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The Review of Economics and Statistics Vol. 79 No. 4 1997

Instrumental-Variable Estimation of Count Data Models: Applications to Models of Cigarette Smoking Behavior

John Mullahy

University of Wisconsin–Madison

Abstract

As with most analyses involving microdata, applications of count data models must somehow account for unobserved heterogeneity. The count model literature has generally assumed that unobservables and observed covariates are statistically independent. Yet for many applications this independence assumption is clearly tenuous. When the unobservables are omitted variables correlated with included regressors, standard estimation methods will generally be inconsistent. Though alternative consistent estimators may exist in special circumstances, it is suggested here that a nonlinear instrumental-variable strategy offers a reasonably general solution to such estimation problems. This approach is applied in two examples that focus on cigarette smoking behavior.

DOI
10.1162/003465397557169
Volume
79
Issue
4
Pages
586-593
Language
en
Sources
openalex crossref

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