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David E Giles
''Hermite regression analysis of multi-modal count data''
( 2010, Vol. 30 No.4 )
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.
Keywords: Count data, multi-modal data, over-dispersion, financial crises
JEL: C4 - Econometric and Statistical Methods: Special Topics
C2 - Single Equation Models; Single Variables: General
Manuscript Received : Aug 19 2010 Manuscript Accepted : Nov 09 2010

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