The spatial aspects of economic crisis in Greece

Transcription

1 Cambridge Journal of Regions, Economy and Society 2016, 9, doi: /cjres/rsv028 Advance Access publication 26 November 2015 The spatial aspects of economic crisis in Greece George Petrakos a and Yannis Psycharis b a Department of Planning and Regional Development, Pedion Areos, Volos, Greece, petrakos@uth.gr b Department of Economic and Regional Development, Panteion University of Social and Political Sciences, 136 Syngrou Avenue, Athens, Greece, psycharis@panteion.gr Received on April 13, 2015; accepted on September 8, 2015 This article sets out to test econometrically the performance and determinants of NUTS III regions in Greece during the recent economic crisis. Results indicate that economic crisis has further intensified regional inequalities by strengthening the prominent role of Athens metropolitan region in the development map of the country. Advanced regions with higher specialization in tradable and export-oriented sectors adjusted better to economic crisis, although deeper integration with the EU market has not been favourable to regional performance. Finally, public policies that improve the productive and social capital of the regions seem to play an important role in deterring the crisis. Keywords: economic crisis, Greece, regional inequalities, resilience, regional policy JEL Classification: R11, R12, R53, R58 Introduction During the economic crisis that started in 2008, Greece has suffered an economic crisis unprecedented in duration and depth that will have long-term effects on its welfare and employment levels and prospects. A complex set of theoretical propositions, ideological preoccupations, policy options and institutional arrangements are confronted with the hard evidence of what seems to be a profound market and policy failure, with serious implications for Greece and perhaps Europe (De Grauwe, 2013; Ioannou and Stracca, 2014; Petrakos, 2014). Although the crisis is still there and its final coordinates and expressions are unknown, one of the critical issues that is receiving increasing attention is related to the spatial impact and variants of the crisis. This article is aiming at contributing to the literature regarding the evolution of regional inequalities during the economic crisis and the determinants of resilience of regions, by providing empirical evidence from Greece. Greece is offering an interesting case study for a number of reasons. Firstly, it has been one of the countries most affected by economic crisis and therefore the spatial impact of economic crisis is of particular importance for scientific investigation. Secondly, the severe and prolonged impact of the economic crisis on the European periphery questions the sustainability of the gains from the cohesion policy, which has favoured The Author Published by Oxford University Press on behalf of the Cambridge Political Economy Society. All rights reserved. For permissions, please journals.permissions@oup.com

2 Petrakos and Psycharis the less well-off areas of the European territory, and which turned out to be the most affected by the economic crisis. Finally, the implementation of appropriate policies in order to ameliorate the impact of the crisis and paving a way out of it is still an open question that goes beyond the idiosyncrasies of the Greek case. A short chronicle of the economic crisis in Greece When, in early 2010, public deficit of the Greek Budget for 2009 was reported to exceed 12% of GDP, the cost of borrowing started to increase dramatically, and soon thereafter financial markets closed for Greece (Bank of Greece, 2011). As the EU Treaties did not have any provision for such crises, an ad hoc rescue mechanism was decided on by the EC, the ECB and the IMF (the Troika), according to which a 110 billion loan (and later, a debt haircut) was provided in combination with an austerity programme and a reform programme (Greek Ministry of Finance, 2010, 2011; Konhler, 2012; Monastiriotis, 2013). The austerity measures were supposed to eliminate the public deficit in a period of 2 3 years, mainly through wage and pension cuts and tax increases. In addition, a long list of structural reforms, including deregulation of markets, reorganization of the state and privatization were included in a Memorandum of Understanding that was signed by the Greek government and the EU, the IMF and the ECB. The austerity programme was implemented in a climate of severe political conflict and social protest with a cross-the-board reduction in public spending, including wages, pensions and public investment and severe increases in taxation. On the other hand, implementation of the reform programme and the privatization programme were delayed due to the indecisiveness of the government, the inability of the public sector to support the reforms, and the strong public and political reaction. A second programme, the Medium-Term Financial Strategy , was followed under the same conditions as the initial one (Greek Ministry of Finance, 2012). These programmes were periodically evaluated, but also updated, with new conditions or goals being added after every review. The impact of the crisis and the austerity programmes was severe and beyond any projection. Greece experienced a deep recession and in a period of 5 years lost 25% of its GDP and about one million employment positions. Unemployment jumped in 2013 to 27% and youth unemployment reached 50% (Eurostat, 2014). The policy mix included the reduction of the Public Investment Programme by more than 36% in the period, at the time that private investment declined by more than 42%, despite the serious reductions in labour costs, because of the uncertainty surrounding the future of the economy and the dramatic increase in taxation (Bank of Greece, 2014). With regard to the long-term prospects of the country, an undermining process of brain-drain is taking place during the crisis, where the young and educated Greek population leaves massively the country in search of employment and security, predominantly in the advanced EU economies. The crisis resulted in severe social polarization and poverty, as about a quarter of the population ended up living below the poverty line. The crisis and the management of the crisis has led to the collapse of the two-party political system where the Centre-right and the Centre-left parties (ND and PASOK) were replacing each other in power, and led to a political polarization which on the one hand brought the left party, SYRIZA, to power after the January 2015 elections and on the other hand allowed for the rise of the extreme right. In August 2015, the new coalition SYRIZA-ANEL government signed the third Memorandum of Understanding with the creditors in order to get an 86 billion loan. It is not yet clear what the long-term effects of the crisis will be on the structure of the economy. Clearly, the previous model of development that was largely based on state-induced 138

