INSTRUMENTAL-VARIABLE ESTIMATION OF COUNT DATA MODELS - APPLICATIONS TO MODELS OF CIGARETTE-SMOKING BEHAVIOR

As with most analyses involving microdata, applications of count data models must somehow account for unobserved heterogeneity. The count mo del literature has generally assumed that unobservables and observed c ovariates are statistically independent. Yet for many applications thi s independence assumption is clearly tenuous. When the unobservables a re omitted variables correlated with included regressors, standard est imation methods will generally be inconsistent. Though alternative con sistent estimators may exist in special circumstances, it is suggested here that a nonlinear instrumental-variable strategy. offers a reason ably general solution to such estimation problems. This approach is ap plied in two examples that focus on cigarette smoking behavior.