Mutual Learning Programme

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1 Mutual Learning Programme DG Employment, Social Affairs and Inclusion Peer Country Comments Paper - Sweden Skills forecasting in Sweden taking the next step Peer Review on Methods for forecasting skills needs for the economy Dublin (Ireland), June 2016 Written by Mattias Wihlborg June 2016

2 EUROPEAN COMMISSION Directorate-General for Employment, Social Affairs and Inclusion Unit A1 Contact: Emilio Castrillejo Web site: European Commission B-1049 Brussels

3 EUROPEAN COMMISSION Mutual Learning Programme DG Employment, Social Affairs and Inclusion Directorate-General for Employment, Social Affairs and Inclusion Peer Review on Methods for forecasting skills needs for the economy Dublin (Ireland), June 2016 June, 2016

4 Europe Direct is a service to help you find answers to your questions about the European Union. Freephone number (*): (*) The information given is free, as are most calls (though some operators, phone boxes or hotels may charge you). LEGAL NOTICE The information contained in this publication does not necessarily reflect the official position of the European Commission This document has received financial support from the European Union Programme for Employment and Social Innovation "EaSI" ( ). For further information please consult: European Union, 2016 Reproduction is authorised provided the source is acknowledged.

5 Table of Contents 1 Background to national approaches for skills forecasting Assessment of the policy measure Assessment of the success factors and transferability Questions... 6 Annex 1: Example of relevant practice... 7 Annex 2: Summary table... 8 References...10

6 1 Background to national approaches for skills forecasting This paper has been prepared for a Peer Review within the framework of the Mutual Learning Programme. It provides information on Sweden 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. Compared to many other European countries, Sweden has fared relatively well following the financial and economic crisis. From a European perspective, the Swedish labour market performs well, with a relatively high employment rate and labour market participation rate. However, with Sweden s increasing focus on technology-intensive and high-value added activities, there is a growing demand from employers for a highly skilled workforce (OECD, 2015). This in turn has resulted in lower skilled workers findings it increasingly to find employment. Young people without upper-secondary education and those with non-eu migrant background, in particular, experience high levels of unemployment (even within a European context). Recent studies indicate that the matching of skills remains problematic in Sweden and that it has resulted in higher unemployment and lower economic growth (Karlson and Skånberg, 2012; and NIER, 2012). The matching inefficiencies are not least manifested by the fact that many employers are looking for skilled labour but are unable to fill their job vacancies. Notably, the matching efficiency has worsened since the financial and economic crisis (NIER, 2012) and may continue to be problematic due to the growing proportion of long-term unemployed (who are less attractive to employers) and increasing numbers of low-skilled migrants. The most urgent skills shortages are in the public sector (e.g. teachers and nurses). There are also some demographic challenges, with younger cohorts moving away from smaller towns to the main cities. Matching of labour demand and supply is an important focus and priority for the Swedish Government to ensure that Sweden benefits from a well-functioning labour market (see, for example, the 2016 budget proposition). An important policy measure in this regard, and in terms of raising awareness, information sharing and forward planning, is to have good forecasting methods to better match demand and supply. In Sweden, there are several different actors involved in skills (or labour market) forecasting, including Statistics Sweden and the Swedish Public Employment Service (Arbetsförmedlingen). A number of social partners also provide forecasting reports and analysis, including the Swedish Confederation of Professional Associations (SACO) and the Confederation of Swedish Enterprise (Svenskt Näringsliv). The social partners particularly use such forecasts to assist in the collective agreement negotiations. May,

