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POLITICKÉ VEDY / POLITICAL SCIENCES
Časopis pre politológiu, najnovšie dejiny, medzinárodné vzťahy, bezpečnostné
štúdiá / Journal for Political Sciences, Modern History, International Relations,
security studies
URL of the journal / URL časopisu: https://www.politickevedy.fpvmv.umb.sk
Author(s) / Autor(i): Milan Vošta
Article / Článok: Regional Differentiation of Selected States of the
Eastern Wing of the EU at the NUTS 2 Level in Relation
to Rural Regions
Publisher / Vydavateľ: Fakulta politických vied a medzinárodných vzťahov –
UMB Banská Bystrica / Faculty of Political Sciences and
International Relations – UMB Banská Bystrica
DOI: https://doi.org/10.24040/politickevedy.2023.26.4.165-179
Recommended form for quotation of the article / Odporúčaná forma citácie
článku:
VOŠTA, M. 2023. Regional Differentiation of Selected States of the Eastern Wing of the EU
at the NUTS 2 Level in Relation to Rural Regions. In Politické Vedy. Vol. 26, no. 4, pp. 165-
179. ISSN 1335 – 2741. Available at: https://doi.org/10.24040/politickevedy.2023.26.4.165-
179
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165
REGIONAL DIFFERENTIATION OF SELECTED STATES OF
THE EASTERN WING OF THE EU AT THE NUTS 2 LEVEL IN
RELATION TO RURAL REGIONS
1
Milan Vošta
ABSTRACT
This article analyzes the current topic of regional disparities in the EU member states. The
aim of the present study is to assess the regional disparities in the selected countries, as well
as to identify the dynamics of the existing disparities in regional averages at the level of NUTS
2 statistical administrative units. The framework of the text is narrowed down to a regional
analysis of seven selected countries of the EU's eastern wing (Bulgaria, Czech Republic,
Hungary, Poland, Romania, Slovakia, Slovenia). The text also highlights the position of rural
areas and their role in the regional balance of the countries. The methodological approach is
grounded mainly in the analysis of the development of disparities based on the analysis of
empirical statistical data for the period 2001 to 2021, as well as on the assessment of the
main features and trends of regional differentiation. To test convergence, the results of the
coefficient of variation of GDP per capita in PPP were compared. The research showed the
existence of significant differences in the economic development of the regions and different
convergence tendencies. According to the results obtained, the countries studied were
divided into three groups. Bulgaria, Czech Republic, Romania and Slovakia recorded the
fastest pace of internal balance, with the Czech Republic and Bulgaria showing the smallest
regional differences at NUTS 2 level. The second group of countries is represented by Poland
and Slovenia, which have seen minimal changes in internal differentiation, while both
countries are the least internally diversified in the group of seven countries examined.
Hungary was the only country with an increase in regional disparities in the period under
review, while Slovakia was one of the countries with the largest internal differences between
regions. There is scope for future research to continue to monitor the evolution of
convergence, including the impact of recent trends.
assoc. prof. PaedDr. Milan Vošta, Ph.D. is an Associate Professor at the Department of
International Relatiosna and European Studies, Metropolitan University Prague, Dubečská
900/10, 100 31 Praha – Strašnice, Czech Republic, e-mail: milan.vosta@mup.cz.
DOI: https://doi.org/10.24040/politickevedy.2023.26.4.165-179
1
This paper is the result of Metropolitan University Prague research project no. 100-3 “International
Relations and Territorial Studies” (2023) based on a grant from the Institutional Fund for the Long-
term Strategic Development of Research Organizations.
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166
Key Words: European Union, Regions, Reginal Disparities, NUTS, Predominantly
Urban Region
Introduction
Most professional studies that focus on the issue of the economic level and
economic development of the territory, while evaluating the regional policies of
states from many angles, do not compare the individual countries from the
regional perspective. And that is what this article is attempting to do. During the
transformation period, but also in the following years, the new EU states (the
states of the eastern wing of the EU) went through a series of processes, the
common denominator of which was the differentiation of the previous, relatively
homogeneous, environment. Differentiation processes have a significant
territorial dimension, as is currently shown by the significant differences in the
economic activity and performance of regions.
The aim of this study is to evaluate regional differences in selected states of
the eastern wing of the EU, and to determine the dynamics of existing disparities
in regional projection at the level of the statistical administrative units NUTS 2.
