Faculty Digital Archive

Archive@NYU >
Stern School of Business >
Economics Working Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2451/26039

Title: Functional Form and Heterogeneity in Models for Count Data
Authors: Greene, William
Keywords: Poisson regression
Negative binomial
Panel data
Heterogeneity
Lognormal
Bivariate Poisson
Zero inflation
Two part model
Hurdle model
Issue Date: Apr-2007
Series/Report no.: EC-07-10
Abstract: This study presents several extensions of the most familiar models for count data, the Poisson and negative binomial models. We develop an encompassing model for two well known variants of the negative binomial model (the NB1 and NB2 forms). We then propose some alternative approaches to the standard log gamma model for introducing heterogeneity into the loglinear conditional means for these models. The lognormal model provides a versatile alternative specification that is more flexible (and more natural) than the log gamma form, and provides a platform for several “two part” extensions, including zero inflation, hurdle and sample selection models. We also resolve some features in Hausman, Hall and Griliches’s (1984) widely used panel data treatments for the Poisson and negative binomial models that appear to conflict with more familiar models of fixed and random effects. Finally, we consider a bivariate Poisson model that is also based on the lognormal heterogeneity model. Two recent applications have used this model. We suggest that the correlation estimated in their model frameworks is an ambiguous measure of the correlation of the variables of interest, and may substantially overstate it. We conclude with a detailed application of the proposed methods using the data employed in one of the two aforementioned bivariate Poisson studies.
URI: http://hdl.handle.net/2451/26039
Appears in Collections:Economics Working Papers

Files in This Item:

File Description SizeFormat
7-10.pdf520.46 kBAdobe PDFView/Open

Items in Faculty Digital Archive are protected by copyright, with all rights reserved, unless otherwise indicated.

 

The contents of the FDA may be subject to copyright, be offered under a Creative Commons license, or be in the public domain.
Please check items for rights statements. For information about NYU’s copyright policy, see http://www.nyu.edu/footer/copyright-and-fair-use.html 
Valid XHTML 1.0 | CSS