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Co‐integration constraint and forecasting: An empirical examination

Co‐integration constraint and forecasting: An empirical examination Does co‐integration help long‐term forecasts? In this paper, we use simulation, real data sets, and multi‐step‐ahead post‐sample forecasts to study this question. Based on the square root of the trace of forecasting error‐covariance matrix, we found that for simulated data imposing the ‘correct’ unit‐root constraints implied by co‐integration does improve the accuracy of forecasts. For real data sets, the answer is mixed. Imposing unit‐root constraints suggested by co‐integration tests produces better forecasts for some cases, but fares poorly for others. We give some explanations for the poor performance of co‐integration in long‐term forecasting and discuss the practical implications of the study. Finally, an adaptive forecasting procedure is found to perform well in one‐ to ten‐step‐ahead forecasts. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Econometrics Wiley

Co‐integration constraint and forecasting: An empirical examination

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References (15)

Publisher
Wiley
Copyright
Copyright © 1996 John Wiley & Sons, Ltd.
ISSN
0883-7252
eISSN
1099-1255
DOI
10.1002/(SICI)1099-1255(199609)11:5<519::AID-JAE410>3.0.CO;2-Q
Publisher site
See Article on Publisher Site

Abstract

Does co‐integration help long‐term forecasts? In this paper, we use simulation, real data sets, and multi‐step‐ahead post‐sample forecasts to study this question. Based on the square root of the trace of forecasting error‐covariance matrix, we found that for simulated data imposing the ‘correct’ unit‐root constraints implied by co‐integration does improve the accuracy of forecasts. For real data sets, the answer is mixed. Imposing unit‐root constraints suggested by co‐integration tests produces better forecasts for some cases, but fares poorly for others. We give some explanations for the poor performance of co‐integration in long‐term forecasting and discuss the practical implications of the study. Finally, an adaptive forecasting procedure is found to perform well in one‐ to ten‐step‐ahead forecasts.

Journal

Journal of Applied EconometricsWiley

Published: Sep 1, 1996

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