3. Aligning vocational education and training with labour market needs in Thailand

In light of structural changes that impact the demand for and the supply of skills, it is becoming increasingly important that the skills of workers are effectively aligned with the needs of the labour market. For example, technology can substitute for labour to carry out certain tasks, while complementing labour in other tasks. According to ILO estimates, three out of five jobs in five major ASEAN countries (Cambodia, Indonesia, the Philippines, Thailand, and Viet Nam) face at least a 70% probability of automation (Chang and Huynh, 2016[1]). Figures for individual countries range from 44% in Thailand to 70% in Viet Nam (see Figure 3.1). Although Thailand’s share is the lowest among the ASEAN countries with available data, it is similar to what is estimated for some OECD countries like Australia (40%) and the United States (47%) (see Figure 3.1). Estimates from OECD countries that focus on tasks carried out in a job rather than the occupation, suggest that only around 14% of jobs on average across OECD countries face a high probability of automation (Nedelkoska and Quintini, 2018[2]), but also that in addition to these, 32% of jobs have a high probability to undergo significant change in the way they are carried out. Hence, the estimated 44% of jobs at high risk of automation in Thailand is likely to comprise both jobs that can be fully automated and jobs that will see significant changes in their content, but will not disappear. In addition, OECD analysis highlights that the risk of job automation is higher among low-skilled workers, women, and workers at low-wage occupations, which may further increase disparities in the labour market (Nedelkoska and Quintini, 2018[2]). However, these estimates only provide an estimate of possible automation in the next few decades, and many factors could limit technology adoption, including the relative price of technology and attitudes towards technology. The COVID-19 crisis may have encouraged some employers to automate certain tasks, as a way to avoid disruptions and uncertainty in the face of mobility restrictions. Furthermore, it is important to note that these figures only capture potential job destruction and do not account for the (potentially larger) number of new jobs that technology will create. While certain jobs may disappear, others will emerge and a sharp decline in overall employment is unlikely. That being said, the jobs created by technological progress generally require very different skills than the ones that are destroyed, and this could result in substantial skills imbalances (OECD, 2019[3]).

Likewise, demographic changes contribute to skills imbalances. Thailand is entering a new era of demographic change involving slow population growth and probable eventual decline, along with an aging population. The declining proportion of the working age population will affect economic growth and can result in labour shortages. As of 2016, 11% of the Thai population (about 7.5 million people) are 65 years or older, compared to 5% in 1995. The fertility rate fell from 6.1 in 1965 to 1.5 in 2015, as a result of rising incomes and education levels and the successful National Family Planning Programme launched in 1970 (Office of the Education Council, 2017[4]). An older population has different needs and consumption patterns, including a stronger demand for personal and health care, which changes the skill needs in the labour market.

Imbalances between the supply and demand for skills can emerge in the form of ‘skill shortages’ – when adequate skills are hard-to-find in the current labour market – or in the form of ‘skill surpluses’ – when certain skills are in excess in the labour market relative to the demand (OECD, 2017[6]). In addition, imbalances also comprise skill mismatch when a workers’ skills or qualifications exceed or fall short of those required for the job under current market conditions (OECD, 2017[6]; Shah and Burke, 2005[7]). Mismatch can be measured along different dimensions, including skills, qualifications and field of study. Imbalances have been found to have negative consequences for individuals, firms and the economy more broadly, through lower productivity, wages and job satisfaction.

A common way to measure skills shortages is to ask employers about the difficulty they face in finding workers with the right skills to fill their vacancies. A survey conducted by SCB Economic Intelligence Centre among 222 firms in six key sectors in Thailand in 2014 showed that 53% of employers had difficulties filling job vacancies within three months (OECD, 2020[5]). These difficulties were faced by almost three in four firms in the hospitality and the food and beverage sector and around 60% of firms in the construction sector, while less than one in three firms in the wholesale and retail sector reported hiring difficulties. Moreover, the issue is most pressing for finding workers with vocational degrees. In this category, the shortfall is 23% of the total numbers of workers needed, meaning that for every 100 job openings for vocational graduates at a given time, only 77 recruits are available. This hiring gap is larger than for university graduates (14%) and for those with a high school education or less (11%). There are various reasons for why employers might not be able to fill their vacancies, with the most common reasons among Thai firms being high labour demand (56%) and mismatch between available skills and the skills they need (47%). Chalapati and Chalapati’s (2020[8]) analysis of the skills system in Thailand confirms that the country does not have enough vocationally skilled workers, and that this has resulted in shortages in the labour market. The lack of relevant vocational skills was confirmed in interviews carried out by the OECD team with Thai government representatives, who highlighted shortage of skilled technicians and operators for the industrial sector that are partially the result of impractical VET programmes – despite efforts to update them.

One area in which many countries are facing shortages is digital skills, and this is also the case in Thailand. ILO (2019[10]) reports that the Thai labour market faces a shortage of highly-skilled ICT specialists, as well as semi-skilled ICT workers that provide support and maintenance for ICT services, including networks, servers, software packages and computer equipment. They attribute the shortage of semi-skilled workers largely to the low quality of vocational education available in Thailand. The 2019 establishment survey on the use of information and communication technology found that firms in Thailand had a need for just over 17 000 information and communication technology (ICT) workers (OECD, 2019[11]). The strongest demand was for ICT associate workers, accounting for just over half of positions, followed by programmers (21%). Officials from the Association of Thai ICT industry (ATCI) estimate that as many as 90% of the ICT graduates each year are unable to meet the basic qualifications for companies to even begin job-specific training, highlighting a massive problem of under-skilled graduates, and irrelevant and outdated curricula (Tan and Tang, 2016[12]). Moreover, a survey by IMC Institute in 2013 found that three quarters of the employers in the ICT sector described the lack of emerging ICT skills as the biggest challenge for the industry. Almost half of the respondents cited the lack of knowledge and training facilities as the reason behind this skills gaps (Tan and Tang, 2016[12]). An employer survey carried out by the World Economic Forum in 2020 confirms the growing demand for ICT profiles and digital skills in Thailand (World Economic Forum, 2020[13]). The five job roles most frequently cited by Thai employers as being in high demand are: i) data analysist and scientists, ii) digital marketing and strategy specialists, and iii) big data specialists, iv) AI and machine learning specialists, and v) software and application developers. Likewise, many employers report technology-related skills as being in high demand, alongside certain transversal skills such as analytical thinking, complex problem solving and active learning. The demand for digital skills is likely to continue to grow in the coming years as employers increasingly adopt digital technologies in the workplace. The COVID-19 crisis already led to an increased demand for digital skills in the Thai labour market, resulting in shortages of such skills (see Box 3.1).

