On regression-based tests for persistence in logarithmic volatility models
AbstractBuilding on the work of Pantula (1986), this paper discusses how the hypothesis of conditional variance nonstationarity in the logarithmic family of generalized autoregressive conditional heteroskedasticity (GARCH) and stochastic volatility processes may be tested using regression-based tests. The latter are easy to implement, have well-defined large-sample distributions, and are less sensitive to structural changes than tests based on the quasimaximum likelihood estimator.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 18 (1999)
Issue (Month): 4 ()
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- Messow, Philip & Krämer, Walter, 2013. "Spurious persistence in stochastic volatility," Economics Letters, Elsevier, vol. 121(2), pages 221-223.
- Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2013. "Estimation and Inference in Univariate and Multivariate Log-GARCH-X Models When the Conditional Density is Unknown," MPRA Paper 49344, University Library of Munich, Germany.
- repec:imd:wpaper:wp2010-25 is not listed on IDEAS
- Genaro Sucarrat & Alvaro Escribano, 2010. "The power log-GARCH model," Economics Working Papers we1013, Universidad Carlos III, Departamento de Economía.
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