3 The spatial aspects of economic crisis in Greece consumption (rather than investment), domestic demand (rather than exports), small-scale production (with limited scale effects) and dominance of the non-tradable sectors of the economy is no longer sustainable. However, several years after the beginning of the crisis, a new model of development has not emerged yet. Despite the fact that the underlying causes and consequences of this severe economic crisis is an open question to scientific and political discussion, the geographical spread of the impact arising from the crisis has attracted relatively limited attention. However, the geography of recession and austerity constitutes a critical question, and Greece provides an interesting case study for theory and policy (Psycharis et al., 2014). Literature review economic crisis and the regions The intensity, geographical coverage and the multi-dimensional expression of the recent economic crisis has placed the regional dimension of economic crisis at the centre of attention for academic and policy debates across the globe. Although the literature is still sporadic, incomplete and unbalanced, the questions regarding the evolution of regional disparities, the determinants of vulnerability and resistance of regions to external shocks, and the policy tools for ameliorating the impact of crisis, provide a new ground for flourishing research. There is already a strand of literature that has related business cycles with the spatial concentration of economic activities (Berry, 1988; Richardson, 1973; Stilwell, 1980). More specifically, waves of economic growth might give rise to regional inequality (spatial concentration), while waves of economic recession may result in decreasing regional inequality (spatial dispersion). Following this line of thought, expansion cycles begin at the poles of economic activity, where the interaction of agglomeration effects and market size provides a lead over other regions. In contrast, during a recession period, these poles are more exposed to demand and supply contractions and, therefore, more likely to be negatively affected than the rest of the regions. An analysis of the evolution of regional disparities in Greece shows that inequalities increase during the periods of economic growth, and decrease during recessions (Petrakos et al., 2005; Petrakos and Saratsis, 2000). However, regional inequalities during the recent economic crisis are an open question for regional analysis. In an official report, the European Commission (2013) concludes that disparities between EU regions have started to grow again after a long period of convergence. In addition, most capital regions have managed to withstand the crisis better than the other regions. Similarly, the OECD (2011) highlights the differentiated impact of economic crisis on the loss of jobs within OECD countries, concluding that three-fourths of OECD regions that showed employment growth between 1999 and 2007 shifted to an employment decline between 2008 and 2009 [whereas] disparities in job losses have increased. Another strand of literature accounting for the spatial impact of economic crises focuses on the type and degree of regional specialization (Grossman and Helpman, 1991; Quah and Rauch, 1990; Romer, 1987; Thompson, 1956). Specialization can make regions more competitive and more protected from economic downturn. However, excessive specialization involves the danger of rendering regions more dissimilar in terms of production structure, making them more vulnerable to a possible industry-specific shock, with a negative effect on growth (Fotopoulos et al., 2010; Kallioras and Petrakos, 2010; Petrakos et al., 2012; Wundt, 1992). In an attempt to explain the asymmetrical impact of economic crisis across European Union countries, De Groot et al. (2011) decompose the spatial heterogeneity of the crisis by 139