Using data from the Thai Labour Force survey, the OECD Skills for Jobs indicators measure skills imbalances in Thailand in an internationally comparable way that allows for detailed results by occupation, sector and skill type (see Box 3.2 for details on the methodology). As Table 3.1 shows, shortages can be found across the skills spectrum in Thailand, including in high-skill occupations (Health Professionals, Legal, Social, Cultural and Related Associate Professionals, Business and Administration Professionals, ICT Professionals, Health Associate Professionals, Teaching Professionals), middle-skill occupations (Metal, Machinery and Related Trades Workers, General and Keyboard Clerks), and low-to-middle skill occupations (Food Preparation Assistants, Protective Services Workers). A similar pattern can be seen at the sector level, with the largest shortages observed in the education sector, the health and social work sector, the mining and quarrying sector, the transportation and storage sector and the manufacturing sector. These imbalances could be the results of several factors, including an inadequate supply (e.g. few university graduates with specialisation in health care, few VET graduates specialised in metal and machinery operations), skills of graduates not matching employers’ requirements (e.g. VET and tertiary education graduates from business and administration fields not having the knowledge and technical and soft skills needed for business and administration jobs), and the attractiveness of working conditions (e.g. food preparation assistant job offering low salaries and difficult work schedules). It is important to note that the data refers to the period before the COVID-19 crisis, and therefore reflects structural imbalances that are unrelated to this recent labour market shock (OECD, 2020[5]).

The shortages observed at the occupational level translate into shortages of cognitive skills, such as mathematical reasoning, writing and reading comprehension, but also certain social skills, like service orientation, and technical skills (e.g. programming and technology design). The knowledge areas found to be most in shortage in Thailand are ‘computers and electronics’, ‘clerical knowledge’ and ‘customer and personal service’. As Thailand continues to be exposed to global mega-trends, such as population ageing, globalisation and automation, shortages of high-level cognitive skills and social skills are likely to become even more pronounced, as is the case in many OECD countries today. Occupations that have a relatively low probability of change due to automation, which are generally the ones requiring high-level cognitive skills and/or social skills, are already more likely to be in shortage in many OECD countries. In the United States, employment growth has been strongest in jobs requiring high levels of both cognitive skills and social skills (Deming, 2017[19]). In OECD countries, the occupations that combine high cognitive skills requirements with social skill requirements are the ones that are facing the strongest shortages (OECD, 2020[5]; OECD, 2017[6]).

Finally, in addition to substantial shortages, the Skills for Jobs data also show that the Thai labour market has a significant share of workers who are mismatched in their job in terms of qualification level and/or field. In 2018, 8% of workers were under-qualified for their occupation, meaning that they work in an occupation for which a higher level of qualification is normally required. An additional 34% were over-qualified, meaning that their education level is higher than what is generally required in the occupation they work in (Figure 3.4). This is quite different from the qualification mismatch pattern observed in OECD countries, where on average 19% of workers are under-qualified and 17% over-qualified. However, similar patterns as observed in Thailand can be found in Turkey, Peru and Brazil. The presence of over-qualification in the Thai workforce is consistent with the fact that employers mostly look for low to medium-skilled workers, while the education system is increasingly delivering tertiary educated graduates (see Chapter 2). Under-qualification, on the other hand, might reflect that employers have difficulties finding workers with the right qualification level and resort to hiring under-qualified workers. It should be noted, however, that under-qualified workers are not necessarily under-skilled for their jobs, as often workers acquire skills informally. As discussed in Chapter 2, a system of recognition of prior learning can help to certify these skills and make them more visible to employers (OECD, 2020[5]).

Over-qualification is most common in Thailand among sales and service workers (61%), followed by Plant & Machine Operators and Assemblers (48%) and Crafts and related trades workers (46%) (see Figure 3.5). The industries with the largest shares of overqualified workers are the Wholesale and Retail industry (55%) and the Accommodation and Food Services industry (50%). By contrast, under-qualification is most common among managers (41%), clerical support workers (40%) and technicians and associate professionals (37%), and in the utilities sector (25%). Mismatch by qualification level is very uncommon in some occupations and industries: Only 10% of professionals and 15% of workers in the education sector are mismatched by qualification level. Workers who have vocational or tertiary degrees in the fields of engineering, manufacturing and construction and in services are most likely to end up working in an occupation that generally requires a lower-level qualification (59% and 55%, respectively, of workers are overqualified). Less than 20% of workers with a vocational or tertiary degree in health and welfare or in education are mismatched by qualification level.

When looking at the field of study rather than the level of education, 37% of Thai workers are mismatched, compared to 32% across OECD countries (Figure 3.4). Field-of-study mismatch is especially common among those who specialised in arts and humanities (83% not working in their field) or in science (82%), while it is least common among graduates in the area of health and welfare (14%). Workers with a vocational or tertiary degree who work in skilled agricultural jobs or in elementary occupations are mostly like to have specialised in a field unrelated to their job, while this is least likely for those working as professionals. Individuals might decide to work in a field that is unrelated to the one they studied for several reasons, including a lack of job opportunities in their own field and more attractive working conditions in other fields.

The above data on skills shortages and mismatch in the Thai labour market show that there is room to improve the alignment of skills demand and supply. VET can play a key role in this respect, as the data show substantial shortages in occupations and sectors for which VET degrees are generally required. This subsection zooms in on the alignment between VET and labour market needs.

Employment rates in Thailand differ significantly between education levels (see Figure 3.6). Among adults aged 16-64 who are not in formal education, those with a tertiary education degree have an employment rate of 86%, while that of adults who completed at most primary education is only 77%. The employment rate of adults with a vocational diploma (post-secondary) is almost as high as those with a tertiary education degree (85%). Adults with a vocational certificate (upper-secondary) have lower employment rates (81%) than those with a vocational diploma, and the employment rate of the former group is roughly equal to that of adults who have a general upper secondary education degree or only a lower secondary education degree. When looking only at the group of adults aged 25 to 34 (not in formal education), the pattern looks roughly the same, with the exception that the employment rate of those with a vocational certificate is higher than that of young adults with a general upper secondary education degree (87% vs. 84%). Hence, vocational diplomas give roughly the same access to paid employment than tertiary degree, while vocational certificates are associated with stronger employment outcomes than the general track in upper-secondary education.

When controlling for personal characteristics (age, marital status and gender) and region, the probability of being in employment is significantly higher for adults (aged 16-64 not in formal education) who have a vocational diploma (2 percentage points higher than those who completed at most at primary education) or a tertiary degree (6 percentage points) than those with lower education levels.

