African Transitions and Fertility Inequality

Is Africa is different?” The question permeates the debate over Africa's fertility transitions, whether analysts ponder the causes, the consequences, or the socioeconomic patterns of these transitions. Do Africa's transitions occur at a lower threshold of economic development compared to, say, Latin American countries (Bongaarts and Casterline 2013; Bongaarts, this volume)? Will they yield a demographic dividend, as was the case among the Asian Tigers (Bloom et al. 2007)? And do they spread evenly across socioeconomic groups, as was claimed for Western Europe, or, instead, do they trickle from top to bottom income groups in ways that increase what we refer to in this chapter as fertility inequality (Caldwell, Orubuloye, and Caldwell 1992; Shapiro and Tambashe 2002)? A tentative consensus is emerging on the first two debates (Bongaarts this volume; Karra, Canning, and Wilde, this volume),1 but not on the last. Unresolved in this third debate is a question about evenness-specifically, whether African transitions follow a horizontal, inequality-preserving pattern (Caldwell, Orubuloye, and Caldwell 1992) or a more top-down sequence (Shapiro and Tambashe 2002). This unresolved question has implications for both the pace and dividends of African transitions. Fertility transitions are more likely to stall, and the dividends from these transitions are less likely to be evenly shared, if transitions occur in a top-down manner that increases fertility inequality. Studies of fertility inequality can thus inform both scientific concerns over stalling transitions (Bongaarts 2008; Garenne 2008; Schoumaker 2009) and policy concerns over the prospects for a shared dividend in sub-Saharan Africa (Bloom et al. 2007). Against this background, we explore how and why fertility inequality is changing during the course of African demographic transitions. To explore this topic, one needs prior clarification on three fronts. First is theory. Monitoring inequality is a simple empirical task, but explaining it requires a capacious theory to reconcile findings across different places, times, and transition stages. In particular, researchers must be able to explain the processes driving the historical ebb and flow in fertility inequality. A second front is about definitions and measures of inequality. At issue is the distinction between differentials, inequality, and divergence, three concepts often used interchangeably in this literature. Differentials are the simplest metric, and they refer to the difference in group-specific averages; for instance, how the average fertility rate of urban women differs from that of rural women (Kirk and Pillet 1998). Inequality is a fuller measure of variability in an outcome at one point in time, insofar as it integrates information about both group rates and group size: a group's contribution to inequality thus depends on how far it deviates from the average but also how large it is (Firebaugh 1999). Finally, divergence is the historical dimension of inequality-that is, whether or not it rises over time. Thus, differentials are a static and partial measure; inequality is a static and full measure; and divergence is a dynamic measure. Confusion arises if these three concepts are used indiscriminately. In particular, the tendency to use differentials as a proxy for inequality can mask the true trend in fertility inequality, while also blurring the distinction between the “leaders” and “drivers” of fertility declines, that is, the first versus the most influential groups in fertility transitions (Giroux, Eloundou-Enyegue, and Lichter 2008). Finally, the third front is about methods of analysis. Consensus on the empirical patterns of transitions requires robust, comparable, and transparent methods of analysis. Causal analysis of national-level outcomes such as inequality is difficult (Levine and Zervos 1993; Rodrik 2012), and researchers must resort to idiosyncratic modeling strategies that are hard to replicate and compare. As a result it is difficult to tell whether the mixed findings reflect substantive or methodological differences. Decomposition methods offer a viable alternative. While they do not establish causation, these methods provide a heuristically useful and methodologically transparent approach in which researchers can clearly identify the main sources (if not causes) of change, and reviewers can easily check both the input data and the results (Firebaugh 1999; Eloundou-Enyegue and Giroux 2012). Against this background, we attempt to explain how and why fertility inequality changes during demographic transitions. We do so by articulating a theory and testing it in sub-Saharan Africa. The theory borrows from diffusion theory (Rogers 1962) and Kuznets's seminal proposition on income inequality (Kuznets 1955). For this reason, we label it a demographic Kuznets argument (dK hereafter). It boils down to two testable propositions: (1) Over the course of fertility decline, fertility inequality first rises and then tapers off and falls in a bell-shaped pattern. (2) This historical trajectory is the outcome of three