Regional Employment Patterns and Prospective Developments in the New EU Member States
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Summary · Grouping the regions of the EU-15 and the new member states (NMS, including Bulgaria and Romania) into five clusters according to the relative importance of broad sectors of activity reveals marked differences in the regional economic structure and development. · In capital cities throughout the EU, GDP per head is significantly higher than in other regions. Regional disparities in GDP per head have widened markedly in the NMS in recent years, though not in the EU-15. · There is no close association across regions between GDP per head and the employment rate, though the capital cities have higher employment than the national average in all countries, while the lowest employment rates are in the basic service regions in both the NMS and the EU-15. The highest employment rate in Poland and Romania is in the agricultural regions; this reflects the large numbers unable to find work elsewhere who make a living from subsistence farming. · Over recent years, however, the employment rate in NMS agricultural regions has fallen more than in other parts; the employment rate in capital cities has fallen less than elsewhere despite the apparent substantial growth in productivity. This contrasts with recent experience in the EU-15 where employment rose in all regional groups - and more in agricultural regions (which in many cases were supported by the EU Structural Funds) than in others. · The sectoral structure of activity across regions tends to reflect variations in the education levels of their working-age populations. Agricultural regions across the EU, therefore, have the largest proportion of people with low education and the smallest proportion of those with high education. Capital cities in both the NMS and EU-15 have the largest proportion of highly educated inhabitants and the smallest proportion of low-educated inhabitants. · The extent of restructuring which still lies ahead of the NMS agricultural and basic service regions, in particular, is indicated by the fact that the share of employment in services is 17-20 percentage points below that of counterpart EU-15 regions. This difference is particularly marked in business and financial services and public services. · The share of employment in agriculture declined in all NMS regional groups in the period 1998-2003. Within industry, there was a shift in employment towards the low-skill sectors in all NMS regional groups. The share of employment in services increased in all NMS regional groups, but less in the agricultural regions than in others despite the former's particular need for restructuring. · Since the share of employment in basic services in NMS regions is not much smaller than in their EU-15 counterparts, it might not increase much further in most of the NMS regions. Nevertheless, the number employed in the sector is still likely to expand significantly, if the present low level of employment overall can be increased. · Comparisons with the EU-15 show, perhaps surprisingly, that scope also seems to exist for employment growth in industry in the NMS industrial and agricultural regions. · Differences in the sectoral structure of employment across regions bear implications for the kinds of jobs on offer and the skills or education levels required. In the NMS capital cities, over 40% of those in employment in 2003 were highly skilled non-manual workers (managers, professionals and technicians) as opposed to only 25% in agricultural regions. Less skilled non-manual workers are also more in demand in the capitals than elsewhere and manual workers correspondingly less so. · In the NMS agricultural regions, almost 60% of jobs were for manual workers; in the other NMS regional groups, manual workers made up over half of those in employment, much more than in the EU-15. Low-skilled manual workers, however, account for a larger share of employment in services in all EU-15 regional groups than in NMS regions. · The occupational structure of employment shifted in favour of highly skilled non-manual workers between 1998 and 2003 in all NMS regional groups as well as in the EU-15; both groups also experienced a relative increase in low-skill non-manual jobs. This was paralleled by a decline in manual jobs, especially for unskilled workers. · Employment rates for those with tertiary education are much higher than the rates for those with lower levels; they hardly vary at all across regions and are very similar in both the NMS and EU-15 regions. This contrasts with the variation across regions in the employment rates of those with only basic schooling; they are much lower in the NMS than in the EU-15. · The employment rate of those with low education fell significantly across all NMS regional groups in the period 1998-2003. By contrast, employment rates for the low-educated in all EU-15 regions outstripped those for the better educated.Cite
This paper analyzes the national and regional (NUTS-2) employment performance and convergence for various aggregations of 27 European countries (EU-25, plus Romania and Bulgaria), mainly using the three employment rates (total, female, older worker) adopted by the European Employment Strategy (EES). At the national level, this analysis confirmed the existence of considerable differences in employment performance between and within the various country aggregations. Empirical analysis highlighted the remarkable net job creations in the EU-15 (and EMU-12) for the period 1997-2003, accompanied by a (national) convergence for all three employment indicators. As regards total employment rates, significant conv erging trends also emerge at the regional level for both EU-15 and EMU-12 aggregations. In the eight Central European Countries, new EU members (8 CEC-NM), a σ diverging trend in the total employment rate began in 1999, whereas converging dynamics were limited to the employment rate of older workers in the period 1998-2001. Regional analyses showed significant β diverging dynamics in the total employment rates (1999-2003) for the eight CEC-NM regions. At the national level of analyses, the relationship between “progress in transition” and employment performance was also briefly examined. Results show that a simple, stable correlation does not exist. However, a weak U-shaped relationship existing in 1998 shifted downward and evolved toward a positive link in 2003. The main results of cluster analysis of the 53 regions of the ten CECs confirmed a high level of regional labour market diversification, and the fact that sector structure affects employment performance significantly.
