Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/79360 
Year of Publication: 
2003
Series/Report no.: 
cemmap working paper No. CWP04/03
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
In an effort to improve the small sample properties of generalized method of moments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilting estimators. We show that these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) estimators. We use this structure to compare their higher order asymptotic properties. We find that GEL has no asymptotic bias due to correlation of the moment functions with their Jacobian, eliminating an important source of bias for GMM in models with endogeneity. We also find that EL has no asymptotic bias from estimating the optimal weight matrix, eliminating a further important source of bias for GMM in panel data models. We give bias corrected GMM and GEL estimators. We also show that bias corrected EL inherits the higher order property of maximum likelihood, that it is higher order asymptotically effcient relative to the other bias corrected estimators.
Subjects: 
GMM , Empirical Likelihood , Bias , Higher Order Efficiency , Stochastic Expansions
JEL: 
C13
C30
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
566.21 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.