successive processes: differentiation in fertility rates, changes in population composition, and a shared decline in fertility. The rest of the chapter is structured as follows. We review why fertility inequality is worth monitoring and how a dK perspective improves understanding of the causes, course, and consequences of fertility transitions. We describe our dK argument and its implications for the direction and the determinants of change in inequality. In general, dK moves the debate away from a single-direction process and single determinant to suggest a non-monotonic and multiphasic process. We present our decomposition methods, which can reveal both the processes and groups driving the historical change. The specific formulation used can serve to directly test the dK argument, by quantifying the extent to which several competing forces drive the change in fertility inequality, as countries move from high to low fertility. Because most African countries are still in early stages of their transitions, a full test of the theory must await further declines in fertility. Nonetheless, trends in fertility inequality in the early stage of transition are themselves meaningful, and we also consider the forces behind this change. We conclude by summarizing the implications of these findings for the future course and dividends of African transitions and for the debate over Africa's exceptionalism. The results suggest that, in addition to being different, Africa is differentiating in ways that warrant concern about future economic inequality. Fertility inequality measures how evenly families share the burden or pleasure of childbearing (Lichter and Wooton 2005). As such, it speaks to intrinsic policy concerns about equity. More instrumentally, fertility inequality can inform broader debates on the causes, course, and consequences of African transitions. In that light, it is both symptom and omen: a historical convergence in fertility suggests a transition driven by social interaction, and it also augurs steady transitions and shared dividends. The connections between fertility inequality and these other debates are discussed below. Demographers still disagree on whether the primary determinants of fertility declines are economic or cultural. Macroeconomic forces have been argued to shape fertility demand via the costs and benefits of children, or its supply via the formation of unions or access to contraception (Schultz 1973; Lesthaeghe 1977; Coussy and Valin 1996; NRC 1993). Equally compelling arguments exist for the role of culture, notably religion, language, ethnicity, gender norms, and social interaction (Pollack and Watkins 1993; Bongaarts and Watkins 1996; Kravdal 2002; Philips et al. 2012). Even if researchers agree that multiple influences are likely to be at work, they disagree over primacy or the boundaries between cultural and economic influences (Bachrach 2014). A dK perspective addresses aspects of this stalemate. First, it distinguishes between the factors initiating a transition and those sustaining it (Mason 1997; Casterline 2001), and it expects class differences to predominate in early stages and to matter less in the latter stages. Second, it expands the debate beyond a narrow dichotomy of economy versus culture, which treats these two components as mutually exclusive and excludes forces that are neither economic nor cultural but demographic. Although infant mortality has been recognized as a possible precursor of fertility decline (Mason 1997), other demographic variables such as population composition deserve attention. Just as the age and sex composition of a population may affect aggregate economic consumption (Bloom, Canning, and Sevilla 2003; Lee and Mason 2006), its socioeconomic composition-in terms of variables such as income, education, or occupation-can shape aggregate inequality. Third and finally, the dK perspective avoids a common ecological fallacy in analyzing fertility transitions. By convention, transitions are a national process. As such, they are tracked with aggregate statistics, nudged with national policies, and probed for their macroeconomic benefits. Yet transitions are the result of decisions made by a myriad of individual families. The challenge for researchers is to reconcile the national scope of the outcomes and the micro-locus of decisions (Robinson 1950; Smith 1989). Although a national-level focus is warranted for policy purposes, it obscures within-country heterogeneity. It further ignores the social agents of these transitions, ultimately blurring and possibly distorting the national picture. Only infrequently have past studies bridged this micro/macro divide (see Knodel, Havanon, and Sittitrai 1990; Knodel and Wongsith 1991; Lam and Marteleto 2008; Eloundou-Enyegue and Giroux 2012). Most studies have instead focused on a single level of analysis, in an implicit trade-off between internal and ecological validity. The trade-off is avoidable with methods that aggregate sub-national trends to understand national change. Although one can also expect some variations within the subgroups used as units of analysis, we expect this