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Biased-Reduced Maximum Likelihood Estimation for the Zero-Inflated Poisson Distribution

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Abstract

We investigate the small-sample quality of the maximum likelihood estimators (MLEs) of the parameters of the zero-inflated Poisson distribution. The finite-sample biases are determined to O(n-1) using an analytic bias reduction methodology based on the work of Cox and Snell (1968) and Cordeiro and Klein (1994). Monte Carlo simulations show that the MLEs have very small percentage biases for this distribution, but the analytic bias reduction methods essentially eliminate the bias without adversely affecting the mean squared error s of the estimators. The analytic adjustment compares favourably with the parametric bootstrap bias-corrected estimator, in terms of bias reduction itself, as well as with respect to mean squared error and Pitman’s nearness measure.

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File URL: http://www.uvic.ca/socialsciences/economics/assets/docs/econometrics/ewp1102.pdf
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Bibliographic Info

Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 1102.

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Length: 18 pages
Date of creation: 15 Feb 2011
Date of revision:
Handle: RePEc:vic:vicewp:1102

Note: ISSN 1485-6441
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Web page: http://web.uvic.ca/econ
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Keywords: Zero-inflated Poisson; bias reduction; maximum likelihood estimation; bootstrap;

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  1. 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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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 16:03:00
  2. Measuring the Quality of an Estimator
    by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2013-03-05 00:41:00

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