期刊
JOURNAL OF APPLIED STATISTICS
卷 40, 期 4, 页码 721-735出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02664763.2012.752448
关键词
count data; estimation; MSE; MAE; multicollinearity; ridge regression; simulation; zero-inflated Poisson
资金
- Sparbankernas Forskningsstiftelse
The zero-inflated Poisson regression model is commonly used when analyzing economic data that come in the form of non-negative integers since it accounts for excess zeros and overdispersion of the dependent variable. However, a problem often encountered when analyzing economic data that has not been addressed for this model is multicollinearity. This paper proposes ridge regression (RR) estimators and some methods for estimating the ridge parameter k for a non-negative model. A simulation study has been conducted to compare the performance of the estimators. Both mean squared error and mean absolute error are considered as the performance criteria. The simulation study shows that some estimators are better than the commonly used maximum-likelihood estimator and some other RR estimators. Based on the simulation study and an empirical application, some useful estimators are recommended for practitioners.
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