within-group variation to be smaller than variation across groups. Over the last decade, fertility stalls and/or reversals were documented in several African countries. The number varies according to authors-anywhere from 12 (Bongaarts 2006, 2008) to 6 (Garrenne and Joseph 2002; Garenne 2008) to 2 (Schoumaker 2009)-but there is a fairly robust consensus that stalls occurred in at least a handful of countries (Schoumaker 2009; Westoff and Cross 2006; Machiyama 2010). Even where declines did not reverse or come to a full halt, they slowed noticeably in many African countries in the latter 1990s and early 2000s (Bongaarts 2008). Such stalls have forced demographers to revisit a long-held assumption that transitions continue irreversibly after reaching a certain threshold (Coale and Watkins 1986). In seeking to understand why transitions might stall, studies have focused on proximate determinants and external conditions (Westoff and Cross 2006; Bongaarts 2008; Ezeh, Mberu, and Emina 2009). We complement this approach by looking at internal patterns of decline and the possible role of fertility inequality. The hypothesis is that stalls depend on the evenness in the initial fertility decline: a national transition is most likely to stall when the initial decline is confined to a small group. Once the change within this vanguard group runs its course, the national decline stops unless the rest of the population follows suit. Research on Africa's demographic dividends has initially focused on average macroeconomic growth (Bloom et al. 2003; Eastwood and Lipton 2011; Lee and Mason 2006). However, with the growing concern over global inequalities, the equitable distribution of dividends becomes a key question. The extent to which Africa's dividend is shared evenly among the national population depends on policy and institutions, as well as on patterns of fertility change. To be sure, all socioeconomic classes potentially benefit from the macroeconomic consequences of a dividend, that is, more jobs and higher incomes. Yet the extent to which individual families can benefit from this economic expansion depends on their investments in education, including quality education. Fertility inequality, especially when manifest along socioeconomic lines, tends to increase resource inequality among children via uneven resource dilution (Blake 1989). By tracking fertility inequality, studies can enrich the research agenda on the dividend. Whether the dividend is shared will ultimately have ripple effects on broader socioeconomic inequality and the opportunities for economic mobility within the region. A dK hypothesis reconciles opposing expectations about the direction and the determinants of fertility inequality. In terms of direction, the opposition is between vertical (and inequality-inducing) declines led by high-socioeconomic groups and horizontal (and equality-conserving) declines unfolding evenly across all groups (Caldwell, Orubuloye, and Caldwell 1992). In terms of determinants, demographers often distinguish between social adaptations driven by changes in rates and those driven by changes in composition. Figure 1 illustrates these two oppositions. Frame A shows a national decline, as marked by a gradual darkening of boxes. Given this decline, Frame B contrasts the two opposite directions, while Frame C shows contrasts between two elementary components. Direction of fertility decline (Frame B). A fertility decline can occur in two elementary directions. It can decline horizontally (scenario B1), with fertility falling at the same pace across all groups; any initial difference in fertility rates between groups (in this case, there is none) is maintained over time. For that reason, this scenario is dubbed “permanent difference” (Bongaarts 2003; Yoo 2014) and it has the most benign implications for the pace and consequences of transitions. It does not alter fertility differentials, it yields an evenly shared dividend, and it is less likely to stall because its broad base makes it less dependent on the behavior of a single group. Because the process is not tied to the circumstances of one group, this scenario is also more likely to reflect broad cultural change or broad economic opportunity rather than selective economic incentives. In the alternative (scenario B2), fertility falls from top to bottom. Under this “leader-follower” scheme (Bongaarts 2003; Yoo 2014), the top socioeconomic group takes the lead and others follow, in descending order of socioeconomic status. Whereas the first scenario showed identical trends at national and group levels, no single group here mirrors the national trend. Rather, national fertility declines through accretion as additional groups lower their fertility. A stall is more likely in this case because forward movement at any point depends on the behavior of a single group. Furthermore, fertility inequality will rise during the early transition stages. Determinants of fertility decline (Frame C). Beyond the direction, fertility transitions can differ in their determinants. Demographers often distinguish between two classic determinants of aggregate change: