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A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes

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  • Esfandiar Maasoumi
  • Jeffrey S. Racine

Abstract

We consider a metric entropy capable of detecting deviations from symmetry that is suitable for both discrete and continuous processes. A test statistic is constructed from an integrated normed difference between nonparametric estimates of two density functions. The null distribution (symmetry) is obtained by resampling from an artificially lengthened series constructed from a rotation of the original series about its mean (median, mode). Simulations demonstrate that the test has correct size and good power in the direction of interesting alternatives, while applications to updated Nelson & Plosser (1982) data demonstrate its potential power gains relative to existing tests.

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Bibliographic Info

Paper provided by Department of Economics, Emory University (Atlanta) in its series Emory Economics with number 0806.

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Date of creation: Oct 2008
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Handle: RePEc:emo:wp2003:0806

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  1. Bai, Jushan & Ng, Serena, 2001. "A consistent test for conditional symmetry in time series models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 225-258, July.
  2. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, 09.
  3. Jushan Bai & Serena Ng, 2005. "Tests for Skewness, Kurtosis, and Normality for Time Series Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 49-60, January.
  4. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  5. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
  6. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
  7. Dagum, Estela Bee & Giannerini, Simone, 2006. "A critical investigation on detrending procedures for non-linear processes," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 175-191, March.
  8. Gamini Premaratne, 2005. "A Test for Symmetry with Leptokurtic Financial Data," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(2), pages 169-187.
  9. McQueen, Grant & Thorley, Steven, 1993. "Asymmetric business cycle turning points," Journal of Monetary Economics, Elsevier, vol. 31(3), pages 341-362, June.
  10. Belaire-Franch Jorge & Peiro Amado, 2003. "Conditional and Unconditional Asymmetry in U.S. Macroeconomic Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(1), pages 1-19, April.
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Cited by:
  1. Simone Giannerini & Eefandiar Maasoumi & Estela Bee Dagum, 2013. "Entropy Testing for Nonlinearity in Time Series," Emory Economics 1307, Department of Economics, Emory University (Atlanta).
  2. Rafael Salas & Juan RodrĂ­guez, 2013. "Popular support for social evaluation functions," Social Choice and Welfare, Springer, vol. 40(4), pages 985-1014, April.
  3. 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.
  4. Narayan, Paresh Kumar & Popp, Stephan, 2009. "Can the electricity market be characterised by asymmetric behaviour?," Energy Policy, Elsevier, vol. 37(11), pages 4364-4372, November.

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