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Olga Demidova ( NRU HSE, Moscow, Russia ) Enrico Marelli (University of Brescia, Italy)

The Difference of Spatial Effects in the Eastern and Western Russian Regions (by the example of the Youth Unemployment Rate). Olga Demidova ( NRU HSE, Moscow, Russia ) Enrico Marelli (University of Brescia, Italy) Marcello Signorelli (University of Perugia, Italy).

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Olga Demidova ( NRU HSE, Moscow, Russia ) Enrico Marelli (University of Brescia, Italy)

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  1. The Difference of Spatial Effects in the Eastern and Western Russian Regions (by the example of the YouthUnemployment Rate) Olga Demidova (NRU HSE, Moscow, Russia) Enrico Marelli (University of Brescia, Italy) Marcello Signorelli (University of Perugia, Italy) Industrial Organization and spatial economics, 10 – 13 October 2012, St.Petersburg, NRU HSE

  2. Structure of presentation • Motivation • Previous studies • Data • Main hypotheses • Traditional spatial model • Modified spatial model • Econometric results • East and West similarities and differences • Conclusions photo photo photo

  3. Motivation • E.Marelli, M.Signorelli • Perugini C., and Signorelli M. (2010b). Youth Unemployment in Transition Countries and Regions, • Perugini C. and Signorelli M. (2010a). Youth Labour Market Performance in European Regions • Marelli E. and Signorelli M. (2010b). Transition, Regional Features, Growth and Labour Market • Marelli E., Patuelli R. and Signorelli M. (2012). Regional Unemployment in the EU before and after the Global Crisis“ • O.Demidova: Spatial models photo photo photo

  4. Rudyard Kipling photo THE BALLAD OF EAST AND WEST Oh, East is East, and West is West, and never the twain shall meet… photo photo

  5. Previous studies • Basile R. “Labour productivity polarization across western European regions: threshold effects versus neighbourhood effects”// The labour market impact of the EU enlargement, Springer-Verlag Berlin, 2010, pp.75-98 • Fuchs-Schundeln N., Izem R. “Explaining the low labor productivity in East German – A spatial analysis // Journal of Comparative Economics 40, 2012, pp. 1-21 • Demidova O., Signorelli M. “Determinants of Youth Unemployment in Russian Regions”// Post-Communist Economies, v.24, n.2, June 2012, p.191-217 • Kolomak E.A. (2011). Spatial Externalities as a Source of Economic Growth • // Regional Research of Russia, 1, 2, pp. 114–119. photo photo photo

  6. Data 75 Russian regions (we have to omit data for 8 regions) Time period 2000-2009 years Dependent variable: YU - the unemployment rate in the 20-29 age group photo photo photo

  7. Some descriptive statistics photo photo photo

  8. Map of youth unemployment photo

  9. Moran’s index photo

  10. Moran’s index photo

  11. Hypotheses • The situation with youth unemployment in Russia is more serious than that of total unemployment • it is necessary to take into account the temporal dynamics of youth unemployment and impact of the 2008-09 crisis • In modelling the processes of youth unemployment in Russia, it is necessary to consider the spatial correlation • There exists a difference between west and east Russian regions photo

  12. Traditional Spatial Model Where W is a weighted matrix (very often boundary matrix), ρ is spatial correlation coefficient, Usual methods of estimation: ML, Arellano-Bond (for panel data) photo

  13. New Model photo

  14. Statistical hypotheses photo

  15. Independent variables photo

  16. Independent variables photo

  17. Independent variables photo

  18. Results of estimation (Arellano-Bond). Example photo

  19. Tested hypotheses. Example photo

  20. Results of estimation with incorporated restrictions photo

  21. Econometric results photo

  22. Conclusions • There is more serious situation for youth unemployment with respect to the total unemployment rate, confirming our first hypothesis • It is necessary to take into account the temporal dynamics of youth unemployment and the greater impact of the 2008-09 crisistoyoung people, confirming our second hypothesis • The existence of the boundary spatial correlation for youth unemployment in Russian regions is clearly detected,which confirms our third hypothesis • The differences between “east and west” estimates of some variablesare statistically significant, that confirms our fourth hypothesis photo

  23. 20, Myasnitskaya str., Moscow, Russia, 101000 Tel.: +7 (495) 628-8829, Fax: +7 (495) 628-7931 www.hse.ru demidova@hse.ru

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