change in rates or group behavior and change in composition or group size (Frame C). The top figure in this frame (scenario C1) shows a transition triggered by changes in rates. In this case, the fertility levels of different groups change over time, although they do not change in lockstep. This stands in contrast to the bottom scenario (scenario C2) where no group alters its behavior. Fertility remains consistently low in the high-socioeconomic group and consistently high in the low-socioeconomic groups. The only transformation is in the size of groups. From being a minority, the top socioeconomic group gradually becomes the overriding majority, and this compositional shift is the reason why national fertility declines. To use education categories as an illustration, the most educated women would neither alter their behavior nor influence anyone else. Rather, they become more numerous. The only reason why fertility declines is the growth in the number of highly educated (fertility-limiting) women. Another way to interpret the difference between these three scenarios is to consider which social group leads the change. Under scenario B1, no group wields a disproportionate influence; under scenario C1, individual groups take turns leading the change; under scenario C2, the top socioeconomic group exerts the most influence. A synthesis. Real life, of course, is more complex than any of the elementary types in Figure 1. Even in a leader-follower hypothesis, groups can vary in the timing and trajectory of their decline (Bongaarts 2003: 6). Similarly, fertility need not change in a single direction. Shapiro and Tambashe (2002), for instance, envision a three-stage process where group differentials grow initially before declining. Just as it is simplistic to postulate a single direction, it is unrealistic to postulate a single, invariant factor. Fertility transitions can be triggered by multiple factors, whose mix may change over time. The mix of directions and factors expected under the dK framework is summarized in Figure 2. First is a sharp rise in fertility inequality, as early adopters separate themselves from the rest of the population; next, inequality increases more slowly and reaches a plateau as the socioeconomic composition of the national population changes; finally, inequality declines under the influence of a shared decline in fertility. This sequence is labeled a demographic Kuznets pattern in reference to this author's classic theory on inequality (Kuznets 1955). Unlike Kuznets, however, our argument also considers not only economic inequality but also fertility inequality, and the inequality is driven not by broad economic and institutional forces but by a mix of factors reminiscent of adoption/diffusion theory (Rogers 1962). The dK thesis thus blends two ideas, with Kuznets providing the descriptive shell and Rogers some of the explanatory core. The theory further extends Shapiro and Tambashe's (2002) three-phased evolution in inequality by applying full measures of inequality and by elucidating the determinants of this trend. The three phases in Figure 2 roughly mirror the three scenarios in Figure 1. The first, second, and third phases in the dK curve correspond to scenarios C1, C2, and B1 in Figure 1. Beyond mere description, Figure 2 highlights the broad processes that drive these trends. The three processes are a differentiation in rates (phase 1), a change in population composition (phase 2), and a shared decline in fertility behavior (phase 3). Again, the differentiation in rates amounts to a selective fertility decline among one or a few groups, which alters the existing fertility gaps (Figure 1, Frame C1). Composition refers to change in the size of different subgroups, whether these are defined by education or other socioeconomic characteristics (Figure 1, Frame C2). By themselves, such changes in composition can mechanically alter the national fertility rate without any change in group-specific fertility. Shared decline, finally, is a decline in fertility that is shared evenly across all groups (Figure 1, Frame B1). One may further speculate about the social forces that trigger the primary processes listed in Figure 2. Differentiation results from groups responding to different cultural or economic incentives or constraints related to fertility (Pollack and Watkins 1993; Campbell, Sahin-Hodoglugil, and Potts 2006). Population composition, likewise, might change for a variety of reasons. Given our focus on education as the composition variable, an important trend to consider here is the region's progress in education throughout the study period. Finally, a shared fertility decline can reflect a shift in norms, itself reflecting of (Bongaarts and Watkins 1996; and Casterline 1996; However, these are not on the primary of change, including a differentiation in rates, a change in the composition of the and a shared To the dK hypothesis boils down to two testable propositions: 1 Over the course of fertility decline, fertility inequality first rises and then tapers off and falls in a bell-shaped 2 this historical trajectory is the outcome of three successive