EuroEconomica, Vol 35, No 1 (2016)

The Impact of the Regional Policy on the European Economy

Romeo-Victor Ionescu1

Abstract. Nowadays, EU28 operates in a very sensitive socio-economic environment. This is why the paper faces to the idea of changing the political approach in the EU. In order to support this idea, two essential common policies (Regional Policy and Cohesion Policy) are analyzed, using pertinent indicators, as GDP per capita, gross value added and labor productivity. A comparative analysis covers EU28 and Euro area. On the other hand, the regional analysis points out the economic disparities between NUTS2 regions. The intermediate conclusions of the analysis led to a cluster approach for the Member States. Moreover, the forecasting procedures applied to the above three economic indicators led to the same idea: an EU more divided than integrated. The main conclusion of the paper is that the present economic approach has to be change into another focused on maintaining and, after that, decreasing the present European socio-economic disparities.

Keywords: Regional disparities; regional cluster; economic gap

1 Introduction

One of the most important European policies is the Regional Policy. Starting to the second enlargement, European Union faced to regional socio-economic disparities. The Member States which adhered to the EU in 2004 and 2007 supported the regional disparities’ increasing. The impact of the latest global economic crisis brought new dimensions to the regional disparities, as well. The economic recovery started in 2010 in almost all Member States is far away of finishing. On the other hand, the importance of the regions, especially NUTS2 regions, increased. Many decision makers consider region as the most dynamic and viable level for socio-economic policies’ implementation.

The greater importance of the regions was point out by a lot of dedicated measures under Regional Policy. The present Regional Policy covers all socio-economic, demographic, geographical, cultural and historical elements which are able to support regional sustainable development.

The Regional Policy is direct connected to Cohesion Policy and other European policies. Their common essential targets are citizen’s welfare and regional sustainable development across Europe.

In order to implement the best Regional Policy, a lot of theoretic approaches developed a distinct science: regional science. According to this science, Regional Policy has to achieve some goals which can be quantified under specific economic indicators.

This scientific paper is focused on the latest economic performances of the Member States in order to conclude if the present Regional Policy is viable or not. Moreover, the analysis in the paper is a test to the EU28 viability under the present socio-economic and political challenges.

2 Related Work

The regional development across the EU is a very interesting research theme for all specialists. The dedicated scientific literature is large enough and covers different aspects with direct and indirect impact on regional development.

The basic idea is related to the growth effect of Regional Policy. A dedicated research paper points out the importance of the European grants to the less developed regions. A couple of funds (Structural Funds and the Cohesion Fund) were able to support the convergence for these regions under GDP per capita close to EU average. The analysis covers 1994-2006 and led to the conclusion that EU transfers generated faster economic growth for 36% from the European regions. On the other hand, a decrease in these transfer implied lower economic growth for 18% from the same regions. The main conclusion of the analysis is that some reallocation of the funds can lead to greater positive effects related to regional economic convergence (Beckera, Eggerf, & von Ehrlichf, 2012).

Another interesting scientific approach put into discussion place-neutral versus place-based policies for economic development. The analysis takes into account the impact of the global challenges on decision makers. Using EU and the developing world as basic examples, the authors try to quantify the effects of the regional development on efficiency and social inclusion. Basically, the final result has to be the territorial cohesion and the maximization of the local and national economic development (Barca, McCann, & Rodríguez-Pose, 2012).

The regional policy has to focus on socio-economic and political integration. The Common Market and the common currency represented important steps but not enough for the integration process. This is why the real progress in European integration was implementation of European Monetary Union (EMU). More specialists consider that the most important consequences of the EMU are: gains in efficiency, reduction of transaction costs associated to the previous existence of different currencies and of the elimination of exchange rate uncertainties (Cuadrado-Roura, & Parellada, 2013).

The global dynamic economic environment led to the need of changing regional policy. This is why Regional and Cohesion Policies were reformed. A new concept was implemented: smart specialization. It was able to modify the policy agenda. This new approach puts together industrial policy and the relationships between economic geography, technology and institutions. The legal and institutional elements were not forgotten. The main idea is that the Regional Policy can be reformed only in connection to the other European policies (McCann, & Ortega-Argilés, 2013).

A distinct direction in analysis of the regional policy is measuring its effects on the economic growth. A regression model was built in order to realize this. It covers the European transfers during 1994-2006. The key of the analysis is GDP per capita before and after receiving European Funds. The main conclusion of the study is that regional allocations have positive impact on regional economic growth (Pellegrini, Terribile, Tarola, Muccigrosso, & Busillo, 2013).

The new economic global challenges led to the necessity of updating regional policy. This means a new approach including the theoretical concepts, instruments and models of the regional policy. The understanding of equilibrium and non-equilibrium economics becomes essentially. The market is still the main element able to ensure equilibrium at regional level. The analysis is focused on the impact of the global crisis on European Economic and Monetary Union and on increasing regional disparities across the EU (Schmidt, 2014).

