1. Changing skill needs in the Japanese labour market

Global megatrends, such as technological progress, globalisation, and population ageing, have altered the structure of labour markets in many OECD countries. These tendencies have resulted in changing demands for skills, both because the content of existing jobs is evolving and because of diverging skill requirements in new jobs versus jobs that have been lost. At the same time, the supply of skills has been shifting due to factors such as rising educational attainment, international migration and population ageing. These changes in the demand for and supply of skills have resulted in skills imbalances in many OECD countries.

The labour market situation in Japan had been steadily improving over recent years. The average unemployment rate between 2007 and 2019 remained relatively low compared to the OECD average, including during the global financial crisis (Panel A of Figure 1.1). In 2019, Japan’s unemployment rate stood in the 2% range, the lowest level in about 26 years, while it is projected to increase to above 3.5% in 2020 due to the COVID-19 crisis. In parallel, the employment rate has remained at higher levels than the OECD average, with a steady upward trend since 2012 (Panel B of Figure 1.1). In 2019, the employment rate was the highest on record since 1968, reaching as high as 78%, although it is projected to decline by 2 percentage points in 2020 due to the COVID-19 crisis (OECD, 2020[1]).

Even though Japan’s working-age population has been declining since 1995 of low birth rates and an ageing population, the number of people in employment has been increasing in recent years, mostly due to a rise in women’s and older people’s employment (Figure 1.2). On the other hand, while longevity and the development of better childcare support measures have boosted the labour force for, respectively, the elderly (65+) and women (15-64), the male (15-64) workforce has not increased likewise. Combined with the general increase in the number of disabled people and foreign-born entering the labour market, the work participation of a wide variety of people is increasing. As a result, adult learning policies will need to change in response to these changes in the composition of the labour force.

Population ageing, in particular, has the potential of substantially altering skill needs in Japan. In fact, while declining only slightly during 2000-18, Japan’s working age population is expected to experience more substantial reductions in the coming decades (OECD, 2019[2]). Japan already has the highest old-age dependency ratio among all OECD countries, and this proportion has increased dramatically from 20% in 1990 to 53% in 2020, and is projected to reach as high as 81% by 2050 (Figure 1.3). By contrast, countries such as Korea and Australia currently have an old-age dependency ratio of about 25%, and the OECD average is 31%.

The consequences of such dramatic change in the composition of the Japanese population on both the demand and supply of skills are multiple. First, as life expectancy rises and working lives get longer, more investment in training might be needed to ensure that workers’ skills remain relevant during their entire working lives. A change of training culture may also be required. At present, in all OECD countries, older adults participate less in job-related training than prime-age adults. One reason might be that employers are less interested in providing training to older workers as they have a shorter time to recoup the costs of the investment when workers are closer to retirement. Similar reasons may reduce older workers’ motivation to train.

Moreover, a shrinking working population may bring about substantial labour shortages. An ageing society also demands certain goods and services, often related to personal care and health care, which increases the demand for particular skills. OECD (2017[3]) shows that OECD countries with rapidly ageing populations are more likely to face strong shortages of health professionals. Shortages of nursing care workers are already acute today in Japan, and the Japanese Ministry of Health, Labour and Welfare estimates that there will be a shortage of 380 000 nursing care workers by 2025 (MHLW, 2015[4]). To alleviate these shortages, the Japanese Government has been easing immigration restrictions and improving working conditions, but has also turned towards care robots. The COVID-19 crisis is already showing the looming consequences of such labour shortages: according to the Japanese Nursing Association, to properly fight against the coronavirus, four times as many nurses as in regular periods are needed. As Japan lacks this health workforce, an urgent plea for retired nurses to return to work was issued in April 2020.

Japan’s labour market expansion has also been coupled with a gradual change in its composition in terms of the types of jobs created. In particular, the percentage of non-regular workers (e.g. part-time, dispatched or contract workers) is on the rise in Japan, as it is across most of the OECD area (OECD, 2015[5]).1 Indeed, the proportion of non-regular workers has increased by about 9 percentage points since 2002, reaching 38% in 2019 (Panel A of Figure 1.4). The number of part-time workers, especially, is well above the OECD average, and the gap has widened largely in the last two decades (Panel B of Figure 1.4).

