The impact of Cohesion Policy on the level and quality of employment in countries of the Visegrad Group summary and conclusions

The impact of Cohesion Policy on the level and quality of employment in countries of the Visegrad Group summary and conclusions Report Warsaw, April 2011 This study is co-financed by the European Regional Development Fund

Contractor: PAG Uniconsult Migdałowa 4 St., 02-796 Warsaw Phone: (22) 256 39 00 Fax: (22) 256 39 10 e-mail: biuro@pag-uniconsult.pl Authors: Jerzy Drążkiewicz Ewa Kusideł Paweł Penszko Contracting Authority: Ministry of Regional Development Department of Structural Policy Coordination Wspólna 2/4 St., 00-926 Warsaw Phone: (+48 22) 461 39 07 Fax: (+48 22) 461 32 63 e-mail: ewaluacja@mrr.gov.pl e-mail: sekretariatdks@mrr.gov.pl Warsaw, April 2011 A study co-financed by the European Regional Development Fund

TABLE OF CONTENTS Table of Contents... 3 Summary... 4 Introduction... 9 Description of the research approaches and methodologies applied in the studies... 9 General trends in labour markets in the Visegrad Group countries in two evaluation sub-periods: 1999-2003 and 2004-2008... 11 3.1 Level of economic activity...11 3.2. The size and structure of the employed population in the Visegrad Group countries...12 3.3. Employment structure by education...14 3.4 Employment rates broken down by gender and age...16 3.5. The unemployed and long-term unemployed...17 Impact of the cohesion policy on changes in the labour market... 18 4.1. Jobs created broken down by gender, age and education...19 4.2. Jobs created for specific groups of people, in particular the disabled and long-term unemployed...21 Impact of the cohesion policy on employment structure by sectors of the economy... 23 Impact of the cohesion policy on the differentiation of regional labour markets... 24 The process of transition to a knowledge-based economy... 26 Evaluation of the effectiveness and efficiency of interventions under the cohesion policy (characterisation and comparison)... 29 8.1. Instruments of support for enterprises...30 8.1.1. Created jobs...30 8.1.2. Maintained jobs...32 8.2. Support instruments for individuals...33 8.2.1. The impact of support for the unemployed...34 8.2.2. The impact of support for the employed...36 8.2.3. The impact of support for business start-ups...37 The quality and sustainability of the jobs created or maintained... 38 9.1. Jobs created or maintained as a result of support for enterprises...38 9.1.1. The quality of created/maintained jobs...38 9.1.2. Sustainability of created jobs...40 9.2. Jobs created/maintained/improved as a result of support for individuals...40 9.2.1. The quality of created/maintained/improved jobs...40 9.2.2. The sustainability of created/maintained jobs...41 Conclusions and recommendations... 43 Annex 1 Comparison of national evaluation methodologies... 46 3

SUMMARY This report summarises the results of the study Impact of the cohesion policy on the level and quality of employment conducted in 2010 by three countries of the Visegrad Group, the Czech Republic, Poland and Hungary, each covering a similar scope and applying similar methodology. Slovakia prepared a report presenting some data on the labour market for the period before and after accession to the EU. The primary objective of the studies was to analyse and evaluate the impact of interventions co-financed with European Union structural funds under the cohesion policy on the level and quality of employment, taking into account the requirements of a knowledge-based economy. The objectives of the synthesis and summary presented in this report are as follows: to formulate conclusions and recommendations regarding the role of the cohesion policy in supporting fuller employment and higher quality jobs to identify its most effective and efficient tools for supporting employment to present recommendations for better concentration of the support after 2013 A common feature of the evaluations conducted in the Czech Republic, Hungary and Poland was the use of a wide range of different methods of data collection and analysis, combining top-down and bottom-up approaches. In each of the national studies, the following methodologies were applied: o o o Desk research: Analysis of documents, earlier reports and studies Analysis of statistical data provided by national statistical offices, Eurostat and national ministries Analysis of databases using methods such as regression models and PSM (Propensity Score Matching) Use of results of economy macro-models, developed independently of the evaluation project (not applied in the Czech report) Quantitative studies based on questionnaires Qualitative studies based on individual or group interviews Case studies of projects that generated jobs in enterprises (not applied in the Czech report) Based on the summary and synthesis of the study results, conclusions were formulated regarding the effectiveness, sustainability and efficiency of intervention within the framework of the cohesion policy on the labour market in the Visegrad countries. The main conclusions are presented below. General trends in the labour markets of the Visegrad countries In view of the declining number of people of working age across Europe, stimulating economic activity is one of the basic challenges of labour market policies, in particular in such countries as Poland and Hungary, where the level of economic activity is below the average noted in the European Union. Analysis of the economic activity rate shows that the Czech Republic and Slovakia have the highest economic activity, while Hungary has the lowest. However, it should be 4

