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Real-time Forecasts of Economic Activity for Latin American Economies

  • Philip Liu
  • Rafael Romeu
  • Troy Matheson

Macroeconomic policy decisions in real-time are based the assessment of current and future economic conditions. These assessments are made difficult by the presence of incomplete and noisy data. The problem is more acute for emerging market economies, where most economic data are released infrequently with a (sometimes substantial) lag. This paper evaluates "nowcasts" and forecasts of real GDP growth using five alternative models for ten Latin American countries. The results indicate that the flow of monthly data helps to improve forecast accuracy, and the dynamic factor model consistently produces more accurate nowcasts and forecasts relative to other model specifications, across most of the countries we consider.

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Paper provided by International Monetary Fund in its series IMF Working Papers with number 11/98.

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Length: 25
Date of creation: 01 Apr 2011
Date of revision:
Handle: RePEc:imf:imfwpa:11/98
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  1. Jana Eklund & George Kapetanios, 2008. "A Review of Forecasting Techniques for Large Data Sets," National Institute Economic Review, National Institute of Economic and Social Research, vol. 203(1), pages 109-115, January.
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  6. K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze & G. Rünstler, 2008. "Short-term forecasting of GDP using large monthly datasets – A pseudo real-time forecast evaluation exercise," Working Paper Research 133, National Bank of Belgium.
  7. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers.
  8. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
  9. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  10. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," FRB Atlanta Working Paper No. 96-13, Federal Reserve Bank of Atlanta.
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