process of catching-up in the new Member States in order to achieve the EU namely the “national growth/regional disparities” effect, europa.eu.int/comm/regional_policy/sources/docgener/studies/pdf/objective1/final_report.pdf.
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Summary This chapter attempts to identify the main policy levers Œ including EU cohesion policy – which could sustain a process of catching-up in the new Member States in order to achieve the EU Treaty objective of economic and social cohesion. The ten economies th at acceded to the EU on 1 May 2004 all have income levels below the EU average – some significantly lower – and there are even gr eater income disparities at the sub-national level, with purchasing power less than half the EU-25 average in many regions of the new Member States. Policy development must be set in the context of the EU™s past experience , which has shown, firstly, that income convergence is not necessarily a rapid, continuous or automatic process. Seco ndly, convergence has been faster at the regional than at the co untry level Œ partly reflecting the fact that disparities have been higher within than between Member States. Thirdly, regional specialisation and concentration have not changed significantly. Lastly, in the early stages of catching-up, growth tends to strengthen first in agglomerations: thus regional income inequalities within countries may initially increase as the national growth rate accelerates. Looking at the situation to date in the new Member States , data on sources of growth between 1996 and 2005 show that economic convergence has been driven by investment and total factor productivity (TFP), while under- utilisation of labour has acted as a bra ke. A scenario for 2006 to 2010, ba sed on a broad continuation of recent experience, shows that the contributions of capital and TFP may be expected to moderate somewhat in the future, while labour is likely to make a positi ve, though limited, contribution to gr owth. However, these projected growth rates are below 5 per cent, except for the Baltic countries, representing only limited progre ss in catching up to the EU average. Existing trends reveal a number of major policy challenges . One important concern is that employment rates are fairly low in most of the new Member States – particularly among older cohorts of the population. It will therefore be especially important to review tax-benefit systems in order to provide incentives to create and take up jobs, and to extend working lives . Labour markets remain relatively inflexible owing to insufficient wage differentiation, the impact of tax-benefit systems, and low regional labour mobility. Investment has been an important source of growth in the new Member States. Investment-to-GDP ratios are higher than in the EU-15, although production is still less cap ital-intensive. Given the early liberalisation of capital movements, foreign direct investment has been a major source of current account financing, closing the gap between domestic savings and investment. The heavily foreign-owned banking sector has been the main channel of financial intermediation. An important challenge for the future is to progressively mobilise higher domestic savings through channels such as pension funds and stock markets in order to promote faster, more broad-based growth. Innovation and knowledge being important triggers for technical progress, it is worth noting that educational attainment levels in the new Member States do not differ mu ch from those in the EU-15. Trade and foreign direct investment have been important for the cross-border transfer of knowledge in management and technology, but innovation has not yet been a central determinant of productivity growth in the new Member States. Activity and employment in R&D and innovation tend to be much lower than in the EU-15, which can best be explained by a different pattern of specialisation. The case for higher expenditure on R&D activities needs to be evaluated critically , given this specialisation, to ensure that it does not divert resources from other uses with higher economic returns. The new Member States have made great advances in trade liberalisation since the early 1 990s, and they have impressively increased trade with the EU, in particular u nder the Europe Agreements. This expansion of trade no doubt contributed significantly to their growth performance over the past decade. Membership brings some further trade liberalisation in sensitive secto rs (agriculture, services) and reduction of non-tariff barriers Œ as well as a possible further reduction in transport costs as a result of lower waiting times at borders and improvements in infrastructure. Less exchange rate volatility in the case of ERM II participation and the adoption of the euro could reduce costs even further and trigger additional trade and growth. The new Member States have also made good progress in establishing a stable macroeconomic framework , though those aiming for rapid progress towards euro-area membership will need to entrench this further , as inflation remains somewhat high and variable in some cases. ERM II can provide a framework within which to enhance policy credibility, thou gh the alternative of keeping greater exchange rate flexib ility offers more latitude for variations in inflation associated with the challenges of transformation and catching-up Œ thus helping to avoid a loss of external competitiveness. The majority of the new Member States still have budgetary deficits that are much higher than the 3 per cent benchmark for euro-area memb ership, although public debt levels are mostly below 60 per cent of GDP; however, fiscal consolidation remains a cons iderable challenge in the light of the need to build up and modernise infrastructure, reorient public spending, and cushion the costs of ongoing restructuring. To safeguard external and financial stability, attention needs to be paid to the interaction of monetary, prudential and fiscal policy regimes and the ways in which these may influence risk behaviour in the private sector. In particular, as the private
