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

Dong Wan Shin, Han Joon Kim, Won Chul Jhee

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)75-82
Number of pages8
JournalStatistics and Probability Letters
Volume77
Issue number1
DOIs
StatePublished - 1 Jan 2007

Keywords

  • Cointegration
  • Efficiency
  • Generalized least-squares estimator
  • Long-run covariance

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