4 Petrakos and Psycharis considering three major possible determinants: financial markets and international trade linkages (or openness), institutions and policy and sectoral composition. The level of integration and connectedness with the global economy via financial and trade linkages, along with differences in sectoral composition, are among the factors that account for the spatial heterogeneity in the severity of the crisis, both at the country and the regional level across Europe. Among the factors that could affect the response of regional economies to economic crisis is the level of urbanization. In a world with high levels of urbanization, the reaction of urban areas and metropolitan regions to economic crisis acquires a prominent role (Brakman et al., 2015). Urban economies are more exposed to international influences, making metropolitan areas more vulnerable to economic crisis (Hadjimichalis and Hudson, 2014; Palaskas et al., 2015). However, the differentiated productive structure, the adaptive, innovative and technologically advanced environment and the concentration of highly skilled and educated human capital of highly urbanized economies could become protective factors against economic decline, helping them to adapt and recover (Balland et al., 2015). Capello et al. (2014) and (2015) investigate the spatial heterogeneity in the costs of economic crisis across cities and regions in Europe and find that external linkages (openness) and cooperation networks, the quality of production factors and the urban endowment all play a key role for the resilience of regions and cities. They conclude that economic resilience increases with the size of the cities and the type of functions hosted in them, highlighting the heavy toll crisis incurred on the less-advanced regions in the European periphery. Van Oort et al. (2014) investigate the contribution of agglomeration economies to the economic growth of European regions and show that spatial regimes classified by population size differ significantly. In particular, in medium-sized urban regions and cities, specialization levels and openness are especially important in relation to productivity and employment growth. In the recent debates, specific attention has been given to what makes a region more resilient to economic downturn. However, resilience is far from being a straightforward issue (Bristow, 2010; Bristow and Healy, 2015; Foster, 2012; Martin, 2012; Pendall et al., 2010). As regards the field of regional science, Davies (2011) asserts that regional resilience is interwoven with: (i) the ability to withstand external pressures; (ii) the capacity to respond positively to external changes; (iii) the longer term adaptability (or learning capabilities) and (iv) the capacities of governmental authorities to engage in the appropriate kinds of planning, action and social learning. Empirical analysis of regional resilience has yielded some interesting outcomes. Fingleton et al. (2012) analyze the resilience of UK regions to employment shocks for the period , using a Seemingly Unrelated Regression model (SURE), and find that UK regions differ in their resilience to these shocks mainly with regards to the initial resistance to shocks rather than the recovery. Cellini and Torrisi (2014), analyzing regional resilience for a very long time-span ( ), find it difficult to discern genuine differences in regional resilience since only a few shocks proved to have specific impact effects that differed across regions, while the recovery experience is ever spatially homogeneous. The spatial impact of the crisis in Greece is gradually receiving attention in the literature, as the required regional statistical data become available. Monastiriotis (2011a, 2011b) analyses the impact of austerity measures on regional income and inequalities, arguing that the horizontal measures are widening existing disparities something that may be difficult to redress in the future. Psycharis et al. (2014) 140

5 The spatial aspects of economic crisis in Greece construct a composite regional resilience indicator in order to detect the resistance/vulnerability of Greek regions to economic crisis. In a special issue, Psycharis et al. (2014) examine the aspects of spatial impact of economic crisis in Greece. However, a model-based approach that will capture the spatial impact of significant determinants of the crisis is not present in the existing literature. The spatial evolution of GDP during the crisis Regional inequalities and economic decline The examination of the regional impact of the crisis has to take into consideration specific characteristics and the idiosyncratic features of the Greek economic space, which is dominated by the presence of the metropolitan area of Athens, which is part of the Attica Region, but functionally extends beyond that, embracing clusters of significant industrial activity located a short distance beyond its borders, in the neighboring regions (Petrakos and Psycharis, 2015). Even without its satellites, the Attica region accounted for 36% of the national population and 50% of national GDP in 2012, maintaining a regional GDP per capita that is the highest in the country and 38% above the national average (Petrakos and Psycharis, 2015). Given this polarized character of the Greek economic a space, the first question that needs to be investigated is whether the economic crisis has affected, or significantly changed, the spatial patterns of growth and development in the Greek economy. The analysis that follows is based on NUTS II and NUTS III data for the Greek economy for the years Although it includes the years in which the crisis was deepest (2011 and 2012), final conclusions will have to wait until Eurostat releases data for the remaining years. The entire period is divided into two subperiods using the year 2008 as the turning point, as it was that last year in which the Greek GDP recorded a positive change. The first period ( ) can be understood as the precrisis period, where the development model of the country with all its problems and inefficiencies was still functioning and no sign of the economic crisis that would follow was evident. The second period ( ) coincides with the period of GDP decline. Although the debt-crisis is considered to have the year 2010 as its starting point, when Greece was excluded from the financial markets and made use of the EU-ECB-IMF rescue mechanism, the economy was already in a recession 2 years earlier. Figure 1 shows the evolution of regional GDP at the NUTS III (51 regions) and NUTS II (13 regions) level for the period The first observation is that the Attica region (bold line) maintains its top position and slowly b Figure 1. The evolution of GDP per capita (in constant 2005 prices) in the Greek NUTS III and NUTS II regions, Source: Own elaboration from Eurostat (2014). 141

