Session: Geographical Differences
Room: Hollister B14
Time: Mon 16:45-18:15

Presenter: Lauren Heller (University of North Carolina, Chapel Hill. Economics)

Discussant: Linda DynanNorthern Kentucky University

Abstract

The upward trends in both the quantity and relative proportions of slum residents in developing countries have led to international health concerns, including the impact of slum residency on health behaviors. Measurement of these impacts, however, requires recognizing that the unobservable household characteristics that affect the location decision may also affect health care choices and health outcomes. To address the potential bias resulting from this pattern of causality, this research models the decision to locate in a particular area and the household's demand for maternal and child health services simultaneously. It uses a unique urban data set from Bangladesh that incorporates sophisticated geographical mapping techniques to carefully delineate between slum and non-slum areas at a particular point in time. The estimation method allows for correlation across outcomes using a flexible, semi-parametric approach to the modeling of unobserved heterogeneity. The results suggest that accounting for the endogenous location decision of a family substantially reduces bias in estimated marginal effects of slum residence on preventive care demand. While community infrastructure variables appear correlated with preventive care demand, the causal effect of the availability of primary health care facilities is indistinguishable from zero when unobserved heterogeneity is taken into account.

Key Terms

Preventive Care, Location, Bangladesh, Urban, Slum, Child Health

Authors:

Lauren Heller (UNC Chapel Hill. Economics)