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sector enters a phase of strong expansion, the design of fiscal policy can play an important supporting role in ensuring that imbalances are limited and that financial market confidence is maintained. Studies increasingly stress the quality of institutions as an important factor in convergence. Here, despite impressive progress in recent years, the new Member States still have considerable gaps to make up Рparticularly with regard to efficiency in public admin istration and the judiciary. Preparation for EU accession provided an external anchor for progress in this area, helping to catalyse political sup port for change. With the ficarrotfl of EU membership no longer available, there is a need for reflection on how mechanisms at th e EU level might play a stronger role in providing further support for this process . EU cohesion policy is the final subject considered in this chapt er. Despite limited financial resources, this policy could have a substantial impact on catching-up Рbut only if a number of conditions are met: stronger spatial concentration, improved thematic concentration, and implementation approaches that better safeguard cohesion goals . Spatial concentration means focusing Structural Funds on those regions and Member States most in need Рwhile ensuring that this selection process works with, rath er than against, market forces. Thematic concentration means choosing, in each case, an effective investment mix Рbased on a sound analysis of existing infrastructure endowment, human resource requirements, and limits on aid to the productive sector. Effective implementation requires that the management of Structural Funds be further simplified, and that the new Member States complete the building of necessary administrati ve capacity. In short, the contribu tion of EU cohesion policy to real convergence will depend above all on the commitment of policy-makers in Member States to coherent national and regional policies Πensuring that the environment in which Structural Funds are utilised is characterised by macroeconomic stability, continuing structural reforms, and good governance. In view of the still limited knowledge of economists about the relative importance and detailed interaction of each of the main policy levers, policy can best foster stronger and more broad-based growth through a comprehensive approach addressing all the strongest drivers of economic growth Πtrade, macroeconomic stability and institutional quality Рas well as making efficient use of EU cohesion policy.
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TABLE OF CONTENTS 1. INTRODUCTION 5 2. CATCHING -UP IN THE EU: WHERE DO WE STAND AND WHAT DO WE KNOW ? 6 2.1 The lessons fro m the past .. .6 2.2 Recent trends in convergence of the new Memb er States . ..9 2.3 Spatial dimensions of convergence ..11 2.4 Summary .. 15 3. HOW TO ACCELERATE CATCH -UP GROWTH IN THE NEW MEMBER STATES ? 16 3.1 The accumulation and diffusion of production factors and knowle dge .17 3.2 Other determinants of economic growth .. .24 4. WHAT CAN BE THE CONTRIBUTION FROM EU COHESION POLICY ? ..35 4.1 Evidence of structur al funds impact . ..35 4.2 Conditions for maxi mising the impact 38 4.3 Policy challenges . .46 REFERENCES 48 ANNEX I: METHODOLOGICAL CONCEPTS OF CONVERGENCE .55 ANNEX II: SEMI -PARAMETRIC TECHNIQUES ..56
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5CATCHING UP, GROWTH AND CONVERGENCE OF THE NEW MEMBER STATES1. Introduction Income levels in a majority of the ten new Member States, which acceded to the EU on 1 May 2004, are significantly below the aver age of the former EU-15. Average GDP per capita in the enlarged EU is almost 10 per cent lower than previously, and inequalities are substantially wider. This makes the objective of achieving greater economic cohesion and convergence even more pressing than before. Graph 1, displaying the level of GDP per capita in euro and in Purchasing Power Standards (PPS) in the 25 Member States in 2004, shows the considerable disp arities between old and new Member States, but also among the new Member States.1 The ranking of Cyprus, Slovenia and Malta is close to that of the fioldfl cohesion countries (Spain, Greece and Portugal). The Czech Republic and Hungary have a notably higher GDP per head than Slovakia, Poland and the three Baltic countries. Disparities at sub- national, regional level are ev en larger. GDP per head in PPS in many regions of the new Member States is less than half of the EU-25 av erage and the poorest ones have even less than a th ird of the EU-25 average. Given that economic and social cohesion is one of the objectives specified in th e EU Treaty, this chapter attempts to identify the main policy levers for a sustained process of catching-up in the new Member States, based on past experi ence of real convergence in the EU as well as on evidence from the broader economic literature. Relevant developments in both the EU-15 and the EU-25 are described in Section 2. Section 3 reviews potential determinants of catching-up, and analyses the empirical evidence in the EU as well as 1 Due to higher costs of living, income expressed in euro is higher than that expressed in PPS in most Member States above EU-25 average; the opposite holds for those below average. the policy challenges for the ten new Member States. Apart from the standard determinants of growth Πlabour, capital and technical progress Πother driving forces of growth such as trade and geography, macroeconomic stability and institutional quality are reviewed. Section 4 discusses the potential contribution Graph 1 : GDP per head in EU Member States, 2003 0102030405060 LVPLLTEECYSKHUCZMTPTSIELESEU-25 ITDEEUR-15 FIFRSEBEUKNLATDKIELU1000EUR PPS Source: Commission services.