The text emphasizes the position of metropolitan regions in selected countries
and their role in the process of equalizing or deepening regional differences in
relation to rural areas. The author focused on the issue of the significance and
size of the interregional differences and their prospective development. In order
to understand the dynamics of regional development, it is necessary to know the
causes of the differentiation in the development of individual regions and the
subsequent relations between the mechanisms of differentiation, or
concentration; cumulative and selective; on the one hand, and levelling on the
other.
The framework of the text is narrowed down to a regional analysis of seven
selected states of the EU's eastern wing. The influence of financial transfers to
the regions and the application of structural funds has already been felt in all the
countries examined. The author is aware of the great difference in the allocation
of EU funds for the needs of the least developed, or structural crisis, affected
regions. The compatibility of the NUTS 2 regions was already a big problem when
selecting the countries for research purposes. Therefore, even the countries of
the eastern wing, which are represented by only one NUTS 2 region, were not
included in this research. The text shows the dominant disparities in the individual
states precisely on the basis of the analysis and comparison of the basic
economic indicator - GDP per capita in the PPP in the regions and the
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167
determination of the degree of regional balance within individual states at the
present time as well as in comparison with 2010. Based on comparable data, a
specific classification was made dividing the countries into several groups
according to the dynamics involved in the balancing of the regional disparities
which highlighted the level and position of those areas with a preponderance of
rural regions.
It can be stated that the analysis of the regional disparities in the selected
seven EU countries, as well as the determination of the degree of regional
balance led to the achievement of the set objective. The author proposes that this
text will serve as an introduction to the further and deeper study of regional issues
within the entire EU area, as well as the smaller regional units, and especially the
rural NUTS 3 regions.
1. The State of the Art
Theories and policies of regional development underwent significant changes
in the second half of the 20th century. The need to examine economic behaviour
in relation to space gave rise to a new branch in the field of Social Sciences. The
branch is called Regional Science.
In the 1950s, theoretical approaches in regional development with an
emphasis on economic impact were the dominant approaches used. The analysis
of the inter-regional mechanism of development was replaced by the intra-
regional mechanism in the 1960s. The common denominator of all approaches
to regional development was the "top-down" principle (e.g. Ivaničková, 2000).
The response to this centralist model of regional development regulation "from
above" was the strengthening of regional governance "from below". Regional
development strategies aim to solve regional problems by using the potential
existing in the region while respecting its specificities. Endogenous approaches
posed the question of how it will be possible to make the best use of the factors
and resources existing in the region, as well as what is the competitive ability of
enterprises in the region. It is in this approach that the quality of the regional
environment plays a significant role (Ivaničková 2000).
In the 1980s and 1990s, regional policy began to be oriented towards the
field of technology and innovation. Innovation-oriented regional policy is focused
on the potential of the region, but it concentrates more on the innovative and
technological capabilities of the region as well as on the interactivity between
local actors. These are considered to be decisive stimulators of regional
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development processes. Strategies based on the endogenous potential of the
relevant region with innovative approaches allow the creation of so-called
regional innovation systems. According to Ivanička (1993), the regional policy of
the eastern EU countries should be directed towards more integrated regional
strategies that would adapt more flexibly to the needs of the regions. Regional
development policy should mainly aim at improving the performance of domestic
companies so that they get a chance to become complementary to foreign
investments in the region. The creation of a network between foreign direct
investment and innovative domestic firms should lead to a new development path
that would connect the physical and communications infrastructure, human
resources development, innovation as well as its management. According to
Thiestein and Egger (2000), the following basic conditions must be met for
successful regional development:
• Regional policy faces the challenges presented by the constant changes
taking place in the economy as well as in society. Technology and
institutional frameworks, therefore, need to have an anticipatory orientation
that would take into account possible development scenarios, provide
relevant information to regional actors, as well as developing strategies to
cope with the challenges likely to be brought by the future.
• Rapidly changing political environments require flexible policies and
efficient and effective public administration. It is necessary to develop new
organisational skills and strengthen management capacities.
• Policy instruments should be time limited. Past experience has shown that
it is difficult to change or cancel those political measures and subsidies that
are used perpetually. Setting a time limit makes it easier to cancel
unsuccessful policies as well as helping to adopt more successful ones.
Other reasons for increasing regional policy efficiency are those programs
which are financed exclusively by start-up costs. This encourages
politicians to propose more economically viable projects.
• Access to information as well as to know-how and information technologies
are becoming ever more important for regional development.