7 2 Assessment of the policy measure The two main skills (or labour market) forecasts in Sweden are produced by Statistics Sweden and the Swedish PES (Arbetsförmedlingen). The data and methods used to develop these forecasts are very different. Statistics Sweden has adopted a very detailed quantitative approach (largely based on administrative data) with a focus on educational levels, whilst the Swedish PES forecasts are more qualitative in nature and based on primary research (including interviews with around 10,000 private sector employers). Moreover, the focus of the PES forecasts is on occupations. Below we provide a brief description of each of the Swedish forecast methods, followed by a comparison with the Irish example. The forecasts produced by Statistics Sweden focus on the supply and demand for specific educational levels (based on the Swedish Educational Terminology (SUN) which is aligned with ISCED). The model used by Statistics Sweden comprise a supply side analysis and a demand side analysis. The supply side analysis provides year-on-year projections of the supply of labour by educational level, whilst the demand side analysis estimates the total demand for labour by educational level (both up to 2035 in the latest projection). The supply side forecast is primarily based on register-based or administrative data. The analysis includes assumptions about mortality (or survival ratios) taken from the population projections (produced separately by Statistics Sweden), as well as assumptions regarding the number of graduates by educational level (largely based on historical register-based data). Consideration is also given to the effect of immigration and emigration (these assumptions are also consistent with the population projections). Finally, the projected labour market participation rate is estimated and applied for each educational level (based on register-based labour market statistics (RAMS) and the PES register of job seekers). The demand side projections are based on the population and employment forecasts (also produced by Statistics Sweden), as well as a projection on the future demand for labour in different sectors (58 in total). The sector employment forecast is produced by Cambridge Econometrics using an econometric model called E3ME. The future composition of occupations within each sector is then derived (based on historic data and trends 148 occupations). Finally, the composition of different types of education is derived for each occupation (101 educational levels detailed analysis on 57 educational levels). Importantly, during this process, the analysts try to weed out some of the skills mismatches in the current labour market. For example, if a qualified civil engineer currently works as a nursery teacher, it is assumed that this type of education will not be demanded in the future, thus reducing its relative importance within the occupation over time. This process involves a large amount of data cleaning and professional judgement. The forecasts produced by Statistics Sweden are used by the Swedish Government in the budget process (e.g. as background information in discussions on increasing or decreasing the number of educational places financed by the state), as well as a range of other Government authorities and agencies (such as the Swedish Council for Higher Education, the Swedish Higher Education Authority and the Public Employment Service). Short-term and long-term skills (or labour market) forecasts are also produced by the Swedish PES. The forecasts are presented for around 200 occupations, which cover around 80 per cent of the labour market in Sweden. The occupations are based on the Swedish Standard Classification of Occupations (SSYK), which in turn is based on the International Standard Classification of Occupations (ISCO)). The short-term forecasts (one year) are based on interviews (face-to-face or telephone) with around 10,000 private sector employers, a number of state employers as well as representatives in all the municipalities and county councils. This evidence is complemented by the knowledge and information collated from the daily activities of May,

8 the PES. The projections for the following year are thus based on employers expected recruitment needs, as well as the PES's estimate of the availability of suitable employment. It also worth noting that the assessment for the short-term forecast is undertaken at the local level and then aggregated and weighted to provide a national assessment. As a complement to the interviews, the PES's analysis department also undertake a macroeconomic analysis and sector forecast which also influence the estimates of how the labour situation in different occupations will evolve in the coming year. A key output of the analysis and projections is a weighted 1 average score of the local public employment offices future assessment of each occupation ( bristindex ). The assessment is based on the following five-point scale: 1=large surplus of job seekers; 2=surplus of applicants; 3=balance between supply and demand; 4=slight shortage of job seekers; and 5=severe shortage of applicants. The short-term forecasts are presented at the national level (in Var finns jobben?) as well as the regional level (in Jobbmöjligheter) The PES also produce longer-term projections (5 and 10 years). These are developed through analysis and calculations of the future supply of labour in different occupations (based on a combination of quantitative and qualitative data). Consideration is given to retirements, graduate numbers, occupational mobility and migration. This then forms the basis for the assessment of long-term developments in the labour market and the demand for labour in different occupations. The long-term forecasts are limited to those occupations where the Swedish PES considers that the underlying data is sufficiently robust to allow projections. The long-term forecasts are only available at the national level. The short-term and long-term forecasts are published by the PES in Yrkeskompassen (see Annex 1 for further information) and Var finns jobben? and are also discussed with an expert group, which includes the social partners as well as experts from Statistics Sweden. The primary purpose of the forecasts are to support the work of the Public Employment Service by providing a more detailed knowledge of future trends and allowing better matching of the unemployed to employers recruitment needs. Another important objective of the Public Employment Service forecasts are to inform and influence external actors, including social partners, educational institutions and students. The most recent forecast (Var finns jobben?, 2016) shows that teachers and health care workers will continue to have good employment prospects in the short-term as well as the long-term. Engineers and IT-specialists are also expected to have good employment prospects. There are also a number of occupations that only require an upper secondary education that have good job opportunities over the five and ten year forecast period (e.g. car and truck mechanics, CNC-operators, chefs, nurses and several construction occupations). The long-term forecasts also allow the identification of vocational education programmes where the likelihood of quickly getting a job is particularly high following graduation. These are as follows: Building and Construction Programme Vehicle and Transport Programme Industrial Technology Programme Health and Social Care Programme There are a number of similarities between the approaches adopted in Ireland and Sweden. For example, Sweden has, just like Ireland a long tradition of skills (or labour market) forecasting both within Statistics Sweden (1960s) and the Swedish PES 1 Based on the proportion of local employees for each occupation. May,