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6of EU cohesion policy, the goal of which is to enhance growth and employment in lagging Member States and regions. 2. Catching-up in the EU: Where do we stand and what do we know? This section provides an over view of recent trends in catching-up and convergence among countries in the EU, at both national and regional levels. It focuses particularly on the EU cohesion countries – which include Spain, Portugal and Greece, as well as the 10 new Member States. 2 In addition, some relevant lessons are drawn from wider experience in the EU. The analysis is based on a qualitative assessment of key trends, as well as on econometric evidence; and the experience of the new Member States during the past decade is also specifically reviewed. 2.1 The lessons from the past Experience suggests that convergence and catching-up are not automatic outcomes of accession to the EU. Graph 2 provides evidence for the former four cohesion countries. It displays their level of GDP per capita, measured in terms of Purchasing Power Standards (PPS), during the period 1960-2003. 3 Ireland, now often cited as a success story, is a particularly interesting case. In 1960, it had a level of GDP per head of about 67 per cent of EU-15 average. Whereas notably during the 1960s and early 1970s the other three economies experienced rapid expansion, the Irish relative position in terms of per capita GDP per headmore or less stagnated until the mid-1980s when the Irish economy truly took off. Since then the country went on to become, by 2003, one of the richest Member States with a GDP per capita nearly twice as high as Portugal. 2 Since 1 st of January 2004 Ireland is no longer eligible to the Cohesion Fund given the level of its Gross National Income (GNI) per head compared to the EU average and therefore no longer included in the group of so-called ficohesion countriesfl. 3 Given that convergence refe rs to a long-term process, a sufficiently long period (1960-2003) is considered here while acknowledging the fact that this does not necessarily correspond to the accession dates of the cohesion countries, i.e. 1973 for Ireland, 1981 in the case of Greece and Portugal and Spain joined in 1986. Also, it should be noted that intertemporal comparison of PPS figures is limited for methodological reasons. These in consistencies have been partly corrected in the data used here; see Eurostat (2002). This performance in Ireland went hand-in-hand with the implementation of stability-oriented macroeconomic policies, and a new approach to industrial relations – which was also initiated in the mid-1980s. However, Ireland™s success cannot be attributed to these factors alone, but was also the result of a variety of mutually reinforcing policies, some of which had been pursued for more than 40 years under a pro-active strategy to foster economic development. Worth noting are the continuity and predictability over this long period of the policy approaches to attracting FDI and promoting clusters of export-led manufacturing and services activities. Highly important, too, were the investments made in education from the mid-1960s, which translated into labour productivity gains in the late 1980s and 1990s. The evolution of Ireland illustrates that convergence is a process having deep roots in a range of policy areas which may take time to bear fruit. Graph 2 : Evolution of GDP per head in PPS to the EU-15 average (EU-15 = 100) 4060 80100 120 140 19601964196819721976198019841988199219962000 Greece Spain Ireland Portugal Source: Commission services. Furthermore, the experience of these countries suggests that catching-up does not ne cessarily occur at a steady pace. Table 1 below provides additional evidence by reporting the 10-year average annual rate of catch-up for these countries, between 1960 and 2003. This indicator measures the average percentage change in the gap between each country™s GDP per capita and the EU-15 average.
