Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-52190
Boes, Stefan (2004). Empirical Likelihood in Count Data Models: The Case of Endogenous Regressors. Working paper series / Socioeconomic Institute No. 404, University of Zurich.
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.
509 downloads since deposited on 29 Nov 2011
136 downloads since 12 months
|Item Type:||Working Paper|
|Communities & Collections:||03 Faculty of Economics > Department of Economics
Working Paper Series > Socioeconomic Institute (former)
|Dewey Decimal Classification:||330 Economics|
|JEL Classification:||C14, C25, J13|
|Deposited On:||29 Nov 2011 22:32|
|Last Modified:||09 Jul 2012 05:03|
|Series Name:||Working paper series / Socioeconomic Institute|
Users (please log in): suggest update or correction for this item
Repository Staff Only: item control page