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Economic Forecasting for Large Russian Cities


  • Raymond Struyk


  • Douglas Wissoker
  • Ioulia Zaitseva



The Budget Code of the Russian Federation requires that local self-governments prepare their budgets for the next year taking into account the likely economic situation in that year. To date these governments have had little guidance to use in preparing their budgets. This paper reports the results of initial steps to develop a procedure for forecasting key economic parameters at the local level. “Local level” is defined as cities that are capitals of Subjects of the Federation (similar to U.S. states); generally these are cities of over 100,000 population. Econometric models are reported for employment, manufacturing production, retail sales, average wage rates, volume of newly constructed housing, and fixed capital formation. The choice of estimation procedures was significantly constrained by data availability. The current document is an interim report, prepared after the basic econometric work has been completed but before the model is tested in actual forecasting. The paper consists of six further sections. The first lists the economic variables to be projected. The second describes the economic logic underlying the models specified for each variable. The third section then outlines the econometric strategy. This is followed in the fourth section with an overview of the data employed in the estimates. The fifth section presents the final models. The paper closes with a short discussion of the plans for future work in this direction. In the next phase of the work the forecasting qualities of these models will be evaluated.

Suggested Citation

  • Raymond Struyk & Douglas Wissoker & Ioulia Zaitseva, 2004. "Economic Forecasting for Large Russian Cities," ERSA conference papers ersa04p318, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa04p318

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    References listed on IDEAS

    1. Dean Croushore, 1998. "Evaluating inflation forecasts," Working Papers 98-14, Federal Reserve Bank of Philadelphia.
    2. A. Granberg & Iu. Zaitseva, 2002. "Growth Rates in the National Economic Space," Problems of Economic Transition, Taylor & Francis Journals, vol. 45(8), pages 72-91.
    3. Berger, Mark C. & Blomquist, Glenn C. & Sabirianova Peter, Klara, 2008. "Compensating differentials in emerging labor and housing markets: Estimates of quality of life in Russian cities," Journal of Urban Economics, Elsevier, vol. 63(1), pages 25-55, January.
    4. 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.
    5. Topel, Robert H, 1986. "Local Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 111-143, June.
    6. Uwe Blien & Alexandros Tassinopoulos, 2001. "Forecasting Regional Employment with the ENTROP Method," Regional Studies, Taylor & Francis Journals, vol. 35(2), pages 113-124.
    7. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    8. Mayo Stephen K. & Stein, James I., 1995. "Housing and Labor Market Distortions in Poland: Linkages and Policy Implications," Journal of Housing Economics, Elsevier, vol. 4(2), pages 153-182, June.
    9. Figlio, David N. & Blonigen, Bruce A., 2000. "The Effects of Foreign Direct Investment on Local Communities," Journal of Urban Economics, Elsevier, vol. 48(2), pages 338-363, September.
    10. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
    11. David G. Terkla & Peter B. Doeringer, 1991. "Explaining variations in employment growth: Structural and cyclical change among states and local areas," Journal of Urban Economics, Elsevier, vol. 29(3), pages 329-348, May.
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