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In this report it is examined whether rural regions in the EU with a relatively high (low) employment growth in the 1980s and early 1990s have some common socio-economic characterics, which can contribute to the explanation of their employment performance. We have grouped the socio-economic characterics around the headings local resources, economic activities and supply of labour. We base our analysis on 465 regions in the EU 15, which we have divided into three groups: most rural regions, intermediate regions and most urban regions. Within each of these groups we have made a further distinction into leading (i.e. high non-agricultural employment growth) and lagging (i.e. low non-agricultural employment growth) regions. The analysis shows that leading rural regions have both growth of industrial employment and services employment and show a population growth as well, whereas in lagging rural regions population growth stagnates. Besides, leading rural regions tend to have a lower unemployment rate than lagging regions and tend to have a higher infrastructure endowment (highways, railways and waterways). On the other hand for quite a number of socio-economic indicators hardly any differences have been found between leading and lagging rural regions, like participation rates, education level of the population, average firm size, share of female employed in total employment and the share of farm holders with other gainful activities.
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Regional labor markets disparities have remained stable in Romania, as is the case in Poland. In spite of a huge output decline in the first years of transition, the process of adjustment to sectoral shifts has been slow. We find a negative relationship between regional unemployment rates and regional sectoral reallocation, but no correlation between these two variables. The most intense labor reallocation--both job creations and job destructions--have taken place in regions with an industrial profile. Job destruction is predominant in agricultural regions. The estimated local unemployment elasticity of wages is negative, suggesting the presence of a wage curve in Romania. Inter-regional migration flows are not correlated with regional unemployment rates while the availability of housing plays an important role in the decision to move across regions. While the agricultural regions are net senders, the industrial and diversified regions are net receivers. The absorption capabilities have declined in both industrial and diversified regions, faster in the industrial regions. It seems that the outflows of migrants from agricultural regions respond to the absorption capability of industrial rather than diversified regions.
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Regional labour markets disparities have remained stable in Romania, as it is the case in Poland. In spite a huge output decline in the first years of transition, the process of adjustment to sectoral shifts has been slow. We find a negative relationship between regional unemployment rates and regional sectoral reallocation, but no correlation between these two variables. The most intense labour reallocation - both job creations and job destructions have taken place in regions with an industrial profile. Job destruction is predominant in agricultural regions. The estimated local unemployment elasticity of wages is negative suggesting the presence of a wage curve in Romania. Inter-regional migration flows are not correlated with regional unemployment rates while the availability of housing plays an important role in the decision to move across regions. While the agricultural regions are net senders, the industrial and diversified regions are net receivers. The absorption capabilities have declined in both industrial and diversified regions, faster in the industrial regions. It seems that the outflows of migrants from agricultural regions respond to the absorption capability of industrial rather than diversified regions.
