Autonomous employment and skill developments vis-à-vis emerging exploration of past and possible future trends in the demand for skills

Transcription

1 MUTUAL LEARNING PROGRAMME: PEER COUNTRY COMMENTS PAPER CZECH REPUBLIC Autonomous employment and skill developments vis-à-vis emerging exploration of past and possible future trends in the demand for skills Peer Review on The Ageing Population and Educational Choices Finland; Helsinki June 2010 A paper submitted by Daniel Münich in consortium with GHK Consulting Ltd and CERGE-EI Date: 25/05/2010

2 This publication is supported for under the European Community Programme for Employment and Social Solidarity ( ). This programme is managed by the Directorate-General for Employment, Social Affairs and Equal Opportunities of the European Commission. It was established to financially support the implementation of the objectives of the European Union in the employment and social affairs area, as set out in the Social Agenda, and thereby contribute to the achievement of the Lisbon Strategy goals in these fields. The seven-year Programme targets all stakeholders who can help shape the development of appropriate and effective employment and social legislation and policies, across the EU-27, EFTA- EEA and EU candidate and pre-candidate countries. PROGRESS mission is to strengthen the EU contribution in support of Member States' commitments and efforts to create more and better jobs and to build a more cohesive society. To that effect, PROGRESS will be instrumental in: providing analysis and policy advice on PROGRESS policy areas; monitoring and reporting on the implementation of EU legislation and policies in PROGRESS policy areas; promoting policy transfer, learning and support among Member States on EU objectives and priorities; and relaying the views of the stakeholders and society at large For more information see: The information contained in this publication does not necessarily reflect the position or opinion of the European Commission.

3 CONTENTS 1 LABOUR MARKET SITUATION IN THE PEER COUNTRY ASSESSMENT OF THE POLICY MEASURE ASSESSMENT OF THE SUCCESS FACTORS AND TRANSFERABILITY QUESTIONS... 8 ANNEX 1: SUMMARY TABLE... 10

4 1 LABOUR MARKET SITUATION IN THE PEER COUNTRY This paper has been prepared for a Peer Review within the framework of the Mutual Learning Programme. It provides information on Czech Republic s comments on the policy example of the Host Country for the Peer Review. For information on the policy example, please refer to the Host Country Discussion Paper. Since 2000, the Czech Republic experienced almost a decade of economic growth reaching 5% in At the end of 2008 with some delay, the economic downturn showed its impact, translating into annual 2009 GDP growth rate, which stood at minus 4.3%, on the background of an average employment decline of 1.3%. The country s public finance deficit quickly rose from 2.8% to 5.9% of GDP. While the impact of the downturn had largely negative consequences (in terms of major economic indicators including GDP, public budget deficits, unemployment and employment rates etc.) and fiscal developments are still worrisome, the Czech economy survived relatively well. But in the following, we focus on longer-term labour market trends and patterns since they are most relevant for the type of anticipation methods which are the focus of the Finnish Peer Review. Overall the Czech labour market is characterised by relatively high employment and participation rates among the prime age population, both men and women. The unemployment rate (ILO defined based on Labour Force Surveys) currently stands at 9.2% and is showing the first signs of declining trends. About half of the unemployment seems to be of a frictional and temporary nature. The remaining half seems to be due to a mix of low skills, health and other disadvantages (like parents of young children, Roma minority, etc), work disincentives, labour market mismatches and the incidence of undeclared work. There are several noticeable peculiarities determining the size of the prospective available pool of labour relevant for the forecasting of labour supply: (a) the employment and participation rate of young people is high but has been declining steadily during the last decade mainly due to continuously increasing average time spent in formal education. The major factors were: the growing proportion of pupils enrolled in 4 year upper-secondary programmes instead of 2 or 3 year programmes and the rapid expansion of enrolment at the tertiary level of education from about 15% of secondary school graduates to current 35%. The youth unemployment rate is above the overall rate in the economy but compared to most other EU countries it is relatively low. (b) Relatively high participation and employment rates of prime age men and women exhibit fast drops after ages and 61-62, respectively. The key role is played here by retirement incentives caused by the statutory retirement age (lower for women depending on the number of children). 1 It should be noted that the educational structure of the senior population closer to retirement ages differs significantly from that of younger cohorts (lower educational attainment and different fields of education). (c) High impact of children on the participation rates of women. This is the result of high employment and participation of women without children and very generous systems of maternity and parental benefits and duration of parental support. (d) Extraordinary low incidence of part-time work arrangements, among women in particular. The Czech Republic reports a very low upper-secondary school drop-out rate. A large proportion of total enrolment is narrowly focused on professional and vocational school programmes and there is correspondingly low enrolment in general curriculum programmes. The country lags behind other upper-middle-income countries in the share of population with college diplomas and this is sometimes viewed as a constraint of the growth potential of the country in the decades to come. 1 The statutory retirement age is to increase steadily to reach 65 in 2020 but further increase will likely be initiated by fiscal pressures imposed on public finances due to fast ageing of the population. 4

