The Role of "Leads" in the Dynamic OLS Estimation of Cointegrating Regression Models

Kazuhiko Hayakawa and Eiji Kurozumi ()

Hi-Stat Discussion Paper Series from Institute of Economic Research, Hitotsubashi University

Abstract: In this paper, we consider the role of "leads" of the first difference of integrated variables in the dynamic OLS estimation of cointegrating regression models. We demonstrate that the role of leads is related to the concept of Granger causality and that in some cases leads are unnecessary in the dynamic OLS estimation of cointegrating regression models. Based on a Monte Carlo simulation, we find that the dynamic OLS estimator without leads substantially outperforms that with leads and lags; we therefore recommend testing for Granger noncausality before estimating models.

Keywords: Cointegration; dynamic ordinary least squares estimator; Granger causality (search for similar items in EconPapers)
JEL-codes: C13 C22 (search for similar items in EconPapers)
Date: 2006-12
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: The role of “leads” in the dynamic OLS estimation of cointegrating regression models (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:hst:hstdps:d06-194

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