Testing constancy of the error covariance matrix in vector models
AbstractThis paper contains a Lagrange multiplier test of the hypothesis that the covariance matrix of a multivariate time series model is constant over time. It is further assumed that under the alternative, the error variances are time-varying whereas the correlation remain constant over time. Under the parameterized alternative hypothesis the variance may change continuously as a function of time or some observable stochastic variables.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 140 (2007)
Issue (Month): 2 (October)
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Web page: http://www.elsevier.com/locate/jeconom
Other versions of this item:
- Eklund, Bruno & Teräsvirta, Timo, 2003. "Testing constancy of the error covariance matrix in vector models," Working Paper Series in Economics and Finance 549, Stockholm School of Economics, revised 18 Jan 2006.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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