Testing Parameter Constancy in Stationary Vector Autoregressive Models Against Continuous Change
AbstractIn this article we derive a parameter constancy test of a stationary vector autoregressive model against the hypothesis that the parameters of the model change smoothly over time. A single structural break is contained in this alternative hypothesis as a special case. The test is a generalization of a single-equation test of a similar hypothesis proposed in the literature. An advantage here is that the asymptotic distribution theory is standard. The performance of the tests is compared to that of generalized Chow-tests and found satisfactory in terms of both size and power.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 28 (2009)
Issue (Month): 1-3 ()
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Other versions of this item:
- He, Changli & Teräsvirta, Timo & González, Andres, 2002. "Testing parameter constancy in stationary vector autoregressive models against continuous change," Working Paper Series in Economics and Finance 507, Stockholm School of Economics, revised 06 May 2004.
- 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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