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The Demographic Dividend in Africa: Old Wine in a New Bottle? (Note)

⚠️Automatic translation pending review by an economist.

Summary:

· In recent years, there has been renewed attention to the consequences of demographic transition in developing countries, particularly in Sub-Saharan African countries.

· There is a consensus that investing in people, i.e. investments in education and health, are key to harnessing the demographic dividend in Africa;

· Recent evidence suggests that the demographic transition may induce gains in terms of human development regardless of its economic returns;

· Estimating the demographic dividend is particularly challenging for both micro- and macro-level studies;

· Early evidence suggests that the adoption of a combination of micro and macro level data may allow reconciling analytical rigor and macro-level implications.

For several years now, there has been renewed attention to the consequences of demographic transition in developing countries, particularly in Sub-Saharan African countries. As suggested by an increasing number of scientific articles and reports on the issue of the demographic dividend in Africa, demographic changes in African countries come with promising signs in terms of economic growth and development.

The demographic transition refers to changes in the population size and age structure due to a shift from both high fertility and mortality to low fertility and mortality. The demographic transition, particularly the change in age structure, is expected to have positive effects on economic growth and development. Conceptualized as the demographic dividend, these potential benefits may arise through a « mechanical » increase in per capita output, as well as through behavioral changes (e.g., human capital investments and savings behaviors) (see Bloom et al., 2003; Eastwood and Lipton, 2011).

Because these gains are not automatic, policies have a great role to play in the realization of the demographic dividend in African countries. While specific contexts may need specific policies to reap the benefits of the demographic transition, there is a consensus that investing in people, i.e., investments in education and health, are keys to harnessing the demographic dividend in Africa. Moreover, recent evidence suggests that the demographic transition may induce gains in terms of human development regardless of its economic returns (Eloundou-Enyegue and Giroux, 2013). Given the importance of human capital accumulation for African countries, this article revisits the links between demography and human capital accumulation through mainly a literature review. I build on a work in progress by Arestoff et al. (2016), who investigate the impact of demographic conditions at birth on children’s health and education.

Demography and Human Capital: Macro and Micro Perspectives

The theoretical literature on the links between demographic variables and human capital investments suggests two main channels through which the demographic transition may affect these investments. First, the literature suggests that longer life (or lower mortality rate) increases the horizon over which the returns to education can be reaped off and induces higher investment in education and health. Second, a decline in fertility (which is expected to be largely driven by the decline in child mortality[1]) is expected to affect parents’ investment in their children’s quality in accordance with the model introduced by Becker (1960) (see, for example, Kalemli-Ozcan, 2002, 2003; Soares, 2005).

Although the empirical evidence from micro- and macroeconomic studies mainly suggests a positive impact of the demographic transition on human capital investments (e.g., Jayachandran and Lleras-Muney, 2009), this link has been challenged recently by a number of papers using different methodologies or using adult mortality or child mortality as demographic variables of interest.

For instance, at the macro level, Acemoglu and Johnson (2006) and Lorentzen et al. (2008) find no effect of life expectancy and adult mortality on school enrollment in cross-sectional data. These results are explained theoretically by Hazan and Zoabi (2006), who argue that when parents choose fertility and the education of their children, a rise in life expectancy could increase not only the returns to quality (more schooling) but also the returns to quantity (more family income), mitigating the incentive to invest more in their children’s education. Moreover, findings by Hazan (2012) suggest that an increase in life expectancy is positively correlated with schooling when life expectancy is taken at birth, but negatively correlated if life expectancy is taken at age 5.

At the micro level, recent studies investigating the existence of a trade-off between the number of children and parents’ investment in each child do not confirm the existence of the quantity-quality trade-off (Black et al., 2005; Angrist et al., 2010). These results reflect cross-country differences, as well as differences across time periods. They further highlight empirical challenges in estimating the effects of demographic variables on human capital investments due to endogeneity issues and data limitations. For example, at the micro level, studies on the quantity-quality trade-off must deal with the fact that parents may choose both the number of children and the level of investments in each child, and that child mortality may be endogenous to child quality through investments in child health and nutrition.

Human capital dividend:what about a micro-macro perspective?