emphasized that while in the other Visegrad countries economic activity fell systematically within the analysed period of 1999-2008, in Hungary it increased by 0.5% from year to year. Hungary (with an indicator of 61.5%) has a long way to catch up with the EU average, which was 70.9% in 2008; however, the positive trend in the economic activity indicator indicates that adequate efforts are being made. All four countries of the Visegrad Group recorded an increase in employment within the period analysed. The highest increase was noted in Slovakia, where the number of people employed grew by an average of 1.6% from year to year. The division into two reporting sub-periods shows that the rate of increase was higher in the period following EU accession. Hungary is an exception, as the growth rate in that time fell compared to the pre-accession period. In terms of education level, similar tendencies occur in all the countries analysed. The percentage of employees with only primary education is dropping, the percentage with secondary education is stabilising and the percentage with tertiary education is increasing. However, the rate of these changes is varied. In at least two cases the changes are rather slow: Hungary, with the highest percentage of uneducated people (ISCED 0-2) among the employed, has the lowest rate of decline of this trend (but the rate was markedly higher in the sub-period of 2004-2008), while the Czech Republic has the lowest percentage of employees with tertiary education and the lowest increase rate in the number of such employees (but the rate of growth was higher after accession). According to the Lisbon Strategy, the measure of success of a labour market is a high employment rate, for which the target in 2010 was an average of 70% in the EU member states, rather than a low unemployment rate. Of all the Visegrad countries, the Czech Republic is closest to this level with the highest employment rate, 66.6% in 2008. In all the Visegrad countries the employment rate differs considerably between women and men (with the greatest difference in the Czech Republic), but there is a similar tendency in many EU countries. The highest employment rate among persons aged 15-24 is recorded in the Czech Republic and Poland. The Czech Republic has the highest total employment rate due to markedly higher employment among persons aged 45-64. Population ageing, which is more noticeable in five-year age groups, is one of the major negative factors affecting the economy and social development in the Czech Republic. The impact of the cohesion policy on changes in the labour markets One of the key issues in the studies and the resulting synthesis is to what extent interventions undertaken within the framework of the cohesion policy helped, directly or indirectly, to maintain existing jobs and create new jobs. The answer is not straightforward because of the different methods applied to evaluate such impact in each country. To overcome this difficulty and assess the scale of the impact of the cohesion policy on employment, the impact of the funds was compared to the number of employed in the last year of the analysis. This produced coherent results showing that the impact of the funds was less than 1% of the number of people employed in 2008 in these countries: from 0.66 to 0.95% in the Czech Republic, 0.3-0.8% in Poland, and 0.53% in Hungary. Jobs created, broken down by gender, age and education In Poland and the Czech Republic the interventions had a particularly positive impact on people aged 15-24 (the share of jobs created due to the interventions was greater than the corresponding share of the total change in employment in the economy). In Poland persons aged 25-54 received relatively large-scale support. 5

As regards the gender of people for whom jobs were created, the intervention was found to have had positive effects for men in the case of Poland and for women in the Czech Republic. Analysis of education level showed that interventions helped create jobs for the least qualified employees (ISCED 0-2) in both the Czech Republic and Poland, although the change in employment among these employees was negative over the period of 2003-2008 in the Polish and Czech economies. However, markedly more jobs were created for the least qualified employees in the Czech Republic. In the case of Poland, interventions addressed to employees with secondary education had large-scale impact. The percentage of jobs for highly-qualified employees (ISCED 5-6) among the jobs created owing to the funds was much lower than this group's share of the actual change in employment, and was lower than their representation on the labour market in 2008 (thus, it can be presumed that those jobs would have been created even without the EU interventions). Jobs created for specific groups, in particular the disabled and long-term unemployed The results discussed in the Hungarian, Polish and Czech reports show that the EU interventions had a positive effect on jobs created for specific groups such as the longterm unemployed or the disabled. The impact of the cohesion policy on differentiation of regional labour markets It cannot be concluded from the data that the cohesion policy has had a positive impact on convergence processes in regional labour markets in the Visegrad countries. Most likely the minor impact of the policy on labour markets, accounting for less than 1% of the market, cannot be significantly reflected in macro-economic indicators (e.g. unemployment rate), especially over such a short time. The process of transition to a knowledge-based economy Observation of trends in employment structure in the Visegrad countries reveals a positive impact of the cohesion policy on the transition to a knowledge-based economy, though it is still minor and the pace of the process is slow. The number of employees in sectors requiring high qualifications and technologies, as well as the number of employees with tertiary education, is growing. Evaluating the effectiveness and efficiency of intervention within the framework of the cohesion policy One of the research questions concerned evaluation of the most effective and efficient types of interventions under structural funds: What types of intervention should be continued and developed in view of changes in the labour market, particularly in the face of the current economic crisis and possible future ones? The analysis distinguished two groups of interventions: those targeted at supporting enterprises and those targeted at individuals, in particular through training and education. The results of the studies in the Visegrad countries were analysed and compared from this perspective. The analyses focused on data obtained using a bottomup approach, i.e. from the beneficiaries of the support, collected using questionnaires, or derived from databases. The effectiveness and efficiency of instruments aimed at creating and maintaining jobs were evaluated. Support targeted at enterprises seems to be an effective instrument for creating new jobs due to high additionality (estimated at 71% in the Czech Republic and 78% in Poland). The effectiveness of interventions evaluated at the level of large economic 6

