Szegedi Tudományegyetem Challenges in CEE and Baltic post-socialist EU member states Challenges in national and international economic policies 3rd Central European PhD Workshop on Economic Policy and Crisis Management Doctoral School in Economics, University of Szeged 13 April 2018, Szeged, Hungary Session 1 – Finance and global challenges Room: KO 101, CoChair: Beáta Udvari, Chair: Balázs Kotosz Kerényi Ádám Szegedi Tudományegyetem

Introduction I am a junior research fellow at the Institute of World Economics of Hungarian Academy of Sciences. I am a controller at SOLVO Biotechnology I teach at the University of Szeged.

Content of my presentation Introduction Theoretical framework Scope of my research & research questions EU as a convergence machine Facts 11 post-socialist EU member states The crisis macroeconomic effect on the CEE region Convergence of the 11 countries to the EU15 Convergence of the 56 NUTS2 region to EU average Potential impacts The impact of cohesion policy 2007-2023: model simulations with Quest III Conclusion, future research agendas

THEORETICAL FRAMEWORK

Introduction Since joining to the European Union CEE and Baltic countries have experienced a historically never-experienced capital inflow due to the EU-funds. My research questions are: What are the results in terms of convergence? What would have happened without those historically never-experienced EU-funds? What can we learn from the previous periods? Can the EU funds be used as quick fix to the problems?

EU as a convergence machine? 2007-2013 Goal 1: Increase convergence Supporting growth and employment in the less developed regions Eligibility criteria: Regions: GDP/capita less than 75% of EU average Individual countries: GNI/capita less than 90% of EU average Goal 2: Enhance competitiveness

Cohesion policy In its Article 174, the Treaty on European Union mandates the Union to "… develop and pursue its actions leading to the strengthening of its economic, social and territorial cohesion. In particular, the Union shall aim at reducing disparities between the levels of development of the various regions and the backwardness of the least favoured regions". Cohesion policy is the European Union's main instrument to achieve this objective, based on the European Regional Development Fund (ERDF), the European Social Fund (ESF), and the Cohesion Fund (CF).

Introduction – latest publication The book is available: http://www.vki.hu/

FACTS

The scope of my research is the 11 post-socialist EU member states After the fall of Berlin wall, following tearing down the oppressive socialist system the Central-East European (CEE) and Baltic countries distinguished themselves with their commitment to capitalist regime. Source: Eurostat

Cohesion policy From the total funds available: 55.1% went to EU12 (new entrants) 44.2% to V4+SLO Baltic states and Hungary: the biggest beneficiaries 2007-2013: 11 CEE countries (without co-financing) EUR 176 bln 14.8% of GDP Source: European Commission

Important support to public investment Cohesion Policy provided more than 50% of government capital investment in some countries 57.1 52.1 50.5 42.5 40.9 39.4 38.7 34.3 27.5 25.1 24.5 18.9 7.1 7 4.4 3.9 2.5 1.7 1.1 1 0.8 0.7 0.4 0.2 COHESION POLICY FUNDING AS A % OF GOVERNMENT CAPITAL INVESTMENT 2007-2013 EU 28 = 6.5% AVERAGE Source: European Commission

Country group-level convergence GDP per capita in market price PPS (EU-15 = 100, 2008 & 2016) European periphery (PIGS): convergence slows down in the early 2000 New-comers: heathy convergence up to the crisis Post-crisis: period: convergence slowed/stopped Convergence continued But! At a slower rate Significant differences among countries Source: Surányi, 2018 and Eurostat, 2017

The crisis macroeconomic effect on CEE GDP at 2010 reference level Sources: AMECO, EUROSTAT

Country-level convergence GDP per capita in PPS (EU-15 = 100, 2008 and 2016) Source: Eurostat, 2017

Regional convergence PPS GDP/capita in PPS NUTS 2 HU and PL regions (EU28=100, 2008 &2015) Real convergence remains far from being complete 50% Source: Eurostat, 2017

Low income regions Low income regions, i.e. those NUTS2 regions with a GDP per head in PPS below 50% of the EU average The low income regions cover parts of Bulgaria, Hungary, Poland and Romania. Most of the economic issues experienced by the low income lagging regions are historic in origin; the countries on the eastern fringe of the EU were amongst the latest to accede to the union, and investment and infrastructure has tended to be concentrated around the capital city or in regions that adjoin other more established Member States.

CEE’s lagging regions Hungary’s lagging regions suffer from: under-investment, low innovation, low levels of educational achievement, and low levels of productivity slow growth in high value, high skilled industries. Region-specific differences may reflect the differences in the effectiveness of EU-fund absorption Source: Eurostat, 2017

THE questIII model on POTENTIAL IMPACTS 2007-2023 THE questIII model on POTENTIAL IMPACTS

The QUEST model and its impact channels The model is developed by the Directorate General for Economic and Financial Affairs of the European Commission. The model simulates the impact of policy interventions on a large number of economic variables relevant to cohesion and rural development policies such as GDP, employment, wages, productivity, or investment from the private sector. The model belongs to the class of New-Keynesian dynamic general equilibrium (DGE) models that are now widely used in economic policy institutions. The model describes fully the dynamics of the system in a general equilibrium framework where changes in the conditions for a particular block are transmitted to the other blocks through various market interactions.

The QUEST model and its impact channels The model is regularly used for the analysis of key fiscal and monetary policy scenarios, for assessing the impact of the structural reforms for contributing to the economic projections of DG ECFIN. This type of approach allows to examine the outcome of various policy scenarios taking into consideration the manner in which interventions affect the allocation of resources throughout the economy, thus enabling an analysis of policy impacts at the macroeconomic level The model provides a fully micro-founded, integrated and optimization-based representation of the economies of the Member States.

The QUEST model and its impact channels The analysis based on the Quest model contributes to the understanding of the macroeconomic potential impacts of the cohesion and rural funds invested in 27 Member States during the period 2007-2015. QUEST is structured around building blocks which represent the behaviour of fundamental economic agents and interactions.

QUEST – Main building blocks The equations, assumptions and calibration of the model are provided in the papers cited above (see also the list of references in annex). The diagram in Figure 3 summarizes the main building blocks in the model and their interactions. The model features two main types of firms: producers of intermediate and final goods and services, and R&D producers of patents. Firms produce goods and services by combining technology, physical capital and labour. The production technology is enhanced by acquiring new processes from the R&D sector which generates innovation by mobilising resources (primarily highly skilled labour). This in turn increases the productivity of producers of goods and services. Source: DG REGIO.

The impact of cohesion policy 2007-2023: model simulations with Quest III Impacts on GDP of cohesion and rural development policies, 2007-2023 (% deviation from baseline) Source: DG REGIO.

Model simulations with Quest III Results Cohesion and rural development policies impacts on selected indicators, 2015 and 2023 (% deviation from baseline) Source: DG REGIO.

Conclusion Disparities PPS GDP/capita in PPS NUTS 2 regions (EU27, 2000-2014) Source: European Commission

Conclusion After 2009 the CEE and Baltic regions very hard, there have been major changes in their policies. After 2004 the European Union CEE and Baltic countries experienced a historically never-experienced capital inflow due to the EU-funds. The convergence of the region towards the core states’ economic development is impressive in country-group and country level, but in regional level the convergence process is taking part more slowly. The lagging regions’ key geographical characteristic is that they are located on the eastern fringe of the European Union.

Further research agenda My future goals are to continue this research on the European integration by attending workshops, conferences and summer schools Examine the use of the 2014-2020 funds Focus more on NUTS2-level data Publish the results

Thank you for your kind attention! kerenyi.adam@eco.u-szeged.hu