The role of “leads" in the dynamic OLS estimation of cointegrating regression models
Use this link to cite this item : https://ir.lib.hiroshima-u.ac.jp/00026402
ID | 26402 |
file | |
creator |
Kurozumi, Eiji
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subject | cointegration
dynamic ordinary least squares estimator
granger causality
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NDC |
Economics
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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. Specifically, we investigate Stock and Watson's [J.H. Stock, M.W. Watson's, A simple estimator of cointegrating vectors in higher order integrated systems, Econometrica 61 (1993) 783–820] claim that the role of leads is related to the concept of Granger causality by a Monte Carlo simulation. From the simulation results, we find that the dynamic OLS estimator without leads substantially outperforms that with leads and lags; we therefore recommend testing for Granger non-causality before estimating models.
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journal title |
Mathematics and Computers in Simulation
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volume | Volume 79
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issue | Issue 3
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start page | 555
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end page | 560
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date of issued | 2008-12
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publisher | Elsevier Ltd
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issn | 0378-4754
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ncid | |
publisher doi | |
language |
eng
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nii type |
Journal Article
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HU type |
Journal Articles
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DCMI type | text
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format | application/pdf
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text version | author
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rights | Copyright (c) 2008 IMACS Published by Elsevier Ltd.
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relation is version of URL | http://dx.doi.org/10.1016/j.matcom.2008.02.027
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department |
Graduate School of Social Sciences
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