5 Retraining (ALMP) programmes in the Czech Republic are not significant (in terms of participants and expenditures) and little is known about their effectiveness. Participation in lifelong learning (LLL) is very low, especially for older, less educated and disadvantaged workers. All of this bodes ill for low-skilled Czech workers and signals excess demand for those with college diplomas. While the inflow of foreign workers in recent years has been rapid, with foreigners reaching over 3% of the population today, it has not been sufficiently skill-biased. During the last five years of economic boom, we observed excess labour demand in almost all professions across all levels and fields of education. Excess demand has been reported for low-skilled blue collar jobs in various types of manufacturing industries through middle level to jobs for highly skilled professionals. The demand was driven by a steadily growing economy fostered by numerous large FDI inflows and high export potential of many industrial sectors. Much of the demand for low-skilled workers has been satisfied with foreign labour. There is little reliable information on the extent of skill mismatch (including at spatial level). Excess demand has been reflected in available data on vacancies posted at the district labour offices as well as on the internet. The Czech economy is heavily dependent on car manufacturing and its supply chain and the proportion of employment in manufacturing is the highest in the EU. The competitive position and comparative advantages of industries is also strongly affected by wide fluctuations in the Crown/Euro and Crown/USD exchange rates, which are difficult to predict in the short and longer term. 2 ASSESSMENT OF THE POLICY MEASURE As in Finland, demographic change and the rapid ageing of the Czech population will be important driving factors of labour supply in the decades to come. At the same time, steady and abrupt changes in the structure of labour demand by different skills are anticipated. As of now, there is no information based rigorous system of regular analysis and forecasting as we observe in Finland. Compared to the skills anticipation situation in Finland, the Czech Republic is much less advanced in both key dimensions: (i) development of technical tools and methodologies of forecasting overall and (ii) institutional setups, coordination and collaboration. In the Czech Republic, there are only some of all components needed to build a complex system of comprehensive anticipation of labour market skills needs. It is also well understood that it is intrinsically difficult to forecast beyond the horizon of the next ten years because developments in such a long horizon endogenously depend on educational and employment policies that will be implemented during the next few years. This is particularly the case of the ongoing curricular reform at the level of primary and secondary education and of the thorough reform of tertiary education and R&D support system, which is expected to be implemented in the near future. Another important factor affecting future labour market outcomes is the pension reform, which can substantially affect labour supply in forthcoming decades. Another specific obstacle in the development of useful anticipation tools is the combination of a low incidence of internal migration, a relatively high degree of regional differences and the curriculum of schools being fragmented into many relatively narrowly defined fields. This implies that, good quality and relevant forecasts would have to be provided at a regional level and for a larger number of educational fields and occupations. This is technically impossible, as in Finland, primarily due to existing data and methodological limits. 5