As suggested by the literature review above, the estimation of a human capital dividend is confronted with challenges related to the level of analysis (micro vs. macro) and its implications. According to Eloundou-Enyegue and Giroux (2013), the question is whether « studies can reconcile the analytical rigor of micro-level studies with the policy interest in macro-level implications »?

Arestoff et al. (2016) add to the literature by combining micro and macro level data to provide evidence on the impacts of demographic conditions on human capital accumulation in Africa, Asia, and Latin America. While preliminary, their results point towards important differences across regions and across indicators. First, the results suggest that Africa is the region that suffers the most from demographic pressure. Second, although the analyses suggest a dividend in terms of health during the study period in Africa, demographic changes do not seem to have produced an education dividend. These results have important policy implications. For instance, they call for an increase in spending in social sectors.

Conclusion

The Demographic Dividend in Africa: Old Wine in a New Bottle? The logical answer to the question in the title of this article would have been to rephrase the sentence as follows: « Old Wine in a New Bottle and New Perspective. » The focus on human development as well as methodological contributions in measuring the gains related to demographic changes are helping to inform and design policies to reap the potential benefits of the transition. Although caution is needed in designing policies to reap these benefits, I would like to share the words of a participant in the 7th African Population Conference who pointed out that if the perspective of a demographic dividend may encourage African governments to invest in sectors such as education and health, we as researchers might not be wrong in emphasizing these potential benefits.

References

Arestoff, F., Djemai, E., Koussoubé, E., and Mage, S. (2016). Demographic conditions and investments in children’s human capital. Mimeo. Paris-Dauphine University.

Acemoglu D. and Johnson S. (2006). Disease and development: the effect of life expectancy on economic growth. NBER working paper no. 12269.

Angrist, J., Lavy, V., & Schlosser, A. (2010). Multiple experiments for the causal link between the quantity and quality of children. Journal of Labor Economics, 28(4), 773-824.

Becker, G. S. (1960). An economic analysis of fertility. In Demographic and economic change in developed countries (pp. 209-240). Columbia University Press.

Black, S. E., Devereux, P. J., & Salvanes, K. G. (2005). The more the merrier? The effect of family size and birth order on children’s education. The Quarterly Journal of Economics, 669-700.

Bloom D., Humair S., Rosenberg L., Sevilla JP. And Trussel J. (2013). A Demographic Dividend for Sub-Saharan Africa: Source, Magnitude, and Realization, PGDA Working Paper, No. 110.

Bloom D. and Canning D. (2008). Global demographic change: dimensions and economic significance, Population and Development Review, 34, pp.17-51.

Canning, D. (2013). The Demographic Dividend in Africa, Mimeo, World Bank.

Eloundou-Enyegue, P. M., & Giroux, S. C. (2013). The role of fertility in achieving Africa’s schooling MDGs: Early evidence for sub-Saharan Africa. Journal of Children and Poverty, 19(1), 21-44.

Galor, O. (2012). The demographic transition: causes and consequences. Cliometrica, 6(1), 1-28.

Hazan M. (2012). Life expectancy and schooling: new insights from cross-country data. Journal of Population Economics, 25, 1237-1248.

Hazan M. and Zoabi H. (2006). Does longevity cause growth? A theoretical critique. Journal of Economic Growth, 11 (4), 363-376.

Jayachandran S. and Lleras-Muney A. (2009). Life expectancy and human capital investments: evidence from maternal mortality declines. Quarterly Journal of Economics, 124 (1): 349-397.

Kalemli-Ozcan S. (2002). Does the mortality decline promote economic growth? Journal of Economic Growth, 7, 411-439.

Kalemli-Ozcan, S. (2003). A stochastic model of mortality, fertility, and human capital investment. Journal of Development Economics, 70(1), 103-118.

Lorentzen P., Mc Millan J., Wacziarg R. (2008). Death and development. Journal of Economic Growth, 13, 81-124.

Soares R. R. (2005). Mortality reductions, educational attainment, and fertility choice. American Economic Review, 580-601.


[1]Other explanations for the observed fertility decline include higher levels of income, technological progress, education, etc. (for a review of theories of demographic transition, see Galor, 2011).

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