In recent decades, technological progress and globalisation have led to considerable automation and outsourcing of jobs with a high-routine content, resulting in relatively low employment growth in such routine-intensive jobs. These routine-intensive jobs are mostly found in the middle of the skills and wage distribution. Therefore, employment growth has been concentrated at the top and the bottom of the wage and skills distribution, i.e. a process generally referred to as wage/job polarisation. Figure 1.5 shows that in almost all OECD countries the importance of middle-skill jobs in total employment declined in the past decades, relative to high- and low-skill jobs. This is also the case in Japan, although the changes were less marked than in many other countries.2 Whereas in the majority of OECD countries employment growth was concentrated in high-skill jobs, the relative growth of low-skill employment was stronger in Japan.

Looking at this trend in more detail, Figure 1.6 shows that the occupations experiencing the strongest employment growth in recent decades in Japan are professional and service occupations. The group of elementary workers, i.e. labourers or carrying, cleaning, packaging and related workers, has also experienced stronger than average employment growth in the overall 1995-2019 period. By contrast, employment in manufacturing, construction and mining occupations has been on the decline. This decline was particularly strong in the early 1990s, and roughly stabilised from the mid-2000s onward. Employment levels in clerical occupations, i.e. a middle-skill occupation that has seen its share in total employment decline in many OECD countries, moved in accordance with the trend in overall employment, implying that its employment share remained roughly stable in this period. This could explain why the polarisation pattern is less pronounced in Japan than in many other OECD countries.

As firms increasingly adopt technology and new technologies are being developed, one could expect more and more tasks to be automated. Since the adoption of technology in non-manufacturing jobs in Japan has been relatively slow compared to other OECD countries, there is still potential for a more extensive technology use that could automate certain tasks. Using experts’ view on the automation potential of technology for certain tasks, Nedelkoska and Quintini (2018[7]) estimate that 15% of jobs in OECD countries have a high risk of automation, meaning that these might entirely be restructured or downsized. An additional 32% of jobs face a medium risk of automation, meaning that a substantial share of the tasks in these jobs could be automated if cutting-edge technology is adopted (Figure 1.7). Hence, these jobs will see significant changes in their content, but they will not disappear altogether.

Estimates for Japan show that 16% of jobs have a high risk of automation, in line with the OECD average, and another 40% of jobs could face significant changes due to automation.3 Hence, overall Japan is more exposed to changes due to technology adoption in the workplace than the average OECD country. In addition, it is worth noting that the COVID-19 crisis is only expected to exacerbate this trend. In fact, the current health pandemic has directly or indirectly created various incentives to boost automation. As the global response to managing the health situation has been enforcing social distancing strategies and reducing human contact, both businesses’ and consumers’ preferences are gradually changing to favour automation and artificial intelligence (AI) (Coombs, 2020[8]). Yet, automation does not necessarily lead to job destruction, as it often implies that jobs change rather than disappear. Data from the 2018 Japan Household Panel Survey shows that only 4% of respondents who state that their firm introduced IT system, AI, robotics and accompanying organisational changes report that their jobs or tasks were at least partially lost.

The probability of automation decreases with education level (Panel A of Figure 1.8). However, this declining education-automation profile is less steep in Japan than it is on average across OECD countries. Similarly, the risk of automation declines with monthly wage level, with Japanese workers in the second decile of the wage distribution having an automation risk that is almost 70% higher than among workers in the highest wage decile. The risk also declines as firm size increases, and this negative relationship is steeper in Japan than in OECD countries. In line with the OECD average, dependent employment jobs in Japan have a higher risk of automation than self-employed jobs, and jobs of temporary employees a higher risk than those held by workers on permanent contracts. The risk of automation is higher in part-time jobs than it is for full-time jobs, and the gap between these two groups is larger in Japan than it is on average across OECD countries. Workers aged 16 to 34 hold jobs at substantially higher risk of automation than older workers, both in Japan and on average in OECD countries. Finally, whereas gender differences in the risk of automation are small on average, the risk in jobs held by female workers in Japan is 18% higher than that in jobs held by male workers.

