government budget deficit as a percentage of GDP, TB is the trade balance, KF is the amount of capital flows to the country, PROT is a measure of the degree of protection conferred on domestic industry, and U is the unemployment rate. The maximization problem faced by a typical urban modern firm is:

“““(L,,,,. T,M. W)

where

(Al2)

- d,.H

(A9)

national labor force, is assumed to be given. assume the average product of rural labor the form:

W,,,,L,m= @(P,,,,,Q,,,,, -

553

URBANlZATION

H = PQ +

qwf_ -

WL O(PQ

t

P,$l

-

PTT - r/(w.ukL,,,

- P,,M - f

rn].

U33)

where q(W, U) is the percentage of a firm’s work force which quits every period (9,,, < 0, y,, < 0). and are the training costs incurY(W, f&L,,,” consequently red by the firm, where c are the per worker training costs. (See Stiglitz, 1974 for the original specification of the labor turnover model). The other variables are defined as in Appendix A. Note that W is now a choice variable for the firm, which seeks to choose the wage

ss4

WORLD

rate that minimizes total unit labor costs. for 0 from (B2) yields:

DEVELOPMENT

Substituting

L,: = y(P,~‘.(;DP’,GOV’.K’,.P,. A,.K;,,,,C’.O’).

TB.

First order traditional PQ,

conditions for labor, sector and imported

= W + Y(W, Uc +

PQ,.=

= hL - qt, CL,,,,,

(B3’)

inputs from the urban intermediates are:

TVQ, + r,,U,

P,+r,

PQM = P,: + h -L

li~.I'HOl'lJ~~

(B4a) (BJb)

+ TTIJ -

bTR hM

(Bat)

@Jd)

where Q,,QT and QM are the marginal products of labor, traditional sector inputs and imported intcrmediates. q,, is the partial derivative of the quit rate with respect to the wage, U, is the partial derivative of unemployment (in the modern sector) with respect to employment in that sector (a “Harris-Todaro” elasticity), and ‘cc). t(,. tz. and r,&, are the partial derivatives of labor’s share with respect to output, unemployment. traditional sector inputs and imported intermediates, respectively. rCj is greater then zero. whtle rl,, tT and x,+, are all less than zero. Note that these first order conditions arc quite distinct from those derived in the neoclassical model. Even for nonlabor inputs. firms must take into account the effect that changing the level of these inputs will have on labor’s demand for rents. The strategy for solving the rent-seeking model is the same as in the neoclassical model. Production and labor demand conditions in the urban traditional and rural sectors are specified. a national labor force identity is employed to derive a measure of the urban population. and a Harris-Todaro zero-migration equilibrium condition is used to close the model. Since these equations are the same as those in Appendix A. they are not repeated here. The reduced form equation for urbanization that emerges from this model is:

(B5)

It is worth commenting briefly on the expected signs of the coefficients in this reduced form. The sign of P,: is uncertain, since imported goods arc both inputs into UM production (and an increase in P,t! would consequently reduce output and employment) and competition for domestically produced UM goods (and an increase in P,: would consequently stimulate an increase in production and employment). GDP and GOV growth increase demand for urban modern product. and consequently are unambiguously positive. Growth of capital stock in both the UM and T sectors raises labor’s marginal value product. thcrcby inducing urban employment growth. Rural sector price incrcascs (PH) and factor productivity growth (A,> W. If U, > 0. the result may still obtain. since C‘, and rc,Q,_ are both greater than zero. In the model as specified there is no avenue for an increase in labor’s share to spur urbanization. Were income distributional concerns and differential demand patterns introduced into the demand for urban modern production. this would no longer be the USC’. Of course. it is possible to substitute for C‘ and 0 in BS. Doing so yields:

1’ d/t = q(P,:,‘,GDP’,C;OV’.K,.P,.A,. K,:,,,.M.P7,T,GIY.BDIY,TB.KF.PROT,U).

(Bh)

Note that W does not appear in Bh, since it is a choice variable of firms (and consequently endogenous).