6 Petrakos and Psycharis increases its distance from the national average (dashed line) until the eruption of the crisis, while it seems to maintain its dominant position during the years of crisis. The second observation is that all other regions (grey lines) follow a similar pattern of growth and decline, although the speed of adjustment may vary according to their special characteristics. Finally, the Figure shows that the great majority of the regions have GDP per capita figures that are below the national average throughout the period, a feature that is related to the dominance of Athens to the Greek regional system. The evolution of regional inequalities in the NUTS III and NUTS II regions is depicted in Figure 2. We observe that the weighted coefficient of variation 1 is increasing throughout the period under examination, indicating the inequalities increased during the period of expansion ( ) and continued to increase also during the period of crisis ( ). The fact that the unweighted coefficient of variation is either stable or slightly declining during the crisis indicates that the performance of the dominant Attica region has become a strong differentiating factor in the regional system of Greece. Overall, the analysis seems to indicate that the crisis did not alter the polarized character of the Greek system of regions. Athens continues to dominate the Greek economy and its performance continues to be relatively better a that the rest of the regions maintaining the previous trends of divergence, although at a slower pace. The spatial expression of GDP decline Which regions have lost the most during the crisis and what are their characteristics? Table 1 and Supplementary Table 1A show that the regions with the highest losses during the crisis were typically island regions, where their economy is based on tourism, and regions hosting significant urban centers with a relative specialization in industrial activity. The regions that were less affected by the crisis are those with a relative specialization in agriculture, and also Athens/Attiki. The crisis hit harder the touristic Aegean and Ionian Islands as well as Crete, because of the social and political conflict that peaked during 2011 and 2012 with continuous demonstrations that received international coverage, as well as negative rhetoric by Government officials in many EU countries, speculation about a possible Grexit and negative publicity in the international media that reduced tourism to the country and made the impact of the crisis more dramatic. Also, regions hosting large cities or specializing in manufacturing (like Central Macedonia and part of Continental Greece, Thrace and Thessaly) were also hit hard due to the difficulties of b Figure 2. Weighted and non-weighted coefficient of variation of GDP per capita in the Greek NUTS III and NUTS II regions,

7 The spatial aspects of economic crisis in Greece Table 1. GDP per capita 2008, 2012 and GDP per capita change Regions (NUTS III) GDP per capita Per capita euro/inh % of national rate most industries in maintaining production in the face of reduced demand, severely cut bank credit for running capital, imported supplies and export guarantees. Among the regions least affected by the crisis are those with a large share of population living in rural areas (Epirus, part of Western Greece and the Peloponnese), where a significant degree of self-consumption and self-sufficiency and a relative dependence on agriculture and subsidies operate as a stabilizer. The least affected from all NUTS II regions is, however, Attica, which is by far the most populated and the most advanced region of the country. This performance of the Athens metropolitan area seems to generate a contradiction that needs to be further examined. Looking at Figure 3 and ignoring Athens/Attiki for a moment, we would clearly state that the most advanced part of the country, which includes the eastern N S axis and the islands (in darker shading) was hit harder by the crisis than the less advanced part, which includes the western part and most border regions (lighter shading). This would lead us to think that the most advanced regions were also the most exposed to the crisis Rank Per capita euro/inh % of national rate Rank (%) change Rank Greece 22, , Notio Aigaio 25, , Ionia Nisia 21, , Kriti 19, , Voreio Aigaio 17, , Sterea Ellada 19, , Kentriki Makedonia 17, , Anatoliki Makedonia, Thraki 16, , Thessalia 16, , Dytiki Makedonia 19, , Peloponnisos 17, , Ipeiros 15, , Dytiki Ellada 16, , Attiki 29, , due to their productive structure. But why, then, does Athens not fit into this picture? Why it is less affected by the crisis, showing similar or better resilience with the agricultural areas? The better performance of Athens is in accordance with the findings of Capello et al. (2015) and OECD (2011), which provide evidence that large cities and urban agglomerations proved to be more resilient during the crisis. Especially, Capello et al. (2015) claim that large cities are proved to be more resilient to the economic downturn, especially when they host diversified high-level functions. However, the relatively better performance of Athens during the crisis should not hide the serious internal divides within the metropolis, as many inner city areas and a large part of the working class districts and the business centre have all suffered from massive lockouts, employment losses and widespread poverty. The picture is very different in the north and south suburbs of the city, where the high or middle-high class appears to be relatively immune from the crisis, revealing a serious spatial polarization in income levels, poverty and 143