The idea of global economic crisis vs regional policy reform is pointed out in connection to a new element: smart specialization. The analysis is started from the assumption that the economic diversification of the regions supports their economic development. This is why two political concepts are used: Constructing Regional Advantage concept (CRA) and the Smart Specialization concept (SS). According to SS, the entrepreneurs are free to select their domains of future specialization. CRA tries to identify “related variety and bottlenecks that prevent related industries in regions to connect and interact”. Both concepts are useful in order to obtain real regional economic development (Boschma, 2014).

The connection between smart specialization and regional growth was reiterated in 2015. The analysis is focused on the Cohesion Policy’s impact on regional development. The smart specialization is analyzed in connection to an explicitly spatial and regional setting, which is able to create difficulties in applying this new concept. Moreover, the best solution for this concept’s implementation seems to the reform of the Cohesion and Regional Policies, as well (McCanna, & Ortega-Argilésb, 2015).

Last, but not the least, the efficiency of the political decisions is analyzed in a recent book. According to this interesting approach, there are three decision levels: first (EU), second (Member States) and third (regions). As a result, the multi-level governance is able to lead to socio-economic cohesion across the EU. A comparative analysis between the above three decision levels points out the conclusion that the most efficient decision level is the regional one (Jeffery, 2015).

3 Problem Statement

According to the above literature review, some specific economic indicators become essential for the regional analysis. The most important one is GDP per capita. The Euro area and EU achieved positive trends for this indicator during 2010-2014 (see Figure 1).

Some ideas have to be pointed out. For the beginning, the GDP per capita trends are the same in Euro area and EU. Second, the GDP per capita in Euro area is greater than in the EU for every year of the analyzed period. Third, the total EU GDP had the same positive trend as GDP per capita during the same period.

Some Member States and regions succeeded in achieving high share of total EU GDP. The latest official statistical data talk about Germany (20.89%), UK (16.15%), France (15.27%), Italy (11.56%) and Spain (7.46%) as main contributors to total EU GDP (see Figure 2).

At regional level, the first ranks are covered by: Nordrhein-Westfalen and Bayern (Germany), Ile de France, Nord-Ovest (Italy) and London. The lowest regional GDP performances were realized in: Severozapaden, Severen tsentralen, Severoiztochem (Bulgaria), Dytiki Makedonia, Ipeiros, Ionia Nisia, Voreio Aigaio (Greece), Ciudad Autonoma de Ceuta, Ciudad Autonoma de Melila (Spain), Guyane, Mayotte (France) and Valle d’Aosta (Italy) (Eurostat 1, 2016).

GDP per capita allows pointing out the great disparities across EU28. The gap between the most and the less developed Member States (Luxembourg and Bulgaria) is 5.7:1, according to the latest official statistical data (Eurostat 2, 2016). At least three groups of Member States may be analyzed according to Figure 3. First group covers states with GDP per capita less than 20000 Euros, the second those countries with GDP per capita between 20000 Euros and 25000 Euros, and the last one with countries which achieved GDP per capita greater than 25000 Euros.

The above disparities may be a result of the different economic structure in the Member States. The gross value added (GVA) in industry, as example, covers 15% from total GVA in EU28, while those from construction and agriculture cover 5.4% and 1.5% (see Figure 4). The difference quantifies the services’ contribution to GVA (Eurostat 3, 2016).

The GVA in industry varies from 5.8% in Luxembourg to 32.4% in Czech Republic, while the GVA in construction varies from 2.6% in Greece to 8.5% in Romania. Even that the average EU’s GVA in agriculture is 1.5%, Bulgaria faced to a rate of 5.1% in 2015. As a general conclusion, GVA leads to great disparities between the Member States. The Northern EU developed countries (Denmark, Netherlands, Sweden and Finland) succeeded in achieving lower GVA rates than the EU average in agriculture and industry and higher rates in services. On the other hand, the periphery and the countries which adhered to the EU in the last three waves face to contradictory trends for this economic indicator (see Figure 5).

Labor productivity becomes a very useful economic indicator able to point out the regional disparities across the EU28. At global level, EU28 and Euro area achieved the same labor productivity rates during 2010-2015 (see Figure 5).

Figure 5. Labor productivity per hour worked (index, 2010=100%)

According to Figure 5, the global crisis’ impact was still greater on Euro area than EU28 average in 2015. On the other hand, the productivity trend was positive for both regional organizations during 2010-2015. Only Greece faced to a decrease in labor productivity in 2015 compared to 2010-2014. The greatest labor productivity rates were achieved in Romania, Latvia, Lithuania, Bulgaria and Poland (see Figure 6).

Labor productivity puts into other balance the Member States. Those economies which are less developed succeeded in achieving greater productivity rates than the EU developed economies. On the other hand, the disparities across EU and Euro area are not little under this economic indicator (Eurostat 4, 2016).

