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A Proposal To Obtain A Long Quarterly Chilean Gdp Series

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  • Juan de Dios Tena

    ()

  • Miguel Jerez
  • Sonia Sotoca
  • Nicole Carvallo

Abstract

An important limitation in order to specify and estimate a macroeconomic model that describes the Chilean economy resides in using variables with sufficient number of observations that allow for a reliable econometric estimation. Among these variables, the GDP constitutes a fundamental magnitude. Nevertheless, for this variable there is not quarterly information before 1980. This paper computes quarterly GDP series for the period 1966-1979 using the approach by Casals et al (2000). As result, the new series incorporates the cyclical dynamic in the quarterly series later to 1979 respecting, in addition, all the annual existing information before the above mentioned period.

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Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws061706.

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Date of creation: Mar 2006
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Handle: RePEc:cte:wsrepe:ws061706

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  1. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
  2. Ernest Pons Fanals & Jordi Pons Novell & Jordi Surinach Caralt, 1997. "Trimestralizacion y conciliacion de magnitudes economicas: una ampliacion del metodo Chow-Lin," Working Papers in Economics 20, Universitat de Barcelona. Espai de Recerca en Economia.
  3. Ng, S. & Perron, P., 1994. "Unit Root Tests ARMA Models with Data Dependent Methods for the Selection of the Truncation Lag," Cahiers de recherche 9423, Universite de Montreal, Departement de sciences economiques.
  4. Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-76, August.
  5. Casals, Jose & Jerez, Miguel & Sotoca, Sonia, 2000. "Exact smoothing for stationary and non-stationary time series," International Journal of Forecasting, Elsevier, vol. 16(1), pages 59-69.
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