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8These results provide a first indication that convergence is indeed taking place, and how long it may take to run its course. Although it appears faster among regions than among countries, these results must be treated with caution for at least two reasons. First, as discussed above, experience shows that the pace of convergence may vary greatly across countries and time periods. Second, as the literature on -convergence points out, least square estimators are lik ely to be biased since they do not control for time-inva riant features that are country- or region-specific. In its simple OLS form, one implicitly assumes that al l countries converge to the same steady state. In order to relax this hypothesis, a fifixed-effect panel estimatorfl can be used instead to take account of unidentified country-specific or region- specific features.8 Columns 3 and 4 of Table 2 provide such estimators for the EU countries and regions. The fixed-effect estimators obtained are only slightly larger than the OLS ones when considering country-level results, but when using region-level data the difference appears to be more substantial. On this approach, the estimated convergence rate oscillates between 2.4 per cent and 2.7 per cent at the country-level and 4.6 per cent and 6.2 per cent at the regional level. 9 Again, convergence is present, a nd appears to be generally stronger among regions. As mentioned earlier, evidence of -convergence among countries, and across regions EU-wide, does not necessarily mean that disparities in GDP per head within the EU are falling, see Annex I. In order to get a more complete picture of the convergence process it is necessary to analyse the e volution of GDP per head disparities as -convergence which measures the change 8 See Islam (1995). Other authors have criticized the regression approach to convergence on the ground that this method provides no information on the dynamics of the entire cross-sectional distribution of regional income and have proposed alternative me thods based on non-parametric statistical techniques which allow considering the existence of ficonvergence clubsfl where countries and regions converge to different steady st ates; see for instance, Quah (1996) and 1997) and Durlauf/Quah (2002) for a review. 9 Note that the fact that fixed-effects estimators of -convergence display larger estimates in absolute terms is a well-known fact in the literature suggesting that the bias of OLS estimators is downward. However, these estimators are more sensitive to the sample of countries or regions considered as well as to the time-length of each time-series; see Tondl (2001). For instance, the estimates found here are rather lower than the ones generally found in convergence studies. Islam (1995) finds a rate of 9 per cent for a sample of OECD countries, Canova/Marcet (1995) find a rate of 23 per cent for EU regions and Tondl (1997) a rate of 20 per cent for EU regions. Table 3: Test of – convergence in the EU, 1982-1996 Year 1982 1988 1996 % annual change 82-88 % annual change 88-96- Country-level results Gini 0.1337 0.1284 0.0977 -0.66 -2.99 Theil 0.0320 0.0291 0.0174 -1.51 -5.03 coef. var* 0.0303 0.0276 0.0167 -1.49 -4.94 Region-level results Gini 0.2127 0.2115 0.2037 -0.09 -0.46 Theil 0.0720 0.0704 0.0652 -0.37 -0.92 coef. var* 0.0703 0.0677 0.0656 -0.62 -0.39 Note: Concerns regions NUTS2 of Be lgium, Germany, Spain, France, Italy, Netherlands, Greece, Portugal. * Half of the square of the coefficient of variation. in the variation around the mean GDP per head. Table 3 provides evidence using three indicators generally used in the convergence literature: the Gini index, the Theil index and the square of the coefficient of variation. 10 The results depicted in Table 3 show, rather unsurprisingly, that inequa lities are larger between EU regions than between countries. More importantly, these results show that inequalities have tended to decrease over the period considered, i.e. from 1982 to 1996, with an accentuated fall from 1988 onward. Interestingly, while the same result holds for both country-level and region-level data, the average annual fall in inequalities seems to be higher for countries than for regions, as shown by the last two columns of Table 3. This suggests that, while so me convergence took place, it was more pronounced at the country level than at the regional level. Although such evidence seems to be at odds with the above -convergence analysis, this needs not to be the case. The estimated -convergence results at the regional level show th at the average convergence rate was well above 2 per cent: individual regions thus had very different experiences, explaining in turn the results obtained for the -convergence. 11 A number of economists have also suggested that region-level and country-level convergence have not followed the same rhythm in the EU over the past decades. In particular, Esteban (1999) and Duro (2001) show that, while GDP per head dispersion between EU countries has decreased 10 Not all EU-15 countries are considered in this table since regional data were not avai lable for all years and all countries. The results thus onl y concern Belgium, Germany, Spain, France, Italy, Netherlands, Greece and Portugal. Also, for the same reason, only the years 1982, 1988 and 1996 are considered. 11 See Chatterji (1992).
