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Some approachs to forecasting economic indicators

Author

Listed:
  • Marina Turuntseva

    (Gaidar Institute for Economic Policy)

  • Sergey Drobyshevsky

    (Gaidar Institute for Economic Policy)

  • Pavel Kadochnnikov

    (Gaidar Institute for Economic Policy)

Abstract

The present paper appears a continuation of the 2002+03 IET research in modeling socio+economic time series. The paper contains a review of recent references and sources of forecasting with the use of various econometric models. The authors suggest the method of forecasting with the use of informative structures. They provide a theoretical justification and results of forecasting and comparisons with the respective results obtained by means of ARIMA models. They consider an econometric model of scenariobased forecasts of Russia's main macroeconomic indicators. The paper provides results of computations of prognostic values built on the basis of two scenarios and attempts to build a system of indicators that would allow forecasting financial crises.

Suggested Citation

  • Marina Turuntseva & Sergey Drobyshevsky & Pavel Kadochnnikov, 2005. "Some approachs to forecasting economic indicators," Research Paper Series, Gaidar Institute for Economic Policy, issue 89P, pages 195-195.
    • Handle: RePEc:gai:rpaper:115
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    File URL: http://www.iep.ru/files/RePEc/gai/rpaper/115Turuntseva.pdf
    File Function: Revised version, 2013
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    Citations

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    Cited by:

    1. Fokin, Nikita & Polbin, Andrey, 2019. "A Bivariate Forecasting Model For Russian GDP Under Structural Changes In Monetary Policy and Long-Term Growth," MPRA Paper 95306, University Library of Munich, Germany, revised Apr 2019.

    More about this item

    Keywords

    forecasting; economic indicators;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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