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Application of Three Alternative Approaches to Identify Business Cycles in Peru

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  • Rodriguez Gabriel

    ()
    (Universidad of Ottawa and Central Bank of Peru)

Abstract

Three alternative econometric approaches are used to estimate business cycles in the Peruvian economy. These approaches are the Plucking model due to Friedman (1964, 1993), the Markov Switching model proposed by Hamilton (1989) and the Smooth Transition Autoregressive (STAR) model suggested by Teräsvirta (1994). The results show strong rejection of the null hypothesis of linearity, presence of asymmetries and nonlinearities. Furthermore, the methods allow to find the principal episodes of recession for the Peruvian economy.

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Bibliographic Info

Paper provided by Banco Central de Reserva del Perú in its series Working Papers with number 2007-007.

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Date of creation: May 2007
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Handle: RePEc:rbp:wpaper:2007-007

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Keywords: Asymmetries; Business Regional Fluctuations; Markov Switching; Transitory and Permanent Components;

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  1. Friedman, Milton, 1993. "The "Plucking Model" of Business Fluctuations Revisited," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 171-77, April.
  2. Lundbergh, Stefan & Teräsvirta, Timo, 1998. "Modelling economic high-frequency time series with STAR-STGARCH models," Working Paper Series in Economics and Finance 291, Stockholm School of Economics.
  3. 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.
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  14. Kim, C-J & Nelson, C-R, 1997. "Friedman's Plucking Model of Business Fluctuations : Tests and Estimates of Permanent and Transitory Components," Discussion Papers in Economics at the University of Washington 97-06, Department of Economics at the University of Washington.
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  18. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
  19. 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.
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  21. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  22. Jansen, Eilev S & Terasvirta, Timo, 1996. "Testing Parameter Constancy and Super Exogeneity in Econometric Equations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 735-63, November.
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  25. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
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  27. 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 307-28, April.
  28. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
  29. 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 S119-36, Suppl. De.
  30. Michael, Panos & Nobay, A Robert & Peel, David A, 1997. "Transactions Costs and Nonlinear Adjustment in Real Exchange Rates: An Empirical Investigation," Journal of Political Economy, University of Chicago Press, vol. 105(4), pages 862-79, August.
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