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Different indexes for forecasting economic activity in Russia (in Russian)

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  • Oleg Demidov

    (Droege & Comp., Moscow, Russia)

Abstract

This paper considers different ways of computing indexes for forecasting economic activity in Russia. The first is the methodology used by the Russian Development Centre based on the concept of "growth cycles". The second combines the dynamic principal components and dynamic factor analyses. The third approach is the NBER methodology based of diffusion indexes constructed using a dynamic factor model. This paper is an attempt to reveal strengths and weaknesses of the three methods in application to Russian data and to develop a better methodology for forecasting economic activity in Russia.

Suggested Citation

  • Oleg Demidov, 2008. "Different indexes for forecasting economic activity in Russia (in Russian)," Quantile, Quantile, issue 5, pages 83-102, September.
    • Handle: RePEc:qnt:quantl:y:2008:i:5:p:83-102
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    References listed on IDEAS

    as
    1. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(6), pages 1113-1141, December.
    2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    3. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages 62-85, May.
    4. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    5. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
    6. 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.
    7. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Anna Pestova, 2015. "Leading Indicators of the Business Cycle: Dynamic Logit Models for OECD Countries and Russia," HSE Working papers WP BRP 94/EC/2015, National Research University Higher School of Economics.
    2. Mikhail E. MAMONOV, Anna A. PESTOVA, Vera PANKOVA, Renat Akhmetov, 2020. "Digital Transformation of Capital Market Infrastructure [Цифровая Трансформация Инфраструктуры Рынка Капитала]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 130-159, November.

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    More about this item

    Keywords

    index of economic activity; leading and coincident indicators; dynamic principal components; factor model; Russia;
    All these keywords.

    JEL classification:

    • 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
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

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