6 There are also other barriers: (a) foreign immigration of labour is very difficult to anticipate as in Finland. The Czech Republic has no clear longer term immigration strategy and existing policies are very volatile depending on the actual stages of business and political cycles. 2 In the Czech Republic, the first initiatives in skill forecasting originated in academia and thanks to EU-funded projects contracted mostly by the Ministry of Labour and Social Affairs (MoL) and the Ministry of Education, Youth and Sports (MoS). Some obstacles of building powerful quantitative skills forecasting model can be identified in key supporting inputs: (a) The most developed and least problematic are demographic prognosis provided by the Czech Statistical Office but also academic demographers at universities. (b) Currently, there is no macroeconomic model specifically tailored for skill forecasting in the Czech Republic. Skills forecasting requires, as input, forecasts of employment in 10 to 15 core sectors of the economy. The existing skills forecasting efforts rely on macroeconomic models (Hermin or the E3ME) which do not provide a sufficiently detailed division of sectors. (c) There is ongoing work on an Integrated System of Working Positions (ISTP). d) Projections of fresh school graduates by levels and fields of education are realised for the horizon of 5 years only while there is no clear schooling system steering strategy to anticipate developments beyond this time horizon. There are two quantitative skills forecasting efforts still in development using as inputs outputs of the aforementioned blocks. Both models are based primarily on Labour Force Survey (LFS) data. First, the model by the Center of Educational Policies (SVP) 3 compares the evolution of the industrial and occupational structure of employment in EU countries and the US to that in the Czech Republic and takes the age structure and qualification requirements into account to generate 10-year forecasts. The detailed methodology used by SVP is yet to be published. Second, the CERGE-EI/RILSA/NTF 4 quantitative approach draws on the Dutch methodology developed by the ROA institute and combines employment and age structure information from the LFS with education-system production data from the MoS and with information on the skill structure of short-term unemployed individuals. The model by CERGE-EI/RILSA/NTF provides quantitative forecast for up to 5 years. NTF also prepared several sectoral studies (e.g. tourism) providing qualitative forecasts combining quantitative information on domestic and foreign sectoral trends and expert opinions. Occasionally, there also appears an ad-hoc partial attempt to anticipate workforce needs in a particular profession or industry. These attempts are not done regularly and systematically, and generally lack sophisticated and methodological rigor. Moreover, since the realisation of those attempts is frequently motivated by a particular interest group of employers or educational institutions, forecasts are prone to bias due to the self-interest of those groups. Simpler methods of forecasting (based primarily on an extrapolation of past trends) are losing reliability in the face of the swiftly changing structure of tertiary education, growing proportions of youth age cohorts obtaining tertiary education, and forthcoming departure of larger cohorts of older workers due to retirement. These phenomena have been rather strong in the Czech Republic. Economic crises such as the current one, also make the past less informative about the future. For example, there is important potential for transferring 2 The ability of general population to communicate practically in major foreign languages is improving slowly imposing barriers on involvement of immigrants with highly skills into the labour force. 3 Středisko vzdělávací politiky 4 Center for Economic Research and Graduate Education (CERGE-EI), National Training Fund (NTF), Research Institute of Labour and Social Affairs (RILSA). 6

7 labour from industry to services (especially to the health and social care sector), but the impact of such structural change on demand for skills cannot easily be forecasted based on past trends. 3 ASSESSMENT OF THE SUCCESS FACTORS AND TRANSFERABILITY The Finnish practice could in principle work appropriately in the Czech Republic. There are three major barriers of real transferability of the system to be overcome: lack of consensus and institutional collaboration, limits regarding the availability of up to date data/statistics, and insufficient expertise. Institutional background The key institutions making strategic decisions affecting future labour supply and having policy steering tools are the Ministry of Schooling, Youth and Sports (MoS) and the Ministry of Work, and Social Affairs (MoL). The former is in charge of co-funding and setting strategic goals and methodological support for regional school administrations (schools up to the upper secondary level) and steering the tertiary level of education. The MoS has an important say in deciding on the number of students enrolled in different school types and different levels of schooling. Such decisions are not based on systematic reflection of skills anticipation and actual developments seem to be driven mainly by autonomous developments with pupils/parental school choice playing an important role to the degree allowed for by rapid demographic changes (shrinking of young cohorts). The MoL has some powers shaping major retraining programmes implemented by District Labour Offices and the preparation of the legislative agenda guiding on-the job training. There are occasional signs that MoL and MoS already recognize the need to have information about future skill demands. However, they still play more or less a passive role by collecting and incorporating suggestions in their own projects rather than preparing strategic concepts for the creation of a system designed for regular anticipation of skill needs with long-term support from the government. Collaboration between the MoL (focussing primarily on employment, unemployment and retraining issues) and the MoS (focussing primarily on formal education) is weak and does not foster collaboration on projects, which would simultaneously tackle education generating skills and labour market outcomes. The Government Council for the Development of Human Resources, which could have played an active role in forming a comprehensive forecasting system, has been dissolved in Regional Councils for the Development of Human Resources exist, but they are only of minor importance for the creation of a skill needs anticipation system at the national level. Due to highly specialised curricula in upper-secondary schools and as a result of interregional mobility of the labour force being persistently low, aggregate nation-wide forecasts of skills needs are not very relevant for local labour markets with heterogeneous industrial structures of labour demand. A related point is that a great deal of control of the supervisory and decision-making agenda in primary and secondary schooling is in the hands of regional government (after a transfer of responsibilities from the central level several years ago). Regional administrators have an important say in terms of structuring upper-secondary education, including the share of general academic, vocational and apprenticeship programmes. While local administrations have better information about the current needs of local labour markets and individual employers, they tend to focus on shortterm goals of education and are more sensitive to lobbying from influential local employers who have a preference for narrowly educated graduates and frequently discount general skills, which are important in the longer term. 7

