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Unemployment Clubs in Russian Regions

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  • Tatiana Danilenko
  • Olga Demidova
  • Marcello Signorelli

Abstract

In this article, we empirically investigate regional unemployment in Russia. We first detect the existence of two unemployment clubs, that is, regions with high (low) unemployment surrounded by regions with high (low) unemployment, and a group that comprises the remaining regions. We then apply a specially designed class of spatial-econometric models to regional data 2005–2012, using difference GMM, and we obtain partial confirmation of our two main hypotheses: (i) spatial effects for the high-high and low-low clubs regions differ significantly; and (ii) the determinants of unemployment of the two clubs significantly differ with respect to those of the remaining regions. Our results have key implications for the national- and regional-level policies.

Suggested Citation

  • Tatiana Danilenko & Olga Demidova & Marcello Signorelli, 2018. "Unemployment Clubs in Russian Regions," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(6), pages 1337-1357, May.
    • Handle: RePEc:mes:emfitr:v:54:y:2018:i:6:p:1337-1357
    DOI: 10.1080/1540496X.2017.1281799
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    Cited by:

    1. Demidova, O. & Timofeeva, E., 2021. "Spatial aspects of wage curve estimation in Russia," Journal of the New Economic Association, New Economic Association, vol. 51(3), pages 69-101.
    2. Demidova, Olga, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
    3. Olga Demidova & Pierluigi Daddi & Ekaterina Medvedeva & Marcello Signorelli, 2018. "Modeling the Employment Rate in Russia: a Spatial-Econometric Approach," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 1383-1398.

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