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MULTISTEP PREDICTION OF PANEL VECTOR AUTOREGRESSIVE PROCESSES

Published online by Cambridge University Press:  16 January 2013

Ryan Greenaway-McGrevy
Ryan Greenaway-McGrevy*
Affiliation:
U.S. Bureau of Economic Analysis
*
*Address feedback and comments to Ryan Greenaway-McGrevy, Bureau of Economic Analysis, 1441 L Street NW, Washington, D.C. 20230, USA; e-mail: [email protected].
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Abstract

This paper considers the conventional recursive (otherwise known as plug-in) and direct multistep forecasts in a panel vector autoregressive framework. We derive asymptotic expressions for the mean square prediction error (MSPE) of both forecasts as N (cross sections) and T (time periods) grow large. Both the bias and variance of the least squares fitting are manifest in the MSPE. Using these expressions, we consider the effect of model specification on predictor accuracy. When the fitted lag order (q) is equal to or exceeds the true lag order (p), the direct MSPE is larger than the recursive MSPE. On the other hand, when the fitted lag order is underspecified, the direct MSPE is smaller than the recursive MSPE. The recursive MSPE is increasing in q for all q ≥ p. In contrast, the direct MSPE is not monotonic in q within the permissible parameter space. Extensions to bias-corrected least squares estimators are considered.

Type
ARTICLES
Information
Econometric Theory , Volume 29 , Issue 4 , August 2013 , pp. 699 - 734
Copyright
Copyright © Cambridge University Press 2013 

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Footnotes

The views expressed herein are those of the author and not necessarily those of the Bureau of Economic Analysis or the Department of Commerce. The author thanks Donggyu Sul, the co-editor, and three anonymous referees for their helpful suggestions and comments.

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