Blockwise empirical entropy tests for time series regressions
AbstractThis paper shows how the empirical entropy (also known as exponential likelihood or non-parametric tilting) method can be used to test general parametric hypothesis in time series regressions. To capture the weak dependence of the observations, the paper uses blocking techniques which are also used in the bootstrap literature on time series. Monte Carlo evidence suggests that the proposed test statistics have better finite-sample properties than conventional test statistics such as the Wald statistic. Copyright 2005 Blackwell Publishing Ltd.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Time Series Analysis.
Volume (Year): 26 (2005)
Issue (Month): 2 (03)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782
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- Jason Allen & Allan W. Gregory & Katsumi Shimotsu, 2008.
"Empirical Likelihood Block Bootstrapping,"
1156, Queen's University, Department of Economics.
- Allen, Jason & Gregory, Allan W. & Shimotsu, Katsumi, 2010. "Empirical Likelihood Block Bootstrapping," Discussion Papers 2010-01, Graduate School of Economics, Hitotsubashi University.
- Jason Allen & Allan W. Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Working Papers 08-18, Bank of Canada.
- Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," Cowles Foundation Discussion Papers 1569, Cowles Foundation for Research in Economics, Yale University.
- Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," Levine's Bibliography 321307000000000307, UCLA Department of Economics.
- Daniel J. Nordman & Helle Bunzel & Soumendra N. Lahiri, 2012. "A Non-standard Empirical Likelihood for Time Series," CREATES Research Papers 2012-55, School of Economics and Management, University of Aarhus.
- Daniel Nordman, 2008. "An empirical likelihood method for spatial regression," Metrika, Springer, vol. 68(3), pages 351-363, November.
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