Chapter 1. A portrait of adult learning participation in Australia

This chapter discusses global trends that are changing job content and skills requirements. It provides a brief comparative snapshot of how well Australia performs on various priorities of adult learning systems, with a focus on trends in the participation of individuals and provision by employers. It identifies groups of adults who have difficulties accessing training and who may have a harder time adapting to changes in skills demand, as well as firms that have difficulties providing training. Finally, the chapter provides an overview of the financial incentives that Australia has in place to promote participation in adult learning.

    

The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.

1.1. Key findings

As demand for skills continues to change under the combined pressures of globalisation, technological change and population ageing, adult learning systems need to adapt. Labour markets in all countries are expected to experience significant structural change, leading to a re-allocation of labour from declining sectors and occupations to emerging ones. The skills profiles needed for existing jobs are also expected to change. To remain employable over longer working lives, adults need accessible and affordable opportunities to upgrade their skills or to retrain to acquire new skills.

A strong system of adult learning is needed in Australia in order to position firms and workers to succeed in the context of these changes. This report focuses on adult learning that is structured (i.e. formal or non-formal learning, Box 1.1) and job-related, i.e. expected to have an effect on performance and productivity at work, or to help adults successfully transition to new employment.

Box 1.1. Defining adult learning

This report focuses on the population of potential adult learners aged 25-64. Adults in this target age group have generally completed initial education and have begun their working lives.

There are three types of adult learning: formal, non-formal and informal. According to Eurostat’s classification, the key criterion distinguishing formal or non-formal learning from informal learning is that it is institutionalised. This report will focus on participation in formal (accredited) and non-formal (unaccredited) learning.

Figure 1.1. Scope of education and training
Figure 1.1. Scope of education and training

Informal learning: non-institutionalised learning activities which are not structured (e.g. no student/teacher interaction) and can take place anywhere, e.g. learning while doing.

Non-formal education (unaccredited training): institutionalised learning activities (e.g. seminars, courses, on-the-job training, open and distance education) which are either of short duration (less than one semester of full-time equivalent) or are not recognised by the relevant education or equivalent authorities.

Formal education (accredited training): institutionalised learning activities which are a minimum of one semester and which are recognised as programmes by the relevant education or equivalent authorities.

Source: Eurostat (2016[1]), Classification of Learning Activities Manual, http://dx.doi.org/10.2785/874604.

The key findings of this chapter include:

  • The OECD Priorities for Adult Learning (PAL) dashboard highlights strong performance for Australia in the areas of coverage and alignment of training content with labour market needs. However, strong performance on coverage is based on cross-country comparative data from the 2012 OECD Survey of Adult Skills (PIAAC). Since the time of the survey, national data sources indicate that participation in adult learning has declined by as much as six percentage points. Declines appear to be concentrated in job-related non-formal learning.

  • Evidence from the Household Income and Labour Dynamics in Australia (HILDA) survey suggests that some groups have below-average participation (average is 31%) in job-related adult learning: low-educated workers, own-account workers, casual workers, and workers in small and medium-sized enterprises (SMEs). These relationships hold even when controlling for differences in socio-demographic characteristics between groups. The gap between the training participation rate of older and younger workers nearly closed between 2007 and 2017 due to a simultaneous decline in the participation of younger workers and a rise in the participation of older workers.

  • Only 26% of workers in jobs at high risk of automation participated in training in 2017 [OECD calculations using the HILDA survey based on Edmonds and Bradley (2015[2]) classification of occupations at risk of automation]. Workers in occupations with a low risk of automation, including managers, professionals, and information and communications technology technicians, are generally more likely to train than workers in occupations with a high risk of automation, including food preparation assistants; agricultural, forestry and fishery labourers; and cleaners and helpers.

  • Employer provision of both accredited and unaccredited training has declined over the 2005-2017 period, likely due in part to declines in financial incentives aimed at employers. A rising share of employers report that their employees are engaged in informal learning.

  • Several financial incentives are available to support adult learners, including subsidies, income-contingent loans and a tax incentive. Altogether, public financial support for adult learning amounts to about AUS 7.5 billion (Australian dollars) per year (0.4% of GDP), which represents a high public investment in adult learning by international standards. Additional public support also comes from states and territories and employment services.

The chapter is structured as follows. Section 1.2 sets the context by discussing how global trends are changing demand for skills. Section 1.3 provides a comparative snapshot of Australia’s adult learning system, with particular emphasis on recent trends in the participation of adults and provision by employers. It identifies groups of adults who have low participation in adult learning and who may have a harder time adapting to changing skills demand as a result. Section 1.4 summarises the financial incentives that Australia currently has in place to promote adult learning.