• Effective regional policy requires a systematic evaluation of policy
measures. Such an approach is helpful in understanding the
implementation of development policies, and seeing if they are effective
and efficient. This evaluation also determines what roles are played by
individual actors in the region. Therefore, there is a need for a learning
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process among the scientific community, public administration and other
regional actors.
The regional dimension in the European Union can be observed on the
example of specific regional units – Euroregions. Euroregions represent a specific
structure of cross-border cooperation structures. It is an association of regional
actors that do specialize in mediation, coordination, information and project
activities. All of them have an international dimension. Both the size and structure
of the budgets of the individual Euroregions are not uniform. They reflect their
size, geographic location, composition of the membership base and also the
ability of the management structures to develop project and other complementary
activities (Abrhám, 2017).
Karlsson (1998) drew attention to the risk of increasing differences between
areas of rapid development and less developed regions due to the possibilities of
access to the free internal market. These are mostly central regions with short
distances between the producer and the market, a well-developed infrastructure,
a high degree of urbanization and a decisive influx of foreign investment. The
question is how long it will take for the marginal and peripheral regions are able
to catch up with the dynamism of the developed regions.
The conclusions and results of already published studies point to a deepening
of interregional differences (regional divergence), or the opposite (regional
convergence). This is a theoretical concept that has been around for decades.
The fundamental difference between these two groups of studies is whether their
authors attach more importance to mechanisms and processes leading to
convergence, or on the contrary, to more differentiated processes and
mechanisms (for more, see: Abrhám, 2017, Blažek and Uhlíř, 2002; Dawkins,
2003; Čajka and Rýsová, 2008; Buček and Rehák, 2010; Stilianos, 2012;
Antonescu, 2015 and others).
Reducing regional disparities between countries and regions is one of the
EU's long-term goals. As part of the EU's economic and social cohesion policy, it
is primarily those differences at the economic level that are being addressed. The
process of convergence, defined as the convergence of economic indicators, in
the EU can be observed from a nominal as well as a real point of view. Real
convergence affects the development of the integration process and the
competitiveness of the EU on global markets in the long term (Durkalič and
Fedaev et al., 2019). Economic indicators such as GDP per capita, wages and
employment, unemployment rates, as well as combinations of these indicators,
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yield similar results and contribute to the ongoing debate on the future of the EU
cohesion policy. Similar to the present study, convergence between EU regions
based on GDP per capita assessments over time has been addressed by Quah
(1993) or Ciurea and Miu (2012) and others.
2. Material and Methods
The development of regional differences in the EU still remains an ongoing
problem and it is a frequently studied topic; and not only at the economic level.
This study continues to analyse the issue of regional differentiation and focuses
on developments between regions in the period 2011 to 2021. In addition to
comparing regional differences in selected countries of the eastern wing of the
EU, the author also focused on evaluating the importance of predominantly rural
regions for the established values of regional differentiation. The author also
assessed the appropriateness of the statistical tools used.
The methodological procedure used in finding the solution is based primarily
on the analysis of the development of disparities discovered in the analysis of
empirical statistical data and the assessment of the main features of, and trends
in, regional differentiation in the dimension of the NUTS 2 regions of selected
states of the eastern wing of the EU. The selection of suitable indicators has a
fundamental influence on the analysis of regional differences. If the phenomenon
described has a developmental character, a higher degree of differentiation and
good identifiability can be expected from it; if it has undergone a process of
geographical diffusion, lower and relatively stable regional differences can be
expected (Štika, 2004). For the analysis presented here, it was necessary to use
an indicator that has sufficient informative value and is available for the selected
regional units. To some extent, the limiting factor was the choice of the analysed
regional statistical territorial unit, which was applicable within the eastern wing of
the EU for only 7 countries. The sources of the European Statistics Office
(Eurostat, 2022) were used as the main data base, and at the time of the study,
the most up-to-date data for 2021 were available. The selected indicator of gross
national product per capita in purchasing power parity appears to be ideal for
evaluating regional differences, as well as for comparing the range of variation in
individual years, because it takes into account the volatility of prices and
exchange rates. The indicator is calculated as the ratio of real GDP to the average
number of inhabitants in a specific year. For clarity, data on the economic level
are interpreted as a percentage of the average value of GDP per capita in
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purchasing power parity in the EU.
Convergence is understood in economics to be the convergence of economic
variables. In the case of the assessment of disparities and the convergence of
the economic and social levels of the given countries, this is real convergence.
