Journal
JOURNAL OF ECONOMETRICS
Volume 128, Issue 1, Pages 99-136Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2004.08.009
Keywords
forecasting; loss function estimation; model selection
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The paper considers multi-step forecasting of a stationary vector process under a quadratic loss function with a collection of finite-order vector autoregressions (VAR). Under severe misspecification it is preferable to use the multi-step loss function also for parameter estimation. We propose a modification to Shibata's (Ann. Statist. 8 (1980) 147) final prediction error criterion to jointly choose the VAR lag order and one of two predictors: the maximum likelihood estimator plug-in predictor or the loss function estimator plug-in predictor. A Monte Carlo experiment illustrates the theoretical results and documents the empirical performance of the selection criterion. (c) 2004 Elsevier B.V. All rights reserved.
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