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El "IMACO": un índice mensual líder de la actividad económica en Colombia

  • Herman Kamil

    ()

  • Jose David Pulido

    ()

  • Jose Luis Torres

    ()

En este trabajo se describe la construcción de un nuevo indicador mensual líder de la actividad económica en Colombia (IMACO). El procedimiento se basa en un algoritmo de búsqueda heurístico que identifica siete variables líderes del nivel de actividad, que anticipan los movimientos del PIB con cinco meses de adelanto y una correlación del 93%. Asimismo, el IMACO tiene otras propiedades predictivas deseables: anticipa los puntos de quiebre del ciclo económico colombiano sin arrojar señales falsas, y minimiza los errores de pronóstico sobre el crecimiento del PIB. Dada su simplicidad y bajo costo computacional, el IMACO provee una herramienta para el seguimiento continuo de la coyuntura y el diseño de la política económica, que puede ser replicado tanto para otros agregados macroeconómicos en Colombia así como en otros países de la región.

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Paper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number 609.

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Handle: RePEc:bdr:borrec:609
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  1. Luis Fernando Melo & Fabio H.Nieto & Carlos Esteban Posada & Yaneth Rocío Betancourt & Juan David Barón, . "Un Indice Coincidente para la Actividad Económica Colombiana," Borradores de Economia 195, Banco de la Republica de Colombia.
  2. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc.
  3. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, September.
  4. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
  5. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2012. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
  6. Michael Pedersen, 2009. "Un indicador líder compuesto para la actividad económica en Chile," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(2), pages 181-208, abril-jun.
  7. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
  8. Roberto Tatiwa Ferreira & Herman Bierens & Ivan Castelar, 2005. "Forecasting Quarterly Brazilian GDP Growth Rate With Linear and NonLinear Diffusion Index Models," Economia, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 6(3), pages 261-292.
  9. Zarnowitz, Victor & Ozyildirim, Ataman, 2006. "Time series decomposition and measurement of business cycles, trends and growth cycles," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
  10. Mario Forno & Marco Lippi & Lucrezia Reichlin & Filippo Altissimo & Antonio Bassanetti, 2003. "Eurocoin: A Real Time Coincident Indicator Of The Euro Area Business Cycle," Computing in Economics and Finance 2003 242, Society for Computational Economics.
  11. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages C62-85, May.
  12. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
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