sectors is similar in industry and in services. Support granted to enterprises increases the percentage of women and young people among the employed. Moreover it provides the long-term unemployed with more opportunities for economic re-integration. The dynamic increase in the level of employment is achieved in particular by support granted to medium-size enterprises. Among support instruments addressed to enterprises, the greatest increase in the number of jobs is achieved by investments in the fixed assets of the companies. However, advisory services provided to companies are the most efficient, as measured by the cost of creating a job. Smaller companies, particularly micro-enterprises, most effectively utilise the support for maintaining jobs. Among the various support instruments for enterprises, the greatest effect in maintaining jobs is achieved by investments in the development of the company s operating capabilities. Support aimed at maintaining jobs in enterprises is more cost-effective than support for the creation of new jobs, in particular as regards jobs for employees with the lowest qualifications. Support addressed to individuals was found to affect the level of employment. In the Czech Republic projects financed under the ESF resulted in 30,000 new jobs. In Poland support granted under structural funds produced approx. 60,000 new businesses (of which most turned out to be sustainable). In addition, some 10,000-15,000 employees in sectors threatened by restructuring found employment in other sectors of the economy following retraining. Moreover, about 700,000 people benefit from training programmes and other forms of qualification enhancement by exploiting their newly-acquired knowledge and skills in their present jobs. PSM analysis of the impact of support for the unemployed on their likelihood of finding jobs led to different conclusions in the Czech Republic, where a net effect of 9-10 pp. was observed, and in Poland, where the total net effect was nil. Nevertheless, the net effect in Poland changed over time, showing a growing trend from a negative effect of 14-18 pp. before the the 3rd quarter of 2005 to a positive one of 8-18 pp. from the beginning of 2007. The effectiveness and efficiency of particular forms of support depend on the target group, so it is difficult to formulate definite conclusions about the superiority of some forms over others. Nevertheless, certain forms of support were identified as worth continuing: support for business start-ups, support for schools and pre-schools, and training in specific occupational skills, computer skills, driving, economics and business knowledge, and foreign languages. The quality and sustainability of created/maintained jobs In estimating the quality and sustainability of jobs created due to support for enterprises, it should be emphasised that the result is not uniform in each country. The study in Poland shows that support granted under EU funds helps to improve the quality of jobs in terms of education, positions, occupations and specialisations, as well as salaries. However, the Hungarian and Czech studies show that if education is taken to be the key parameter of job quality, high-quality jobs have not been created as a result of support granted to enterprises in these countries. Still, the jobs created are sustainable. The greatest number of permanent jobs are created by stable medium enterprises with a long-term history. As regards support for individuals, it should be noted that as in the case of support for enterprises, the conclusions concerning the quality are not identical in each country. In the Czech Republic and Hungary the quality of jobs created and improved with the use of ESF is indicated by such features as the occupational category, wages and education of the employees, but the conclusions are opposite: while in the Czech Republic support was mainly for low-quality jobs, ESF support in Hungary encouraged the establishment of high-quality jobs. The Polish study evaluated the impact of training on the quality of an 7

employee's job. Over a period of at least 2 years 75% of project participants experienced job improvement in the form of promotion, higher salary, new benefits or improvement of general working conditions. However, only 21% of respondents experienced such improvement and attributed it to their participation in the project. For this reason it should be noted that the impact of the cohesion policy on the job quality of training beneficiaries has limited scope. As in the case of support for enterprises, optimistic conclusions can be drawn from the evaluation results regarding the sustainability of the effects of support granted to persons under the ESF. 8

INTRODUCTION Since the expansion of the European Union to include Central and East European countries, issues relating to economic and social cohesion have become increasingly important. The countries of the Visegrad Group the Czech Republic, Poland, Slovakia and Hungary have become the main beneficiaries of the cohesion policy. In these countries issues relating to unemployment as well as the level and quality of employment are the most challenging social and economic problems. Adopting an effective and efficient employment policy and determining the best tools to support employment are among the main challenges for all member states of the European Union. In this context it is worth considering the role of the European cohesion policy and its impact on the level and quality of employment in the Visegrad countries. Identification of common elements tools that have proved successful and effective in all of these countries is essential. In 2010 three countries of the Visegrad Group the Czech Republic, Poland and Hungary conducted a study entitled Impact of the Cohesion Policy on the level and quality of employment, with each country covering a similar scope and applying similar methodology. Additionally, Slovakia prepared a brief document presenting the labour market and employment situation, together with information about the impact of the cohesion policy on employment in the country. A synthesis and summary of the results obtained in each country should help to formulate conclusions and recommendations regarding the role of the cohesion policy in supporting fuller employment and higher-quality jobs, including jobs characteristic of a knowledge-based economy. The synthesis should contribute to the discussion between the European Commission and member states concerning the future of the European cohesion policy. This report is an attempt to present such a synthesis. 1 DESCRIPTION OF THE RESEARCH APPROACHES AND METHODOLOGIES APPLIED IN THE STUDIES A common feature of the evaluation studies performed in the Czech Republic, Hungary and Poland is the use of a broad spectrum of methods of data collection and analysis, combining top-down and bottom-up approaches. In each of the national studies the following methodologies were applied: o o Desk research: Analysis of documents, earlier reports and studies Analysis of statistical data provided by national statistical offices, Eurostat and national ministries o Analysis of databases 2 using methods such as regression models and PSM (Propensity Score Matching) 1 The study analysed the following reports: Impact of the Cohesion Policy on the level and quality of employment in the Czech Republic, Prague, July 2010; The impact of Cohesion Policy on the level and quality of employment in Poland, Warsaw, July 2010; Impact of the Cohesion Policy on employment level and quality in the Visegrád countries, Budapest, November 2010 and Data for the summary report of the Impact Evaluation of the Cohesion Policy implemented between 1 January 2004 and 31 December 2008 on the level and quality of employment in the V4 Member States, Bratislava, November 2010. 2 Databases of beneficiaries who received support co-financed with EU funds, as well as databases of the unemployed and databases of enterprises administered by public offices. 9