1.2. Introduction

As demand for skills continues to change under the combined pressures of globalisation, technological change and population ageing, adult learning systems need to adapt. All OECD countries face these challenges to varying degrees.

Technological change has had a profound impact on Australia’s labour market over the last decades. Technological progress raises demand for skills and knowledge which complement new technologies, including cognitive and soft skills, and at the same time reduces the demand for human labour to perform routine tasks, as these tasks can be more easily codified and therefore performed more cheaply by machines and computers. Recent Australian analysis tracks a steady decline in the demand for labour to perform routine tasks since the late-1980s, along with a rise in demand for labour to perform abstract tasks (Borland and Coelli, 2017[3]; Deloitte Insights, 2019[4]). OECD analysis estimates that 11% of Australian jobs face a high risk of automation, while another 25% are likely to be affected by significant changes in task content (Figure 1.2). Altogether 36% of Australian jobs face a significant risk of automation, which is less than the OECD average (45%), but represents a sizeable share of the adult population who will need to upskill or retrain to remain employable. Australian research (Edmonds and Bradley, 2015[2]) has found that over the last decade the susceptibility of automation in Australia has decreased as highly susceptible jobs have become automated. A decomposition analysis concludes that for the most part, this decline is due to Australian industries having reduced the share of jobs performing routine tasks, while increasing the share of jobs performing cognitive, interpersonal or problem-solving tasks (Edmonds and Bradley, 2015[2]). At the same time, employment in Australia has also shifted away from industries that have a high risk of automation (historically manufacturing) and towards those where technology is less likely to replace workers, including education, professional and health care services.

Figure 1.2. Risk of automation
% of workers facing significant (50-70% of tasks) or high (70%+) risk of automation
Figure 1.2. Risk of automation

Note: Belgium refers to Flanders only, United Kingdom to England and Northern Ireland.

Source: Nedelkoska and Quintini (2018[5]) “Automation, skills use and training.”

Population ageing is also putting pressure on Australia’s adult learning system by increasing the need for workers to upskill or retrain over longer working lives, by contributing to skills and labour shortages due to the retirement of large cohorts, and by changing the demand for goods and services (OECD, 2019[6]). The share of the population age 65+ is projected to increase from 23% to 37% in Australia between 2015 and 2050; a non-trivial increase, but less than in other countries (71% of the Japanese population is projected to be over the age of 65 by 2050).

Australia is a strong commodity exporter, but less exposed to international trade than many OECD countries (the sum of exports and imports as a percentage of GDP is one of the lowest across OECD countries). Australia is therefore affected by changes in skills demand that come from greater integration in global value chains – such as growing demand for high-level skills needed to specialise in high-tech manufacturing industries and complex business services – though less so compared to other countries.

These dynamics have contributed to the current shortages and surpluses observed in Australia (OECD, 2018[7]). The OECD Skills for Jobs database identifies shortages for Australia in education and training, health services, and mathematics and sciences, as well as transversal skills like verbal and reasoning abilities and basic literacy and numeracy skills (Figure 1.3). At the same time, surpluses are observed in knowledge related to manufacturing and production, as well as physical abilities like fine manipulative abilities, control movement and physical strength. Figure 1.4 shows that many of the occupations facing a high risk of automation in the Australian labour market (including plant and machine operators, cleaners and helpers, and labourers) also tend to show signs of surplus (lower wage and employment growth than the national average, lower levels of hours worked, and higher unemployment rate growth).

Figure 1.3. Skills shortages and skills surpluses, Australia, 2016
Skills Needs Indicator
Figure 1.3. Skills shortages and skills surpluses, Australia, 2016

Note: Positive values indicate shortages while negative values indicate surpluses. The indicator is a composite of five sub-indices: wage growth, employment growth, growth in hours worked, unemployment rate and growth in under-qualification.

Source: OECD Skills for Jobs (database), www.oecdskillsforjobsdatabase.org.

Figure 1.4. Correlation between risk of automation and skills needs, Australia, 2016
Figure 1.4. Correlation between risk of automation and skills needs, Australia, 2016

Note: For the skills needs indicator, positive values indicate shortages and negative values indicate surpluses. Occupations are represented by 2-digit ISCO code (see Table 1.1 for legend). The R2 (the percentage of the variance in the risk of automation between occupations that can be explained by the variance in the Skills Needs indicator values) is 0.16.

Source: OECD Skills for Jobs (database), https://www.oecdskillsforjobsdatabase.org/; Nedelkoska and Quintini (2018[5]), “Automation, skills use and training”.

