Asymptotic efficiency of the ordinary least-squares estimator for SUR models with integrated regressors

DOI10.1016/j.spl.2006.05.024zbMath1107.62054OpenAlexW2090828612MaRDI QIDQ870325

Dong Wan Shin, Han Joon Kim, Won-Chul Jhee

Publication date: 12 March 2007

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2006.05.024

zbMATH Keywords

efficiencycointegrationgeneralized least-squares estimatorlong-run covariance

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05)

Cites Work

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• Statistical Inference in Instrumental Variables Regression with I(1) Processes
• Fully modified semiparametric GLS estimation for regressions with nonstationary seasonal regressors
• Time series: theory and methods
• Limiting efficiency of OLS vs. GLS when regressors are fractionally integrated
• Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments.
• A note on fully-modified estimation of seemingly unrelated regression models with integrated regressors.
• Matrix Analysis
• Least Squares Regression When the Independent Variable Follows an ARIMA Process
• Multiple Time Series Regression with Integrated Processes
• Asymptotic Equivalence of Ordinary Least Squares and Generalized Least Squares in Regressions With Integrated Regressors
• ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR FOR REGRESSIONS WITH UNSTABLE REGRESSORS
• When are Gauss-Markov and Least Squares Estimators Identical? A Coordinate-Free Approach
• On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
• An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias