The unconditional distributions of the OLS, TSLS and LIML estimators in a simple structural equations model
Giovanni Forchini and
Bin Jiang
Econometric Reviews, 2019, vol. 38, issue 2, 208-247
Abstract:
The exact distributions of the standard estimators of the structural coefficients in a linear structural equations model conditional on the exogenous variables have been shown to have some unexpected and quirky features. Since the argument for conditioning on exogenous (ancillary) variables has been weakened over the past 20 years by the discovery of an “ancillarity paradox,” it is natural to wonder whether such finite sample properties are in fact due to conditioning on the exogenous variables. This article studies the exact distributions of the ordinary least squares (OLS), two-stage least squares (TSLS), and limited information maximum likelihood (LIML) estimators of the structural coefficients in a linear structural equation without conditioning on the exogenous variables.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/07474938.2016.1261072 (text/html)
Access to full text is restricted to subscribers.
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:taf:emetrv:v:38:y:2019:i:2:p:208-247
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/LECR20
DOI: 10.1080/07474938.2016.1261072
Access Statistics for this article
Econometric Reviews is currently edited by Dr. Essie Maasoumi
More articles in Econometric Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by ().