At the occupational level, managers, professionals, and technicians and associate professionals are the occupations with the lowest risk of automation, whereas the highest risk is observed among skilled agricultural jobs and jobs in elementary occupations (Panel B of Figure 1.8). While the automation risk in Japan is below the OECD average in most manually intensive occupations, it is higher in non-manual and service occupations. The industries with the lowest risk of automation in Japan are the education sector and the information and communication sector. The highest risk of automation is observed in the agricultural sector and in the accommodation and food service sector. The picture in Japan looks broadly similar to the OECD average, particularly for manually intensive sectors in Japan have automation where the probabilities are close to the OECD average (e.g. manufacturing, construction, transport and storage). On the other hand, the risk of automation in cognitive skill- and social skill-intensive sectors (e.g. arts, entertainment and recreation, financial and insurance activities, wholesale and retail trade) is higher than the OECD average. These findings are consistent with the relatively slow adoption of technology in non-manufacturing jobs in Japan (as discussed above), which suggests significant room for automation of certain tasks in those jobs.

Differences between countries in terms of automation risk partly reflect the degree to which technology has already been adopted to automate certain tasks: countries that have on average a low risk of automation are likely to have already automated more tasks than in countries that are estimated to face a high risk of automation. Moreover, automation probabilities only reflect the potential of technology, and will only materialise if firms actually adopt technology. Technology adoption depends on many factors, including the relative cost of technology and attitudes towards technology. For example, a survey among Japanese adults shows that there is a strong preference for personal services, such as childcare, health care and education, to be provided by human workers rather than technology (Morikawa, 2017[9]).

A recent survey among youth aged 18 to 24 showed that youth in Japan are less optimistic that technological change will provide job opportunities in the future than their peers in other countries. Among the 19 countries participating in the survey, the share of young individuals who agreed with the statement that technological change would provide job opportunities in the future was smallest in Japan. A survey among Japanese adults shows that 30% of adults feared that they would lose their job because of technology, and this fear was larger among young, low-educated and non-regular workers (Morikawa, 2017[9]). Another survey finds that 89% of Japanese adults think that it is likely that in the next 50 years robots and computers will do much of the work currently done by humans (Pew Research Center, 2018[10]). Moreover, 74% of Japanese think that people will have a hard time finding jobs if robots and computers indeed manage to carry out those tasks. This share is lower in Japan than in the other eight countries participating in the survey, and a relatively large share of Japanese adults think that technology can also lead to the creation of new better-paying jobs (35%) and to a more efficient economy (83%).

While the estimated probabilities of automation focus on potential job destruction, technological progress also leads to job creation. There is evidence to suggest that the number of jobs created due to technological progress has been larger than job displacement due to automation in European countries and the United States in recent decades (Autor and Salomons, 2018[11]). Analysing the impact of AI adoption in Japan in the last five years on workers in jobs that are deemed to have a large potential for automation, Kitahara and Shinozaki (2019[12]) find that introduction of AI leads to a reduction in working hours. A similar analysis for employment levels across all occupations (irrespective of their automation probability) finds that there is no impact of AI adoption on total employment and a positive impact on employment of regular employees.

The fact that technological progress has not led to massive employment losses can also be seen from trends in employment rates, which have been on an upward trajectory in recent decades in the majority of OECD countries (including Japan). Employment in Japan grew mainly in industries with high digital intensity, while it experienced an important decline in low digital-intensive occupations (Figure 1.9). In contrast, on average across OECD countries employment grew in industries at all levels of digital intensity. This, together with the substantial impact that automation can have on the task content within jobs, implies that skills needs are changing and an increasing share of adults might need access to upskilling or reskilling opportunities.

All these megatrends are happening against a background of rapidly rising educational attainment (Figure 1.10). In Japan, the share of adults with a tertiary education qualification rose from 34% in 2000 to 52% in 2018, and is now the second highest among OECD countries. Japan’s high tertiary attainment rate is driven by short-cycle tertiary education programmes. Over one-third of first-time entrants into tertiary education in 2017 enrolled at this level, 18 percentage points higher than the OECD average of 17% (OECD, 2019[15]). The quality of education is also high, with Japan’s upper secondary education students ranking among the top performers in reading, mathematics and science in the OECD’s Programme for International Student Assessment (PISA).

