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Discovering the signs of Dutch disease in Russia

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  • Mironov, Valeriy V.
  • Petronevich, Anna V.

Abstract

This paper examines the problem of Dutch disease in Russia during the oil boom of the 2000s, from both the theoretical and empirical points of view. Our analysis is based on the classical model of Dutch disease by Corden and Neary (1982). We examine the relationship between changes in the real effective exchange rate of the ruble and the evolution of the Russian economic structure during the period 2002–2013.

Suggested Citation

  • Mironov, Valeriy V. & Petronevich, Anna V., 2015. "Discovering the signs of Dutch disease in Russia," Resources Policy, Elsevier, vol. 46(P2), pages 97-112.
  • Handle: RePEc:eee:jrpoli:v:46:y:2015:i:p2:p:97-112
    DOI: 10.1016/j.resourpol.2015.09.007
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    Cited by:

    1. repec:gam:jecomi:v:5:y:2017:i:2:p:13-:d:96167 is not listed on IDEAS
    2. Mironov, Valeriy V. & Petronevich, Anna V., 2015. "Discovering the signs of Dutch disease in Russia," Resources Policy, Elsevier, vol. 46(P2), pages 97-112.
    3. repec:eee:jrpoli:v:52:y:2017:i:c:p:90-99 is not listed on IDEAS
    4. Ville Kaitila, 2016. "GDP growth in Russia: different capital stock series and the terms of trade," Post-Communist Economies, Taylor & Francis Journals, vol. 28(2), pages 129-145, April.
    5. Gasmi, Farid & Laourari, Imène, 2017. "Has Algeria suffered from the dutch disease?: Evidence from 1960–2013 data," TSE Working Papers 17-780, Toulouse School of Economics (TSE).

    More about this item

    Keywords

    Dutch disease; Resource curse; Real effective exchange rate; Cointegration model; Economic policy; Russia;

    JEL classification:

    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
    • 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

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