Please use this identifier to cite or link to this item:
Blundell, Richard
Bond, Steve
Windmeijer, Frank
Year of Publication: 
Series/Report no.: 
IFS Working Papers W00/12
This chapter reviews developments to improve on the poor performance of the standard GMM estimator for highly autoregressive panel series. It considers the use of the system GMM estimator that relies on relatively mild restrictions on the initial condition process. This system GMM estimator encompasses the GMM estimator based on the non-linear moment conditions available in the dynamic error components model and has substantial asymptotic efficiency gains. Simulations, that include weakly exogenous covariates, find large finite sample biases and very low precision for the standard first differenced estimator. The use of the system GMM estimator not only greatly improves the precision but also greatly reduces the finite sample bias. An application to panel production function data for the US is provided and confirms these theoretical and experimental findings.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
444.25 kB

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