Abstract
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 language | English |
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Pages (from-to) | 327-351 |
Number of pages | 25 |
Journal | Journal of Econometrics |
Volume | 142 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2008 Jan |
Externally published | Yes |
Keywords
- Dynamic regression
- GLS correction method
- Spurious regression
- Test for cointegration
ASJC Scopus subject areas
- Economics and Econometrics