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Quantiles for Counts

Author

Listed:
  • J.A.F. Machado

    (Faculdade de Economia, Universidade Nova de Lisboa)

  • J. M. C. Santos Silva

    (ISEG, Universidade Técnica de Lisboa)

Abstract

This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the discretization of a continuous process, or are based on a smoothed objective function. However, these methods have several drawbacks. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimator are illustrated by simulations and an application.

Suggested Citation

  • J.A.F. Machado & J. M. C. Santos Silva, 2003. "Quantiles for Counts," Econometrics 0303001, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0303001
    Note: Type of Document - Acrobat PDF; prepared on IBM PC ; pages: 39
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    Keywords

    Asymmetric maximum likelihood; Jittering; Maximum score estimator; Quantile regression; Smoothing.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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