9 (1990s). This means that capacity has been built up over time and that projections have been produced on a regular basis over a number of decades. The Statistics Sweden projections are produced every three years, whilst the labour market forecasts by the PES are completed twice a year. Similarly, in Ireland the MTR sectoral employment forecasts are produced every three years. In both Ireland and Sweden (at least in the case of the forecasts produced by Statistics Sweden), an econometric model (E3ME in Sweden and HERMES-13 in Ireland) is used to forecast sectoral employment. The sectoral employment forecasts are then converted into occupations using an industry-occupation matrix. The model used in Sweden, however, allows for a much greater disaggregation by sector (58 sectors compared to 11 (or 15) sectors in Ireland). Both countries have adopted a finely grained level of occupational disaggregation in the forecasts. Whilst the Irish example also seeks to use the occupational projections to derive educational levels, it is limited to four broad educational groups. In Sweden, the occupational forecast produced by Statistics Sweden is converted into very detailed educational levels (covering 101 educational groups). Rather than using constant shares (as in Ireland), it is assumed that the historic trend will continue, but the pace of change is halved to present a more conservative estimate of change. Continuing the trend is an important assumption as several studies have shown that there has been a continuous increase in the educational levels among the workforce over the last few decades 2. Notwithstanding the many similarities between Sweden and Ireland in terms of their methods for skills forecasting, there are also a number of differences. For example, the Statistics Sweden forecasts include both a demand side and supply side analysis which allows an assessment of the overall balance in the labour market. A difference between +/-5 per cent is considered balanced, whilst anything above that is considered as successively unbalanced. The Swedish forecasts produced by Statistics Sweden also benefit from addressing both expansion and replacement demand explicitly within the forecasts. This is different to the Irish example, where replacement demand is estimated separately. The methods used by the Swedish PES, with its focus primary data collection, is also very different to the Irish example. In Sweden, this additional level of analysis is an important complement to the largely modelling based forecasts produced by Statistics Sweden. 2 See, for example, Tåhlin (2007) Överutbildning i Sverige utvecklingen och konsekvenser and Le Grand et al (2004) Over-education or Lack of Skills? Job Matching on the Swedish Labour Market May,

10 3 Assessment of the success factors and transferability Similar to Ireland, Sweden has been able to build up and develop its expertise and methods for all aspects of the process over a long period of time. This has not only helped refine the methods used but also assisted in developing the in-house expertise. In fact, most of the experts in this field in Sweden are employed by Statistics Sweden, the Swedish PES and regional authorities. Sweden, like Ireland, make best use of existing data sources. However, in Sweden, there is a greater reliance on register-based data which has a number of advantages over survey based data (such as the QNHS). In Sweden, the importance of having an occupational register has been highlighted as an important tool for the provision of very detailed occupational data. The use of occupations as a proxy for skills is used in both Ireland and Sweden, particularly in the PES projections but also in the Statistic Sweden forecasts. However, Statistics Sweden also place a strong emphasis on educational levels and thus project both the supply and demand for detailed educational levels (in detail for 57 out of the 101 educational levels). The use of standard classifications for occupations and educational levels allows existing datasets to be used and combined, including registerbased data in the case of Sweden. There is, however, a growing debate as to whether occupations and/ or educational levels adequately reflect the competences required by employers. Consequently, efforts are increasingly made to making skills and competences more visible in labour market matching (e.g. through ESF funded projects such as SKiM and Competency Matching). The close connection between the work of skills forecasting and the mechanisms for informing policy is highlighted as an important success factor in the Irish example. A similar set up is present in Sweden, at least in the case of the Swedish PES, albeit with the important difference that it is connected to the delivery of the policy rather than the policy-making process. The connection with policy makers in Sweden is less direct for Statistics Sweden, although results are discussed in an expert group. Both countries make the results available to public agencies and other stakeholders through publically-accessible publications and databases. In Sweden, this is also complemented with ad hoc data analysis for specific agencies and purposes. Once a robust method has been developed, one of the key challenges is to make sure that the results are effectively used to support policy and delivering employment services (e.g. guidance or counselling). Connected to this, it is also important that the econometric modelling is complemented with expert input from stakeholders, including the social partners. May,

11 4 Questions The link with the Expert Group on Future Skills Needs is interesting. How does that work in practice? Do they have an input into the forecast methods and assumptions as well as the design of the policy measures? Has a retrospective evaluation ever been undertaken to assess the accuracy of the forecasts produced (particularly by the HERMES-13 model)? There is a growing interest in competences when it comes to defining skills in Sweden. How can that be usefully incorporated within the skills forecasting process? Does the Irish skills forecast provide year-on-year estimates or just an estimate for 2020? Does the Irish skills forecast provide a local/ regional breakdown? Are there data protection and/ or privacy laws that restrict the use of administrative data in Ireland? May,

