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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.

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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
Date of revision:
Handle: RePEc:eui:euiwps:eco2006/12
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  1. repec:att:wimass:9417 is not listed on IDEAS
  2. Lars E.O. Svensson, 1998. "Inflation Targeting as a Monetary Policy Rule," NBER Working Papers 6790, National Bureau of Economic Research, Inc.
  3. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  4. Kenneth D. West, 1994. "Asymptotic Inference About Predictive Ability," Macroeconomics 9410002, EconWPA.
  5. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
  6. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, October.
  7. 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.
  8. Jiri Jonas & Frederic S. Mishkin, 2003. "Inflation Targeting in Transition Countries: Experience and Prospects," NBER Working Papers 9667, National Bureau of Economic Research, Inc.
  9. 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.
  10. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
  11. 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, June.
  12. Clements, Michael P. & Hendry, David F., 1998. "Forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 14(1), pages 111-131, March.
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