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Do WAEMU Countries Exhibit a Regional Business Cycle?. A Simulated Markov Switching Model for a Western Africa area

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  • Aka, B.F.

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    Abstract

    This paper examines the issue of existence and identification of a regional business or economic cycle in aggregated West African economic and monetary union (WAEMU) economy and single member countries’ real GDP as well, by using a Markov regime switching model and the Gibbs Sampling simulation method. We found similarities of business cycle among individual countries. Comparing countries’ cycles to the aggregated one, the chronology and amplitude of Côte d’Ivoire’s business cycle appears to be closer to the union’s cycle. Using the real GDP data the aggregated WAEMU business cycle can be characterized, according to its mean duration (8 years), as a Juglar type cycle.

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    Bibliographic Info

    Article provided by Euro-American Association of Economic Development in its journal Applied Econometrics and International Development.

    Volume (Year): 4 (2004)
    Issue (Month): 4 ()
    Pages:

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    Handle: RePEc:eaa:aeinde:v:4:y:2004:i:1_27

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    Related research

    Keywords: Growth; Business cycles; Non-linear Time series; Markov Switching model; Gibbs sampling;

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    1. Guisan, M.Carmen & Aguayo, Eva & Exposito, Pilar, 2001. "Economic growth and cycles: Cross-country models of education, industry and fertility and international comparisons," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 1(1), pages 9-37.
    2. 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.
    3. Clements, M.P. & Krolzig, H-M., 1999. "Business Cycle Asymmetries: Characterisationand Testing Based on Markov-Switching Autoregression," The Warwick Economics Research Paper Series (TWERPS) 522, University of Warwick, Department of Economics.
    4. Krolzig, H.-M. & Toro, J., 2001. "Classical And Modern Business Cycle Measurement: The European Case," Economics Series Working Papers 9960, University of Oxford, Department of Economics.
    5. Clark, Peter K, 1987. "The Cyclical Component of U.S. Economic Activity," The Quarterly Journal of Economics, MIT Press, vol. 102(4), pages 797-814, November.
    6. Holmes, Mark J, 2003. "Are the Trade Deficits of Less Developed Countries Stationary?. Evidence for African Countries," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 3(3).
    7. Hamilton, James D, 1991. "A Quasi-Bayesian Approach to Estimating Parameters for Mixtures of Normal Distributions," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 27-39, January.
    8. 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 357-84, March.
    9. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1991. "Stochastic trends and economic fluctuations," Working Paper Series, Macroeconomic Issues 91-4, Federal Reserve Bank of Chicago.
    10. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-27, June.
    11. Krolzig, Hans-Martin, 2001. "Business cycle measurement in the presence of structural change: international evidence," International Journal of Forecasting, Elsevier, vol. 17(3), pages 349-368.
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