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Forecasting in large cointegrated processes

✍ Scribed by Hiroaki Chigira; Taku Yamamoto

Book ID
102215306
Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
276 KB
Volume
28
Category
Article
ISSN
0277-6693

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✦ Synopsis

Abstract

It is widely recognized that taking cointegration relationships into consideration is useful in forecasting cointegrated processes. However, there are a few practical problems when forecasting large cointegrated processes using the well‐known vector error correction model. First, it is hard to identify the cointegration rank in large models. Second, since the number of parameters to be estimated tends to be large relative to the sample size in large models, estimators will have large standard errors, and so will forecasts. The purpose of the present paper is to propose a new procedure for forecasting large cointegrated processes which is free from the above problems. In our Monte Carlo experiment, we find that our forecast gains accuracy when we work with a larger model as long as the ratio of the cointegration rank to the number of variables in the process is high. Copyright Β© 2009 John Wiley & Sons, Ltd.

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