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The unconditional distributions of the OLS, TSLS and LIML estimators in a simple structural equations model
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.ORCID iD: 0000-0002-1377-9469
2017 (English)In: Econometric Reviews, no forthcomingArticle in journal (Refereed) In press
Abstract [en]

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.

Place, publisher, year, edition, pages
2017. no forthcoming
Keyword [en]
Exact distribution, limited information maximum likelihood, linear structural equations, ordinary least squares, two-stage least squares
National Category
Economics and Business
Research subject
Econometrics
Identifiers
URN: urn:nbn:se:umu:diva-131480DOI: 10.1080/07474938.2016.1261072OAI: oai:DiVA.org:umu-131480DiVA: diva2:1074372
Available from: 2017-02-15 Created: 2017-02-15 Last updated: 2017-03-06

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf