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Hermite regression analysis of multi-modal count data

Author

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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.

Suggested Citation

  • David E Giles, 2010. "Hermite regression analysis of multi-modal count data," Economics Bulletin, AccessEcon, vol. 30(4), pages 2936-2945.
  • Handle: RePEc:ebl:ecbull:eb-10-00512
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    File URL: http://www.accessecon.com/Pubs/EB/2010/Volume30/EB-10-V30-I4-P269.pdf
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    References listed on IDEAS

    as
    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;European Society for Population Economics, vol. 13(2), pages 173-188.
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    Cited by:

    1. Bent Jørgensen & Célestin C. Kokonendji, 2016. "Discrete dispersion models and their Tweedie asymptotics," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(1), pages 43-78, January.

    More about this item

    Keywords

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

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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