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9 Table 4: Decomposition of – convergence: within vs. between countries components, 1982-96 1982 1988 1996 % annual change 82-88 % annual change 88-96 Theil index Between country 0.0494 0.0464 0.0396 -1.01 -1.86 Within country 0.0225 0.0240 0.0257 1.09 0.89 Coefficient of variation Between country 0.0450 0.0410 0.0372 -1.45 -1.18 Within country 0.0253 0.0266 0.0284 0.86 0.82 Note: Concerns regions NUTS2 of Be lgium, Germany, Spain, France, Italy, Netherlands, Greece and Portugal. during the 1980s and the 1990s, inequalities between regions within the same country have tended to increase.12 In order to see this, the Theil index as well as the coefficient of variation for EU regions can be decomposed into within and between countries™ variations. 13 The results of such a decomposition are reported in Table 4. According to these results, the slight decrease in regional inequalities observed in the EU between 1982 and 1996 masks in fact two opposite shifts: inequalities between countries have tended to decrease, while inequalities within countries have tended to increase. The overall picture for the EU noted above Œ one in which there is a general fall in regional inequalities Œ thus reflects the dominance of favourable changes across countries over adverse changes within countries. A number of authors have offered potential explanations for this phenomenon. The main one put forward in the literature is that economic integration, which advanced quite strongly during the period considered here, may benefit mainly a limited number of regions, at least initially. These would include, notably, the most dynamic and innovative regions in each country Œ those that are also best placed to benefit from potential externalities within the EU economy as a whole. 14 The resulting pattern would be that convergence increases at the country level, but that it is in practice driven mainly by a few regions. Within countries, by contrast, levels of GDP per head could well tend to diverge. (Section 2.3 will consider these issues in more detail.) Such a conclusion would be of clear relevance to the new Member States, where GDP pe r head disparities within countries typically are at pr esent more marked than in 12 Duro™s (2001) result is reported by Puga (2002). 13 For the description of such decomposition, see Annex I. 14 See Giannetti (2002). the former EU-15. It may be that Œ as convergence proceeds at the country level Œ these internal disparities could become yet wider, at least on a temporary basis. 2.2 Recent trends in convergence of the new Member States Analysis of convergence developments in the new Member States is constrained by the fact that the time series for GDP per capita are available only for a short time span – in general, since the beginning of the 1990s. 15 This poses a major problem for estimating -convergence, for example, sin ce this requires time series over a much longer period. The consequence is that no proper econometric tests can be carried out. Nonetheless, apparent patterns in the available data do suggest some interesting insights. Graph 3 displays the relative level of per capita GDP for Greece, Portugal, Spain and the 10 new Member States, individually, compared to the EU-25 average for the years 1991, 1997 and 2003. The figure also shows how the weighted average of GDP per capita for these respective country groups Œ the three existing cohesion countries and the new Member States evolved. 16 On average, the relative level of GDP per head of both groups rises over the period. In 1991 the level of GDP per head of the three cohesion countries amounted to 84.2 per cent of the EU- 25 average, while by 2003 it had risen to 90.3 per cent. For the group of new Member States, the increase is even more pronounced in relative terms – advancing from 42.3 per cent to 53.3 per cent of the EU-25 average. Graph 3 : Evolution of GDP per capita in Greece, Portugal, Spain and the new Member States, GDP per capita in PPS 1991-2003 CYCZEEHULTLTLVMTPLPLSKSKES + PT + EL New Member States CYCYCZCZEEEEESESESELELELHUHULTLVLVMTMTPLPTPTPTSKSLSLSL204060801001991199319951997199920012003 EUR-25 GDP per capita = 100 Source: Commission services. 15 Even for that period, data are only fully comparable between 1995 and 2003 because a revision of purchasing power standards (PPS) before 1995 has not yet been made. 16 Total population is used as weight.
