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Forecasting Emerging Market Indicators: Brazil and Russia

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Author Info
Victor Bystrov
Abstract

The adoption of inflation targeting in emerging market economies makesaccurate forecasting of inflation and output growth in these economies of primary importance. Since only short spans of data are available for such markets, autoregressive and small-scale vector autoregressive models can be suggested as forecasting tools. However,these models include only a few economic time series from the whole variety of data available to forecasters. Therefore dynamic factor models, extracting information from a large number of time series, can be suggested as a reasonable alternative. In this paper two approaches are evaluated on the basis of data available for Brazil and Russia. The results allow us to suggest that the forecasting performance of the models considered depends on the statistical properties of the series to be forecast, which are affected by structural changes and changes in operating regime. This interaction between the statistical properties of the series and the forecasting performance of models requires more detailed investigation.

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Paper provided by European University Institute in its series Economics Working Papers with number ECO2006/12.

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Date of creation: 2006
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Handle: RePEc:eui:euiwps:eco2006/12

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Related research
Keywords: forecasting; emerging markets; factor models;

Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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    Other versions:
  4. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October. [Downloadable!] (restricted)
    Other versions:
  5. Favero, Carlo A & Marcellino, Massimiliano, 2001. "Large Datasets, Small Models and Monetary Policy in Europe," CEPR Discussion Papers 3098, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  6. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2004. "Forecasting Macroeconomic Variables for the Acceding Countries," Working Papers 260, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
  7. Joel Bogdanski & Alexandre Antonio Tombini & Sérgio Ribeiro da Costa Werlang, 2000. "Implementing Inflation Targeting in Brazil," Working Papers Series 1, Central Bank of Brazil, Research Department. [Downloadable!]
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  9. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895.
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