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Forecasting Emerging Market Indicators: Brazil and Russia


  • Victor Bystrov


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.

Suggested Citation

  • Victor Bystrov, 2006. "Forecasting Emerging Market Indicators: Brazil and Russia," Economics Working Papers ECO2006/12, European University Institute.
  • Handle: RePEc:eui:euiwps:eco2006/12

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    References listed on IDEAS

    1. Carlo A. Favero & Massimiliano Marcellino, "undated". "Large Datasets, Small Models and Monetary Policy in Europe," Working Papers 208, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
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    3. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
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    8. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
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    forecasting; emerging markets; factor models;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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