8 Petrakos and Psycharis Figure 3. Changes in GDP per capita at NUTS III regions in Greece between 2008 and Source: AMECO and National Statistical Authority, Authors elaborations. unemployment (Artelaris and Kandylis, 2014; Maloutas, 2014). In general, it is safe to claim that the crisis has affected all regions, but it has affected more those in the low and middle-low classes. This is shown in Table 2, which presents the Transition Matrix for the 51 NUTS III regions of Greece between 2008 and The figures of the Transition matrix show that in this period 34 out of 51 NUTS III regions, despite their losses, managed to stay in the same income group, 16 moved to a lower income group and only 1 moved to a higher income group. Although the crisis has affected all income groups, the greatest negative impact and the greatest movement is found in the lower income groups. The drivers of spatial differentiation of the crisis The discussion in the literature and the analysis above have revealed that differences in the performance of the Greek regions during the crisis are partly attributed to the level 144

9 The spatial aspects of economic crisis in Greece Table 2. Transition matrix of GDP per capita in Greece 2008 and 2012 (NUTS III regions) Total Total of development and the structure of the local economy. The critical question here is what structures are less vulnerable and more resilient to the crisis. Do regions specializing more in tradable sectors like manufacturing or tourism have had a better pace of adjustment than regions more dependent on sheltered sectors like government? Has the performance of the regions been affected by the degree of openness in the international environment and the degree of trade integration with the EU? How has the adjustment of the characteristics related to structure and internationalization affected regional performance? In order to address these questions we construct a conditional growth (decline) model for the period of the form: Y = β + β Y + γ X it 0 1 it j= 1 j jit n + λ j X j= 1 jit n + µ j Xjit X ε j= 1 jit i n (1) i = 1,, 51 NUTS III regions j = 1,, N independent variables and estimators t = 1,, 5 time periods in The dependent variable of the model is GDP per capita percentage change during the period The independent variables include the level of development measured by GDP per capita (GDPCAP), as well as a number of structural variables, such as, (i) the degree of openness of each region (OPEN) measured as the share of trade (exports and imports) to GDP; (ii) the level of integration with the EU28 economy (INTEGR), measured as the ratio of trade with the EU28 over total trade; (iii) the share of regional GDP produced in the tradable sector of the economy (TRADB) 2 ; (iv) the share of regional GDP produced in the sheltered sector of the economy (SHELT) 3 and (v) public investment spent in each region (PUBLIC) as a share of GDP. Level variables are available for each of the 5 years and are intended to measure the impact of initial conditions on GDP performance in each period. We also include in the model the variables ΔOPEN, ΔINTEGR, ΔTRADB and ΔSHELT and ΔPUBLIC, which measure the annual percentage change of the above variables during the period and are intended to capture the effect of the adjustment in international relations and the structural characteristics of the regions on their growth performance. As it has already been shown, we expect GDPCAP to have a positive effect on the performance of the regions, primarily due to the superior performance of the metropolitan region of Athens (Capello et al., 2015). Economic crisis has increased the gap in GDP per capita between leading and lagging regions in half of the OECD countries (OECD, 2013). Typically, we would also expect OPEN and INTEGR to have a positive effect, as more open and more integrated regions increasingly benefit from their interaction with the international economy and the EU market. However, earlier research for the EU (Petrakos et al., 145