These high educational attainment levels and the high-quality education system translate into high skill levels of the adult population, with Japanese adults having on average the highest literacy and numeracy proficiency among OECD countries (see Figure 1.11 for literacy skills). Skill levels of young adults in Japan are substantially higher than those of adults aged 55-65, reflecting the rapid rise in educational attainment in recent decades. While such a gap exists in all OECD countries, it is bigger than average in Japan. The gap between older and young adults in Japan becomes smaller when controlling for gender, education, immigrant and language background and parental education, but the difference remains substantial (23 score points versus 36 points without controls) and larger than on average in OECD countries (OECD, 2019[16]). This means that older adults have lower literacy skills than young adults even when they have the same education level and socio-economic background. The remaining difference could be linked to several factors, including improvements in the quality of education over time and adults facing skills depreciation during working life.

The picture looks slightly less positive when looking at digital problem-solving skills of Japanese adults, see Figure 1.12. While Japan has an above average share of adults with strong digital problem-solving skills (42% versus 32%), it also has a higher fraction of adults who lack basic ICT skills (25% vs. 19%). This contrasts with countries like Australia, Denmark, Finland, the Netherlands, New Zealand, Norway and Sweden, which also have large shares of adults with high digital problem-solving skills, but less than 10% of adults who lack basic ICT skills. Digital skills are particularly low among older adults in Japan, with 41% of 55-65 year-olds lacking basic ICT skills (versus 34% in the OECD on average), and among those without an upper-secondary education degree (54.5% lacking basic digital skills, versus 42% in the OECD on average) (OECD, 2019[16]). Interestingly, low levels of digital skills are also more common among young adults and adults with tertiary education in Japan than on average across the OECD: 10% of young adults (aged 25-34) and 11.5% of adults with tertiary education lack basic digital skills, versus 8% and 4% on average in OECD countries, respectively.

Looking at some specific applications of digital skills, many adults in Japan report to have limited digital skills for data processing (Figure 1.13). Just over 40% of adults say that they can (without trouble or to some extent) carry out basic data processing using spreadsheet software. This share drops to 22% for data processing skills using macro functions and 8% using programming languages. Self-reported computer skills are lower among older adults, with 63% of adults in their thirties having basic data processing skills using spreadsheet software compared to only 34% of adults in their sixties. The gap between men and women is also substantial, with 53% of men claiming to have basic data processing skills using spreadsheet software, compared to only 29% of women.

Prior to the COVID-19 crisis, an improving labour market situation and gradual economic recovery, led to increasing labour shortages. The effective job-opening ratio, an indicator of how many jobs are available out of the total number of job seekers registered at the public employment service (Hello Work), hit a 45-year high of 1.6 in 2019 (Panel A of Figure 1.14). This is due to the continued economic recovery, which has increased the willingness of companies to hire, as well as a significant drop in the number of unemployed people and fewer people looking for jobs. Although there are still regional differences in the status of labour shortages, the differences between regions are smaller than in the past, for example in 1974 when the effective job-opening ratio was at the exact same level (Panel B of Figure 1.14).

While the job-opening rate was greater in 2019 than in the past, the mismatch between vacancies and job seekers was also widening. The Beveridge curve – i.e. the relationship between the unemployment rate and the vacancy rate – has been shifting to the right since 2000 indicating that the same vacancy rate now coexists with higher rates of unemployment. The shift signals a worsening of the matching process between job vacancies and job seekers. (Figure 1.15).

Companies are facing difficulties in recruiting workers with the right vocational skills. According to the Basic Survey on Human Resource Development, 53% of firms face important challenges in transferring vocational skills within firms through seniors’ mentoring due to difficulties in recruiting motivated young and mid-career workers. In particular, difficulties in finding new hires with the right vocational skills are frequent in the food and hotel industry and in health care, while the problem is less pervasive in industries such as finance and insurance (Figure 1.16).

An international employer survey finds that 88% of surveyed employers in Japan are facing talent shortages (ManpowerGroup, 2020[17]). This is higher than in any of the other OECD countries covered by the survey, with the OECD average equal to 53%. Medium-sized and large employers in Japan are more likely to report talent shortages than small firms. The jobs that Japanese employers find hardest to fill are engineering, sales and marketing, and IT jobs. The Ministry of Economy, Trade and Industry also estimates that there will be a shortage of 450 000 ICT related workers in Japan by 2030 (The Ministry of Economy, 2019[18]).

