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Use of Dynamic Factor Analysis in Macroeconomic Forecasts

Author

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  • Álvaro Aguirre R.
  • Luis Felipe Céspedes C.

Abstract

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

Suggested Citation

  • Álvaro Aguirre R. & Luis Felipe Céspedes C., 2004. "Use of Dynamic Factor Analysis in Macroeconomic Forecasts," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 7(3), pages 35-46, December.
    • Handle: RePEc:chb:bcchec:v:7:y:2004:i:3:p:35-46
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    References listed on IDEAS

    as
    1. Elena Angelini & Jérôme Henry & Ricardo Mestre, 2001. "Diffusion index-based inflation forecasts for the euro area," BIS Papers chapters, in: Bank for International Settlements (ed.), Empirical studies of structural changes and inflation, volume 3, pages 109-138, Bank for International Settlements.
    2. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    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.
    4. Michael Artis & Anindya Banerjee & Massimiliano Marcellino, "undated". "Factor forecasts for the UK," Working Papers 203, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
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