10 Petrakos and Psycharis 2011) but also Greece (Petrakos and Saratsis, 2000; Petrakos et al., 2012) has shown that regions with a weak productive base may face difficulties in adapting to their external environment and may experience adverse internationalization and integration effects (van Oort et al., 2014). We would expect TRADB to have a positive effect on growth performance, as regions with a greater specialization in tradable sectors would normally adjust better to the crisis, as their productive base is more qualified to seek alternative markets. To the extent that this specialization in tradable sectors is also combined with an outward-looking (more open and more integrated) economy, the effect should be even better (De Groot et al., 2011). We would expect SHELT to have a negative effect on GDP performance during the crisis, as regions specializing in sheltered sectors normally have greater difficulties in adapting to the new conditions when their protection is reduced or removed (Rodriguez-Pose and Fratesi, 2007). The impact of PUBLIC is expected to be positive, as regions endowed with a higher share of public investment have a better chance of attracting new activities. The impact of the change variables (ΔOPEN, ΔINTEGR, ΔTRADB, ΔSHELT and ΔPUBLIC) is critical and depends on the direction of adjustment in each region. On average, the regions increased their degree of openness in the international economy significantly during the crisis years by 35% (from 22% in 2008 to 29% in 2012). However, this increasing internationalization was not due to the expansion of trade with the EU28, as the level of integration with the EU decreased by 1%. While 66% of total trade of the regions took place with the EU in 2008, this figure declined slightly to 65% in Although many regions responded to the crisis by expanding their relations with foreign markets, this expansion does not always seem to include the EU. Of course, a declining share does not imply an absolute decline in monetary terms, but possibly means that trade with EU countries has grown less than trade with non- EU ones. For reason related to the fragmented character of their productive base and their specialization (Petrakos et al., 2012), many regions find it difficult to penetrate the EU and seek trade opportunities in third markets, where entry requirements may be lower. Interestingly, the Greek regions manifested an average 13% increase in the level of dependence on sheltered types of activities during the period , and a decrease of 5% in the participation of the tradable sectors in their GDP. This is related to the specific path of the crisis, which hit the private sector harder than the (more protected) public sector. Given that the private sector has lost over one million employment positions, while the broad public sector has lost about two hundred thousand (including early retirement programmes), it is clear that many regions have experienced a peculiar mix of a more open and at the same time more sheltered productive base during the crisis. Overall, we would expect regions that manage to become more open and more integrated with the EU and at the same time improve their productive structure by increasing tradable activities and reducing sheltered activities, to achieve a better performance during the crisis. In Table 3 we present four models estimating the impact of the internationalization, structure and policy variables on regional growth performance. All models have been estimated with a Panel EGLS method, combining data for five periods and 51 NUTS III regions using Cross- Section weights. 4 All equations include the initial level of development and therefore they can be considered as conditional convergence/divergence models. They also include public investment as a policy variable. The first model includes all level and change variables, while the second 146

11 The spatial aspects of economic crisis in Greece Table 3. Results of the econometric model of GDP per capita growth in NUTS III regions in Greece, Independents Dependent: growth of GDP/cap (1) (2) (3) (4) CONSTANT a a a a GDPCAP 3.41 (10 4 ) a 3.83 (10 4 ) a 2.14 (10 4 ) a 2.03 (10 4 ) a PUBLIC b a c a ΔPUBLIC a a a a OPEN INTEGR TRADB a a a SHELT a a ΔOPEN c ΔINTEGR a ΔTRADB a a ΔSHELT a OPEN*ΔOPEN 1.15 (10 5 ) b INTEGR*ΔINTEGR c TRADB*ΔTRADB 1.21 (10 5 ) a a SHELT*ΔSHELT a ΔTRADB* ΔOPEN c a ΔTRADB* ΔINTEGR 2.21 (10 4 ) a 1.75 (10 4 ) a R F a a a a N a Statistically significant at the 1% level, b statistically significant at the 10% level, c statistically significant at the 5% level. also includes interactive effects between the level and change variables, in order to explore the conditioning effect of initial values on the impact of change values. The third and fourth model focuses on a smaller number of variables, and at the same time explore the interactive effects of changes in the productive base and the international environment. The overall explanatory power of the models, provided by the Coefficient of Determination, is relatively satisfactory for panel models, while the independent variables with a statistically significant impact on regional performance appear in a consistent and robust way. The initial level of development (GDPCAP) is positive and statistically significant in all models, indicating that the advanced regions (especially Athens) are in a better position to confront the crisis. It also indicates that the process of regional divergence that has taken place in the country over the last 15 years has not been interrupted, as the crisis has not altered the polarized character of the economy. The coefficient of the public investment variable PUBLIC is positive, consistent and statistically significant in all models, indicating that regions with a higher level of support by public policy were better equipped to deal with the crisis. Also the coefficient of ΔPUBLIC is positive and significant indicating that changes in public investment during the crisis had a significant effect in the performance of regions, as the regions that experienced the lowest cuts in public investment faced a lower decline in their GDP. The level variables OPEN and INTEGR, which depict the initial conditions with respect to the process and type of internationalization of the regions, were not found to have any significant independent impact on growth performance. As will be discussed later, initial conditions play a role in conditioning the 147

