Robust estimation for structural spurious regressions and a Hausman-type cointegration test

Chi Young Choi, Ling Hu, Masao Ogaki

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)


This paper analyzes an approach to correcting spurious regressions involving unit-root nonstationary variables by generalized least squares (GLS) using asymptotic theory. This analysis leads to a new robust estimator and a new test for dynamic regressions. The robust estimator is consistent for structural parameters not just when the regression error is stationary but also when it is unit-root nonstationary under certain conditions. We also develop a Hausman-type test for the null hypothesis of cointegration for dynamic ordinary least squares (OLS) estimation. We demonstrate our estimation and testing methods in three applications: (i) long-run money demand in the U.S., (ii) output convergence among industrial and developing countries, and (iii) purchasing power parity (PPP) for traded and non-traded goods.

Original languageEnglish
Pages (from-to)327-351
Number of pages25
JournalJournal of Econometrics
Issue number1
Publication statusPublished - 2008 Jan
Externally publishedYes


  • Dynamic regression
  • GLS correction method
  • Spurious regression
  • Test for cointegration

ASJC Scopus subject areas

  • Economics and Econometrics


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