IGARCH effect on autoregressive lag length selection and causality tests
AbstractUsing Monte Carlo experiments, we show how information criteria determine, in the presence of GARCH errors, an optimal lag length in univariate time series and causality tests. We illustrate the simulations by testing the presence of serial correlation in exchange rates as well as Granger-causality between interest rates.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics Letters.
Volume (Year): 3 (1996)
Issue (Month): 5 ()
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- Jerome Henry & Jens Weidmann, 2005. "The French-German Interest Rate Differential Since German," International Finance 0503009, EconWPA.
- R. Scott Hacker & Abdulnasser Hatemi-J, 2006. "Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application," Applied Economics, Taylor & Francis Journals, vol. 38(13), pages 1489-1500.
- Stavros Degiannakis & Evdokia Xekalaki, 2007. "Assessing the performance of a prediction error criterion model selection algorithm in the context of ARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 149-171.
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