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/ Will slower population I growth decrease the degree ~ of inequality in the distribution of income? Given a certain level of per capita income, greater variance in the distribution of income generally entails a larger percentage of a population living below whatever absolute income standard defines the poverty line. Consequently, a reduction of income disparities has become a widespread goal of development policy. These disparities can be measured with respect to identifiable characteristics such as occupation or region or with respect to income itself. In the latter case, standard measures such as the Gini coefficient express the amount of inequality in income distribution. Measures of income inequality are to be sharply distinguished from measures of poverty, which focus on households and persons with incomes below some defined income level. From the perspective of developing countries, the likely effect of changes in population growth on poverty is far more important than the effect on inequality, but in this discussion we confine our attention to income inequality. Although the distributional measures are standard, there is considerable ambiguity about their interpretation. One important question is whether inequality should be measured on a per capita basis or on a per household basis. Since larger households in developing countries tend to have higher total incomes but lower per capita incomes (Snnivasen and Bardhan, 1974; Kuznets, 1976), results can be quite sensitive to the choice of the unit of measurement. Further ambiguity is present because measures of income This chapter is based heavily on Lam (1985) 62
DISTRIBUTION OF INCOME 63 inequality can actually increase as a result of poorer households suddenly becoming richer. Also, some economic decisions (e.g., the decisions of low- income families to have another child) can result in both increased welfare and increased income inequality. When inequality is measured with respect to income itself, very little of a general nature can be said about the effects of population growth (i.e., higher levels of fertility). Lam (1985) discusses why empirical time-series and cross-national analyses have not been and are not likely to be fruitful in this area. Nevertheless, some relatively straightforward conclusions can be drawn from theoretical analyses on the assumption that fertility change in a household does not alter its total income. In the short term, the effects of fertility change depend heavily on the class distribution of that change. If the fertility change is differentiated by income class, per capita measures of inequality can change even in the short term. If lower income groups have proportionally larger fertility declines, then per capita income inequality will decrease. (This relationship holds generally but not universally; Lam, 1985.) If higher income groups have proportionally larger declines, as is often observed in the early stages of a fertility decline (Poker, 1978), then per capita income inequality will increase. When a fertility change is induced by a government-sponsored family planning program, the effects just described will be exaggerated: subsidized family planning services are themselves a form of income to the household, and whichever income groups take greater advantage of the services will have not only higher per capita incomes in the short term, but also greater increases in imputed income from increased service availability. On the other hand, if the fertility decline is induced by setting quantity limits on the number of children per couple, the unmeasured effect of the policy could offset measured changes in income distribution: for example, if high fertility is a greater economic benefit to poorer classes, the imposition of quantity limits could aggravate the* poverty (Rodgers, 1984:171~. Longer term effects of fertility change on income distributions are far more complex. They depend on the income-class distribution of the "extra" births and on Me income classes of those children when they become adults. They also depend on the impact of those births on aggregate rates of return to venous factors of production. On this matter, economic theory is relatively clear, and evidence supports the theoretical predictions: increases in the supply of labor relative to over factors of production (capital and natural resources) are expected to reduce the rate of return to labor and increase the rate of return to over factors of production, other things being equal. Since high-income groups generally own a disproportionate amount of the other factors of production, their incomes can be expected to rise disproportionately, making the population's income more unequally distributed. These effects