The term nominal convergence is used within the European Union in connection
with the convergence of nominal macroeconomic quantities. In this article, we
evaluate the convergence process within the regional units of a group of selected
EU countries (Abrhám, 2008). To compare the development of regional
differences, the methods of calculating the basic statistical indicators of variability
were applied – the standard deviation and the coefficient of variation were derived
from it. The range of variation was determined by comparing the values found at
the beginning and at the end of the monitored period (2011 and 2021).
The standard deviation is often used as a basic measure of interregional
variability. Its use is problematic, as its size depends on the choice of
measurement units. For this reason, it is not very suitable for comparing different
indicators or long-term comparisons, when significant changes in the values of
the indicators which are being investigated can occur (Blažek, 1996). As a
methodical procedure for testing the convergence (differences in economic
disparities) of the regions within the examined states, a comparison of the results
of the coefficient of variation of the values of the gross domestic product per
inhabitant in purchasing power parity was chosen. The coefficient of variation is
given by the ratio of the standard deviation and the arithmetic mean. The
coefficient of variation is usually given as a percentage (the value is multiplied by
a hundred).
For the results of the coefficient of variation, the higher the value, the greater
the difference within the examined set. When examining disparities, we therefore
assess whether there is an increase or decrease in the coefficient of variation
over time. If the coefficient of variation decreases, convergence occurs within the
examined sample, and conversely, if the values increase, divergence can be
observed. The aim was to compare the situation at the beginning and end of the
monitored period from 2011 to 2021. We observed the regional disparities of a
selected group of countries in the eastern wing of the European Union (Bulgaria,
Czech Republic, Hungary, Poland, Romania, Slovakia, Slovenia) and divided the
examined countries into several groups according to the results. At the same
time, the expected influence of predominantly rural NUTS regions (predominantly
rural regions) on the overall regional variability in the examined countries was
evaluated.
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For the analysis of regional economic development, it was necessary to
determine the level of investigation and define the correct aggregate of research.
Due to the comparability of the individual territorial units, the uniform territorial
classification of the European Union was used. This divides the territories of the
member states into NUTS regions (The Nomenclature of the Territorial Units for
Statistics), so as to ensure uniformity within the selected member states, while at
the same time ensuring further comparison with the economic level of
predominantly rural regions. In our text, we will follow the regions of the NUTS 2
category (53 NUTS 2 regions in 7 countries), according to whose economic level
the amount of financial support provided within the EU regional policy to individual
EU regions is determined. For the sake of completeness, we state that the
hierarchical system consists of three NUTS levels: 1, 2 and 3; and the regions
eligible for support from the cohesion policy were defined precisely at the NUTS
2 level (Eurostat 2022).
Table 1, given here, shows all NUTS 2 regions in the examined states. For
our research, a sample of selected states of the eastern wing of the European
Union was used. These states’ territory is divided into two or more statistical units
of the NUTS 2 level according to the unified European administrative
nomenclature. For this reason, a group consisting of the following states was
used: Bulgaria, Czech Republic, Hungary, Poland, Romania, Slovakia, Slovenia;
in which it was possible to monitor regional differences over a longer period of
time using the aforementioned methodological procedure. The resulting values of
the coefficient of variation were compared with the economic level of
predominantly rural regions, whose data is provided by Eurostat as a whole, and
their position in the convergence or divergence processes of the examined
countries was highlighted. For these purposes, indicators of GDP per inhabitant
in PPP were used, as well as the total share of rural regions in the GDP of states
and the territorial representation of rural areas in the assessed NUTS 2 regions.
Table 1: Regions NUTS 2 in selected states: Bulgaria, Czechia, Hungary, Poland,
Romania, Slovakia, Slovenia
BG (6)
Severozapaden
Severen tsentralen
Severoiztochen
Yugoiztochen
Yuzhen tsentralen
Yougozapaden
CZ (8)
Praha
Střední Čechy
Severovýchod
Severozápad
Jihovýchod
Střední Morava
Moravskoslezsko
Jihovýchod
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H (8)
Budapest
Pest
Közép-Dunántúl
Nuygat-Dunántúl
Dél-Dunántúl
Ézsak-Alföld
Ézsak- Magyarorzság
Dél- Alföld
PL (17)
Malopolskie
Pomorskie
Zachodniopomorskie
Wielkopolskie
Dolnoslaskie
Opolskie
Kujawsko-pomorskie
Podlaskie
Lódzkie
Swietokrziskie
Lubelskie
Podkarpackie
Warszawski stol.