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Summary · Grouping the regions of the EU-15 and the new member states (NMS, including Bulgaria and Romania) into five clusters according to the relative importance of broad sectors of activity reveals marked differences in the regional economic structure and development. · In capital cities throughout the EU, GDP per head is significantly higher than in other regions. Regional disparities in GDP per head have widened markedly in the NMS in recent years, though not in the EU-15. · There is no close association across regions between GDP per head and the employment rate, though the capital cities have higher employment than the national average in all countries, while the lowest employment rates are in the basic service regions in both the NMS and the EU-15. The highest employment rate in Poland and Romania is in the agricultural regions; this reflects the large numbers unable to find work elsewhere who make a living from subsistence farming. · Over recent years, however, the employment rate in NMS agricultural regions has fallen more than in other parts; the employment rate in capital cities has fallen less than elsewhere despite the apparent substantial growth in productivity. This contrasts with recent experience in the EU-15 where employment rose in all regional groups - and more in agricultural regions (which in many cases were supported by the EU Structural Funds) than in others. · The sectoral structure of activity across regions tends to reflect variations in the education levels of their working-age populations. Agricultural regions across the EU, therefore, have the largest proportion of people with low education and the smallest proportion of those with high education. Capital cities in both the NMS and EU-15 have the largest proportion of highly educated inhabitants and the smallest proportion of low-educated inhabitants. · The extent of restructuring which still lies ahead of the NMS agricultural and basic service regions, in particular, is indicated by the fact that the share of employment in services is 17-20 percentage points below that of counterpart EU-15 regions. This difference is particularly marked in business and financial services and public services. · The share of employment in agriculture declined in all NMS regional groups in the period 1998-2003. Within industry, there was a shift in employment towards the low-skill sectors in all NMS regional groups. The share of employment in services increased in all NMS regional groups, but less in the agricultural regions than in others despite the former's particular need for restructuring. · Since the share of employment in basic services in NMS regions is not much smaller than in their EU-15 counterparts, it might not increase much further in most of the NMS regions. Nevertheless, the number employed in the sector is still likely to expand significantly, if the present low level of employment overall can be increased. · Comparisons with the EU-15 show, perhaps surprisingly, that scope also seems to exist for employment growth in industry in the NMS industrial and agricultural regions. · Differences in the sectoral structure of employment across regions bear implications for the kinds of jobs on offer and the skills or education levels required. In the NMS capital cities, over 40% of those in employment in 2003 were highly skilled non-manual workers (managers, professionals and technicians) as opposed to only 25% in agricultural regions. Less skilled non-manual workers are also more in demand in the capitals than elsewhere and manual workers correspondingly less so. · In the NMS agricultural regions, almost 60% of jobs were for manual workers; in the other NMS regional groups, manual workers made up over half of those in employment, much more than in the EU-15. Low-skilled manual workers, however, account for a larger share of employment in services in all EU-15 regional groups than in NMS regions. · The occupational structure of employment shifted in favour of highly skilled non-manual workers between 1998 and 2003 in all NMS regional groups as well as in the EU-15; both groups also experienced a relative increase in low-skill non-manual jobs. This was paralleled by a decline in manual jobs, especially for unskilled workers. · Employment rates for those with tertiary education are much higher than the rates for those with lower levels; they hardly vary at all across regions and are very similar in both the NMS and EU-15 regions. This contrasts with the variation across regions in the employment rates of those with only basic schooling; they are much lower in the NMS than in the EU-15. · The employment rate of those with low education fell significantly across all NMS regional groups in the period 1998-2003. By contrast, employment rates for the low-educated in all EU-15 regions outstripped those for the better educated.
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At the beginning of the second decade of the 21st century, several countries in the periphery of Europe began suffering from sovereign debt crises, resulting from and contributing to economic weakness. As of late 2013, each country was struggling with double-digit unemployment rates with rates in Greece and Spain near 27%. Though economic weakness was responsible for falling employment, the linkage between economic growth and employment, known as the employment intensity of economic growth (also called employment elasticity), may differ between nations. Estimation of models developed reveal different dynamics in the respective countries. Regardless of the model employed, the results revealed a very high employment intensity of economic growth in Spain relative to the other nations, indicating that employment was highly sensitive to changes in economic growth. As such, an equivalent decline in GDP had a much larger impact on employment in Spain than the other PIIGS. There is evidence that the structure of the labor market may play some role in explaining different employment elasticities for the countries in question. In particular, the degree of unionization appeared to be negatively correlated with employment intensity (economic growth had a smaller impact on employment in nations that have a larger percentage of unions) while the portion of workers on temporary contracts was positively correlated with employment intensity; countries with a larger percentage of workers on temporary contracts, such as Spain, had a higher employment intensity as employment responded more to changes in economic growth.
