Fertility and Labour Market Participation
Over time, a consensus has emerged from the empirical literature that fertility has a large and statistically significant negative effect on female labour supply. Recently, however, some authors have begun to doubt the universality and integrity of this result, given the estimation problems, such as omitted variable bias, which plagues the estimation of labour supply models in the literature. Key amongst these studies is a paper by Aguero and Marks (2008) in which they introduce a new instrumental variable to the literature and wherein they find that there is no evidence of a negative relationship between fertility and female labour supply in a selection of Latin American countries. This paper investigates the degree to which their strategy can be extended to the developing country context. Two alternative instruments are employed to establish whether there are any non-linearities in the effect of shocks to fertility on female labour force participation.
The addition of infertility to the available arsenal of instruments for family size has opened up a new debate in the literature on fertility and female labour supply. Previously, the consensus in the literature was that there is a large and statistically significant negative relationship between family size and female labour force participation. Recent evidence from instrumental variable regressions in middle income Latin American countries suggests that there may actually be no relationship. This paper has shown that the same may be true for developing countries in Sub-Saharan Africa. These developments have important implications for theories of labour supply and for future research in the empirical field. Future research will have to re-evaluate the relationship between fertility and female labour supply and assumptions on this relationship in models of labour supply. More clarity is needed on the impact of fertility on labour supply at various stages in the growth of families, while the instrumental variables on offer require further validation, particularly in the developing world.
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