Not only the quantity of jobs matter, but also their quality. Wages are an important aspect of job quality, and data form the Thai labour force survey show that median hourly wages of workers with vocational certificates are higher than those of adults who have completed at most upper secondary general education (20% difference, see Panel A of Figure 3.7). Wages are higher for adults with a vocational diploma than those with a vocational certificate (11% difference). However, wages of tertiary educated workers are much higher, with a difference of 85% between tertiary educated workers and workers with a vocational diploma.

These raw wage differences could reflect differences in the composition of workers, for example in terms of age or gender. However, even when controlling for personal characteristics (age, gender, marital status) and region, differences remain substantial. Panel B of Figure 3.7 shows that –when accounting for these background differences- adults with a general education degree earn 33% more than adults who have completed at most elementary education. For adults with a vocational certificate and vocational diploma, this wage premium amounts to 45% and 60%, respectively. The wage premium is even higher for tertiary educated workers, at 110%. Hence, these results show that participation in VET pays off –especially at the diploma level-, but also that the benefits are much lower than the benefits associated with obtaining a tertiary education qualification. However, when looking at the trend in wage premia, it is also evident that the gap between vocational qualifications and tertiary education has been on the decline. This is due to a falling wage premium for tertiary educated adults, which is likely a result of the oversupply of graduates –especially in certain fields-of-study for which the demand is low.

These findings are consistent with earlier literature on wage returns to education in Thailand. Hawley (2003[21]) finds that an additional year of schooling provides an additional 11%–12% of monthly earnings for both men and women, but also that the impact of an additional year of schooling for urban residents is higher than for rural residents. Moreover, vocational secondary education is found to provide higher earnings returns than general secondary education (Hawley, 2003[21]; Moenjak and Worswick, 2003[22]). Likewise, Tangtipongkul (2015[23]) finds that that if students decide not to continue to higher education then vocational education attainment will give higher earnings than general education attainment. The results from that analysis also show that secondary vocational education attainment is about eight percentage points higher on private returns and five percentage points higher on social returns than secondary general education. However, a bachelor’s degree is found to give the highest private and social returns among all education levels.

Another important aspect of job quality is whether one works in the formal or informal economy. As discussed in Chapter 1 and later in this chapter, Thailand has a relatively large informal economy. Moreover, data from the 2019 Thai informal employment survey show that the share of informal employment decreases with education, with 71% of workers who completed at most elementary education being in informal employment, compared to 54% of those with lower-secondary education, 46% of those with upper-secondary education, and 25% of those with tertiary education (Figure 3.8). While these data are not available by orientation of the programmes (i.e. vocational versus general), proxy measures allow to get a sense of the degree of informality among workers with vocational qualifications. According to data from the 2018 Thai Labour Force Survey, 38% of workers with a vocational certificate and 32% of adults with a vocational diploma are working as self-employed workers without employees or as unpaid family workers. This is lower than among workers with a general upper secondary degree (45%), but substantially higher than among tertiary educated workers (20%).

The overall labour market outcomes for adults with a vocational degree hide differences between the specialisation of their studies. As discussed in Chapter 1, the largest fields-of-study in VET in Thailand are industry and commerce/business. Data from the Thai Labour Force Survey show substantial differences in labour market outcomes between different fields of study (see Figure 3.9).1 Employment rates are just below 80% for adults with vocational diplomas in the fields of services, while they are 90% for vocational diploma holders in engineering, manufacturing and construction and in agriculture. The employment rate of adults with a vocational certificate ranges between 73% in the field of social sciences, business and law, and 89% in the field of engineering, manufacturing and construction. Employment rates of diploma holders are very similar to those of adults with a tertiary degree in the field of engineering, manufacturing and construction, and diploma holders even have a higher employment rate than tertiary educated adults in the field of agriculture. In the field of “social sciences, business and law” –which is among the largest fields for VET students-, tertiary educated adults have better outcomes than adults with a VET degree. Certificate holders generally have lower employment rates than adults with a vocational diploma, except in services.

Likewise, wages differ between fields-of-study. The median wage of VET diploma holders specialised in the field of health and welfare is 33% higher than for those with a VET diploma in science or in services. Differences between fields are smaller for vocational certificate holders. Wages of tertiary education graduates are substantially higher in all fields. Informality also differs between fields-of-study, with workers specialised in health and welfare having the lowest share of informal employment at all education levels and workers specialised in agriculture having the highest informality rate. Informality is higher among certificate holders than diploma holders in all fields. Informality is lower for tertiary educated adults than those with a VET qualification in all fields, but the gap is largest in agriculture and services.

Taken together, these labour market indicators show that VET graduates in the fields of health and welfare (which is a very small VET field) and in the fields of engineering, manufacturing and construction have the best chances of securing high-quality jobs. Nonetheless, the gap between them and tertiary educated workers remains substantial, especially with respect to wages.

As discussed in Chapter 2, participation in VET differ by region, and certain quality differences are visible, for example in terms of the availability of qualified teachers and of adequate teaching resources. Equally important as ensuring that those who want to participate in VET can do so and have access to high-quality teaching and learning, is to ensure that the types of programmes provided are aligned with the skill needs of the local area. In Thailand, the type of public VET institutions available varies by region, with especially Bangkok standing out (see Figure 3.10). While, in other regions, one in three public VET institutions are industrial and community education colleges, this is only 10% in Bangkok. By contrast, commercial, vocational and polytechnic colleges are relatively more common among public VET institutions in Bangkok than in other regions. Differences between the other regions are relatively small. The Northern and Southern region have relatively more colleges of agriculture and technology among their public VET institutions, while the Central and Northeast regions have more technical colleges in the mix. The types of institutions reflect the economic structure of the regions, with, for example, Bangkok being dominated by the service industry and certain other regions having a relatively large agricultural sector (e.g. the Southern region) (see Chapter 1). As mentioned in Chapter 2, private providers are more likely to be offering business and commerce programmes than more technical programmes.

Looking at fields of study of VET students in public institutions also shows some interesting regional differences (see Table 3.2). In all regions except Bangkok between 50 and 60% of students are in the industry field. In Bangkok the largest field is Commerce/Business, accounting for 45% of students. This field is also popular in other regions, accounting for between 25% and 30% of students. Bangkok also has a relatively large share of students in fine arts programmes (16%), while this is negligible in other regions. Difference between the other regions are relatively small, with the exception of the tourism field that is substantially larger in the Southern region (and the Central region to a lesser extent) and the home economics field that is larger in the Northern and Southern regions than in the Northeast and the Central region. The IT field is very small in all regions, in spite of the strong demand for ICT skills (as discussed above). Industry and commerce/business programmes are offered by the large majority of institutions in all regions (except for industry in the Bangkok region). For certain other fields the number of institutions providing them is relatively low, e.g. the tourism field in the Southern region (which has a large tourism sector) and the ICT field across all regions (for which there are many shortages, see above).

