Lag-augmented two- and three-stage least squares estimators for integrated structural dynamic models
Cheng Hsiao and
Siyan Wang ()
Econometrics Journal, 2007, vol. 10, issue 1, 49-81
Abstract:
We consider a lag-augmented two- or three-stage least-squares estimator for a structural dynamic model of non-stationary and possibly cointegrated variables without the prior knowledge of unit roots or rank of cointegration. We show that the conventional two-and three-stage least-squares estimators are consistent but contain non-standard distributions without the strict exogeneity assumption; hence the conventional Wald type test statistics may not be chi-square distributed. We propose a lag order augmented two- or three-stage least-squares estimator that is consistent and asymptotically normally distributed. Limited Monte Carlo studies are conducted to shed light on the finite sample properties of various estimators. Copyright Royal Economic Society 2007
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (4)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Working Paper: Lag-Augmented Two- and Three-Stage Least Squares Estimators for Integrated Structural Dynamic Models (2006)
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:ect:emjrnl:v:10:y:2007:i:1:p:49-81
Ordering information: This journal article can be ordered from
http://www.ectj.org
Access Statistics for this article
Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms
More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().