Use of results of economy macro-models developed independently of the evaluation project (not applied in the Czech report) Quantitative studies based on questionnaires Qualitative studies based on individual or group interviews Case studies of projects that generated jobs in enterprises (not applied in the Czech report). There are certain differences between the sets of methods and techniques applied in the different countries. The Czech evaluation did not use the results of an economy macromodel or case studies. Only the Polish study used trends extrapolation and a panel of experts. Different techniques of quantitative and qualitative studies were applied in each country. In the Czech Republic an online questionnaire (CAWI) and individual in-depth interviews (IDI) 3 were used, the Polish study used computer-aided personal interviews (CAPI), computer-assisted telephone interviews (CATI), individual in-depth interviews (IDI) and an expert panel, while in the case of Hungary a questionnaire was sent by email and focus group interviews (FGI) were conducted. In addition, the Czech and Polish evaluations used PSM to determine the net effect of interventions targeted at the unemployed, while in Hungary it was used only to identify a sample of enterprises, which was then analysed with the difference-in-differences regression method 4. A summary of the methods applied is presented in Table 1 in Annex 1 to this report. Each country not only used a different set of methods but also applied different methods to study particular issues (which is crucial for comparability of the results). If seven research areas were to be distinguished 1) analysis of the condition and structure of employment before and after accession (not included in the Hungarian report), 2) measurements of the overall impact of the EU funds on the level and quality of employment in the economy, 3) convergence of regions, 4) impact of the intervention on competitiveness and innovation of enterprises, 5) impact of intervention on human capital development, 6) impact of intervention on modernization and development of infrastructure, and 7) integration and verification of conclusions, then the Polish evaluation is distinguished by the greatest specialisation of methods, i.e. the same method is seldom used for more than one research area. In the case of the Czech Republic and in particular Hungary, the same research methods were applied to examine many types of effects. Analysis of documentation, previous reports and studies was used in many areas in all of the countries. An example of the differences in the methods applied by the different countries is that while the Polish and Hungarian reports used the results of economy macro-models within the top-down approach to measure the total impact of the cohesion policy, the Czech report based a similar evaluation on available databases. Furthermore, the Czech and Polish evaluations used PSM to assess the effects of support to the unemployed, whereas in the Hungarian report the issue was addressed only in FGI interviews. A separate method for integration and verification of conclusions was applied only in the Polish evaluation. A more detailed summary of the methods applied in particular research areas is presented in Table 2 in Annex 1. The survey questionnaires were developed independently within each country's evaluation, which poses some limitations on comparison of results. Slovakia prepared a brief report instead of an evaluation study, based on statistical data and summarising the results of evaluations conducted in the country. 3 More specifically, individual guided interviewing technique was used (interviewees were given a set of previously prepared questions). 4 The difference-in-differences method, like PSM, is used to construct the counterfactual in order to measure the impact of the funds without selection bias. 10

GENERAL TRENDS IN LABOUR MARKETS IN THE VISEGRAD GROUP COUNTRIES IN TWO EVALUATION SUB-PERIODS: 1999-2003 AND 2004-2008 In this chapter the labour market in four Visegrad countries is characterised in two evaluation sub-periods before accession to the European Union (1999-2003) and after accession (2004-2008) to answer the following question: have trends in economic activity, employment rate and the structure of the employed population changed within the period after accession to the EU? The answer to this question will make it possible to answer the question posed by the Contracting Authority of this report, i.e. how many jobs have been created taking into account the following categories: Level of education of the employed (according to Eurostat) o Pre-primary, primary & lower secondary, ISCED level 0-2 o Upper secondary & post secondary, ISCED level 3-4 o Tertiary education, ISCED level 5-6 Age of the employed (with special attention to young people and those of postworking age) o 15-24 o 25-54 o 55-64 gender of the employed specific groups (e.g. the disabled and the long-term unemployed) Unfortunately, analysis of the reports did not allow for a satisfactory synthesis of the results regarding this question (in particular taking into account all the groups mentioned above), so in many cases analyses were performed using data from Eurostat databases 5. 3.1 Level of economic activity The main factor determining supply in the labour market is the level of economic activity, i.e. the number of persons that can and want to work. Economic activity depends on many economic factors, such as demand for work, salaries, sources of income other than salaries, and social factors (preferred family model, working attitudes, tradition of professional work among women, consumption models). In view of the shrinking number of people fit for work in Europe, stimulating economic activity among citizens will be one of the primary challenges of labour market policies, particularly in such countries as Poland or Hungary, where the level of economic activity is below that noted in Europe. The countries analysed differ significantly in the number of economically active people, due to considerable differences in population size (compare Charts 3.1.a and 3.1.b); therefore, in such comparisons it is more convenient to use economic activity indicators, 5 In the first section in particular the authors' own calculations had to be included because even where the report discussed the issues addressed, the form of presentation of the results did not allow for their coherent comparison. The analyses presented in the first section of this synthesis were performed under the control of the reports of the respective countries and if Eurostat data conflicted with those presented in the report, the inconsistency and/or its likely cause were clearly indicated. 11