Labour market outcomes of VET students also differ strongly between regions, reflecting the different economic structure of the regions (see Chapter 1) and potentially the mismatch between the programmes on offer (and their quality) and the needs of the labour market. Data from the Thai labour force survey show that employment rates are higher in all regions for adults with a vocational diploma than for adults with a vocational certificate (see Figure 3.11). The difference is particularly large in Bangkok (8 percentage points) and in the Northeast (5 percentage points). By contrast, in the South and North employment rates differ only by a few percentage points between these two types of vocational degrees. The Central region is the only region where adults with a vocational diploma have a higher employment rate than tertiary educated adults. Differences between general and vocational upper-secondary education are small in all regions except Bangkok, where the employment rate of adults with a general upper-secondary degree is almost 5 percentage points higher than that of adults with a vocational certificate.

Likewise, in all regions median wages of vocational diploma holders are higher than those of vocational certificate holders, with the gap ranging between 11% in the Southern region and 20% in Bangkok and the North. In all regions the median wage of adults with a general upper-secondary degree is lower than that of adults with a vocational degree at the same level (i.e. vocational certificate), and the difference is largest in Bangkok and the Central region. The wage gap between vocational qualifications and tertiary education is large in all regions, and especially so in the Northeast where the wages of adults with a tertiary degree are more than twice as high as wages of vocational diploma holders.

Finally, similar patterns are observed for informality. In all regions except Bangkok, adults with general upper-secondary education are more likely to be in informal employment than those with a vocational certificate. Informal employment is less common for vocational diploma holders than for those with a vocational certificate, with the difference being largest in the Northern region. Adults with tertiary qualifications are even less likely to be in informal employment in all regions, and in the Northeast the gap between tertiary education and vocational diplomas amounts to 21 percentage points.

Overall, these results show that VET graduates do particularly well in the Central Region, and in Bangkok – albeit only for vocational diplomas. However, even in these regions the wages of adults with VET degrees are substantially lower than those of tertiary educated adults.

As discussed above, mismatch is very common among Thai workers, both in terms of their education level and their education field. Looking at this specifically for adults with a VET degree, Figure 3.12 shows that adults who have a VET degree are more likely than those with a tertiary degree to be over-qualified for their job. While only 30% of workers with a tertiary degree work in occupations that generally require a lower level of education, this is the case for 63% of workers with a vocational diploma and 67% of workers with a vocational certificate. Compared to adults with an upper-secondary degree with general orientation and those with a lower secondary degree, those with a VET degree are less likely to be overqualified and more likely to be under-qualified. This shows that VET does help adults into higher-skilled jobs than general education at the upper-secondary level and lower levels of education, albeit it to a much more limited extent than tertiary education.

Workers with a VET degree are also more likely than those with a tertiary education degree to work in an occupation that is unrelated to their field of study: 45% and 47% of workers with a vocational certificate or a vocational diploma, respectively, are mismatched by field of study, compared to only 33% of workers with a tertiary education degree. This result is surprising, given that VET is mostly designed to immediately prepare students for the labour market.

The likelihood of working in an occupation that does not match one’s field of study is larger for some programmes than for others (see Figure 3.13). For example, in Thailand almost all adults with a VET degree in education and science work in occupations unrelated to those fields of study. For the field of education this reflects that it is a very small field in the VET sector and this field is mostly delivered at the tertiary level. Adults specialised in education at the tertiary level are relatively unlikely to work in jobs unrelated to the education field, with only 31% of them being mismatched by field of study. For science fields the picture looks different, as this is a relatively large field for VET – at least following the definition used in the Thai Labour Force Survey-, especially at the short cycle tertiary level, and also adults with a tertiary level science degree are likely to be mismatched by field of study (73%). This is surprising given that the science field also includes computer sciences, and there is strong demand for ICT profiles in the Thai labour market. This could reflect that the skills of the computer science graduates –especially from VET programmes- do not match the needs of employers and/or that careers in ICT jobs are less attractive than other careers.

While having relatively low incidence of field-of-study mismatch, adults with a VET degree in social sciences, business or law are much more likely to be mismatched than adults with a tertiary degree in these fields. The same is true for the field of health and welfare, but this is a very small field in the VET sector.

To better understand where adults with a VET degree in a particular field end up, Figure 3.14 shows the distribution of workers over occupations for the two largest fields of study in VET. Almost half of adults with a VET degree (at both levels) with a specialisation in engineering, manufacturing and construction end up in crafts and related trades jobs or as plant and machine operators or assemblers, i.e. medium-skill technical occupations. Only 5% and 13% of adults with an upper secondary or short-cycle tertiary VET degree, respectively, work as associate professionals or technicians, i.e. the higher-skilled occupations often targeted by VET programmes. Around one-fifth of adults with VET degrees in engineering, manufacturing and construction work as clerical or sales and service workers. For the fields of social sciences, business and law, just over half of adults with a VET degree work in clerical or sales and service jobs. Given that this field encompasses many specialisations and sales and services jobs refer to a broad range of occupations, it is hard to assess to what extent these workers are mismatched or not.

High-quality information on skills demand and supply can help designing responsive VET policies and programmes that support the Thai economy in getting access to workers with the right skills. This type of information can contribute to avoiding and tackling skills imbalances and to improving labour market outcomes of VET students. Countries differ widely in terms of methods used to identify their skill needs, but also in terms of the level at which these exercises are conducted and stakeholder involvement (OECD, 2016[25]). In general, an assessment of skill needs should build on a wide range information, including quantitative information from a variety of sources (e.g. labour force survey, employer surveys, vacancy data, graduate tracer surveys) and qualitative information gather from key stakeholders in the skills system. In Malaysia and South Africa, a broad set of indicators using data from a variety of sources is used to measure which occupations are in shortage or high demand (see Box 3.3). Regions and sectors can differ strongly in their skills needs, and therefore it can be useful to carry out assessment by region and/or by sector.

In countries, results from skills assessment and anticipation exercise have mainly been used by governments to update occupational standards; design or revise training policies for workers or the unemployed; design, revise or decide on the allocation of courses provided in formal education (especially VET programmes and apprenticeships, see Box 3.4 for examples from Australia and South Africa). In addition, some governments use this information to guide migration policy, as well as their transition to a digital or green economy. Social partners (employer organisations and trade unions) also use this information to lobby governments on education and employment policy, develop training programmes, or provide advice to their members on skill development. Both social partners and governments use the information for broad dissemination purposes to inform workers and students about trends in current or future skill demand and supply (OECD, 2016[25]). Despite some good practices in the use of skill assessment and anticipation information in countries, governments and social partners still face several barriers when it comes to using the available information. In general, the identified barriers are twofold: i) involving and co-ordinating with stakeholders; and ii) bringing the skills assessment and anticipation exercises closer to the needs and requirements of policy-makers (OECD, 2016[25]).