8 Data limits The core database needed for quantitative forecasts is the standard Labour Force Survey. 5 Despite its seemingly high sample size, only very broad education fields and level-genderoccupation-industrial criteria can be considered. Existing sample size allows for acceptably detailed forecasts at the aggregate level but not at the regional level. Surveys should be established, which would pair information on educational attainment with information on actual skill content of education for school graduates entering the labour market (this is particularly the case for nation-wide testing of graduates from uppersecondary programs being under preparation). The information on international mobility of the Czech labour force needs to be enhanced (currently, there is no survey, which could provide information on the extent of the Czech brain drain; similarly, the existing data on EU nationals working in the Czech Republic needs to be examined and tested for accuracy). In addition, the information on immigrants is only gradually becoming reliable and wage information needs to be combined from sources other than the LFS. While data on formal educational attainment of the population and fresh school graduates are available and are rather precise, there is little information on the actual skill content of education. Employer surveys also need to focus more on the skill structure of labour demand. Expertise At this moment, only a few institutions and small teams in the Czech Republic have solid experience with this type of forecasting and know-how to tackle long-term forecasting in this area. 6 From this perspective, learning from experience and practices in other countries is important and can be a way to implement credible skills anticipation schemes in a relatively short time horizon. Some of the ongoing projects outlined above could be developed into a comprehensive institutional system providing regular forecasting and early identification of skill needs. The existing methodological approaches could be usefully combined into a joint methodology. For instance, quantitative forecasts should be regularly confronted with qualitative sectoral studies. There also needs to be more record keeping of the forecasts performance. Similarly, existing forecasts, together with other pieces of expert information, need to be channelled more effectively to relevant stakeholders and users. 4 QUESTIONS To what extent is the quality of forecasts evaluated - comparing them with already known actual economic developments? How precise were the forecasts made around year 2000 based on existing information in those times for the year 2010? To what extent is the provision of future skills needs forecast competitive? Are several institutions providing their own competing forecasts? Or are there only unique forecasts which are a result of a consensus reached among experts of different institutional background? How were Finnish results disaggregated to the regional level (page 12). Is this taking into account interregional mobility of the labour force and job commuting - and how? 5 Quarterly rotating panel of 25th. households and about 60th. Individuals 6 This group includes the National Training Fund (NTF), CERGE-EI at the Charles University and Czech Academy of Sciences, the Research Institute of Labour and Social Affairs (RILSA) at the MoL, and the Institute of Education Policy (SVP) at the Charles University in Prague. 8

9 How are the forecasts translated into education plans and provisions? How it works that municipal schooling authorities take into account long-term educational goals instead of short term interests of local employers? Similarly, what is the division of steering powers between central schooling authority of the state and autonomous universities when setting educational priorities by fields and tertiary levels of education (BC, MA, and PhD levels)? 9

10 ANNEX 1: SUMMARY TABLE Labour market situation in the Peer Country Relatively high employment and participation rates of prime age population, relatively low unemployment. Steadily declining participation rate of young people due to extending access to education. Extraordinarily large share of employment in manufacturing and car making in particular. Changing competitive conditions and relative comparative advantages of industries due to the fluctuating exchange rate of the Czech crown. Assessment of the policy measure The steering of the Czech schooling and training systems desperately needs to take into account anticipated future skills needs of the economy - qualitative and quantitative. The Finnish system is much more than the Czech system based on inter-institutional collaboration and is much more advanced and comprehensive. The Czech Republic is facing similar demographic challenges as Finland with regard to an ageing population. Distribution of decision making power in education between central, regional and municipal authorities is the limiting factor in the efficient steering of the educational system towards long-term targets. Assessment of success factors and transferability Development of complex forecasting tools and supportive segments is time consuming and requires high level expertise. This can take decade(s) to be developed in the Czech Republic. The lack of a consensual and collaborative culture may slow down system development. Data limits can be removed, but it requires collaboration of several different institutions. There are real limits of forecasting due to high dependency of future demand for skills on hard to predict comparative advantages of industries and dynamic demographic changes. Questions To what extent is the quality of past forecasts being evaluated and compared with already known actual economic developments? To what extent is the provision of future skills need forecasts competitive several forecasting institutions competing and to what extent are forecast unique being the result of a consensus reached among experts of different institutional backgrounds? How have forecasts results been disaggregated to the regional level. More about the translation of forecast into education plans and provisions. 10