Empirical likelihood in count data models: The case of endogenous regressors - Stefan Boes (University of Zurich, Socioeconomic Institute, 2004)
Recent advances in the econometric modelling of count data have often been based on the generalized method of moments (GMM). However, the two-step GMM procedure may perform poorly in small samples, and several empirical likelihood-based estimators have been suggested alternatively. In this paper I discuss empirical likelihood (EL) estimation for count data models with endogenous regressors. I carefully distinguish between parametric and semi-parametric methods and analyze the properties of the EL estimator by means of a Monte Carlo experiment. I apply the proposed method to estimate the effect of women's schooling on fertility.
Keywords: C14; C25; J13; 330; nonparametric likelihood; Poisson model; endogeneity; fertility and education; Nichtparametrisches Verfahren; Schätztheorie; Statistische Verteilung