In Thailand, a data-driven analysis of skill needs does not seem to be carried out in a regular and holistic way. Several analyses have been done for specific sectors or regions (e.g. for the new S-curve industries and for the Eastern Economic Corridor). Every few years, the National Statistics office carries out an employer survey to understand labour demand (the latest one dates back to 2013). Finally, on a monthly basis, information is provided about vacancies and jobs fulfilled by industry, occupation and province. Taking stock of these exercises and facilitating knowledge sharing between the actors involved, could foster better collection and use of skill needs information in Thailand, including for VET policy-making (OECD, 2020[5]).

As discussed above, information about labour market outcomes of VET students provide interesting insights that can be used in VET policy-making. To gather more detailed information on the labour market outcomes of VET students, a tracer study can be put into place. Such a tracer study allows following VET graduates in the labour market or further education at different points after graduation. Information can be collected on the time needed to find a job, characteristics of the jobs (e.g. occupation, tasks, wages, working time arrangements), reasons for working in jobs outside of one’s field etc. Moreover, if these tracer studies collect detailed information about the type of VET training the graduate went through (e.g. dual programmes, other forms of work-based learning, detailed field of study, private versus public institutions), it is also possible to compare outcomes by types of VET provision. This type of information can be used to improve the quality of VET and to align programmes better with the needs of the labour market (OECD, 2020[5]). Box 3.5 provides more details and examples of tracer surveys.

All VET systems need mechanisms to make sure that the number of people trained in different occupations matches labour market needs– and, within each field, that the mix of specific and general skills is aligned with skill requirements in the related sectors and occupations in the labour market. One important strategy for creating responsive VET systems that contribute to aligning the demand and supply of skills is to involve employers and trade unions in different aspects of VET (OECD, 2010[35]). Thailand’s VET system, as in many other countries, suffers from weak partnership with labour market actors – employers more specifically. This leaves the vocational system less equipped to respond to the requirements of the economy and less able to support the transition of young people into good jobs by equipping them with relevant skills. Ensuring a strong involvement of social partners in determining VET policy and provision, either through consultation or directly within decision-making processes, characterises effective VET because it helps ensure that the design and delivery of provision reflects both labour market demand and the competing needs to be attractive to employers, prospective learners and to society (OECD, 2010[35]; OECD, 2014[36]). Countries should construct effective mechanisms to involve social partners at each governance level where VET policy is being determined (Bergseng, 2019[37]).

The governance of a VET system relates to the structure of VET, how it is operated and financed, as well as the system of quality assurance which underpins it. Governance is defined as the formal and informal arrangements that determine how decisions relating to provision are made, who makes them and on what basis. Effective VET systems are based upon governance mechanisms that carefully balance multiple interests. There is not one right form of governance model for education or for VET that can be implemented across all countries. Successful models can be substantially different and still lead to good outcomes (Bergseng, 2019[37]).

As discussed in Chapter 1, the Ministry of Education is responsible for formal VET programmes in Thailand. VET institutions are managed by the Office of the Vocational Education Commission (OVEC) – under the Ministry of Education (UNESCO-UNEVOC, 2015[38]). In addition, the OVEC shares these responsibilities with many different actors, such as Ministry of Higher Education, Science, Research and Innovation (MHESI), Department of Skill Development (DSD), Ministry of Labour (MoL), Thailand Professional Qualification Institute (TPQI), Office of National Education Standards and Quality Assessment (ONESQA), but also actors from the industrial and business sector, such as Federation of Thai Industries, Thai Chamber of Commerce, and Tourism Council of Thailand (Office of the Educational Council, 2020[39]). For example, the Ministry of Transport has its own VET programmes in the field of logistics and transport; and the Ministry of Tourism and Sports designs and delivers VET programmes for tour guides and hotel and hospitality personnel (Ministry of Labour, 2020[40]). Such a division of responsibilities for VET leads to uncoordinated governance and a system that is difficult to navigate for students and inhibits social partner engagement, with implications for the quality and attractiveness of the provision (as also discussed in Chapter 2). In many countries, there are some steering structures to support the governance of the VET system (see Box 3.6 for an example of stakeholder engagement in Switzerland).

There has been a trend in Thailand, as in many other countries, to increase local autonomy in the organisation of the education system, including in VET. OVEC has recently decentralised governance arrangement by establishing the centre for promotion and development of vocational education in five regions, to promote the academic development, and the Provincial Vocational Education Service Area in five regions, to link with the groups of vocational schools at the provincial level (Office of the Vocational Education Commission, 2020[42]).There are also 77 provincial VET committees organised by the colleges. But it seems that this might have contributed to a lack of coherence and cooperation in VET policies, especially since it did not always go hand-in-hand with capacity building. In such cases, an overarching steering body for the VET system would enhance the coherency, and consequently the quality, of the VET provision.

Stakeholders and observers of the Thai VET system have shared concerns about the lack of industry involvement in the design and the steering of VET programmes, and in its funding. Some companies, such as 7 Eleven, prefer to set up their own education and training facilities (Chalapati and Chalapati, 2020[8]).

Recent efforts in Thailand have aimed at strengthening cooperation with industry for a better matching of VET provision with labour market needs. The TPQI (Thailand Professional Qualification Institute) has developed occupational standards in 52 sectors and 835 occupations, accounting for 2 174 qualifications, together with the Ministry of Education, OVEC, TPQI (Thailand Professional Qualification Institute), DSD (Department of Skills Development) and the Office of the Education Council, and in link with the ASEAN Qualifications referencing Framework. Those standards typically include skill sets in digital literacy, English proficiency and e-commerce and production management. OVEC is working with TPQI to integrate those standards into existing VET curriculum. By the end of 2021, it is expected that at least 25 areas of occupational curriculum offered in 120 colleges will have been reviewed and revised according occupational standards of TPQI and DSD. Moreover, twenty-five networks of colleges that offer programmes in the same fields were created, to share resources and develop learning communities and to better collaborate with the industry (TPQI, 2021[43]).