processes: differentiation in fertility rates, changes in population composition, and a shared decline in fertility. the first proposition requires only a simple descriptive or analysis the historical change in fertility inequality during the course of a national rather than measures of inequality are used in this For we three the of variation and the use the most because it is to Although fertility inequality can be for groups defined by different we focus on an economic socioeconomic This is most from a because it resource inequality among children (Blake 1989). is here by for of data and because education with other of and its effects on can both income and effects and In we a fertility level that is identical across groups and is to the national average fertility As a there is no fertility on fertility inequality. The shared decline will be to by there is no in this shared Although this has in for changes in fertility inequality, it is useful when explaining trends in average fertility. We use data from all and in sub-Saharan Africa between and a of in countries. The is neither nor sub-Saharan countries are not of those the number of varies from 1 to with the as Nonetheless, this the region's and demographic with from to more stages in the The mix from where fertility rates 2006, to with levels 2009; 2013; Africa The fertility data are from from the are for several subgroups, including education groups. for the fertility and of women with no some primary and some This information is to levels of fertility inequality and to the historical change in inequality. Figure in how the levels of fertility inequality change as national fertility declines on the that countries with more more data The is then by its A is the most with the dK hypothesis and its of a the hypothesis is and data are for the full of transition then a the point at which fertility inequality reaches a plateau and to This is the point at which the first of the To test the hypothesis, we whether a the compared to a or an The results of all these are summarized in Figure suggest the First, a a to the for as as of the in fertility inequality. The is for the of variation compared to the or the A few In (2002), to a and for instance, the levels of inequality are higher than expected at this Similarly, we levels of inequality in Nonetheless, the and the curve clearly a rise in inequality during the early transition Second, results are mixed when we a to a or The the data than the for the and it to the however, the is still when the and are used and but not when the is used these results the of a rise in fertility inequality during the early but not that of an down of inequality in transition stages. This is by the from the The by these at of or but these are rather than The of countries is still high and we are still in the early of the dK Although this no on the of a plateau (if it the initial point in the transition where fertility inequality to inequality to rise as as national falls the high fertility plateau for most African countries. the findings from a perspective the first of the dK hypothesis, that is, a rise in inequality in the early of the demographic is of a in inequality at this early where of the still a national of can Figure as a of that is, a tendency to historical trends from In rather than the historical trajectory of the data in Figure differences between countries that have lower fertility and those that have high fertility. For such a more approach focus on historical We thus the analysis in on countries with multiple of study In this the number of from 2 to and the between the first and last from and to 1 the national of countries in this are on their whether 6 between and 6 between and or at the group the data an initially rise in inequality that tapers The are whether the data are or From a fertility inequality increases from to to and as one average inequality in these of countries. In other the initially increases to The results are if one in a more historical at the average change within of these The and for of the of countries. Again, the for the last group suggests a in the growth of inequality. Finally, one can at individual countries and explore whether declines in fertility are by a rise in fertility inequality. The results in the to this Only in and did fertility inequality to as national fertility is the more because of its high fertility. on the other the dK hypothesis and its of a decline in fertility inequality during the transition stages. Given that inequality does not decline in the few other vanguard countries here and and in the of data on the other vanguard countries or our empirical of the second of the dK hypothesis remains The especially case, also

Demographic dividend · Demographic economics · Demographic transition · Development economics · Economics · Fertility · Inequality · Latin Americans · Political science · Population · Socioeconomic status · Sociology · Demographic Trends and Gender Preferences · Demography · Family Dynamics and Relationships · Insurance, Mortality, Demography, Risk Management

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