which measure the share of economically active individuals in a particular age sector in this case 15-64. Chart 3.1a. Average population (1999-2008) Chart 3.1b. Average number of economically active persons (1999-2008) 45000000 40000000 35000000 30000000 25000000 20000000 15000000 10000000 5000000 0 CR Hungary Poland Slovakia Source: the authors' own analysis based on data from: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_agaed&lang=en. Analysis of the economic activity rate (see Chart 3.1.c) reveals that the Czech Republic and Slovakia have the highest economic activity and Hungary has the lowest. In 1999-2008 the average rate of economic activity was 71% for the Czech Republic, 69% for Slovakia, 65% for Poland and 61% for Hungary. However, it should be noted that while in the first three countries economic activity systematically decreased, in Hungary it increased by 0.5% every year (Chart 3.1.c). Hungary has in this respect a long way to catch up with the EU25 average, which was 70.9% in 2008 6, but the positive trend in the economic activity rate demonstrates adequate efforts. Chart 3.1c. Economic activity indicator 15-64 73,00 70,00 67,00 64,00 61,00 58,00 55,00 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia Source: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsi_act_a&lang=en. 3.2. The size and structure of the employed population in the Visegrad Group countries As mentioned earlier, the countries analysed differ considerably in population size, which is reflected in the significantly different size of the labour market (the largest labour market is almost 7 times the size of the smallest). Therefore, changes in the number of employed people cannot be analysed in absolute terms, as the information that in the Czech Republic, Hungary, Poland and Slovakia 280,000, 80,000, 893,000 and 298,000 more people were employed in 2008 than in 1999 7 cannot be applied directly to 6 Malta and Hungary lag furthest behind (data for 2008). Poland ranks 8th in this respect (difference of 7.6 pp.). The Scandinavian countries have the highest economic activity rates (about 80%). The Czech Republic and Slovakia achieve the average for EU25. 7 Based on data available at http://appsso.eurostat.ec.europa.eu/nui/show.do. 12

comparisons between the countries. After comparing these differences with the base period, i.e. taking into account the scale of the phenomenon, the data presented in Table 3.2.a are obtained. The table shows that all Visegrad countries noted an increase in employment, with the greatest changes over the entire period noted in Slovakia, where 14% more people were employed in 2008 than in 1999. Dividing the period in half shows that in all countries except for Hungary positive changes in employment occurred, in particular in the period following the accession to the EU. Table 3.2a. Change in the number of employed people in % 2008/1999 2003/1999 2008/2004 Czech Rep. 6% 0% 6% Hungary 2% 3% -1% Poland 6% -9% 15% Slovakia 14% 2% 12% Source: the authors' own calculations based on data from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egaps&lang=en. The above analysis also does not fully illustrate the nature of the phenomenon analysed as it compares changes for a particular year; if employment was exceptionally high or low in that year, the share change in the number of employed will be underestimated or overestimated. Therefore, the most appropriate indicator for assessing changes in these labour markets is the average rate of change in the number of employed persons as presented in Table 3.2.b. Table 3.2b. Average rate of change in the number of employed people in the three evaluation periods 1999-2008 1999-2003 2004-2008 Czech Rep. 0.6% 0.1% 1.6% Hungary 0.3% 0.8% -0.1% Poland 0.7% -2.4% 3.7% Slovakia 1.5% 0.4% 3.0% Source: the authors' own calculations based on data from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egaps&lang=en. 13

Chart 3.2a. Number of employed people in Poland (in thousands) Chart 3.2b. Number of employed people in the Czech Republic (in thousands) Chart 3.2c. Number of employed people in Hungary (in thousands) Chart 3.2d. Number of employed people in Slovakia (in thousands) Source: the authors' own analysis based on data from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egaed&lang=en. Once again it can be concluded that all four countries of the Visegrad Group have noted an increase in employment within the period analysed. The strongest increase was recorded in Slovakia, where the number of employed increased by 1.6% every year (Table 3.2b and Chart 3.2d). The division into two evaluation subperiods shows that the rate of increase in the number of people employed was stronger (and positive) in the period following accession to the European Union. Hungary is the only exception, where the rate of increase in this period fell compared to the pre-accession period. 3.3. Employment structure by education The division into three categories of education primary, secondary and tertiary was based on the International Standard Classification of Education (ISCED). The most recent ISCED classification distinguishes 7 educational levels, 0, 1, 2, 3, 4, 5 and 6, from preprimary (ISCED level 0) to the second stage of tertiary education (leading to an advanced research qualification ISCED 6). The levels are as follows: ISCED 0: pre-primary education, ISCED 1: primary education or first stage of basic education, ISCED 2: lower secondary education or second stage of basic education, ISCED 3: (upper) secondary education, ISCED 4: post-secondary non-tertiary education, ISCED 5: first stage of tertiary education (not leading directly to an advanced 14

research qualification), ISCED 6: second stage of tertiary education (leading to an advanced research qualification 8. These levels may be grouped into three broader levels of education: 1. Primary (low qualification) ISCED 0-2, 2. Secondary (medium qualification) ISCED 3-4, 3. Tertiary (high qualification) - ISCED 5-6. Below are charts showing the percentages of the employed population with each level of education 9. Chart 3.3a. Percentage of the employed population with primary education Chart 3.3b. Percentage of the employed population with secondary education Chart 3.3c. Percentage of the employed population with tertiary education 0,20 0,15 0,10 0,05 0,85 0,80 0,75 0,70 0,65 0,26 0,22 0,18 0,14 0,00 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia 0,60 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia 0,10 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia Source: the authors' own analysis based on data from: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egaed&lang=en. The above charts show that Hungary has the highest percentage of employed people with primary education (on average 15%) and Slovakia has the lowest (on average 6%). The highest percentage with secondary education is in Slovakia and the Czech Republic (on average approx. 80%), while in Poland and in Hungary it is on average 70%. The greatest percentage with tertiary education is in Hungary and Poland (on average 19%), while in Slovakia and the Czech Republic it is 14%. The charts point to similar tendencies in all the countries: a decrease in the percentage of employees with primary education, a stable number with secondary education and an increase in the number with tertiary education. However, the rate of change is varied. The rate of the decrease in the percentage of employees with primary education is similar for the Czech Republic, Poland and Slovakia. In the case of Hungary, which has the greatest percentage of uneducated workers, the rate of decrease is slower. For employees with secondary education, as shown above, there is no growing tendency the level is relatively stable over time. The percentage of employees with tertiary education is growing in all countries, with the highest number in Poland, followed by Slovakia, Hungary, and the Czech Republic. To sum up, it should be noted that for at least two countries an increase in rate of change can be postulated, as follows: In Hungary, the rate of decrease in the percentage of the employed population with the lowest qualifications (while the percentage without education is highest (ISCED 0-2), the rate of increase in this area is the lowest) 8 Based on the CEDEFOP report Future skill deeds in Europe. Medium-term forecast. Synthesis report. Office for Official Publications of the European Communities, Luxemburg 2008, s. 110-112 9 To avoid repetition, the following terms are used interchangeably in this subsection to refer to the ISCED 0-2 education level: primary education, without education, low qualifications, primary. 15