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10Table 5: Average annual % catch-up rate for the new Member States, 1991-2003 1991-94 1995-98 1999-2003 1991-2003 new MS 1.84 -1.74 -2.07 -1.01 Cyprus -6.34 0.57 -2.87 -2.59 Czech Rep. 1.04 0.71 -1.29 -0.04 Estonia 0.62 -2.44 -2.48 -1.90 Hungary 0.88 -0.86 -2.73 -1.21 Lithuania 16.00 -2.56 -2.51 2.10 Latvia 14.84 -1.21 -2.88 2.11 Malta -5.18 -3.36 0.76 -2.10 Poland -1.53 -2.55 -1.05 -1.67 Slovakia -2.33 -2.08 -1.29 -1.81 Slovenia 0.36 -3.64 -4.38 -2.95 ES+EL+PT 3.37 -2.82 -2.98 -1.34 Spain 3.33 -6.12 -6.20 -3.79 Greece 3.74 1.38 -5.34 -0.83 Portugal 3.04 -3.73 2.59 0.59 Source: Commission services. The overall evolution seems ra ther favourable, however, with some differences both across time and countries. The years between 1991 and 19 94 represent a period of relatively slow catching-up which can be explained by the economic downturn of the early 1990s and by the transition process in new Member States. 17 Some differences also appear between countries which do not necessarily correspond to the distinction between cohesion countries and new Member States. For instance, countries such as Spain, Cyprus, Slovakia and Slovenia experienced steady catching-up, while other countries such as Lithuania and Latvia – and also, to some extent, the Czech Re public and Portugal – experienced uneven developments. In order to shed more light on how fast countries actually caught up towards average EU income during the past decade, Table 5 reports the average annual catch-up rate of the new Member States together with Greece, Portugal and Spain, using the EU-25 average as benchmark. 18 Overall, Spain has experienced the fastest catching-up, with an average annual rate of convergence of -4 per cent. Other countries such as Cyprus, Estonia, Malta, Slovenia, Poland and Slovakia have displayed average catch-up rates of arou nd -2 per cent. Again, the timing differs across these economies. Countries such as 17 During the period 1992-1994 the average growth rate of the new Member states was equal to -0.08 per cent, 0.76 per cent for Spain, 0.01 per cent for Portugal, 0.37 per cent for Greece and 1.58 per cent for the rest of the EU. 18 Note that the differences in the catch-up rates between the first column of Table 5 and the last row of Table 3 are due to the different reference group considered which is the EU- 25 average in the first case and the EU-15 average in the second case. Table 6: Test of – convergence in the EU, 1995-2001 Year 1995 1998 2001 % chg. 1995-1998* % chg. 1998-2001* Country-level results Gini 0.177 0.165 0.160 -1.54 -0.95 Theil 0.055 0.050 0.047 -3.08 -1.96 coef. var 0.050 0.045 0.043 -2.80 -1.92 Region-level results Gini 0.284 0.259 0.248 -2.95 -1.45 Theil 0.143 0.124 0.112 -4.49 -3.11 coef. var 0.129 0.112 0.105 -4.58 -1.96 Note: Including regions NUTS2 of France, Italy, Germany, Netherlands, Portugal, Spain, Greece, Austria, Italy, United Kingdom, Belgium, Sweden, Slovakia, Hungary , the Czech Republic and Poland. * percentage annual change. Source: Commission services. Cyprus, Malta, Poland and Slovakia experienced catching-up during the years 1 991-1994, while the rest of the countries experienced a less favourable evolution over that period due to transition crises. In particular, Lithuania and Latvia saw their GDP per capita drop on average by 16 and 15 percentage points, respectively, compared to the EU-25 level, reflecting the deep impact of transition. Following this mixed picture, the years after 1994 are marked by a general tendency for most countries to catch-up toward average EU GDP per capita levels. While a -convergence analysis cannot be undertaken because of a too short data time series, some results can still be obtained for -convergence although the results must be considered with caution for the same reason. Table 6 shows the results for all EU-15 members except Ireland, Denmark and Luxembourg (for which regional data were not available at the NUTS2 level) but, in addition, Poland, the Czech Republic, Slovakia and Hungary. 19 19 Other new Member States di d not have regional data on an annual basis for the period considered while others, such as Estonia, Cyprus, Latvia, Lithuania and Malta have no NUTS2 breakdown.
