Estimation of hurdle models for overdispersed count data
Hurdle models based on the zero-truncated Poisson-lognormal distribution are rarely used in applied work, although they incorporate some advantages compared with their negative binomial alternatives. I present a command that enables Stata users to estimate Poisson-lognormal hurdle models. I use adaptive Gauss–Hermite quadrature to approximate the likelihood function, and I evaluate the performance of the estimator in Monte Carlo experiments. The model is applied to the number of doctor visits in a sample of the U.S. Medical Expenditure Panel Survey. Copyright 2011 by StataCorp LP.
Volume (Year): 11 (2011)
Issue (Month): 1 (March)
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References listed on IDEAS
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- Rainer Winkelmann, 2004.
"Health care reform and the number of doctor visits-an econometric analysis,"
Journal of Applied Econometrics,
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- A. Colin Cameron & Pravin K. Trivedi, 2010. "Microeconometrics Using Stata, Revised Edition," Stata Press books, StataCorp LP, number musr, January.
- J. M. C. Santos Silva, 2003. "A note on the estimation of mixture models under endogenous sampling," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 46-52, June.
- Wong, Irene O.L. & Lindner, Michael J. & Cowling, Benjamin J. & Lau, Eric H.Y. & Lo, Su-Vui & Leung, Gabriel M., 2010. "Measuring moral hazard and adverse selection by propensity scoring in the mixed health care economy of Hong Kong," Health Policy, Elsevier, vol. 95(1), pages 24-35, April.
- Winfried Pohlmeier & Volker Ulrich, 1995. "An Econometric Model of the Two-Part Decisionmaking Process in the Demand for Health Care," Journal of Human Resources, University of Wisconsin Press, vol. 30(2), pages 339-361. Full references (including those not matched with items on IDEAS)
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