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

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

Abstract

For seemingly unrelated regression (SUR) models with integrated regressors, two sufficient conditions are identified, under which the ordinary least-squares estimator (OLSE) is asymptotically efficient. The first condition is that every pair of regressor processes are cointegrated in a specific way that one regressor is a linear combination of the other regressor up to a zero-mean stationary error and the second condition is that, for every pair of regressor processes, the pair of error processes deriving the regressor processes have zero long-run covariance.

Suggested Citation

  • Shin, Dong Wan & Joon Kim, Han & Jhee, Won-Chul, 2007. "Asymptotic efficiency of the ordinary least-squares estimator for sur models with integrated regressors," Statistics & Probability Letters, Elsevier, vol. 77(1), pages 75-82, January.
    • Handle: RePEc:eee:stapro:v:77:y:2007:i:1:p:75-82
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