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The Osrednjeslovenska region as one of twelve statistical or NUTS-3 regions is economically the most developed and important region in Slovenia. The municipalities of the Slovenian capital of Ljubljana, which is situated in the Osrednjeslovenska region, create around three-fourth of employment and generate more than 80 percent of value added in this region. The role of agriculture and industry in employment is shrinking, while the service sector is expanding. The fastest job creation is for university educated, which in 2002 represents around 20 percent of employees in this region. Relatively fast growth in employment is also recorded for secondary educated and for certain lowskilled jobs. The empirical results of the panel-based production function confirm that the coefficient of elasticity pertains to physical capital is greater than the coefficient of elasticity pertains to labor. The disparities in economic growth are to a greater extent associated to physical than to human capital as the coefficient of elasticity pertains to human capital is approximately three times as high as the coefficient of elasticity pertains to physical capital. Human capital represents the factor that significantly contributes to the reduction of disparities in economic growth at the municipal level in the Osrednjeslovenska region. Labor productivity is higher in job creating service activities that generate additional value added. In the European Union (EU), structural and cohesion policies play a crucial role to encourage growth in less developed and remote regions and to reduce disparities in local and regional development. By a European standard classification system of Nomenclature des Unites Territoriales Statistiques/Nomenclature of Territorial Units for Statistics (NUTS), at NUTS-3 regions, Slovenia is divided into twelve statistical regions, where disparities in the level of development are quite large, being gross domestic product (GDP) per capita in Osrednjeslovenska region twice as high as in Pomurska region (e.g. Bojnec 2005). The Osrednjeslovenska region is also economically the most important region and thus the Slovenian economic indicators are biased to this region. The municipalities of the Slovenian capital of Ljubljana, which is situated in the Osrednjeslovenska region, create around three-fourth of employment and generate more than 80 percent of value added in this region. The role of agriculture and industry in employment is shrinking, while the service sector is expanding. The fastest job creation is for university educated, then for secondary educated and for certain lowskilled jobs.
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European regions have experienced a polarisation of their unemployment rates between 1986 and 1996, as regions with intermediate rates have moved towards either extreme. This process has been driven by changes in regional employment, only partly offset by labour force changes. Regions' outcomes have closely followed those of neighbouring regions. This is only weakly explained by regions being part of the same Member State, having a similar skill composition, or broad sectoral specialisation. Even more surprisingly, foreign neighbours matter as much as domestic neighbours. All of this suggests a reorganisation of economic activities with increasing disregard for national borders.
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A detailed assessment of employment trends in the public sector from 1979 to 2001 is provided. Particular attention is paid to the relative level of public sector employment is Wisconsin . The analysis also examines the relationship between the size of state and local government and overall employment growth from 1979-2001. Results suggest that growth in total employment and employment in the public sector are highly correlated; higher shares of total employment in the public sector in the beginning of the period are not correlated with subsequent growth rates; but a state that sees the public sector grow faster then overall employment growth tends to be associated with slower overall growth. In addition, when measuring the size of the public sector in terms of employment, Wisconsin does not appear to be out of balance when compared to other states. Employment growth in state government over the period 1979-2001 is one of the lowest in the country and employment growth at the local government level is slightly above the national average. Detailed changes in employment by category are also examined for the US and Wisconsin from 1993 to 2002. These data suggest that there has been significant disinvestment in several areas that contribute to the overall quality of life in Wisconsin which may in turn hinder the future potential for economic growth and development.
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