12 Petrakos and Psycharis adjustment that these variables undertook during the crisis. On the other hand, the structural variables TRADB and SHELT appear with a positive and statistically significant effect in the models that were included. A first interpretation is that a higher share in the tradable sector of the economy would protect regions from a deeper decline of GDPCAP. At the same time, however, regions hosting a high share of sheltered activities (like the public sector) experience a lower decline in GDPCAP than otherwise. These seemingly conflicting results simply indicate that at the regional level we may find two possible growth or survival strategies. On the one hand, some regions still host significant public sector activity like energy plants, universities or military camps, which play an important role in the local economy. On the other hand, and in the absence of a public economic base, some other regions maintain significant tradable activities, like tourism or manufacturing, that help them to deal with the crisis. The impact of the change variables ΔOPEN, ΔINTEGR, ΔTRADB and ΔSHELT has been tested in models (2) (4) in an interactive way with the level variables. The idea behind the interactive setting is that the impact of a change variable may be affected by the initial conditions of this variable. As Equation 3 shows, the impact of ΔΧ depends on the values of the level variable X. This impact can be positive when both estimators λ j and μ j are positive, or when X ij > λ j/ μ j. The notion that the impact of change variables on growth depends on level variables refers to the possibility of a rather cumulative nature in economic behavior. It allows the impact of change variables to increase or decrease with size, initial conditions or experience, or take place after some critical scale of the level variable has been achieved. The interactive effects are tested econometrically and take place only when the estimators μ j are statistically significant. θ Y / θ X = λ + µ X (2) i ij j j ij Model (1) tests for the independent growth impact of the change variables, while models (2) (4) have added tests for the interactive impact. The first model seems to have a disappointing message, which diverges from the mainstream understanding about the impact of openness, integration and structural change on regional growth. The estimators of ΔOPEN and ΔINTEGR are negative and statistically significant, indicating that improving openness and integration into the EU market would have an adverse effect on regional growth. On the other hand, the negative sign of the sheltered activities (ΔSHELT) seems to be in line with theoretical expectations. Model (2) presents interactive effects that change the picture to some extent. The interactive effect of openness now becomes positive and significant, indicating that a prior experience in open markets is a requirement for regions attempting to internationalize their economy. On the other hand, a prior experience of deeper economic relations with the EU does not help regions to turn deeper integration into a dynamic growth experience. The EU market seems to be too competitive for the internationalization efforts of the Greek regions. The interpretation of the interactive effect of SHELTER on growth could be that sheltered regions can continue to grow (or decline less) if sheltered activities do not expand that much (at the expense of the other more productive activities). Models (3) and (4) focus attention on the impact of the productive sector of the economy on growth, and its interaction with the international environment. They show that increasing the tradable share of the local economy is expected to have a significant effect on regional performance, but this effect is conditional on prior experience with the tradable sector (TRADB), and the ability of the regions to become more open (ΔOPEN) and more integrated (ΔINTEGR). In Model 3, the first partial derivative of ΔΥ with respect to ΔTRADB is shown in Equation 3: 148