Slaskie
Mazowiecki region
Warminko-mazurskie
Lubuskie
R (8)
Nord-Vest
Centro
Sud-Muntenia
Nord-Est
Bucuresti-Ilfov
Sud-Est
Sud-Vest Oltenia
Vest
SK (4)
Bratislavský kraj
Západné Slovensko
Východné Slovensko
Stredné Slovensko
SI (2)
Vzhodna Slovenija
Zahodna Slovenija
Source: EUROSTAT (2022)
3. Results and Discussion
Regional differentiation within the EU has been a relevant topic for decades.
Differences can be observed among individual member states, and internal
differentiation within the territories of the states is also typical. This is something
that we monitor as it is projected through the NUTS 2 regional units. NUTS 2 is
the most used level for the analysis of the convergence process in EU, while less
attention has been devoted to the NUTS3 level. Some exceptions can be found
in recent contributions, focusing on a group of NUTS3 regions in the EU or on
regions belonging to single countries (Postiglione, Cartone, Panzera, 2020).
Using a finer geographical scale may reveal also local spatial effects that are
not evident at NUTS 2 level. Several trends in the development of regional
differentiation can be observed, supported by the results of our research. In some
countries, the disparities are decreasing, while in others, they continue to grow.
Throughout the EU, the bloc’s expansion has played a crucial statistical role, as
mostly less developed countries with a significant share of poor rural regions
(specifically, the countries of the so-called eastern wing) became members.
That is what makes the comparison of the narrow group of the examined
states of the eastern wing of the EU so interesting. To assess regional
differentiation, at both state and regional level, it is important to monitor
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developments over time and compare them with the current state. If we look for
the causes of regional differentiation in selected countries, we can say that an
important reason was, and still is, the low economic development of rural areas.
These make up a substantial part of the population in some states. At the same
time, they are a large part of the dynamics of economic activity in central regions.
Rural regions are often characterized as occupying a worse competitive position,
as well as having unsuitable economic structure, and an unsuitable geographical
exposure. These factors have a fundamental influence on balanced regional
development. Table 2 shows the proportion of rural areas in the population of the
states, then the height of the total GDP of the states, and in the last two columns
it shows the economic level of the rural areas compared to the EU average. It can
be seen that in the monitored countries, with the exception of Slovakia, there was
a growth dynamic in rural areas between 2011 and 2020.
Table 2: Predominantly Rural Regions: GDP: PPS per inhabitant (% of EU avg.)
in years 2011 and 2020
Country
Population: % of
Country
GDP: PPS %
of Country
GDP: PPS per
inhabitant 2011
GDP: PPS per
inhabitant 2020
BG
33
17.4
32
36
CZ
37
8.8
71
78
H
47
12.1
43
48
PL
33
25.9
48
52
R
45
37.45
33
49
SI
44
48.5
70
74
SK
50
29.5
58
55
Source: Own calculations based on Eurostat 2023
For the examined group of seven countries of the eastern wing of the EU, the
usual type of transformation was that associated with significant regional
differentiation, and practically up to the current time we can observe the changing
regional structure of economies. This is accompanied by convergence and
divergence trends. We can observe the approximation of countries to the EU at
regional level, but also the dynamics at play in the development of regional
disparities within individual states. Compared to previous decades, which were
characterised by internal divergences at NUTS 2 regional level, the results of the
statistical measurements show different tendencies during the period 2001 to
2021 and according to the calculation of the coefficient of variation, the selected
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countries can be divided into several groups. In four countries (Bulgaria, Czech
Republic, Romania and Slovakia) there has been a relatively significant increase
in disparities at NUTS 2 regional level over the period under consideration, see
Table 3. Two countries (Poland and Slovenia) experienced only minor changes;
Poland diverging and Slovenia converging. Only Hungary showed a clear
increase in regional disparities at NUTS 2 level. It should be noted that in the case
of Slovenia, the country is divided into only two NUTS 2 regions with very similar
characteristics, and this plays an important role in the outcome. The position of
the metropolitan area is not as strong in relation to the rural regions, which is
another conclusion that can be drawn from the overall degree of regional balance
in the countries. This is where the best results were achieved by Slovenia and
Poland, and where the coefficient of variation values of 26.4 and 36.9 respectively
were measured. The Slovenian case is of a similar nature and has been
mentioned above. The least regional balance can be seen in the case of Hungary
and Slovakia, where the coefficient of variation was measured to be 56.6 and
57.8 respectively, documenting the very weak growth dynamics of rural areas
relative to the metropolitan region. In the case of Hungary, in addition to the very
strong position of the metropolitan area, a very low share of rural regions in the
country's total GDP can be noted. In Slovakia, the difference between the
metropolitan area and rural regions is again dominant.
