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Counting on count data models

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  • Rainer Winkelmann

    (University of Zurich, Switzerland, and IZA, Germany)

Abstract

Often, economic policies are directed toward outcomes that are measured as counts. Examples of economic variables that use a basic counting scale are number of children as an indicator of fertility, number of doctor visits as an indicator of health care demand, and number of days absent from work as an indicator of employee shirking. Several econometric methods are available for analyzing such data, including the Poisson and negative binomial models. They can provide useful insights that cannot be obtained from standard linear regression models. Estimation and interpretation are illustrated in two empirical examples.

Suggested Citation

  • Rainer Winkelmann, 2015. "Counting on count data models," IZA World of Labor, Institute of Labor Economics (IZA), pages 148-148, May.
    • Handle: RePEc:iza:izawol:journl:y:2015:n:148
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    References listed on IDEAS

    as
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    2. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
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    More about this item

    Keywords

    Poisson regression; negative binomial distribution; zero-inflation; hurdle model;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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