13 The spatial aspects of economic crisis in Greece θ Υ / θ TRADB = * TRADB * OPEN * INTEGR (3) The net effect of these driving forces has been estimated for the period of crisis and it has been found to be positive for most, but not all, regions. The expansion of the tradable sector contributes to growth in regions with significant prior experience in this sector, and in regions that increase the internationalization of their productive base. However, the expansion of the tradable sector seems to find difficulties in contributing to growth in regions that are increasing their exposition to the forces of EU integration, as the specific type and mix of tradable activities seem not to be competitive enough to survive in these highly demanding markets. The models also indicate that greater openness of the economy is expected to have a positive and significant effect on regional performance, which, however, is stronger in the regions specializing in tradable activities (Equation 4). This is a meaningful finding, as it makes no sense to increase the level of internationalization of an economy if its productive system is inward-looking and has no significant tradable sector. θ Υ / θ OPEN = * TRADB (4) On the other hand, improving the level of integration with the EU is found to have a negative and significant effect on regional performance, which, however, depends on the degree to which the regional economies are specializing in tradable activities (Equation 5). θ Υ / θ INTEGR = * TRADB (5) How can we interpret this finding, which is at variance with the standard theoretical understanding of economic integration and economic unions? And why does further openness have a positive effect on regional performance, while further integration has a negative one? A possible interpretation is that the type of tradable sector that has been developed in Greece does not have the qualitative or sectoral requirements that would allow it to compete in the advanced and highly demanding core EU countries. Typical Mediterranean products may find it difficult to compete at the lower end of the EU market, where competition is fierce from other Southern EU and non-eu countries, and they lack the qualitative characteristics, the sophistication and the branding that would enable them to be placed in the more demanding but less crowded upper end of the EU market. These findings have significant implications. On the one hand, they highlight the interactions between the international conditions and domestic structure of regional economies; and on the other hand, they differentiate the effects of internationalization from the effects of EU integration, on the basis of the experience of the Greek regions. The results indicate that the internationalization of an economy can be a credible growth strategy only to the extent that it is supported by domestic policies allowing for a significant expansion of the tradable sector. The international markets today provide the required diversity and range of opportunities which can successfully be exploited by most countries and regions. This may not be the case in the experience of Southern regions with the process of EU integration. Further integration into the EU market may prove to be a much more challenging and difficult process than openness, as it may require not so much the expansion, but rather the restructuring of the tradable sector of Southern economies like that of Greece. Expanding the already high share of trade with the EU may not be a credible growth strategy for weaker regions if it is not supported by active measures to change the quality of the tradable sector. Conclusions This article has shown that the economic crisis has not altered in any fundamental way the spatial regularities of the Greek regional 149

14 Petrakos and Psycharis system. Inequalities continued to increase during the recession years, although at a slower pace, maintaining a process of divergence that was initiated in the early The fact that divergence trends are maintained in both the upwards and downwards phase of the economic cycle is related, to a certain extent, to the dual character of the economy and the dominant position of the Athens metropolitan region. While less advanced rural areas follow more or less an anticyclical path based on a partly subsidized agriculture, more developed intermediate cities and islands are strongly affected by the decline of industry and services following a procyclical pattern of adjustment. Against this background, Athens stands alone with its size and variety, combining the effects of scale and openness with a mix of tradable and sheltered activities that have allowed it to maintain its dominant position in the economy. The article has also shown that regions with a higher level of development, greater support through public investment policy, a stronger tradable sector, a more sheltered initial environment and a response function that increased the openness of the local economy and at the same time improved and restructured the tradable sector of the production base, will experience a less severe impact of the crisis than otherwise. The results have also shown that deeper integration into the EU market cannot be a credible growth strategy, unless it is supported by a long-term plan that will deal with the structural weaknesses of the tradable sector. In this highly diverse pattern of spatial change, where destruction prevails and defensive adjustments are stronger and more visible than policy initiatives, a number of regularities emerge. They indicate that the effects of scale (and perhaps variety), in the form of higher level of development, as well as public policies that improve the productive and social capital of the regions, will play an important role (if available) in deterring the crisis. They also indicate that the adjustments in the international and productive environment may also play an important role, but they work better when they go hand-in-hand. In that sense, regions that seek to internationalize their economy, and at the same time work to expand and upgrade the tradable sector of the economy, have better chances to deter faster the crisis. Supplementary material Supplementary material is available at Cambridge Journal of Regions, Economy and Society online. Endnotes 1 The formula for the population weighted coefficient of variation is as follows: CV W = 1 n P 2 2 i = x x i 1 ( i ) x P, while x i stands for variable under consideration at regional level, x = national average, P i = population of region i, P = total population of the country. 2 We include in the tradable sector of the economy manufacturing, tourism and agriculture, to the extent that it is related to agricultural exports. 3 We include in the sheltered sector of the economy the public sector and agriculture, to the extent that it is related to EU subsidies. 4 The econometric models were estimated with the E-Views version 7 Program. References Artelaris, P. and Kandylis, G. (2014) Mapping poverty at regional level in Greece, Région et Développement, 39: Balland, P.-A., Rigby, D., and Boschma, R. (2015) The technological resilience of US cities, Cambridge Journal of Regions, Economy and Society, 8: Bank of Greece (2011) Bulletin of Conjunctural Indicators, 136. Bank of Greece (2014) Annual Report, Athens. Berry, B. J. (1988) Migration reversals in perspective: the long-wave evidence, International Regional Science Review, 11: Brakman, S., Garretsen, H., and van Marrewijk, C. (2015) Regional resilience across Europe: on urbanization and the initial impact of the 1 150

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