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11Table 7: Decomposition of – convergence: within vs. between countries components, 1995-2001 1995 1998 2001 % chg. 1995-1998 % chg. 1998-2001 Theil index Between countries 0.117 0.095 0.082 -6.12 -4.75 Within countries 0.027 0.029 0.031 2.65 2.36 Coefficient of variation Between countries 0.095 0.075 0.066 -6.98 -4.13 Within countries 0.034 0.036 0.039 2.12 2.54 Note: Includes NUTS2 regions of France, Italy, Germany, Netherlands, Portugal, spain, Greece, Austria, Italy, United Kingdom, Belgium, Sweden, Slovakia, Hungary , the Czech Republic and Poland. As expected, inequalities are significantly larger when including the new Member States. The results also tend to confirm the developments noted in the earlier discussion relating to the 1982-96 period. In particular, the average annual variation of the three measures of convergence shows that in all cases GDP per head disparities in the EU have narrowed. This result holds at both country-level and region-level, although it is less pronounced when considering country-level results for the period 1998-2001. Fu rthermore, the pace of catching-up seems to have in creased compared to the earlier period, especially at re gional level, although the starting level of regional inequalities is also much higher. Table 7 indicates that the decrease in regional inequalities is essentially due to a fall in between-country inequalities, as was found in the earlier analysis. In turn, w ithin -country inequalities have increased at rates varying between 2.4 per cent and 2.6 per cent a year depending on the indicator used. This result thus tends to reinforce the findings observed for the EU-15: while some convergence can be observed at the country level and regional level for the EU-25 as a whole, there has been a rise in regional inequalities within countries. In sum, experience suggests th at the road to convergence is far from an easy one. Firs t, over the long run, some convergence has been taking place in the EU, but this process was rather slow. Econometric results show that the rate of convergence was just under 2 per cent over the past decade – meaning that it may take around 30 years, on average, to halve any GDP per capita gap vis- à-vis the EU average. Sec ond, the pace of catching-up has varied a good deal across countries and time periods. Third, the experience of former cohesion countries underscores that accession does not automatically trigger rapid catching-up. Fourth, evidence at the regional level is complex. Convergence periods appear, at first glance, shorter for regions than for countries, based on EU-wide developments. But this masks a tendency that regions within countries have, initially at least, diverged rather than converged which reflects the strong performance of the more dynamic regions in a country. 2.3 Spatial dimensions of convergence The economic literature suggests two potential trade- offs that may explain why convergence is not even across countries and regions. The first is that countries and regions differ in their initial potential to benefit from any given increase in integration as some may be more attractive for the location of economic activities than others. The second is that, over long periods of integration, regions within countries may develop along different paths. In particular, for countries starting from relatively low levels of income, fast national growth may entail rising regional inequalities given that economic development is ra ther localised around a limited number of growth poles. In practice, both of these effects interact and de termine the way the benefits of economic integration spread across regions. These issues are considered in more detail below. 2.3.1 The location of economic activities in the EU The question of the potential impact of economic integration on the location of economic activities has generated a sizeable amount of literature over the past decade. In particular, resear chers have largely used the framework of New Economic Geography (NEG) to draw possible conclusions about the impact of EU integration on the location of economic activities and, ultimately, the relative wealth of the countries and regions concerned. 20 A frequent general interpretation is that economic integration may, at least initially, improve the competitiveness of core EU regions more rapidly than peripheral areas – thus deepening income inequalities throughout the EU. 21 Accordingly, the relationship between economic integration and the spatial distribution of activity would be non-monotonic: as trade costs decline, aggl omeration initially increases – but subsequently it begins to decline, provided trade costs fall to a sufficient degree. 22 Using this theoretical backgr ound, empirical studies on the EU have considered how the spatial distribution of 20 This literature has provided extensive discussion of the importance of elements such as market size, economic linkages, imperfect competition and returns to scale in determining the geographic lo cation of economic activities. See Krugman (1991), Krugman and Venables (1996) and Duranton and Puga (2004). 21 See Combes and Overman (2004). 22 Martin and Ottaviano (1999) and Baldwin, Martin and Ottaviano (2001) have built economic geography models with endogenous growth to show that the interactions between agglomeration and growth are also likely to be influenced by the decrease in transport costs and act as an additional force in favour of agglomeration.
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