The Ministry of Education and the Ministry of Labour each have their own system to engage stakeholders, which in itself reflects the issues regarding lack of co-ordination and fragmentation. Within the Ministry of Education, a national Joint Public and Private Committee for Vocational Education (PPC for VE) was established in 2014. PPC for VE committees comprise industrial representatives, education leaders, teachers, and representatives from related agencies and organisations (skills standards agencies, universities, employer associations such as the Federation of Thai Industry and the Chamber of Commerce). Together 33 occupational cluster steering committees were created, chaired by an industry representative, in sectors such as automotive, electronics and electricity, ICT, logistics, food moulding, tourism, petroleum and petrochemical (see Box 3.7 for a description of the main objectives of these subcommittees).

Within the Ministry of Labour, DSD has put its effort in extending skill development networks through the memorandum of understandings in various fields with its potential partners, both public and private. At the national level, there is a National Skill Development and Vocational Training Coordination Board (NVBTC) which is a national bipartite mechanism consisting of representatives from both public and private sector, having the deputy prime minister as a chair of the board. The main function of this Board is to provide recommendations on human resource development at the national level and to set up a master plan on skill development. At the regional level, there is a similar board to the NVBTC known as Provincial Skill Development and Vocational Training Coordination Sub-committee (PBVTC) whose primary roles are to regulate and carry out workforce development activities at provincial level and to give advice to other related agencies in the province on human resource development (Ministry of Labour, 2020[40]). However, neither provinces nor vocational institutions enjoy particular freedom in adapting the content of VET programmes to the local economy – with few exceptions (OECD, 2019[11]).

In responsive VET systems, vocational provision rests on a systematic assessment of employer needs, now and in the future. However, if provision is determined exclusively on the basis of employers’ views, some risks emerge. Employers may want very narrow skills in occupational niches, or skills for declining industries and for low quality jobs, or they may want an oversupply of skills to drive down wages in the associated occupations. Industries in structural decline may also complain of skills shortages because they cannot attract workers into low wage positions with few obvious career prospects. In the latter case, adjustments to the vocational training system will not solve these problems. Therefore employer demands need to be kept in balance with the interests of society at large, including the interests of the student (OECD, 2010[35]). Negotiating VET provision with both employers and unions provides valuable information to governments seeking to ensure the design of VET qualifications meets labour market needs while remaining attractive to learners. Effective engagement will ensure that the interests of a professional sector outweigh those of individual employers. The role of the trade unions is also important, because they can balance, for example, the tendency of employers to focus too much on short-term firm-specific skills and excessively long apprenticeships which reduce employer costs (Bergseng, 2019[37]; OECD, 2010[35]; OECD, 2018[45]). Across the OECD countries, the engagement of social partners varies from purely advisory to decision making. For example in some countries with apprenticeship systems, such as Denmark and Norway, social partners can decide on the content of the programmes (Kuczera and Jeon, 2019[46]).

Achieving the ideal balance of responsibilities between actors from the education system and actors from the employment system on decisions related to all processes of VET, from curriculum design through application and updating, can be challenging. The skills provided by VET programmes benefit employers directly. The distribution of benefits will depend on the mix of skills being learnt – for example skills specific to an industrial sector yield benefits to that sector. The distribution of benefits should ideally be reflected in the distribution of funding responsibilities so as to provide the right incentives for optimal skills provision. In response to these shared benefits, a variety of funding models have emerged, involving some sharing of the costs of provision between government, student, and employer. Some contributions will be in kind, for example in terms of the time and facilities contributed by employers to workplace training (OECD, 2010[35]). However, there is an asymmetry in the information and resources available to educators and employers (Renold et al., 2018[47]), which complicates setting up fair funding mechanisms.

A study of governance systems in relatively high-performing VET systems in Germany, Switzerland, Denmark, the Netherlands and Austria, Emmenegger, Graf and Trampusch (2018[48]) identified six core areas of decision-making in VET: i) system development, ii) content definition, iii) matching the demand and supply, iv) organisation of the training, v) financing, and vi) monitoring, examination and certification. Understanding who does what in these areas and which stakeholders to involve and how to do that, can guide Thailand in reviewing its governance arrangement.

Bodies involving social partners to steer the system can be established nationally, regionally, according to economic sectors, or even at the level of individual institutions (OECD, 2010[35]). In Thailand, although sectoral co-operation is possible, for example through the occupational cluster steering committees mentioned before, decentralised co-operation between social partners and authorities is very limited. This is a matter of concern, as the demands of different economic sectors for skills vary significantly across regions (see Chapter 1 and above). Co-operation between social partners and VET schools is not institutionalised and varies considerably. While schools and employers collaborate on work-based placements for students, and schools are expected to have a good understanding of employer needs, provision is distorted by the dominant role of large employers. In Thailand, there is scope to strengthen co-operation with social partners, especially employers, at the regional level. This could take the form for example of VET-specific advisory bodies, who could also ensure a close contact between the labour market and institutions. Such regional committees, representing the diversity of the regional economy in terms of firm size and sector of activity, could allow the provision to reflect and be relevant to the breadth of the related labour market.

Collaboration between VET institutions and other stakeholders is crucial for getting the offer in line with demand. At the local level, provincial authorities, local private sectors and schools should join forces to tailor the content of curricula to regional needs, as they differ across the country. They are indeed best positioned to incorporate current and future needs into the content of VET programmes.

Funding incentives can also be used for steering partnerships between VET institutions and employers. In Sweden, for example, to launch a programme, an education provider has to show that there is labour market demand for the skills provided by the programme, and that it has a framework to engage employers. This means that institutions are eligible for public funds when they can form a partnership with employers willing to offer the workplace training (OECD, 2014[36]). But it should be noted that research in financial and non-financial incentives for VET programmes in general, and apprenticeships in particular, showed only a relatively small proportion of employers will increase the provision of education and training places in response to financial incentives. Such schemes usually involve substantial deadweight. A further risk is that financial incentives may succeed in engaging employers who are primarily interested in the subsidy, rather than training students (Kuczera, 2017[49]). While involvement at national level allows for broad advice on VET policy, employer engagement at local level can help to improve the links and partnerships between the workplace and individual VET institutions (OECD, 2010[35]). Consultations bodies can also be created at the institutional level, to decide for example on the number of VET school admissions by programme of study. Collaboration with social partners locally can enable greater co-operation between local schools and employers in relation to the sourcing of work placements (see Box 3.8 for an example from Denmark).

The current strategy for stakeholder engagement in the Thai VET system focuses on getting large employers on board. As such, one of the main concerns in the VET sector is that it mostly caters to the needs of big companies. However, in 2016, there were approximately 3.01 million SMEs in Thailand, which constituted more than 99% of all enterprises. They altogether contributed to 42% of the country's GDP and accounted for 79% of total private sector employment (OECD, 2020[50]). The value added created by small-sized enterprises grew faster than that of other firms in recent years. This implies that SMEs are an important source of economic growth in Thailand (OECD, 2020[5]).In spite of their important role in the Thai economy and labour market, SMEs are only involved to a limited extent in the VET system, and especially those operating in the informal sector. As a result, their skill needs are not sufficiently taken into account in the design and delivery of VET.