Table 3: GDP: PPS per inhabitant (% of EU avg.) a Coefficient of variation (%) in
years 2010 and 2021
country
rok
GDP: PPS per inhabitant (EU=100)
Coefficient of variation (%)
Bulgaria
2011
32
46.1
2021
36
45.4
Czechia
2011
71
48.4
2021
78
45.8
Hungary
2011
43
54.9
2021
48
56.6
Poland
2011
48
36.7
2021
52
36.9
Romania
2011
33
53.1
2021
49
49.6
Slovenia
2011
70
26.6
2021
74
26.4
Slovakia
2011
58
63.1
2021
55
57.8
Source: Own calculations based on Eurostat 2023
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The peripheral regions of those EU eastern wing states which were studied,
often have 40-50 per cent of the national populations and economic levels
between 40-50 per cent of the EU average GDP per capita (EU = 100). A number
of Romanian and Bulgarian regions are still currently even lower, at between 30
and 40 per cent. Their endowment with growth factors is low and differences in
economic structure remain a significant cause of regional disparities. The
structural features of regions remain an important factor in regional disparities. In
many cases, a link can be traced to the traditional reasons for development
disparities often cited in academic studies, namely the dichotomy in development
between centre-peripheral rural regions and differentiated development between
western regions (close to the borders with the more developed EU countries) and
eastern mostly rural regions (Abrhám, 2008; Chapman, Meliciani, 2018; Capello,
Caragliu, 2021).
Conclusions
This paper demonstrates the existence of significant differences in the
economic development of NUTS 2 regions in a sample of seven selected
countries from the EU's eastern wing. It showed that while a number of regions
have experienced positive growth dynamics and converged towards the average
GDP per capita in the EU's PPP, this fact is also associated with an increase in
regional disparities within the countries. On the basis of the analysis and
coefficient of variation calculations, the analysed EU eastern wing Member States
Bulgaria, Czechia, Hungary, Poland, Romania, Slovakia, Slovenia experienced
several development trends in the period 2001-2021. The convergence process
varied by country group. The group of countries that experienced the fastest pace
of internal convergence included Bulgaria, Czech Republic, Romania and
Slovakia, with the Czech Republic and Bulgaria showing the smallest regional
differences at NUTS 2 level. In the Czech Republic, the relative development of
rural regions has a large impact, with only one region (North-West) not yet
approaching 75% of the EU average GDP per capita in PPP. In Bulgaria, on the
other hand, we can observe a low economic level of the rural regions (in the range
of 29-45% of the EU average GDP per capita in PPP), but also a low level of the
metropolitan region (96% of the EU average GDP per capita in PPP).
The second group of countries is represented by Poland and Slovenia, which
have experienced minimal changes in internal differentiation over the 20-year
period. However, it should be noted that both countries are also among the least
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177
diversified countries in the seven-country group. As noted above, Slovenia is
divided into only two relatively homogeneous NUTS 2 regions, which is crucial,
and the position of the metropolitan area is not as strong in relation to the rural
regions. Also, Poland's balanced position was justified by the relatively strong
growth dynamics of the rural regions in relation to the metropolitan area. Hungary
was the only country where regional disparities increased during the period under
review. Here again, large differences in regional growth factors are shown to be
crucial. High growth dynamics and high economic levels were recorded in the
metropolitan region (156% of the EU average GDP per capita PPP), while rural
areas in particular have significantly lower values (50-60% of the EU average
GDP per capita PPP). At the same time, Hungary and Slovakia are among the
countries with the greatest regional imbalances within the group of seven
countries of the EU's eastern wing. The research carried out builds upon and
extends the findings of previously published studies. The main limitation of the
research is to some extent the limited availability of data. This paper uses
previously known data from the Eurostat database for 2021. At the time the
analysis was carried out, more recent data were not available. The issue analysed
creates room for further research that takes into account the implications of
another growth factor, namely the Covid 19 pandemic.
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