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Modeling Cyclical Asymmetries in GDP: International Evidence

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  • José Cancelo
  • Estefanía Mourelle

Abstract

This paper models asymmetric behavior in GDP growth in the USA, Germany, France, and Japan. It develops smooth transition autoregressive models and interprets nonlinear dynamics in terms of cyclical asymmetries. A procedure for defining data-based, qualitative cyclical regimes from the estimated models is proposed, and generalized impulse response functions are computed to assess to what extent the response to a shock changes over different phases of the cycle. Copyright International Atlantic Economic Society 2005

Suggested Citation

  • José Cancelo & Estefanía Mourelle, 2005. "Modeling Cyclical Asymmetries in GDP: International Evidence," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 33(3), pages 297-309, September.
    • Handle: RePEc:kap:atlecj:v:33:y:2005:i:3:p:297-309
    DOI: 10.1007/s11293-005-8172-x
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    References listed on IDEAS

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    1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    2. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    3. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
    4. Victor Zarnowitz & James H. Stock (ary), 1992. "What is a business cycle?," Proceedings, Federal Reserve Bank of St. Louis, pages 3-83.
    5. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    6. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    7. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    8. repec:bla:econom:v:64:y:1997:i:255:p:441-60 is not listed on IDEAS
    9. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
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    Citations

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    Cited by:

    1. Apergis, Nicholas, 2015. "Financial portfolio choice: Do business cycle regimes matter? Panel evidence from international household surveys," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 14-27.
    2. Almeida, Pedro Cameira de & Fuinhas, José Alberto & Marques, António Cardoso, 2011. "A assimetria dos ciclos económicos: Evidência internacional usando o teste triples [The asymmetry of business cycles: International evidence using triples test]," MPRA Paper 35208, University Library of Munich, Germany.
    3. José Cancelo, 2007. "Cyclical Asymmetries in Unemployment Rates: International Evidence," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 13(3), pages 334-346, August.
    4. repec:kap:iaecre:v:13:y:2007:i:3:p:334-346 is not listed on IDEAS

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    More about this item

    Keywords

    E32; C22; E37;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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