OLS or GLS in the presence of specification error? An expected loss approach

DOI10.1016/0304-4076(87)90033-9zbMath0617.62116OpenAlexW1485112296MaRDI QIDQ1822188

Jerry G. Thursby

Publication date: 1987

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(87)90033-9

zbMATH Keywords

regression analysisheteroscedasticityloss functionautocorrelationOLS estimatorspecification errortime series modelsGLS estimatorOmitted variablescross-section models

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Linear regression; mixed models (62J05)

Related Items (3)

OPTIMALITY OF GLS FOR ONE-STEP-AHEAD FORECASTING WITH REGARIMA AND RELATED MODELS WHEN THE REGRESSION IS MISSPECIFIED ⋮ Using least squares to generate forecasts in regressions with serial correlation ⋮ OLS or GLS in the presence of specification error? An expected loss approach

Cites Work

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• Estimation and testing for functional form and autocorrelation
• OLS or GLS in the presence of specification error? An expected loss approach
• Differencing as a Test of Specification
• A Simplified Version of the Differencing Test
• Some Properties of Tests for Specification Error in a Linear Regression Model
• Specification Tests in Econometrics
• Errors in Variables and Serially Correlated Disturbances in Distributed Lag Models
• The Role of Approximate Prior Restrictions in Distributed Lag Estimation
• Application of Least Squares Regression to Relationships Containing Auto- Correlated Error Terms

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