Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/76239
Authors: 
Boes, Stefan
Year of Publication: 
2007
Series/Report no.: 
Working Paper, Socioeconomic Institute, University of Zurich 0704
Abstract: 
As previously argued, the correlation between included and omitted regressors generally causes inconsistency of standard estimators for count data models. Using a specific residual function and suitable instruments, a consistent generalized method of moments estimator can be obtained under conditional moment restrictions. This approach is extended here by fully exploiting the model assumptions and thereby improving efficiency of the resulting estimator. Empirical likelihood estimation in particular has favorable properties in this setting compared to the two-step GMM procedure, which is demonstrated in a Monte Carlo experiment. The proposed method is applied to the estimation of a cigarette demand function.
Subjects: 
nonparametric likelihood
poisson model
nonlinear instrumental variables
optimal instruments
approximating functions
semiparametric efficiency
JEL: 
C14
C25
D12
Document Type: 
Working Paper

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