12 Annex 1: Example of relevant practice Name of the practice: The Occupational Compass [Yrkeskompassen] Year of implementation: 2009 Coordinating authority: The Swedish Public Employment Service (Arbetsförmedlingen) Objectives: Yrkeskompassen is a guidance service on arbetsformedlingen.se showing the labour market situation and outlook for around 200 occupations. The service is designed primarily to provide support to all who are about to make a career choice. Yrkeskompassen is also a help for people who work with guidance. Main activities: Yrkeskompassen contains short-term (one year) and long-term (five and ten years) forecast information for around 200 occupations. The annual assessment is based on local employment offices projections. The assessment is therefore made at the local level and then aggregated and weighted to provide a regional and national assessment. The five and ten year forecasts are produced centrally by the PES s research department and is partly based on retirements, the availability of training and educational choices and labour market participation. The long-term forecasts are only presented at the national level. Long-term projections are only produced for those occupations where the number of employed are large enough and the statistical data is reliable. Moreover, conditions change quickly in occupations with few employees. Consequently, not all occupations are covered in Yrkeskompassen. Yrkeskompassen also provide a description of each occupation, as well as education and training information that is retrieved from Yrken A-Ö. Yrkeskompassen also provides a link to the SCB forecast information, where available. The occupations available in Yrkeskompassen corresponds to the largest and most common occupations in the labour market and occupations that are showing signs of increasing in importance. Yrkeskompassen covers the occupations that account for around 80 per cent of employment in the labour market. Results so far: Yrkeskompassen provides a useful tool for job seekers and employment service advisors in terms of career guidance. It can also be used by school children that are about to enter the labour market, as well as careers advisors in educational institutions. May,

13 Annex 2: Summary table Background to national approaches for skills forecasting There is a long-tradition of skills (or labour market) forecasting in Sweden, both within Statistics Sweden (1960s) and the Swedish PES (1990s). Forecasting reports and analysis is also produced by social partners, including the Swedish Confederation of Professional Associations (SACO) and the Confederation of Swedish Enterprise (Svenskt Näringsliv). Assessment of the policy measure An econometric model is used to forecast sectoral employment in both Ireland and Sweden (at least in the case of the forecasts produced by Statistics Sweden). Both countries have adopted a fine grained level of occupational disaggregation in the forecasts. The Swedish forecasts include both a demand side and supply side analysis which allows an assessment of the overall balance in the labour market. The forecasts produced by Statistics Sweden also benefit from addressing both expansion and replacement demand explicitly within the forecasts. This is different to the Irish example, where replacement demand is estimated separately. The methods used by the Swedish PES, with its focus on primary data collection, is also very different to the Irish example. It is considered an important complement to the largely modelling based forecasts produced by Statistics Sweden. Assessment of success factors and transferability Both Ireland and Sweden have been able to build up and develop its expertise and methods for all aspects of the process over a long period of time. Both countries make best use of existing data sources, although Ireland relies more heavily on survey data as opposed to administrative data. The use of occupations (and, to a lesser extent, educational levels) as a proxy for skills is used in both Ireland and Sweden. There is, however, a growing debate as to whether occupations and/ or educational levels adequately reflect the competences required by employers. The close connection between the work of skills forecasting and the mechanisms for informing policy is highlighted as an important success factor in the Irish example. A similar set up is present in Sweden, at least in the case of the Swedish PES, albeit with the important difference that it is connected to the delivery of the policy rather than the policy-making process. Both countries make the results available to public agencies and other stakeholders through publically-accessible publications and databases. Questions The link with the Expert Group on Future Skills Needs is interesting. How does that work in practice? Do they have an input into the forecast methods and assumptions as well as the design of the policy measures? May,

14 Has a retrospective evaluation ever been undertaken to assess the accuracy of the forecasts produced (particularly by the HERMES-13 model)? There is a growing interest in competences when it comes to defining skills in Sweden. How can that be usefully incorporated within the skills forecasting process? Does the Irish skills forecast provide year-on-year estimates or just an estimate for 2020? Does the Irish skills forecast provide a local/ regional breakdown? Are there data protection and/ or privacy laws that restrict the use of administrative data in Ireland? May,

15 References OECD (2015), OECD Economic Surveys: Sweden 2015, OECD Publishing, Paris Karlson, N. and Skånberg, O. (2012), Matching on the Swedish labour market [Matchning på den svenska arbetsmarknaden], Underlagsrapport 9 till Framtidskommissionen, Stockholm Ministry of Finance (2015) Budget proposition for 2016 [Budgetpropositionen för 2016] NIER (2012), Wage Formation in Sweden [Lönebildningsrapporten] Arbetsförmedlingen, 2016, Where are the jobs? [Var finns jobben?] May,

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