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Hermite regression analysis of multi-modal count data

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  • David E Giles

    ()
    (University of Victoria, Canada)

Abstract

We discuss the modeling of count data whose empirical distribution is both multi-modal and over-dispersed, and propose the Hermite distribution with covariates introduced through the conditional mean. The model is readily estimated by maximum likelihood, and nests the Poisson model as a special case. The Hermite regression model is applied to data for the number of banking and currency crises in IMF-member countries, and is found to out-perform the Poisson and negative binomial models.

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File URL: http://www.accessecon.com/Pubs/EB/2010/Volume30/EB-10-V30-I4-P269.pdf
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Bibliographic Info

Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 30 (2010)
Issue (Month): 4 ()
Pages: 2936-2945

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Handle: RePEc:ebl:ecbull:eb-10-00512

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Related research

Keywords: Count data; multi-modal data; over-dispersion; financial crises;

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  1. Domac, Ilker & Martinez Peria, Maria Soledad, 2003. "Banking crises and exchange rate regimes: is there a link?," Journal of International Economics, Elsevier, vol. 61(1), pages 41-72, October.
  2. Francisco Covas & J.M.C. Santos Silva, 2000. "A modified hurdle model for completed fertility," Journal of Population Economics, Springer, vol. 13(2), pages 173-188.
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Blog mentions

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  1. Count Data & the Hermite Distribution
    by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-04-13 20:54:00

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