Arbeitspapier
Robust estimation of zero-inflated count models
Applications of zero-inflated count data models have proliferated in empirical economic research. There is a downside to this development, as zero-inflated Poisson or zero-inflated Negative Binomial Maximum Likelihood estimators are not robust to misspecification. In contrast, simple Poisson regression provides consistent parameter estimates even in the presence of excess zeros. The advantages of the Poisson approach are illustrated in a series of Monte Carlo simulations.
- Language
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Englisch
- Bibliographic citation
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Series: Working Paper ; No. 0908
- Classification
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Wirtschaft
Hypothesis Testing: General
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
- Subject
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excess zeros
Poisson
overdispersion
negative binomial regression
Zähldatenmodell
Stochastischer Prozess
Maximum-Likelihood-Methode
Monte-Carlo-Methode
Robustes Verfahren
Theorie
- Event
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Geistige Schöpfung
- (who)
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Staub, Kevin E.
Winkelmann, Rainer
- Event
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Veröffentlichung
- (who)
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University of Zurich, Socioeconomic Institute
- (where)
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Zurich
- (when)
-
2009
- Handle
- Last update
-
10.03.2025, 11:46 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Staub, Kevin E.
- Winkelmann, Rainer
- University of Zurich, Socioeconomic Institute
Time of origin
- 2009
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