1. September 9, 2014, EFRI, Rijeka September 9, 2014, EFRI, Rijeka Consequences of Joining the EU for the Economic Performance of Countries’ Internal Regions Vera Boronenko (Daugavpils University, Latvia; University of Rijeka, Croatia) Vladimirs Mensikovs (Daugavpils University, Latvia) The presentation is worked out with support of the Marie Curie FP7-PEOPLE-2011-COFUND program - NEWFELPRO (The new International Fellowship Mobility Programme for Experienced Researchers in Croatia) within the project «Rethinking Territory Development in Global Comparative Researches (Rethink Development)», Grant Agreement No. 10 (scientist in charge – Dr. Sasa Drezgic)

2. Main subjects of the research Economic performance of countries’ internal regions – in economic research practice traditionally measured by GDP per capita (by PPS) Regional (di)convergence - a process of temporal (discrepancy)closing on of the levels of economic performance of regions in a country NOTE: it is crucial not to confuse regional (di)convergence with (di)convergence of the levels of economic performance of the regions of different countries: for instance, in the European Union

3. Research rationale The countries of Central and Eastern Europe that entered the EU in 2004 and 2007 have a higher level of regional differences in comparison to the “old” EU countries The inequality among large and small regions in many “new” countries of the EU countries is increasing due to the rapid development of metropolitan regions in comparison to peripherian ones

4. Hypothesis In terms of regional (di)convergence, for the economic performance of the investigated countries’ internal regions the consequences of entering the EU are not direct, but indirect due to sufficiently rapid economic growth of these countries after their entering the EU

5. Research methodology (1) Theoretical approach of J. Williamson who founds that the development of a sovereign state promotes the growing of regional differences at the early stages. But further the economic growth contributes to regional convergence. This process can be illustrated by the inverted U-shape curve

6. Inverted U-shape curve

7. Research methodology (2) The conception of σ (sigma)-convergence that is defined as a reduction in the inequality of levels of economic performance of regions (in its turn, the opposite process is defined as σ - divergence) (Sala-i-Martin, Barro, Quah and many others)

8. Method of application The analysis of panel data (Fiscer, Daniels, Eisenhart, Heckman) which comprise three dimensions: features – objects – time Features – GDP per capita, coefficient of its interregional variation Objects – NUTS 3 regions of the «new» EU countries and Croatia as a control country Time – 2000-2011

9. GDP per capita in the “new” EU countries, in EUR by PPS YearBGROCZEEHULTLVPLSLSKHR 2000 54005000135008600103007500 6900 920015200 9500 2001 59005500144009200115008300 7600 940015800 1030010000 2002 650060001500010200125009100 8400 990016800 1110010700 2003 6900650015800113001290010300 9100 1010017300 1150011300 2004 7500740016900124001360011100 10100 1090018700 1230012100 2005 8200780017800138001420012300 11100 1150019600 1350012800 2006 9000910018900156001490013600 12500 1230020700 1490013700 2007 100001040020600175001530015500 14300 1360022100 1690015100 2008 109001170020200172001590016100 14600 1410022700 1810015800 2009 103001110019400149001530013600 12700 1420020200 1700014500 2010 108001170019700156001610015100 13500 1540020600 1810014300 2011 1170012200203001740016900 15000 1640021200 1890015300

10. Coefficients of interregional variation of the GDP per capita for NUTS 3 regions YearBGROCZEEHULTLVPLSLSKHR 2000 0.2650.3430.3080.4190.3760.249 0.504 0.4000.185 0.4690.291 2001 0.2710.3140.3310.4300.3630.270 0.522 0.3890.195 0.4770.295 2002 0.2830.3460.3420.4500.3930.298 0.525 0.4030.201 0.4970.286 2003 0.2890.3370.3570.4720.3820.302 0.537 0.3970.219 0.4920.305 2004 0.2960.3370.3550.5070.3920.300 0.536 0.3990.222 0.4970.329 2005 0.3220.4090.3600.4830.4110.319 0.559 0.4120.226 0.5650.327 2006 0.3810.4060.3660.5120.4350.347 0.605 0.4220.240 0.5370.320 2007 0.4310.4140.3810.4820.4350.361 0.543 0.4250.238 0.5480.322 2008 0.4460.4390.3920.4700.4410.326 0.540 0.4150.232 0.5210.317 2009 0.4880.4190.3800.5170.4570.332 0.485 0.4310.238 0.5730.321 2010 0.4950.4170.3840.4670.4490.321 0.493 0.4400.237 0.5620.354 2011 0.4680.4480.3740.4850.4600.310 0.426 0.4360.226 0.5780.337

11. Research questions whether the increase in the interregional variation of economic performance in the “new” countries of the EU is persistent if so, whether increase in the differences between the regions in the “new” EU countries is the result of the entry of these countries into the European Union or the interregional variation of the economic performance in these countries is determined by GDP growth

12. % change of coefficient of interregional variation of GDP per capita for 2011/2000 in the “new” EU countries

13. Country Kendall’s correlation coefficient between country’s average GDP per capita (in EUR) and joining the EU (yes or no) Kendall’s correlation coefficient between country’s interregional variation of GDP per capita (coefficient of variation) and joining the EU (yes or no) Partial correlation between interregional variation of GDP per capita and joining the EU, with blocked variable “GDP per capita” Bulgariar=0.728**, p=0.004 r=0.628, p=0.039 Romaniar=0.734**, p=0.004 r=-0.252, p=0.454 Czech Republicr=0.696**, p=0.007r=0.653*, p=0.011r=-0.282, p=0.401 Estoniar=0.702**, p=0.006r=0.609*, p=0.017r=0.561, p=0.073 Hungaryr=0.702**, p=0.006r=0.658*, p=0.011r=0.099, p=0.772 Lithuaniar=0.702**, p=0.006r=0.653*, p=0.011r=0.269, p=0.424 Latviar=0.696**, p=0.007r=0.131, p=0.610r=0.321, p=0.336 Polandr=0.696**, p=0.007r=0.609*, p=0.017r=0.052, p=0.880 Sloveniar=0.696**, p=0.007r=0.707**, p=0.006r=0.331, p=0.320 Slovak Republicr=0.702**, p=0.006r=0.680**, p=0.008r=0.369, p=0.263

14. Trends of Latvian average GDP per capita and its variation between internal regions (NUTS 3) of Latvia, 2000-2011, % (2000=100%), n = 6 regions

15. Trends of Slovenian average GDP per capita and its variation between internal regions (NUTS 3) of Slovenia, 2000-2011, % (2000=100%), n = 12 regions

16. Trends of Croatian average GDP per capita and its variation between internal regions (NUTS 3) of Croatia, 2000-2011, % (2000=100%), n = 21 regions

17. Conclusion The “new” EU countries are undergoing a natural inverted U-shaped trend of changes of their GDP’s per capita interregional variation that depends both on the GDP growth and on the length of the period of self-development in market economy rather than on the factor of unionization as such within the EU

18. Consequences of Joining the EU for the Economic Performance of Countries’ Internal Regions