There are more than 1 million unregistered SMEs, most of them engaging in agriculture-related activities (OECD, 2011[51]). As discussed in Chapter 1, almost one in two workers are employed in informal jobs in Thailand. The informal economy is heterogeneous and is made up of increasingly diverse group of workers and enterprises in both rural and urban areas operating with no work-based social protection. Many informal economy workers engage in multiple informal and sometimes formal activities, usually multiple part-time activities, that might vary according to the time of year or season (OECD/ILO, 2019[52]).

Informality can be found in different sectors, to varying extend. In 2019, out of almost 6 million jobs in the retail and trade sector, more than 3.2 million were informal (55%) (see Figure 3.15). Accommodation and food services jobs also remain highly informal, with an informality rate of 62%. Other sectors, such as construction and manufacturing, also show a large share of informal jobs (45% and 21% respectively). Informality is most common in low- and middle-skill jobs, but interestingly, even a non-negligible proportion of professionals, technicians and individuals in managerial positions work under informal arrangements. In 2019, 7% of professionals, 9% of technicians and 33% of workers in managerial positions in Thailand had informal jobs (see Figure 3.15, Panel B).

Efforts have to be made to ensure that smaller companies are consulted and get to have a say in the design and steering of the VET system, to make sure that the system works for the different sectors of the labour market. Involving also the informal sector is important, alongside policies to reduce the informality rate. One of the policy concern with informal enterprises is how to retain its employment‐generating potential while making them economically more profitable as well as compliant with regulations (Bhattacharya, 2019[53]). Box 3.9 describes how digital technologies can contribute to the formalisation of the economy, and also help certify the skills of workers in informal sectors. More training and better skills in informal sector companies, could help to raise their productivity, stimulate the overall economy and support socio-economic development. VET can provide opportunities for training to informal sector business owners and workers, but it needs to be flexible and adult-friendly, as described in Chapter 2. Informal sector employers often lack the financial resources to provide training opportunities for their workers and worry about workers leaving the informal sector once trained. Additional support might therefore be needed to ensure that informal sector employers provide training.

In theory, students in VET in Thailand have an opportunity to take part in work-based learning (WBL) in companies, for at least one semester in the case of school-based VET programmes (i.e. all programmes excluding the dual programmes). WBL typically takes place during the fifth and/or sixth semesters for upper secondary students, and third and/or fourth semesters for postsecondary ones, with each institutions deciding. WBL is credit-bearing and typically lasts 18 weeks. VET institutions collaborate directly with enterprises and set goals for students. The placements are graded according to the curriculum (Office of the Education Council, 2017[4]). In practice, the length and the quality depends of the willingness of employers to offer high-quality placements to students. Recent programmes, such as the Factory-in-School initiative from the Ministry of Education, push for the inclusion of more WBL in the vocational school programmes.

The workplace provides a strong learning environment, and facilitates recruitment; while trainees contribute to output. Work-based learning opportunities are also a direct expression of employer needs. Expanding opportunities for work-based learning should go hand in hand with strong quality assurance mechanisms, to ensure that these work-based learning opportunities indeed allow students to develop the skills related to their field of study. To realise the benefits of work-based learning, it should be made an integrated element of the vocational programmes, rather than an add-on. This means that the learning outcomes expected from the work-based learning component need to be defined, so that what the student has learnt can be assessed. Quality standards for work-based learning help to avoid the allocation of students to unskilled tasks and ensure they acquire useful occupational skills. Such standards may cover the content and duration of training, the assessment of training outcomes and the competences of those who supervise trainees (see Box 3.10 for an example from Denmark) (OECD, 2014[36]).

One widely-known form of work-based learning is apprenticeships, also called in some national contexts the dual system. Such programmes combine learning in the workplace with school-based learning in a structured way. In most cases, dual programmes last several years. Most often the apprentice is considered an employee, and has a work contract and a salary (OECD, 2019[11]).

The concept of dual programmes has been around in Thailand for many years, but was only formally established as part of the Vocational Education Act in 2008, with the goal of linking the VET curriculum courses in colleges with internships in the workplace (Burapharat and Chupradit, 2009[59]). Every programme in both secondary and post-secondary vocational education can be delivered under the dual education mode. This is a strength of the Thai VET system and it is echoes the situation in some OECD countries, where the same qualifications can be pursued either as a school-based qualification or a work based ones. There are important benefits as it allows to adapt to the characteristics of students and the different employers, while also opening-up dual training in non-traditional trades, such as ICT or business (OECD, 2018[45]).

In dual programmes, students spend more than half of the time in the workplace, combining 3-4 days in the workplace and 1-2 days in the VET institutions. But the exact organisation of the learning periods in VET institutions and in the workplace depends on the agreement between the industry and the training institutions, as well as students and parents: students might alternate on a weekly or monthly basis (Office of the Education Council, 2017[4]; Goncalves, 2019[44]). Across countries, how on-the-job and off-the-job components alternate varies: in Austria, Germany and Switzerland, they are typically alternated within a week, in Ireland in blocks of several weeks. In Norway, a two-year long school-based component is followed by two years spent in the workplace (OECD, 2018[45]).

The number of students enrolled in dual programmes depends on the availability of work placements. The number of students in the dual VET system increased steadily in recent years, especially in diploma programmes. In 2019, around 87 000 diploma students and 47 000 certificate students were in the dual system. These numbers increased by 87% and 11%, respectively, in the period 2015-2019. 19 300 employers provided training places for these dual VET students in 2019. To encourage employers to participate in the system, the Thai government implemented a 100% tax exemption for expenditure incurred because of the apprenticeship. In addition, the Department of Skills Development provides subsidies for expenses of training, transportation of apprentices and accommodation, uniform and safety equipment, as well as equipment for training and insurance.

Dual programmes must be of high quality to compete with alternative pathways. Beyond the immediate financial implications of different pathways, individual choices, linked often to parental preferences, depend on the prospects that people feel they offer. If apprenticeships are of high quality, employment outcomes for apprenticeship graduates will be higher. Evidence for France shows that employment outcomes are higher for graduate apprentices than for students with equivalent school-based qualifications (Couppié and Gasquet, 2021[60]). But when apprenticeships are poor quality, apprenticeship becomes a second choice and those who can will pursue other options. With apprenticeships of poor quality, employers cannot rely on them as a proof of strong occupational skills, so it makes sense for them to prefer graduates of school-based programmes or those with a postsecondary or tertiary qualification (OECD, 2018[45]). In Thailand, there have been recent efforts to strengthen the quality of the dual programmes: OVEC provides guidelines and related documents to training institutions to help them work collaboratively with industry. Trainers in industries must be qualified according to the standards of the apprenticeship programme (Goncalves, 2019[44]). But stakeholders have also pointed that there are quality issues regarding the training received in the workplace, with students something doing unqualified and irrelevant tasks.

