Information-Theoretic Analysis of Serial Dependence and Cointegration
AbstractThis paper is devoted to presenting wider characterizations of memory and cointegration in time series, in terms of information-theoretic statistics such as the entropy and the mutual information between pairs of variables. We suggest a nonparametric and nonlinear methodology for data analysis and for testing the hypotheses of long memory and the existence of a cointegrating relationship in a nonlinear context. This new framework represents a natural extension of the linear-memory concepts based on correlations. Finally, we show that our testing devices seem promising for exploratory analysis with nonlinearly cointegrated time series.
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Bibliographic InfoArticle provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.
Volume (Year): 3 (1998)
Issue (Month): 3 (October)
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Web page: http://www.degruyter.com
Other versions of this item:
- Aparicio, Felipe M. & Escribano, Álvaro, 1998. "Information-Theoretic Analysis of Serial Dependence and Cointegration," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/2560, Universidad Carlos III de Madrid.
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- Dilip M. Nachane, 2011. "Selected Problems in the Analysis of Nonstationary & Nonlinear Time Series," Journal of Quantitative Economics, The Indian Econometric Society, vol. 9(1), pages 1-17.
- Felipe M. Aparicio & Alvaro Escribano, 2003. "Cointegration Tests Based On Record Counting Statistics," Statistics and Econometrics Working Papers ws036615, Universidad Carlos III, Departamento de Estadística y Econometría.
- Yoon, Gawon, 2010. "Do real exchange rates really follow threshold autoregressive or exponential smooth transition autoregressive models?," Economic Modelling, Elsevier, vol. 27(2), pages 605-612, March.
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