Download CLER conference 2014

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 σdivergence) (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 – 2000-2011

GDP per capita in the
“new” EU countries, in EUR by PPS
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
BG
5400
5900
6500
6900
7500
8200
9000
10000
10900
10300
10800
11700
RO
5000
5500
6000
6500
7400
7800
9100
10400
11700
11100
11700
12200
CZ
13500
14400
15000
15800
16900
17800
18900
20600
20200
19400
19700
20300
EE
8600
9200
10200
11300
12400
13800
15600
17500
17200
14900
15600
17400
HU
10300
11500
12500
12900
13600
14200
14900
15300
15900
15300
16100
16900
LT
7500
8300
9100
10300
11100
12300
13600
15500
16100
13600
15100
16900
LV
6900
7600
8400
9100
10100
11100
12500
14300
14600
12700
13500
15000
PL
9200
9400
9900
10100
10900
11500
12300
13600
14100
14200
15400
16400
SL
15200
15800
16800
17300
18700
19600
20700
22100
22700
20200
20600
21200
SK
9500
10300
11100
11500
12300
13500
14900
16900
18100
17000
18100
18900
HR
9500
10000
10700
11300
12100
12800
13700
15100
15800
14500
14300
15300
Coefficients of interregional variation
of the GDP per capita for
NUTS 3 regions
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
BG
0.265
0.271
0.283
0.289
0.296
0.322
0.381
0.431
0.446
0.488
0.495
0.468
RO
0.343
0.314
0.346
0.337
0.337
0.409
0.406
0.414
0.439
0.419
0.417
0.448
CZ
0.308
0.331
0.342
0.357
0.355
0.360
0.366
0.381
0.392
0.380
0.384
0.374
EE
0.419
0.430
0.450
0.472
0.507
0.483
0.512
0.482
0.470
0.517
0.467
0.485
HU
0.376
0.363
0.393
0.382
0.392
0.411
0.435
0.435
0.441
0.457
0.449
0.460
LT
0.249
0.270
0.298
0.302
0.300
0.319
0.347
0.361
0.326
0.332
0.321
0.310
LV
0.504
0.522
0.525
0.537
0.536
0.559
0.605
0.543
0.540
0.485
0.493
0.426
PL
0.400
0.389
0.403
0.397
0.399
0.412
0.422
0.425
0.415
0.431
0.440
0.436
SL
0.185
0.195
0.201
0.219
0.222
0.226
0.240
0.238
0.232
0.238
0.237
0.226
SK
0.469
0.477
0.497
0.492
0.497
0.565
0.537
0.548
0.521
0.573
0.562
0.578
HR
0.291
0.295
0.286
0.305
0.329
0.327
0.320
0.322
0.317
0.321
0.354
0.337
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
Partial correlation
Kendall’s correlation coefficient between
between
coefficient between
country’s
interregional
country’s average
interregional
variation of GDP per
GDP per capita (in variation of GDP per capita and joining the
EUR) and joining the capita (coefficient of
EU,
EU (yes or no)
variation) and joining with blocked variable
the EU (yes or no)
“GDP per capita”
Bulgaria
r=0.728**, p=0.004
r=0.728**, p=0.004
r=0.628, p=0.039
Romania
r=0.734**, p=0.004
r=0.734**, p=0.004
r=-0.252, p=0.454
Czech Republic
r=0.696**, p=0.007
r=0.653*, p=0.011
r=-0.282, p=0.401
Estonia
r=0.702**, p=0.006
r=0.609*, p=0.017
r=0.561, p=0.073
Hungary
r=0.702**, p=0.006
r=0.658*, p=0.011
r=0.099, p=0.772
Lithuania
r=0.702**, p=0.006
r=0.653*, p=0.011
r=0.269, p=0.424
Latvia
r=0.696**, p=0.007
r=0.131, p=0.610
r=0.321, p=0.336
Poland
r=0.696**, p=0.007
r=0.609*, p=0.017
r=0.052, p=0.880
Slovenia
r=0.696**, p=0.007
r=0.707**, p=0.006
r=0.331, p=0.320
Slovak Republic
r=0.702**, p=0.006
r=0.680**, p=0.008
r=0.369, p=0.263
Trends of Latvian average GDP per capita
and its variation between internal regions
(NUTS 3) of Latvia, 2000-2011,
% (2000=100%), n = 6 regions
Trends of Slovenian average GDP per
capita and its variation between internal
regions (NUTS 3) of Slovenia, 2000-2011,
% (2000=100%), n = 12 regions
Trends of Croatian average GDP per
capita and its variation between internal
regions (NUTS 3) of Croatia, 2000-2011,
% (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