Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables

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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 languageEnglish
Pages (from-to)37-50
JournalJournal of Econometrics
Volume158
Issue number1
DOIs
Publication statusPublished - 1 Jan 2010

Keywords

  • Cointegration
  • Vector autoregression
  • Rare events
  • Impulse response

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