Differences in the design of schemes affect how attractive apprenticeships will be for potential apprentices and employers, as well as how it will affect public finances. Building apprenticeships in countries where apprenticeships are uncommon or creating new programmes in economic sectors that typically rely on other forms of training is challenging. Some simple principles underpin effective provision (OECD, 2018[45]):

  • Social partners should be involved in the design and implementation of apprenticeship schemes. This is essential to encourage their engagement with apprenticeship and ensure that programmes are suited to their needs and capacity to provide placements.

  • Competition between apprenticeships and alternative learning pathways (e.g. school-based programmes, postsecondary or tertiary education) needs to be fair.

  • Apprenticeships are easier to implement where formal qualifications bring substantial benefits to the learner.

Box 3.11 gives some indications on how design features can have an impact on the policy aim.

Across countries, the popular image of an apprentice is often of working in a skilled trade or craft, like construction or manufacturing. This accurately reflects the apprenticeship landscape in many countries, where apprenticeships are most common in manufacturing and construction. But this constrains apprenticeships to a small part of the labour market. Over the past decades, OECD economies have seen a shift in employment away from manufacturing and towards services, and in some countries the apprenticeship offer has evolved in the same direction. In Switzerland for example, the three most popular apprenticeship occupations are commercial employee, retail clerk and healthcare worker. In Germany, the three most popular apprenticeship occupations are in management and retail sectors (OECD, 2018[45]). Various countries have created apprenticeships in the IT sector, at different education levels, in response to the strong demand for IT-related skills in the labour market (see Box 3.12 for examples).

International evidence suggests that small firms are less likely than large ones to offer apprenticeships. In Switzerland, for example, around 25% of companies with fewer than 10 employees provide apprenticeships, compared to 80% of large firms employing 100 people or more (Muehlemann, 2016[65]). Small firms may lack the capacity to plan and determine training needs. They will be less efficient in offering training: large firms can train several apprentices using one instructor and for them bearing the fixed costs of dealing with administrative requirements will be easier to handle. Small firms may also be unable to train for the full range of skills required by a particular apprenticeship qualification (OECD, 2018[45]). Also, the bigger the employer, the more likely it is to retain apprenticeship graduates as skilled workers. This might happen either because small firms cannot offer a job to their qualified apprentice as a skilled worker or because their apprenticeship graduates prefer to work for larger employers with better career prospects. In the absence of long-term benefits from recruitment, many small firms will only provide apprenticeships if they can recoup their investment by the end of the training period. Despite these hurdles, across OECD countries SMEs are major providers of apprenticeships. In countries with available data from the Survey of Adult Skills, a product of the Programme for the International Assessment of Adult Competencies (PIAAC) (i.e. Austria, Australia, Canada, Denmark, Netherlands), over half of all apprentices work in firms with 50 or fewer employees (OECD, 2018[45]).

To support SMEs to take on apprentices, countries can establish external bodies take over some of the tasks generated by the provision of apprenticeship, e.g. searching for a suitable apprentice or dealing with administrative tasks, and they can also organise the sharing of apprentices between several employers. Such bodies can be run and managed by employers themselves or by a third party (OECD, 2018[45]) (see Box 3.13). Inter-company bodies or networks can also allow pooling of resources, sharing information and exchanging knowledge. For example, a lead company may bear the overall responsibility for training, while specific training modules may be delivered by partner companies. Larger firms may offer periods of training in their training workshops to apprentices of their supply chain partners, usually SMEs. In Switzerland for example, host company networks (Lehrbetriebsverbünde) group together enterprises to share the responsibilities of apprenticeship training. This arrangement is especially aimed at maximising the training potential of those companies that are too small and/or specialised to cover all the competencies specified in a defined VET curriculum as a singular entity, but may be able to offer the full spectrum by joining forces to train apprentices as a group. Usually, one enterprise or a separate organisation takes the role of coordinator and organizes the coaching, training and rotation of apprentices between various companies during their apprenticeship (ILO, 2017[66]).

Some of the most promising non-financial incentives aim to support employers in getting the best out of apprentices – for example by providing assistance with the administrative aspects of setting up an apprenticeships, or by offering training for workplace trainers (Kuczera, 2017[49]). Owing to their limited size and resources, SMEs often find it difficult to train qualified workers to supervise apprentices. Evidence suggests that better prepared apprentice supervisors underpin high-quality training (BIBB, 2009[67]). But to meet these requirement, SMEs need targeted support focused on flexible and customised training provision for trainers. For example in Norway training for apprentice supervisors is free to participants, and delivered by counties, schools or training offices, but optional. Counties provide the course, learning materials, subsistence and travel expenses, while firms pay supervisors during the course (OECD, 2018[45]).

There are unbalances in Thailand between the skills taught in the education and training system and those needed by the labour market, in which VET plays an essential role. VET graduates have relatively strong labour market outcomes, but they differ strongly between regions, reflecting the differences in the economic structures, and between fields-of-study. Employers report hiring difficulties for certain VET profiles and a mismatch between the skills of VET graduates and their needs. In addition, a significant share of workers with VET qualifications are employed in jobs that do not match their qualification level and/or field. These findings suggest misalignment between the VET programmes on offer (and their content and quality) and the needs of the labour market.

Aligning VET provision with the needs of the labour market, at the national but also at the local and sectoral levels, means using high-quality information on skills demand and supply. Responsive VET programmes can use quantitative information from a variety of sources (e.g. labour force survey, employer surveys, vacancy data, graduate tracer surveys). Such measures have to be complement with mechanisms that engage relevant stakeholders in the design and delivery of VET, at each level where VET policy is being determined. The complex VET system in Thailand complicates such stakeholder engagement. Currently, employer engagement in Thailand is mostly focussed on large companies, and the needs of SMEs and the informal economy are not sufficiently reflected. Quality work-based learning in all VET programmes and the development of apprenticeships is a strong policy tool to build a more responsive system that fosters strong labour marker outcomes for students. The recent efforts to further develop the Thai dual system are a step in the right direction, but more can be done to ensure that work-based learning is of high quality.

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Note

← 1. Fields-of-study in the Thai labour force survey are classified according to ISCED 1997. These fields are different from the categories used by OVEC in their reporting.

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