期刊
JOURNAL OF ECONOMETRICS
卷 164, 期 2, 页码 218-238出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2011.04.003
关键词
Structural breaks; AIC; Mallows' Cp; BIC; Information criteria
资金
- Ministry of Education, Culture, Sports, Science and Technology [18730142]
- 21st Century Center of Excellence Project
- Global COE program
- Research Unit for Statistical and Empirical Analysis in Social Sciences at Hitotsubashi University
- Grants-in-Aid for Scientific Research [23243038, 18730142] Funding Source: KAKEN
This paper considers the issue of selecting the number of regressors and the number of structural breaks in multivariate regression models in the possible presence of multiple structural changes. We develop a modified Akaike information criterion (AIC), a modified Mallows' C(p) criterion and a modified Bayesian information criterion (BIC). The penalty terms in these criteria are shown to be different from the usual terms. We prove that the modified BIC consistently selects the regressors and the number of breaks whereas the modified AIC and the modified C(p) criterion tend to overfit with positive probability. The finite sample performance of these criteria is investigated through Monte Carlo simulations and it turns out that our modification is successful in comparison to the classical model selection criteria and the sequential testing procedure robust to heteroskedasticity and autocorrelation. (C) 2011 Elsevier B.V. All rights reserved.
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