64 POP Ul~TION GROWTH AND ECONOMIC DEVELOPMENT are expected so long as a decrease in the ratio of wage rates to We price of another factor results in a less-than-proportional substitution of labor for the other factor (see Lam, 1985~. Evidence suggests that this is the case (Lam, 1985~. Eventually, the greater returns to capital induced by higher fertility can lead to more investment and lower returns to investment, so that effects in the very long term, after all adjustments are completed, can be moderated. In our discussion of renewable resources (Question 2), historical evidence from England was cited that suggests that population growth had the predicted effects of driving down wages and raising returns to owners of land. Evenson's (1984b) results for northern India suggest the same effect there. Khan (1984) finds evidence that population growth has reduced agricultural wages in Bangladesh. leading to a sharp increase in landlessness and agricultural · . _ ~ __ , ~ car ~ ~ poverty; in other Asian countries, the effects were not nearly so apparent, probably because industrialization proceeded at a more rapid pace in those countries than in Bangladesh. Unless population growth slows the rate of investment substantially, the"Bangladesh effect" need not arise. Similar mechanisms can be expected when workers are disaggregated into skilled and unskilled groups, educated and uneducated groups, or finer categories. Because workers of different Apes are not perfect substitutes for . · . one another (see Kelley and Williamson, 1984y, relative increases in one type of worker would decrease wages for that type relative to workers of another type. Williamson and Lindert (1980) examine evidence on inequality in the United States and find that changes in measured inequality reflect closely the changes in wage differences between skilled and unskilled workers, which in turn are a positive function of the rate of population grown. They conclude that faster population grown has produced greater income inequality in the United States, with a major role played by faster population growth depressing relative wages. Behrman and Birdsall (1985) find similar _ ~ , ~ _ ~ · ~ ~ ~ a ~ ~ ~ ~ ~ ~ _ ~ _ 3 1 _ ~= _ _ ^~ _ _ ~ effects in Bail: wages of unskilled workers are lower, ail otner Snags being We same, if they are members of an unusually large cohort. Relative to the wages of unskilled workers, earnings of well-educated workers are increased by membership in a large cohort. In addition to these effects, which essentially operate through private markets, the effects of population growth on income inequality may also be mediated by government programs. Many government programs are redistributive in their net tax and expenditure effects. If population growth alters the scope or characteristics of these programs, it can change income distribution. Lithe is known about these relationships. In a cross-national study, K`>lley (1976) finds that total government expenditure as a share of GNP is insignificantly affected by the relative size of the your cohort but singly and positively associated with the relative size of the elderly
DISTRIBUTION OF INCOME 65 cohort. Total expenditure is also negatively but weakly related to the total size and density of the population, perhaps because only central government expenditures are included, and they can be expected to decline as a fraction of all government expenditures when a country's population grows larger. In any event, the net implication of Kelley's results seems to be that government expenditures as a fraction of GNP will rise as population growth declines. In the preceding chapter, we reviewed evidence suggesting that government school expenditure per school-aged child rises when fertility falls, which supports the notion that there may be redistributional gains from declining fertility that are mediated by government programs. Population growth can affect inequality as measured in other dimensions. For example, intergenerational inequality can be altered by varying levels of fertility. In one sense, all the questions we consider in this volume bear on the issue of intergenerational equality, since we are asking how the future will differ from Me present when fertility is lower instead of higher. The fact that the number of members of the next generation is being jointly determined (in part) with its average level of welfare adds great ambiguity to the issue of intergenerational equality. Few people would consider a future generation to be better off if it consisted of only one member with princely weals; a discussion of the difficulty of making social choices when both numbers and conditions are involved can be found in Dasgupta (1985~. A more tractable issue relates to inequality by sex. In most countnes, women bear most of the time, health, and energy burdens of bearing and raising children. When this burden is increased by unwanted children, there is probably a greater welfare loss for women than for men. Programs to improve contraception are thus likely to raise the welfare of women relative to men; in most societies, such a change would produce a reduction in sewal inequality. CONCLUSIONS So long as the process of income generation is independent of fertility, the short-term effects of altered fertility on per capita measures of income inequality depend primarily on differences in the amount of fertility change by income class. These differences cannot be predicted a priori. To the extent that publicly supported family planning programs are targeted at the poor and permit them to exercise greater fertility control than they otherwise might, per capita income inequality will be reduced. Longer term effects, which have mainly been investigated in the economic histories of now~eveloped countries, tend to confirm theoretical predictions that slower population growth will decrease income inequality by increasing the rate of return to labor relative to returns to other factors of production.