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Asymmetric persistence in GDP? A deeper look at depth

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  • Hess, Gregory D.
  • Iwata, Shigeru

Abstract

If economic time series behave asymmetrically, then an interpretation of economic fluctuations based on linear time series models could be misleading. Beaudry and Koop (1993) recently argued that for post war U.S. GDP data there exists a statistically significant difference in persistence between negative and positive shocks. Their finding, if true, would be quite interesting since it would bring a new perspective to the literature on business cycle, which has been dominated by two conflicting views: the trend-reverting view of Blanchard (1981) and the permanent view of Campbell and Mankiw (1987). The purpose of this paper is to reexamine the evidence of asymmetric persistence of GDP by analyzing the statistical properties of BK's test. In particular, we show there are two pitfalls for this test: First, the t-statistic for testing asymmetry in persistence does not have a conventional interpretation. Second, a highly significant t-value may come from sources different from asymmetry. Using international data, we also explore the robustness of the BK result across the G-7 countries and find that the evidence is quite varied. Moreover, there appears to be no simple explanation for why countries display similar types of asymmetric behavior.
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  • Hess, Gregory D. & Iwata, Shigeru, 1997. "Asymmetric persistence in GDP? A deeper look at depth," Journal of Monetary Economics, Elsevier, vol. 40(3), pages 535-554, December.
  • Handle: RePEc:eee:moneco:v:40:y:1997:i:3:p:535-554
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    13. Clements, Michael P & Krolzig, Hans-Martin, 2003. "Business Cycle Asymmetries: Characterization and Testing Based on Markov-Switching Autoregressions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 196-211, January.
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    15. Luo, Bin & Gao, Xiaoli, 2022. "High-dimensional robust approximated M-estimators for mean regression with asymmetric data," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    16. Beatriz C. Galvao, Ana, 2002. "Can non-linear time series models generate US business cycle asymmetric shape?," Economics Letters, Elsevier, vol. 77(2), pages 187-194, October.
    17. Chang‐Jin Kim & James Morley & Jeremy Piger, 2005. "Nonlinearity and the permanent effects of recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 291-309.
    18. Khurshid M. Kiani & Prasad V. Bidarkota, 2004. "On Business Cycle Asymmetries in G7 Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 333-351, July.
    19. Ishida, Junichiro & Yokoo, Masanori, 2004. "Threshold nonlinearities and asymmetric endogenous business cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 54(2), pages 175-189, June.
    20. Diego Valderrama, 2002. "Nonlinearities in international business cycles," Working Paper Series 2002-23, Federal Reserve Bank of San Francisco.
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    22. Khurshid M. Kiani, 2009. "Asymmetries in Macroeconomic Time Series in Eleven Asian Economies," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 8(1), pages 37-54, April.
    23. Mahmood Ul Hassan & Pär Stockhammar, 2016. "Fitting probability distributions to economic growth: a maximum likelihood approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(9), pages 1583-1603, July.
    24. Matti Vir, 2000. "Analysing long memory and asymmetries," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 240-258.
    25. Lima, Luiz Renato & Xiao, Zhijie, 2007. "Do shocks last forever? Local persistency in economic time series," Journal of Macroeconomics, Elsevier, vol. 29(1), pages 103-122, March.

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