Explaining the Decline of Child Mortality in 44 Developing Countries: An Bayesian Extension of Oaxaca Decomposition for Probit Random Effects Models

Antonio Pedro Ramos , University of California, Los Angeles
Leiwen Gao, University of California, Los Angeles
Martin Flores, University of California, Los Angeles
Robert Weiss, University of California, Los Angeles
Patrick Heuveline, University of California, Los Angeles

This paper investigates the decline of infant mortality in 42 low and middle income countries. We use micro data from 84 Demographic and Health Surveys, a Bayesian hierarchical model, and a new extension of the Oaxaca decomposition method to study the factors associated with over time reductions in infant mortality rates. We estimate mortality risk for each one of the births in our data and decompose reductions in infant mortality rates into differences in the distribution of the factors versus the differences due to their effects. We found that most of the decline is explained by changes in effects of the factors, not their distributions. However, there is a a considerable heterogeneity between countries. Our results suggest that increasing the coverage of basic factors, such as increasing maternal education and reducing the age of the first birth can greatly reduce infant mortality.

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 Presented in Session 3. Population, Development, & the Environment; Data & Methods; Applied Demography