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Uso de Análisis Factorial Dinámico para Proyecciones Macroeconómicas

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Author Info
Álvaro Aguirre R.
Luis Felipe Céspedes C.

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Abstract

In this paper we use the dynamic factor analysis methodology developed by Stock and Watson (1998) in order to forecast inflation and an index of economic activity for the Chilean economy. Our results indicate that using factors in the process of forecasting of these macroeconomic variables improve significantly out of sample forecasts. Additionally, we find that factor augmented Phillips curve forecasts perform better than conventional Phillips curve forecasts based only on output gap measures.

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Paper provided by Central Bank of Chile in its series Working Papers Central Bank of Chile with number 274.

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Date of creation: Nov 2004
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Handle: RePEc:chb:bcchwp:274

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  1. Israel Sancho & maximo Camacho, 2002. "Spanish diffusion indexes," Computing in Economics and Finance 2002 276, Society for Computational Economics.
  2. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," NBER Working Papers 10220, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  3. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April. [Downloadable!] (restricted)
    Other versions:
  4. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  5. Michael ARTIS & Anindya BANERJEE & Massimiliano MARCELLINO, 2001. "Factor Forecasts for the UK," Economics Working Papers ECO2001/15, European University Institute. [Downloadable!]
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  6. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  7. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October. [Downloadable!] (restricted)
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  8. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis. [Downloadable!]
  9. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February. [Downloadable!] (restricted)
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  10. Marc-André Gosselin & Greg Tkacz, 2001. "Evaluating Factor Models: An Application to Forecasting Inflation in Canada," Working Papers 01-18, Bank of Canada. [Downloadable!]
  11. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  12. Elena Angelini & Jerome Henry & Ricardo Mestre, 2001. "Diffusion index-based inflation forecasts for the euro area," Working Paper Series 061, European Central Bank. [Downloadable!]
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