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Asymmetries in the Conditional Mean Dynamics of Real GNP: Robust Evidence

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  • Prasad V. Bidarkota

Abstract

We investigate asymmetries in the conditional mean dynamics of U.S. GNP. Because the statistical evidence on nonlinearities in the conditional mean could be influenced by the presence of outliers or by a failure to model conditional heter oske dasticity, we explicitly account for outliers by assuming that the innovations are drawn from the stable family, and model time-varying volatility by a GARCH(1, 1) process. We also allow for the possibility of long memory in the series with fractional differencing. Our results indicate statistically significant nonlinearities in the conditional mean that persist even after accounting for these features in the data. © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

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  • Prasad V. Bidarkota, 2000. "Asymmetries in the Conditional Mean Dynamics of Real GNP: Robust Evidence," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 153-157, February.
    • Handle: RePEc:tpr:restat:v:82:y:2000:i:1:p:153-157
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    Cited by:

    1. Kiani, K.M., 2009. "Neural Networks to Detect Nonlinearities in Time Series: Analysis of Business Cycle in France and the United Kingdom," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
    2. George, Halkos & Ilias, Kevork, 2005. "Το Υπόδειγμα Τυχαίου Περιπάτου Με Αυτοπαλίνδρομα Σφάλματα [The random walk model with autoregressive errors]," MPRA Paper 33312, University Library of Munich, Germany.
    3. Bidarkota, Prasad V. & McCulloch, J. Huston, 2003. "Consumption asset pricing with stable shocks--exploring a solution and its implications for mean equity returns," Journal of Economic Dynamics and Control, Elsevier, vol. 27(3), pages 399-421, January.
    4. Bildirici, Melike & Alp, Aykaç, 2008. "The Relationship Between Wages and Productivity: TAR Unit Root and TAR Cointegration Approach," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 5(1), pages 93-110.
    5. Khurshid M. Kiani, 2007. "Asymmetric Business Cycle Fluctuations and Contagion Effects in G7 Countries," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 6(3), pages 237-253, December.
    6. Khurshid M. KIANI & Terry L. KASTENS, 2006. "Using Macro-Financial Variables To Forecast Recessions. An Analysis Of Canada, 1957-2002," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(3).
    7. 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.
    8. KIANI, Khurshid M., 2007. "Business Cycle Asymmetries In Stock Returns: Robust Evidence," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 4(2), pages 99-120.
    9. 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.
    10. Prasad V. Bidarkota and J. Huston McCulloch, 2001. "Consumption Asset Pricing with Stable Shocks: Exploring a Solution and Its Implications for the Equity Premium Puzzle," Computing in Economics and Finance 2001 70, Society for Computational Economics.
    11. Ana Bartolome & Michael McAleer & Vicente Ramos & Javier Rey-Maquieira, 2009. "Cruising is Risky Business," CIRJE F-Series CIRJE-F-664, CIRJE, Faculty of Economics, University of Tokyo.
    12. Yasuhiko Nakamura, 2008. "On Forecasting Recessions via Neural Nets," Economics Bulletin, AccessEcon, vol. 3(13), pages 1-15.
    13. Khurshid Kiani, 2005. "Detecting Business Cycle Asymmetries Using Artificial Neural Networks and Time Series Models," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 65-89, August.
    14. Chaudhuri, Kausik & Wu, Yangru, 2003. "Random walk versus breaking trend in stock prices: Evidence from emerging markets," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 575-592, April.
    15. George Halkos & Ilias Kevork, 2005. "A comparison of alternative unit root tests," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(1), pages 45-60.

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