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Almost Unbiased Estimation of the Poisson Regression Model

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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 an empirical application.

Suggested Citation

  • David E. Giles & Hui Feng, 2009. "Almost Unbiased Estimation of the Poisson Regression Model," Econometrics Working Papers 0909, Department of Economics, University of Victoria.
    • Handle: RePEc:vic:vicewp:0909
    Note: ISSN 1485-6441
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    File URL: https://www.uvic.ca/socialsciences/economics/_assets/docs/econometrics/ewp0909.pdf
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    References listed on IDEAS

    as
    1. Qian Chen & David Giles, 2012. "Finite-sample properties of the maximum likelihood estimator for the binary logit model with random covariates," Statistical Papers, Springer, vol. 53(2), pages 409-426, May.
    2. Atish R. Ghosh & Anne-Marie Gulde & Holger C. Wolf, 2003. "Exchange Rate Regimes: Choices and Consequences," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262072408, December.
    3. 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.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Bias-Corrected MLEs
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-05-01 21:03:00

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    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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