Efficient Estimation with Panel Data When Instruments Are Predetermined: An Empirical Comparison of Moment-Condition Estimators

James Ziliak

Journal of Business & Economic Statistics, 1997, vol. 15, issue 4, 419-31

Abstract: The author examines the empirical performance of instrumental variables estimators with predetermined instruments in an application to life-cycle labor supply under uncertainty. The estimators studied are two stage least squares, generalized method-of-moments (GMM), forward filter, independently weighted GMM, and split-sample instrumental variables. The author compares the bias/efficiency trade-off for the estimators using bootstrap algorithms suggested by D. A. Freedman (1984) and B. W. Brown and W. K. Newey (1995). Results indicate that the downward bias in GMM is quite severe as the number of moment conditions expands, outweighing the gains in efficiency. The forward filter estimator, however, has lower bias and is more efficient than two stage least squares.

Date: 1997
References: Add references at CitEc
Citations: View citations in EconPapers (145)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:15:y:1997:i:4:p:419-31

Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano

More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().