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Reducing the bias of the maximum likelihood estimator for the Poisson regression model

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  • David E Giles

    ()
    (University of Victoria, Canada)

  • Hui Feng

    ()
    (Department of Economics, Business and Mathematics, King''''s University College, UWO)

Abstract

We derive expressions for the first-order bias of the MLE for a Poisson regression model and show how these can be used to adjust the estimator and reduce bias without increasing MSE. The analytic results are supported by Monte Carlo simulations and three illustrative empirical applications.

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File URL: http://www.accessecon.com/Pubs/EB/2011/Volume31/EB-11-V31-I4-P265.pdf
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Bibliographic Info

Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 31 (2011)
Issue (Month): 4 ()
Pages: 2933-2943

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Handle: RePEc:ebl:ecbull:eb-10-00813

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Keywords: Poisson regression; maximum likelihood estimation; bias reduction;

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  1. Qian Chen & David E. Giles, 2009. "Finite-Sample Properties of the Maximum Likelihood Estimator for the Poisson Regression Model With Random Covariates," Econometrics Working Papers 0907, Department of Economics, University of Victoria.
  2. David E. Giles, 2009. "Bias Reduction for the Maximum Likelihood Estimator of the Scale Parameter in the Half-Logistic Distribution," Econometrics Working Papers 0901, Department of Economics, University of Victoria.
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