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Hermite Regression Analysis of Multi-Modal Count Data

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Abstract

We discuss the modeling of count data whose empirical distribution is both multi-modal and overdispersed, 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," Econometrics Working Papers 1001, Department of Economics, University of Victoria.
    • Handle: RePEc:vic:vicewp:1001
    Note: ISSN 1485-6441
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Count Data & the Hermite Distribution
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-04-14 01:54:00

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    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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