Macro-level modeling is still the dominant approach in many demographic applications because of its simplicity. Individual-level models, on the other hand, provide a more comprehensive understanding of observed patterns; however, their estimation using real data has remained a challenge. The approach we introduce in this article attempts to overcome this limitation. Using likelihood-free inference techniques, we show that it is possible to estimate the parameters of a simple but demographically interpretable individual-level model of the reproductive process from a set of aggregate fertility rates. By estimating individual-level quantities from widely available aggregate data, this approach can contribute to a better understanding of reproductive behavior and its driving mechanisms. It also allows for a more direct link between individual-level and population-level processes. We illustrate our approach using data from three natural fertility populations.
The emergence of Child-Headed Households (CHH) and Young Adult Households (YAH) has largely been taken as an indicator of the erosion of the traditional safety nets in sub-Saharan countries and a direct consequence of the increasing number of orphans in the region. However, the initial evidence presented so far suggests that the process of formation of CHH and YAH is more complex than it appears to be. Using the four available waves of the Zimbabwe Demographic and Health Surveys (1988, 1994, 1999, and 2005/2006) we find that the proportion of households with no adults have remained stable in the last years, although the number of orphans have increased significantly. In fact, a large number of children living in CHH are non-orphans, which suggests that this kind of living arrangements is not always a direct consequence of parental death. Moreover, our analysis show that children living in CHH and YAH are less likely to have unmet basic needs than children in households headed by working-age adults and other vulnerable households.
After 30 years of active development, mechanistic models of the reproductive process nearly stopped attracting scholarly interest in the early 1980s. In the following decades, fertility research continued to thrive, relying on solid descriptive work and detailed analysis of micro-level data. The absence of systematic modelling efforts, however, has also made the field more fragmented, with empirical research, theory building, and forecasting advancing along largely disconnected channels. In this paper we outline some of the drivers of this process, from the popularization of user-friendly statistical software to the limitations of early family building models. We then describe a series of developments in computational modelling and statistical computing that can contribute to the emergence of a new generation of mechanistic models. Finally, we introduce a concrete example of this new kind of model, and show how they can be used to formulate and test theories coherently and make informed projections.
This paper analyzes how the transition out of the parental home has changed in the last two and a half decades in Uruguay. Using National Household Surveys from 1981 to 2005, we show that although young people in Uruguay have postponed the formation of new households, considerable gaps still exist between individuals from different socio-economic backgrounds. The most educated have avoided further delays in their emancipation by adopting non-family living arrangements as an increasingly popular alternative. Women have experienced the most significant change, reflecting the movement towards more egalitarian relationships between genders. Although the greatest proportional decline of young people living independently has been experienced in a period of relatively favorable economic conditions, our findings suggest that for a large part of the population, the postponement of the formation of a new household is a coping mechanism rather than a choice.
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