International data on skills imbalances are usually limited to employer surveys on hiring difficulties, which are often subjective in nature and might therefore give a biased picture of the real situation (OECD, 2017[3]). Moreover, usually these indicators are not very detailed and provide limited information on the type of skills that are deemed difficult to find by employers. In an effort to provide internationally comparable objective data on skills imbalances, the OECD Skills for Jobs database uses labour market data from labour force surveys and other similar datasets to calculate shortage and surplus intensities for occupations, sectors and skills. Box 1.1 describes how the Skills for Jobs indicators have been calculated for Japan.

Figure 1.17 summarises the OECD Skills for Jobs indicators at the occupation level, and shows that shortages are on average most intensive in security occupations, construction and mining occupations, and transport and machine operation occupations. Surpluses, on the other hand, are strongest on average in administrative and management occupations and in sales occupations. These average by broad occupation group mask large difference between the occupations within each group. As Figure 1.17 shows, some occupation groups contain occupations with strong shortages and strong surpluses. This is the case, for example, for service occupations, which are on average almost in balance, but the average balance is the result of shortages in care service occupations and surpluses in customer service occupations which cancel out. At this more detailed occupation level, the largest shortages are found for i) Legal workers and Management, finance and insurance specialists, ii) Social welfare specialists, and iii) Care service workers. By contrast, the largest surpluses are found for i) Product inspection workers, ii) Merchandise sales workers, and iii) Railway drivers, ship and aircraft operators and other transport workers. While not shown in this chart for reason of limited comparability of occupational classifications, shortages in the average OECD countries are more strongly concentrated in high-skill occupations (i.e. managers, professionals, technicians and associate professionals) than in Japan.

Using information on skills requirements by occupation, the occupational shortage index can be used to calculate the extent to which certain skills, abilities and knowledge types are in shortage. Skills, abilities and knowledge are the different aspects of competence used in the O*NET database. Knowledge is the understanding of a given field; it is mental or theoretical, rather than practical. Abilities are natural or inbuilt whilst skills are learned behaviours. As shown in Figure 1.18, the largest shortages of knowledge are found in Japan for health services and education and training knowledge, in line with the OECD average. For skills and abilities, the largest shortages are found in Japan for psychomotor abilities, strength and flexibility, and spatial abilities. This is fairly different from the OECD average, where these skills are in surplus, and the largest shortages are found in the areas of verbal abilities and basic skills. These differences between Japan and the OECD average can to a large extent be explained by the fact that shortages in the average OECD country are much more concentrated in high-skill occupations than in Japan, and these occupations make more extensive use of verbal abilities and basic skills and less use of psychomotor and spatial abilities and strength and flexibility. It is important to note that the skill group averages shown in Figure 1.18 could hide substantial differences in shortage or surplus intensity between the more detailed skills within those groups. This is, for example, the case for the social skills category, which is in surplus on average in Japan, but groups some skills that are in surplus (e.g. negotiation, persuasion) and some shortage skills (e.g. instructing, social perceptiveness). Moreover, a surplus of a certain skill does not mean that this skill is not needed in the labour market, but only that the supply exceeds the demand.

A substantial share of workers in Japan are employed in occupations that do not match their education level or field (Figure 1.19). For 31% of workers in Japan, their highest qualification level is greater than the level someone would need when applying for that person’s job today. This is higher than on average across OECD countries (21%), and only in France, Israel and New Zealand an even larger share of workers are over-qualified for their job. By contrast, only 8% of workers in Japan are under-qualified for their job, compared to 12.5% on average across OECD countries. Workers cannot only be mismatched in their job in terms of education level, but also in terms of their field of study. In Japan, 46% of workers are employed in an occupation that does not match the field of their highest obtained qualification. This is higher than the OECD average (41%), but still below what is observed in Chile, Korea, Mexico, New Zealand and the United Kingdom where more than 50% of workers are mismatched by field of study.

Qualification mismatch is most common in Japan among workers with a post-secondary non tertiary-degree and among workers whose field of study is services. By contrast, qualification mismatch is particularly low among workers with a qualification that is focused on science, mathematics and computing. Qualification mismatch levels are similar for men and women, for workers in different age groups, and for permanent and temporary workers. Part-time workers have a higher incidence of qualification mismatch than full-time workers (mostly because they are more likely to be overqualified), and the probability of being mismatched by qualification level declines with firm size. Field-of-study mismatch is most often observed among workers with an education specialisation in humanities, languages and arts, but also those specialised in agriculture and veterinary and teacher-related fields. This type of mismatch is more common among non-regular workers than among regular workers, and among workers in smaller firms.