4. Analysis of Results

The use of the above economic indicators leads to the idea of great regional disparities between Member States. Moreover, these disparities increased during the recent period and supported the idea of clusters approach.

Using the GDP per capita, the value added as % of GDP and labor productivity, three clusters can be built (see Figure 7).

Figure 7. Regional disparities under cluster approach

According to Figure 7, the use of different economic indicators leads to different approaches, but the same conclusion: EU becomes more divergent that convergent.

The greatest disparities come from GDP per capita. The gap between the most and the less developed Member States is too big to be eliminate on short or medium term. On the other hand, it is useful to quantify the GDP trend across EU28 and Euro area at least until 2020. In order to do this, the analysis period has to be extended to 2004-2015 (see Figure 8). According to this figure, both regional economic entities will face to negative GDP growth rate trend during 2017-2018, if the economic environment will be unchanged. The GDP growth rates will be higher in EU28 than in Euro area. This can be a result of the economic (non)performances in Greece and Spain, for example.

The economic reforms’ implementation, especially in Greece and Spain, can lead to better macroeconomic results until the end of the present financial perspective.

VAR00001 – EU28; VAR00002 – Euro area.

Figure 8. Real GDP trend across the EU28 and Euro area (%)

Source: Personal contribution using SPSS-IBM Software

The most homogeneous indicator is value added as % of GDP. Almost all Member States achieved value added rates of 89% of GDP in 2015. The forecasted values of the indicator are presented in Figure 9. According to this figure, the value added will decrease slowly during 2016-2020.

Some great disparities are supported by labor productivity, as well. Only 14 countries achieved labor productivity rates greater than EU average in 2015.

5 Conclusions

EU28 faces to new challenges in 2016. The Greek crisis, the emigrants’ crisis, the official position of Island of leaving the group of candidate countries and the possible Brexit are just the latest such challenges.

For the first time, the Member States were powerfully divided in 2015 in their political decisions. And for the first time, as well, the Member States focused mainly on their national interests, not on organization’s interests. Their positions were supported by the socio-economic realities, especially at regional levels.

Step by step, the Cohesion Policy and the Regional Policy became unable to realize their goals. The disparities increased across the EU28. The situation is worsening at regional level. The above analysis, based on important economic indicators, led to the same conclusion.

Moreover, the possibility to divide the Member States in different clusters, according to their economic development, is dangerous as long as EU28 operates under Europe 2020 Strategy.

Maybe the worst thing is that there are not solutions to solve these problems, at least on short and medium term. A new socio-economic approach becomes necessary in order to maintain and, after that, to decrease slowly the regional disparities between the Member States. As a result, the Europe 2020 Strategy’s goals have to be changed to other more realistic.

6 References

Barca, F.; McCann, P. & Rodríguez-Pose, A. (2012). The case for regional development intervention: place-based versus place-neutral approaches. Journal of Regional Science, Volume 52, Issue 1, 134–152.

Beckera, S.O.; Eggerf, P.H & von Ehrlichf, M. (2012). Too much of a good thing? On the growth effects of the EU's regional policy. European Economic Review, Volume 56, Issue 4, 648–668.

Boschma, R. (2014). Constructing Regional Advantage and Smart Specialisation: Comparison of Two European Policy Concepts. Scienze Regionali/Regional Sciences, Vol. 13, Issue 1, 51-68.

Cuadrado-Roura, J.R. & Parellada, M. (2013). Regional Convergence in the European Union: Facts, Prospects and Policies. London: Springer Science & Business Media.

Eurostat 1 (2016). Quick facts on European Regions. Retrieved from

Eurostat 2 (2016). Main GDP aggregates per capita. Retrieved from:

Eurostat 3 (2016). Gross value added and income by A*10 industry breakdowns.

Eurostat 4 (2016). Labour productivity per hour worked. Retrieved from

Jeffery, C. (2015). The Regional Dimension of the European Union: Towards a Third Level in Europe? London: Routledge.

McCann, P. & Ortega-Argilés, R. (2013). Transforming European regional policy: a results-driven agenda and smart specialization. Oxford Review of Economic Policy, Volume 29, Issue 2, 405-431.

McCann, P. & Ortega-Argilésb, R. (2015). Smart Specialization, Regional Growth and Applications to European Union Cohesion Policy. Regional Studies, Volume 49, Issue 8, 1291-1302.

Pellegrini, G., Terribile, F., Tarola, O., Muccigrosso, T. & Busillo, F. (2013). Measuring the effects of European Regional Policy on economic growth: A regression discontinuity approach. Papers in Regional Science, Volume 92, Issue 1, 217–233.

Schmidt, P. (2014). EU regional policy and its theoretical foundations revisited. Retrieved from

1 Romanian Regional Science Association,


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