Abstract
Quasi-maximum-likelihood (QML) estimation of a model combining cointegration in the conditional mean and rare large shocks (outliers) with a factor structure in the innovations is studied. The goal is not only to robustify inference on the conditional-mean parameters, but also to find regularities and conduct inference on the instantaneous and long-run effect of the large shocks. Given the cointegration rank and the factor order, chi(2) asymptotic inference is obtained for the cointegration vectors, the short-run parameters, and the direction of each column of both the factor loading matrix and the matrix of long-run impacts of the large shocks. Large shocks, whose location is assumed unknown a priori, can be detected and classified consistently into the factor components. (C) 2010 Elsevier B.V. All rights reserved.
Original language | English |
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Pages (from-to) | 37-50 |
Journal | Journal of Econometrics |
Volume | 158 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2010 |
Keywords
- Cointegration
- Vector autoregression
- Rare events
- Impulse response