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)

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

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

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

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

Inverted U-shape curve

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)

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 –

GDP per capita in the “new” EU countries, in EUR by PPS YearBGROCZEEHULTLVPLSLSKHR

Coefficients of interregional variation of the GDP per capita for NUTS 3 regions YearBGROCZEEHULTLVPLSLSKHR

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

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

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

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

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

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

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

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