The impact of piped water provision on infant mortality in Brazil: A quantile panel data approach
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We examine the impact of piped water on the under-1 infant mortality rate (IMR) in Brazil using a recently developed econometric procedure for the estimation of quantile treatment effects with panel data. The provision of piped water in Brazil is highly correlated with other observable and unobservable determinants of IMR - the latter leading to an important source of bias. Instruments for piped water provision are not readily available, and fixed effects to control for time-invariant correlated unobservables are invalid in the simple quantile regression framework. Using the quantile panel data procedure in Chen and Khan [Chen, S., Khan, S., Semiparametric estimation of non-stationary censored panel model data models with time-varying factor. Econometric Theory 2007; forthcoming], our estimates indicate that the provision of piped water reduces infant mortality by significantly more at the higher conditional quantiles of the IMR distribution than at the lower conditional quantiles (except for cases of extreme underdevelopment). These results imply that targeting piped water intervention toward areas in the upper quantiles of the conditional IMR distribution, when accompanied by other basic public health inputs, can achieve significantly greater reductions in infant mortality. © 2009 Elsevier B.V.
Published Version (Please cite this version)10.1016/j.jdeveco.2009.02.006
Publication InfoGamper-Rabindran, S; Khan, S; & Timmins, C (2010). The impact of piped water provision on infant mortality in Brazil: A quantile panel data approach. Journal of Development Economics, 92(2). pp. 188-200. 10.1016/j.jdeveco.2009.02.006. Retrieved from https://hdl.handle.net/10161/2010.
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Professor of Economics
Professor Khan is on leave at Boston College for the 2016-17 academic year.Professor Khan specializes in the fields of mathematical economics, statistics, and applied econometrics. His studies have explored a variety of subjects from covariate dependent censoring and non-stationary panel data, to causal effects of education on wage inequality and the variables affecting infant mortality rates in Brazil. He was awarded funding by National Science Foundation grants for his projects ent
Professor of Economics
Christopher D. Timmins is a Professor in the Department of Economics at Duke University, with a secondary appointment in Duke’s Nicholas School of the Environment. He holds a BSFS degree from Georgetown University and a PhD in Economics from Stanford University. Professor Timmins was an Assistant Professor in the Yale Department of Economics before joining the faculty at Duke in 2004. His professional activities include teaching, research, and editorial responsibilities. Professor Timmi
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