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Modeling heaped duration data: An application to neonatal mortality

Arulampalam, Wiji, Corradi, Valentina and Gutknecht, Daniel (2017) Modeling heaped duration data: An application to neonatal mortality Journal of Econometrics, 200 (2). pp. 363-377.

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In 2005, the Indian Government launched a conditional cash-incentive program to encourage institutional delivery. This paper studies the effects of the program on neonatal mortality using district-level household survey data. We model mortality using survival analysis, paying special attention to substantial heaping, a form of measurement error, present in the data. The main objective of this paper is to provide a set of sufficient conditions for identification and consistent estimation of the (discretized) baseline hazard accounting for heaping and unobserved heterogeneity. Our identification strategy requires neither administrative data nor multiple measurements, but a correctly reported duration point and the presence of some flat segment(s) in the baseline hazard. We establish the asymptotic properties of the maximum likelihood estimator and derive a set of specification tests that allow, among other things, to test for the presence of heaping and to compare different heaping mechanisms. Our empirical findings do not suggest a significant reduction of mortality in treated districts. However, they do indicate that accounting for heaping matters for the estimation of the hazard parameters.

Item Type: Article
Divisions : Faculty of Arts and Social Sciences > School of Economics
Authors :
Arulampalam, Wiji
Gutknecht, Daniel
Date : 5 July 2017
DOI : 10.1016/j.jeconom.2017.06.016
Copyright Disclaimer : © 2017 Elsevier B.V. All rights reserved.
Uncontrolled Keywords : Discrete time duration model; Heaping; Measurement error; Parameters on the boundary; Neonatal mortality
Depositing User : Clive Harris
Date Deposited : 01 Mar 2018 12:28
Last Modified : 06 Jul 2019 02:08

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