In the Czech Republic, the rate of increase in the percentage of the employed population with tertiary education (with the lowest percentage and the lowest rate of increase in this area) 3.4 Employment rates broken down by gender and age According to the Lisbon Strategy, the measure of success of a labour market is less a low unemployment rate (analysed in section 3.5) as a high employment rate 10, for which the target for 2010 was a 70% average for EU member states. Among all countries of the Visegrad group, the Czech Republic is the closest to that level, with the highest employment rate at above 65%, as seen in Chart 3.4.a. This is emphasised by the authors of the Czech report (p. 18), which points out that the employment rate in the Czech Republic is above the average for the EU-25. Within the period analysed the employment rate in Poland first fell (1999-2003) and then rose to 59% (2004-2008), which means that 59 persons were employed among every 100 persons aged 15-64. In the other countries the increases in the employment rate were much weaker in Slovakia and Hungary it increased by averages of 0.47% and 0.51% from year to year within the period of 1999-2008. In the Czech Republic it was relatively stable (as indicated in p. 17 of the Czech report). In Poland substantial differences are observed between the employment rates for women and men: the percentage of working women is on average 25% lower than that of men. A similar gap (on average in 1999-2008) is noted in Hungary and Slovakia, where the employment rate among women is 26% and 24% lower, respectively, than in the case of men. In the Czech Republic there is a 29% gap (see p. 17 of the Czech report and Charts 3.4.b and 3.4.c). Chart 3.4a. Employment rate for persons aged 15-64 70,0 65,0 60,0 55,0 50,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia Source: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_argan&lang=en, Czech report, p. 17. Chart 3.4b. Employment rate for women aged 15-64 Chart 3.4c. Employment rate for men aged 15-64 80,0 80,0 75,0 75,0 70,0 70,0 65,0 65,0 60,0 60,0 55,0 55,0 50,0 50,0 45,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 45,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia CR Hungary Poland Slovakia Source: the authors' own analysis based on data from 10 The employment rate is the percentage of persons employed in the overall working age population. 16

http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_argan&lang=en. As regards the age structure of the employed population, analysis of the reports does not allow for a synthesis of data because the Polish and Czech reports (only these two contain any analysis of this type) refer to different age ranges. Nevertheless, a synthesis was performed using the age ranges proposed in the Czech report (p. 18): 15-24, 25-44, 45-64 and 65+. Changes within these groups are presented in Charts 3.4d-3.4g. Chart 3.4d. Employment rate for persons aged 15-24 40,0 35,0 Chart 3.4e. Employment rate for persons aged 25-44 86,0 82,0 30,0 25,0 78,0 74,0 20,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 70,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia CR Hungary Poland Slovakia Chart 3.4f. Employment rate for persons aged 45-64 Chart 3.4g. Employment rate for persons aged 65+ 75,0 10,0 70,0 65,0 60,0 55,0 8,0 6,0 4,0 50,0 2,0 45,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 0,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia CR Hungary Poland Slovakia Source: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_urgaed&lang=en Analysis of these charts shows that the Czech Republic enjoys the highest employment rate in the 15-24 age group, as well as a markedly higher rate in the 45-64 and 25-54 age groups than the other countries. The Czech report (p. 18) draws attention to the fact that the process of population ageing (which is better observed in five-year age groups) is one of the major negative factors affecting the economy and social development in the Czech Republic. 3.5. The unemployed and long-term unemployed In considering unemployment in Poland in 1999-2008, a clear division into two subperiods can be observed: the unemployment rate increased until 2002 and then began to fall in 2005, first slowly and then rapidly. Similar tendencies may be observed in the Slovak economy, where the unemployment rate is similar to that of Poland the average for both countries in 1999-2008 is above 15%, which is twice the average rate in Hungary and the Czech Republic (see Chart 3.4.a.). In the case of Slovakia, the unemployed population includes a high percentage of long-term unemployed, who accounted for a record 75% of the total unemployed population in 2006 (see Charts 3.5a-3.5b). 17

