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A Dynamic Factor Model for the Colombian Inflation

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Author Info
Eliana González ()
. Luis F. Melo ()
Viviana Monroy ()
Brayan Rojas ()

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Abstract

We use a dynamic factor model proposed by Stock and Watson [1998, 1999, 2002a,b] to forecast Colombian inflation. The model includes 92 monthly series observed over the period 1999:01-2008:06. The results show that for short-run horizons, factor model forecasts significantly outperformed the auto-regressive benchmark model in terms of the root mean squared forecast error statistic.

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Paper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number 549.

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Handle: RePEc:bdr:borrec:549

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Related research
Keywords: Dynamic factor models; static factor models; forecast accuracy. Classification JEL: C13; C33; C53.;

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References listed on IDEAS
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  1. Zaher, Fadi, 2007. "Evaluating factor forecasts for the UK: The role of asset prices," International Journal of Forecasting, Elsevier, vol. 23(4), pages 679-693. [Downloadable!] (restricted)
  2. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, EconWPA, revised 24 Oct 1994. [Downloadable!]
  3. Forni, Mario & Reichlin, Lucrezia, 1998. "Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics," Review of Economic Studies, Blackwell Publishing, vol. 65(3), pages 453-73, July. [Downloadable!] (restricted)
  4. Ziegler, Christina & Eickmeier, Sandra, 2006. "How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Discussion Paper Series 1: Economic Studies 2006,42, Deutsche Bundesbank, Research Centre. [Downloadable!]
  5. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. Marc-André Gosselin & Greg Tkacz, 2001. "Evaluating Factor Models: An Application to Forecasting Inflation in Canada," Working Papers 01-18, Bank of Canada. [Downloadable!]
  7. Kapetanios, George & Labhard, Vincent & Price, Simon, 2008. "Forecast combination and the Bank of England's suite of statistical forecasting models," Economic Modelling, Elsevier, vol. 25(4), pages 772-792, July. [Downloadable!] (restricted)
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  8. Otrok, Christopher & Whiteman, Charles H, 1998. "Bayesian Leading Indicators: Measuring and Predicting Economic Conditions in Iowa," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 997-1014, November.
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  9. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
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  10. Matheson, Troy D, 2006. "Factor Model Forecasts for New Zealand," MPRA Paper 807, University Library of Munich, Germany. [Downloadable!]
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  11. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526. [Downloadable!] (restricted)
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  12. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January. [Downloadable!] (restricted)
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This page was last updated on 2009-11-20.

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