Qualification mismatch is lowest among managers and professionals. While the latter also have relatively low incidence of field-of-study mismatch, this is not the case for the former. Mismatch is highest among elementary workers, both in terms of education level and field, but these workers are least likely to report training needs. When looking at sectors, the education and finance and insurance sectors are found to face the lowest incidence of qualification mismatch, while field-of-study mismatch is lowest in the health and social work sector, real estate sector and construction sector. The administration sector and the accommodation and food services sector have both high qualification and field-of-study mismatch.

Another way to look at mismatch is to analyse the extent to which workers use their skills at work. Data from the Survey of Adult Skills show that while employed adults in Japan have very high literacy and numeracy proficiency, the intensity of use of these skills is lower than in many other OECD countries (Figure 1.21). Numeracy use at work in Japan is close to the OECD average. Workers in Japan are more frequently engaged in reading at work, with an average intensity that is above the OECD average. However, workers in countries like Australia, New Zealand, Norway, the United Kingdom and the United States more frequently engage in reading-related tasks at work, although on average they have lower literacy proficiency than Japanese workers.

Looking at skill use by type of worker shows that the gender gap in skill use at work is larger in Japan than on average across OECD countries, with women in Japan having 17% lower reading use and 20% lower numeracy use at work than men. Part-time workers also have much lower skill use than full-time workers, and this difference is larger in Japan than across OECD countries. Prime age workers have higher skill use than young workers and older workers, and the difference between these age groups is slightly larger in Japan than the OECD average. The gender gap and the gap between full-time and part-time workers remains when comparing individuals with similar skill proficiency, personal and work characteristics and employed in similar occupations and industries, both in Japan and on average across OECD countries (with the gaps being larger in Japan). Older workers are found to have lower numeracy skill use at work than young and prime age workers when controlling for these characteristics, and the difference remains larger in Japan than on average. By contrast, reading at work is found to be the same for older workers and prime age workers, but lower for young workers (both in Japan and the OECD average, with a larger difference between young and prime age workers in Japan).

Overall, while technology adoption is changing skill demands, women and older adults, who have contributed significantly to the growth of Japan’s workforce in recent years, have more difficulties working with information technology, as discussed in previous sections. In addition, many differences – including a gender gap and a gap between full-time and part-time workers’ use of skills at work – are higher in Japan than on average across OECD countries, which could inhibit opportunities for women, older workers and part-time workers to develop their skills in the workplace. This could lead to further polarization and a delay in corporate ICT adoption, if proper adult learning is not provided.


[22] Asao, Y. (2011), Overview of non-regular employment in Japan, The Japan Institute for Labour Policy and Training, https://www.jil.go.jp/english/reports/documents/jilpt-reports/no.10_japan.pdf (accessed on 13 August 2020).

[11] Autor, D. and A. Salomons (2018), “Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share”, Brookings Papers on Economic Activity, Vol. 2018, http://dx.doi.org/10.3386/w24871.

[13] Calvino, F. et al. (2018), “A taxonomy of digital intensive sectors”, OECD Science, Technology and Industry Working Papers, No. 2018/14, OECD Publishing, Paris, https://dx.doi.org/10.1787/f404736a-en.

[8] Coombs, C. (2020), “Will COVID-19 be the tipping point for the Intelligent Automation of work?”, International Journal of Information Management, http://dx.doi.org/10.1016/j.ijinfomgt.2020.102182.

[19] Handel, M. (2012), “Trends in Job Skill Demands in OECD Countries”, OECD Social, Employment and Migration Working Papers, No. 143, OECD Publishing, Paris, https://dx.doi.org/10.1787/5k8zk8pcq6td-en.

[12] Kitahara, S. and T. Shinozaki (2019), “Do Digital Technologies Complement or Substitute for Human Labor?”, ESRI Discussion Paper Series, No. 351, ESRI, Tokyo, https://form.cao.go.jp/esri/en_opinion-0002.html (accessed on 4 March 2020).

[17] ManpowerGroup (2020), Talent Shortage 2020 - Closing the Skills Gap: What Workers Want.

