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Estimation Of The Cyclical Component Of Economic Time Series

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  • Maria-Helena A. Dias
  • Joilson Dias
  • Charles L. Evans

Abstract

The objective of this paper is to show an alternative technique to smooth time series from Monte Carlo Simulations. The technique considers that time series can contain more than one structural break, coming from movements in coefficients of trend or from intercept. The Hodrick-Prescott Filter (HP) does not provide identification of such possible breaks in order to smooth trend from the series to analyze its cyclical component. If the series are relatively stable, this problem may not have relevant implications. Otherwise, for economies relatively unstable, trend movements may interfere in the specification of the cyclical component, and Hodrick-Prescott smoothing could lead empiricists to achieve simplistic forms to economic cycles. In the context, we present an empirical methodology that allows structural breaks in any point of time, from coefficients or from intercepts. We apply this recursive technique to different models with variations in trend, from coefficients and from intercepts, using series simulated by Monte Carlo. Moreover, we compare the results of both techniques to the Brazilian GDP.

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Paper provided by ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics] in its series Anais do XXXII Encontro Nacional de Economia [Proceedings of the 32th Brazilian Economics Meeting] with number 104.

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Date of creation: 2004
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Handle: RePEc:anp:en2004:104

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  1. Perron, P., 1986. "Trends and Random Walks in Macroeconomic Time Series: Further Evidence From a New Approach," Cahiers de recherche 8650, Universite de Montreal, Departement de sciences economiques.
  2. Vogelsang, Timothy J., 1997. "Wald-Type Tests for Detecting Breaks in the Trend Function of a Dynamic Time Series," Econometric Theory, Cambridge University Press, vol. 13(06), pages 818-848, December.
  3. Eric Zivot & Peter C.B. Phillips, 1991. "A Bayesian Analysis of Trend Determination in Economic Time Series," Cowles Foundation Discussion Papers 1002, Cowles Foundation for Research in Economics, Yale University.
  4. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
  5. Phillips, Peter C B & Hansen, Bruce E, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," Review of Economic Studies, Wiley Blackwell, vol. 57(1), pages 99-125, January.
  6. Perron, Pierre & Vogelsang, Timothy J, 1992. "Nonstationarity and Level Shifts with an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 301-20, July.
  7. Bruce E. Hansen, 1998. "Testing for Structural Change in Conditional Models," Boston College Working Papers in Economics 310., Boston College Department of Economics.
  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. Peter C.B. Phillips & Pierre Perron, 1986. "Testing for a Unit Root in Time Series Regression," Cowles Foundation Discussion Papers 795R, Cowles Foundation for Research in Economics, Yale University, revised Sep 1987.
  10. Perron, P., 1989. "Testing For A Unit Root In A Time Series With A Changing Mean," Papers 347, Princeton, Department of Economics - Econometric Research Program.
  11. repec:cup:etheor:v:13:y:1997:i:6:p:818-49 is not listed on IDEAS
  12. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  13. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
  14. Peter C.B. Phillips & Bruce E. Hansen, 1988. "Statistical Inference in Instrumental Variables," Cowles Foundation Discussion Papers 869R, Cowles Foundation for Research in Economics, Yale University, revised Apr 1989.
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