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The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity

Hyungsik Moon () and Benoit Perron ()

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

Abstract: This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

Keywords: seemingly unrelated regressions; efficient estimation; rchasing wer rity; cointegration (search for similar items in EconPapers)
JEL-codes: C10 C13 C14 (search for similar items in EconPapers)
Date: 2000
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http://hdl.handle.net/1866/328 (application/pdf)

Related works:
Working Paper: The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:2000-03

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