Chart 3.5a. Unemployment rate 25,0 20,0 15,0 10,0 Chart 3.5b. Percentage of long-term unemployed in the total unemployed population 80,0 70,0 60,0 50,0 5,0 40,0 0,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 30,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 CR Hungary Poland Slovakia CR Hungary Poland Slovakia Source: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_urgaed&lang=en IMPACT OF THE COHESION POLICY ON CHANGES IN THE LABOUR MARKET This chapter presents the results obtained by evaluators in each country regarding the impact of the cohesion policy on the level and quality of employment. Detailed results are presented in the table below. Table 4. The impact of the cohesion policy on the employment of persons aged 15-64 Czech Republic Hungary Poland Slovakia Impact of the cohesion policy in thousands of people* 32.6-47 20.2 46-124 No data available Volume of employment in 2003 in thousands of people 11 Volume of employment in 2008 in thousands of people 12 Change in employment in 2008/2003 in thousands of people 4,649.3 3,899.4 13,379.5 2,159.9 4,933.5 3,849.2 15,557.4 2,423.4 284.2-50.2 2,177.9 263.5 Share of the impact in the size of the market in 2008 0.66%-0.95% 0.53% 0.3%-0.8% No data available Share of the impact in the total change of employment in 2003-2008 11.5-16.5% - 2.1-5.7% No data available Source: the authors' own analysis based on the Czech, Polish and Hungarian reports (first row) and data from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egaps&lang=en (second and third rows) 11 Based on data from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egaps&lang=en. 12 As above. 18

It is very difficult to compare the impact of EU funds between the countries because of the different methodologies applied to calculate it (see the chapter on methodology). Another difficulty is that the Czech report also evaluated programmes for 2007-2013, while the Polish and Hungarian reports did not. The Polish report compared the impact of the funds with the total change in employment from the year before accession to 2008, which showed that the cohesion policy accounted for 2-6% of the total change in employment (see the last row in Table 4). Such a comparison cannot be made for Hungary, where the number of employed fell in 2003-2008 (the question arises of how to treat impact equivalent to approx. 20,000 working people against a drop in employment of about 50,000. Can it be assumed that employment in the economy would have been even lower without the cohesion policy?). To meet these challenges and give an idea of the scale of the cohesion policy's impact on employment, the comparisons focused on the impact of funds on the volume of employment in the last year covered by the analysis. Coherent results were obtained, showing that the impact of the funds accounts for less than 1% of the employed population in 2008 in the countries analysed: from 0.66 to 0.95% in the Czech Republic, 0.3 0.8% in Poland and 0.53% in Hungary. 4.1. Jobs created broken down by gender, age and education One of the primary evaluation questions referred to in the beginning of Chapter 3 concerned the distribution of the jobs created by education level, age and gender, as well as among specific groups of individuals (e.g. the disabled and the long-term unemployed). The Polish and Czech reports contain sufficient data to answer these questions. 13 Comparisons of the data are presented in Table 4.1.a. Table 4.1a. Age, gender and education structure of created jobs (in %) Poland Czech Republic 15-24 0.136 0.132 25-54 0.836 0.815 55-64 0.027 0.052 Women 0.330 0.430 Men 0.670 0.570 ISCED 0-2 0.030 0.335 ISCED 3-4 0.780 0.545 ISCED 5-6 0.180 0.128 Source: data from the Polish and Czech reports. These data show that the age breakdown of created jobs is similar for Poland and the Czech Republic, but the gender and education structure is different. While the figures for age are almost identical (ages 25-54: 81.5-83.6%, ages 15-24: 13.2-13.6%, ages 55-64: 2.7-5.2%), there are differences in the gender of the employed, with more jobs created for men in Poland (Table 4.1.a). There are also differences in the breakdown by education. In the Czech Republic more than 30% of the jobs were created for people with the lowest qualifications, while in Poland the figure was just 3% (here jobs have been created mainly for persons with secondary education - 78% of the total number). 13 Data quoted in the Polish report do not strictly apply to all jobs created but only to the structure deduced from the study of enterprises. It was assumed in the study that this structure may resemble that of the overall number of jobs created in the economy. The Hungarian report provides only results regarding education structure, which will be presented later. 19

The data indicate that the most privileged group among the beneficiaries of the support was men aged 25-54 with secondary education (the greatest number of jobs was created for these groups). However, it should be noted that this group is the most numerous among the employed. Creating 83.6% of jobs (among the overall number of jobs created) for persons aged 25-54 who account for 90% of the total number of employed is quite different from creating jobs for a group accounting for just 40%. Thus if it is assumed (simplifying) that changes in employment in the entire economy constitute a control group for the structures presented in Table 5.1.a, a different comparison is obtained, as can be seen in Table 4.1.b. 14 Table 4.1b. Age, gender and education structure of jobs created due to the funds and changes in the labour market (in %) Poland Czech Republic Poland Czech Republic Poland Czech Republic Jobs created due to interventions Changes in the labour market 2008/2003 Structure of the labour market in 2008 15-24 14% 13% 9% -13% 9% 8% 25-54 84% 82% 52% 84% 55% 54% 55-64 3% 5% 39% 29% 35% 39% women 33% 43% 40% 28% 45% 43% men 67% 57% 60% 72% 55% 57% ISCED 0-2 3% 34% -10% -13% 8% 6% ISCED 3-4 78% 55% 53% 57% 68% 79% ISCED 5-6 18% 13% 57% 56% 23% 15% Source: the authors' own analysis based on data in Table 5.1.a and data from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egaps&lang=en. The table above shows that in Poland and the Czech Republic interventions aimed at supporting people aged 15-24 have had a particularly positive impact (the percentage of jobs created due to intervention is greater than the corresponding proportion of the total change of employment in the economy). 15 In the case of Poland, a relatively large scale of support is noted for persons aged 25-54, who accounted for just 54% of the overall labour market in 2008, i.e. much less than the percentage of jobs created owing to the interventions. In contrast, in the Czech Republic the 82% of jobs created due to the interventions should be compared with an almost identical percentage (84%) of the total number of jobs created in the economy in 2003-2008. Among the oldest employees (55-64), both in the Czech Republic and in Poland the percentage of jobs created owing to the funds was lower than this age group's share in the overall change in employment in the economy, and lower than its share in the labour market in 2008. Hence the impact of the intervention was lowest for the oldest employees, since the growth in that group in the Polish and Czech economies, as well as their share in the market, were much greater than the number of jobs created owing to the funds. 14 The summary in Table 4.1.b allows for only approximate conclusions regarding the scale of intervention, as the balance of employment in the economy applies to both created and lost jobs, while the data in Table 4.1.a relate to created jobs only. Since the Czech report lacks data about lost jobs (such information is included in the Polish report), the only point of reference is changes in the entire economy. This innovative approach (not present in the other evaluations) was proposed by the authors of the Polish report in subsection 5.1.2 Triangulation of results.. According to the authors of this synthesis such comparisons provide grounds for the triangulation of results on a micro and a macro scale, in particular in the absence of data on lost jobs. 15 The analysis of data with a control group in the Polish report (Chart 43) substantiates these results, as the percentage of jobs created owing to the interventions for persons aged 15-24 is greater than in the control group. While it is true that the analysis of lost jobs (available in the Polish report) shows that more jobs for men were lost than created, in the absence of data on lost jobs in the Czech report, the only method for comparing those results is the one presented in this chapter. 20

