Estimation in dynamic panel data models: Improving on the performance of the standard GMM estimator

R Blundell, S Bond, F Windmeijer

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

208 Citations (Scopus)

Abstract

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 bins. An application to panel production function data for the U.S. is provided and confirms these theoretical and experimental findings.

Original languageEnglish
Title of host publicationADVANCES ECOOMETRICS, VOL 15, 2000
Place of PublicationNEW YORK
PublisherJAI-Elsevier Science Inc
Pages53-91
Number of pages39
Publication statusPublished - 2000

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