[4] MHLW (2015), Estimates of Supply and Demand for Nursing Care Personnel for the Year 2025 (Fixed Value).

[20] Montt, G. (2015), “The causes and consequences of field-of-study mismatch: An analysis using PIAAC”, OECD Social, Employment and Migration Working Papers, No. 167, OECD Publishing, Paris, https://dx.doi.org/10.1787/5jrxm4dhv9r2-en.

[9] Morikawa, M. (2017), “Who Are Afraid of Losing Their Jobs to Artificial Intelligence and Robots? Evidence from a survey”, RIETI Discussion Paper Series, No. 17-E-069, RIETI, http://www.rieti.go.jp/en/ (accessed on 4 March 2020).

[7] Nedelkoska, L. and G. Quintini (2018), “Automation, skills use and training”, OECD Social, Employment and Migration Working Papers, No. 202, OECD Publishing, Paris, https://dx.doi.org/10.1787/2e2f4eea-en.

[1] OECD (2020), Employment Outlook 2020 Japan Country Note, OECD, Paris, https://read.oecd-ilibrary.org/view/?ref=134_134923-qy8ex0wvt6&title=Employment-Outlook-Japan-EN (accessed on 5 August 2020).

[15] OECD (2019), “Japan”, in Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris, https://dx.doi.org/10.1787/1a143b02-en.

[14] OECD (2019), Measuring the Digital Transformation: A Roadmap for the Future, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264311992-en.

[2] OECD (2019), OECD Economic Surveys: Japan 2019, OECD Publishing, Paris, https://dx.doi.org/10.1787/fd63f374-en.

[6] OECD (2019), OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris, https://dx.doi.org/10.1787/9ee00155-en.

[16] OECD (2019), Skills Matter: Additional Results from the Survey of Adult Skills, OECD Skills Studies, OECD Publishing, Paris, https://dx.doi.org/10.1787/1f029d8f-en.

[3] OECD (2017), Getting Skills Right: Skills for Jobs Indicators, Getting Skills Right, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264277878-en.

[21] OECD (2016), OECD Employment Outlook 2016, OECD Publishing, Paris, https://dx.doi.org/10.1787/empl_outlook-2016-en.

[5] OECD (2015), In It Together: Why Less Inequality Benefits All, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264235120-en.

[10] Pew Research Center (2018), In Advanced and Emerging Economies Alike, Worries About Job Automation, Pew Research Center, http://www.pewresearch.org.

[18] The Ministry of Economy, T. (2019), Study on IT Personnel Supply and Demand, https://www.meti.go.jp/policy/it_policy/jinzai/gaiyou.pdf.


← 1. While there is no explicit definition of regular and non-regular workers in the Japanese legislation, the term regular worker is commonly used to identify “an employee who is hired directly by his/her employer without a predetermined period of employment, and works for scheduled hours. In other words, it can be summarised as open-ended, full-time, direct employment” (Asao, 2011[22]) By contrast, a non-regular worker is defined is an employee who does not meet one of the three conditions (open-ended, full-time, and direct employment) for regular employment. In particular, in the Japanese Labour Force Survey, non-regular employment includes all workers under the categories: “part-time workers”, “temporary workers”, “dispatched workers at worker dispatch offices”, “contract workers”, “commissioned workers” and “other workers”.

Non-regular workers is defined as any group that falls into a category other than “regular workers”.

← 2. Differences between Japan and other countries included in Figure 1.5 could partially reflect the fact that the Japanese occupational data underlying this figure use a very different occupational classification than the International Standard Classification of Occupations (ISCO), making the correspondence with ISCO rather loose. The Japanese occupation group of Transport and Communication Workers, for example, is classified as middle-skill, while it combines jobs that would fall under ISCO group 3 (i.e. technicians and associate professionals, high-skill) and 7 (i.e. plant and machine operators and assemblers, middle-skill).

← 3. Differences in automation probability between countries are due to differences in the composition of occupational structure and differences in the job content (i.e. whether workers carry out less automatable task, such as planning other workers’ activities, influencing people and solving problems, even within the same occupation). Japan employs more workers in occupations that have a relatively high risk of automation than in many other OECD countries. This is consistent with the less pronounced pattern of job polarisation in Japan, which shows that the decline in routine-intensive employment has been relatively modest.

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