The Hungarian report provides no detailed data on the age structure of the jobs created, but cites the results of worldwide studies (p. 88) which show that the size of the deadweight effect depends on the target group. For example, wage support for young people results in either high deadweight or the crowding-out effect (young people are employed in place of older ones). The authors do not study these effects in the report itself, but are inclined towards this hypothesis. The results in Table 4.1.b seem to point more to the crowding-out effect, as the positive effects of intervention among employees aged 15-24 are far greater than among those aged 55-64. This hypothesis is also supported by the analysis of lost jobs in the Polish report (p. 55), which indicates a generational switch: more people over 54 and about to retire were employed in the lost jobs, while more young people are employed in the newly created jobs. As regards the gender of people for whom jobs are created, a similar comparison of data demonstrates positive effects of intervention among men in the case of Poland and women in the case of the Czech Republic (in Poland both the percentage of men working in 2008 and the percentage of men in the change in employment in 2003/2008 is much lower than the percentage of jobs created for them owing to the interventions). 16 As regards education, in both the Czech Republic and Poland jobs were created for the least qualified employees (ISCED 0-2) owing to interventions, despite the fact that the change in the employment of this group was negative in 2003-2008 in the Polish and Czech economies. However, far more jobs for the least qualified have been created in the Czech Republic. In the case of employees with medium-level qualifications (ISCED 3-4), the share of jobs created in the Czech Republic matched the overall changes in the country, but was well below their share in the labour market in 2008. Poland, in contrast, noted a substantial impact of the intervention addressed to employees with secondary education, while the percentage of jobs created for the best educated employees (ISCED 5-6) owing to the funds was much lower than the share of this group in the overall change in employment, and lower than their representation on the labour market in 2008 (thus it can be concluded that jobs would have been created even without EU interventions). According to the Hungarian report (p. 79), based on a questionnaire survey 41% of jobs are created for employees with primary education, 33% for persons with secondary education and 25% for those with tertiary education 17. This indicates that in Hungary the interventions had the greatest impact on employees with the lowest qualifications (Hungarian report, p. 89), because the percentage of maintained jobs not requiring qualifications is relatively low (15%), while jobs for people with primary education constitute the largest share (in %) of jobs created. 4.2. Jobs created for specific groups of people, in particular the disabled and long-term unemployed The Czech report (p. 16 and earlier) provides information on many specific groups: job seekers, job applicants, the long-term unemployed (broken down into those unemployed from 6 to 12 months and for over 12 months), the disabled, and mothers on maternity leave (see Chart 4.2a). 16 The analysis of data with a control group in the Polish report (Chart 43) corroborates these results, as the percentage of jobs created for men/women in the control group is lower/higher than among the group that benefited from the support. At the same time the number of lost jobs was very high, so the authors of the Polish report concluded that the additionality of projects addressed to women was greater. In the absence of data on lost jobs in the Czech economy, these data cannot be verified. 17 The focus surveys did not produce any definite opinions regarding the value of such support. While respondents stated that the main beneficiaries of support were persons with the lowest qualifications, their added value was so low that only their employment for the duration of the EU support was declared (Hungarian report, p. 89). 21

Chart 4.2a. Representation of specific groups in newly created jobs Source: Charts 8 and 9 in the Czech report, pp. 12-13. The Czech report states that jobs created for the long-term unemployed accounted for 22% and 5.4% (unemployed for over 6 months and over 12 months, respectively) of the total, while 4.5% were created for the disabled. A similar structure is obtained in Poland (Chart 4.2b). Chart 4.2b. Distribution of created/lost jobs among groups of people in a specific situation in the labour market Source: Polish report, p. 67, Chart 37. The Polish report states that there are indications that support granted to enterprises under SOP ICE improves job quality (jobs for persons with tertiary education, in knowledge-intensive sectors, in managerial positions). Moreover, these enterprises more often employed the long-term unemployed and the disabled (Polish report, p. 6). The Hungarian report refers to the world literature and states that according to Köllő (2007), real positive employment impact can be assumed in those groups which would otherwise find employment with much difficulty only (for example, people with reduced working abilities and mothers with young children) 18. 18 Hungarian report, p. 88. 22