A dynamic hurdle model for zero-inflated count data: with an application to health care utilization
AbstractExcess zeros are encountered in many empirical count data applications. We provide a new explanation of extra zeros, related to the underlying stochastic process that generates events. The process has two rates, a lower rate until the first event, and a higher one thereafter. We derive the corresponding distribution of the number of events during a fixed period and extend it to account for observed and unobserved heterogeneity. An application to the socio-economic determinants of the individual number of doctor visits in Germany illustrates the usefulness of the new approach.
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Bibliographic InfoPaper provided by Department of Economics - University of Zurich in its series ECON - Working Papers with number 151.
Date of creation: Apr 2014
Date of revision:
Excess zeros; Poisson process; exposure; hurdle model;
Find related papers by JEL classification:
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- I10 - Health, Education, and Welfare - - Health - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-04-11 (All new papers)
- NEP-ECM-2014-04-11 (Econometrics)
- NEP-GER-2014-04-11 (German Papers)
- NEP-HEA-2014-04-11 (Health Economics)
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