Table 1.1. Occupations (2-digit ISCO code) by risk of automation
Ranked according to share of jobs in the occupation with risk of high or significant change in task content

Fewer than 25% of jobs

25-50% of jobs

Over 50% of jobs

11

Chief executives, senior officials & legislators

54

Protective services workers

44

Other clerical support workers

23

Teaching professionals

53

Personal care workers

75

Food processing, wood working, other craft & trades workers

13

Production & specialised serv. managers

74

Electrical & electronic trades workers

96

Refuse workers & other elementary workers

12

Admin. & commercial managers

31

Science & engineering associate prof.

73

Handicraft & printing workers

14

Hospitality, retail & other serv. managers

51

Personal service workers

93

Agricultural, forestry & fishery labourers

22

Health professionals

52

Sales workers

93

Labourers in mining, construction, manufact. & transport

24

Business & admin. professionals

42

Customer services clerks

41

General and keyboard clerks

26

Legal, social & cultural professionals

71

Building & related trades workers, excl. electricians

83

Drivers and mobile plant operators

21

Science & engineering prof.

72

Metal, machinery & related trades workers

94

Food preparation assistants

35

ICT technicians

43

Numerical & material recording clerks

81

Stationary plant & machine operators

34

Legal, social, cultural & related associate prof.

61

Market-oriented skilled agricultural workers

91

Cleaners & helpers

25

ICT professionals

 

 

33

Business & admin. associate prof.

 

 

32

Health associate professionals

Source: Nedelkoska and Quintini (2018[5]), “Automation, skills use and training”.

In this context, the Australian labour market requires skilled individuals who can perform the available jobs. However, according to the OECD Survey of Adult Skills, 24% of Australian workers report that they need more training to do their current tasks. Furthermore, nearly 22% of adults in Australia have low literacy and/or numeracy proficiency (at Level 0 or 1), and 22% have low problem-solving skills in technology-rich environments. According to the Australian Industry Group survey, 39% of employers report that their businesses were highly affected by low levels of literacy and numeracy among their employees1.

Australia requires a strong system of adult learning in order to position firms and workers to succeed in the context of technological change, globalisation and population ageing. This implies an adult learning system that is well-financed, can be aligned with labour market needs, and which affords opportunities for all adults to continuously acquire and upgrade their skills throughout their working lives.

1.3. Current performance

The OECD Priorities for Adult Learning dashboard (PAL) allows countries to benchmark themselves along seven dimensions of future-readiness of adult learning systems (Figure 1.5). According to the PAL, Australia performs relatively well in the area of aligning training with labour market needs. As highlighted in (OECD, 2018[7]), Australia is a leader in the variety of skill assessment and anticipation exercises it carries out, and also in how it uses the information from these exercises to inform policy, including training policy. While Australia performed above the OECD average in terms of coverage at the time of the 2012 Survey of Adult Skills, national data sources (Household Income and Labour Dynamics in Australia [HILDA] survey and the Australian Bureau of Statistic’s Work-Related Training and Adult Learning [WRTAL] survey) suggest that overall participation has decreased in recent years, as will be discussed in more detail in this section.

Australia is in the middle of the pack in several dimensions, including self-reported impact, i.e. the impact that training has had on the employment and career opportunities of the adults concerned; and inclusiveness, having relatively modest differences in participation between groups such as men and women, low-wage and medium/high-wage workers, unemployed and employed workers. Australia also performs close to the OECD average on the financing indicator. Cost is an important barrier to training for adults in Australia: 18% of adults report cost to be a barrier relative to 16% across OECD countries. Section 1.4 will provide an overview of Australia’s current set of financial incentives to support adult learning, and Chapter 2 will share experiences with financial incentives used in other countries which could be instructive for Australia.

Australia falls behind the OECD in flexibility and guidance, a measure of whether adults have access to guidance about learning opportunities and whether learning opportunities are available in flexible formats. Availability of career guidance and flexible learning opportunities will be discussed as part of the framework conditions necessary for financial incentives to function effectively in Chapter 3.

Figure 1.5. Priorities for Adult Learning dashboard, Australia
Figure 1.5. Priorities for Adult Learning dashboard, Australia

Note: The seven dimensions of the dashboard aggregate multiple indicators. Indicator scores are normalised (min-max) for the aggregation and the aggregate scores are therefore the relative performance of countries.

Source: OECD Priorities for Adult Learning dashboard (http://www.oecd.org/employment/skills-and-work/adult-learning/dashboard.htm).

1.3.1. Participation in adult learning

For a future of work that is both productive and inclusive, broad-based coverage of adult learning is necessary. To assess trends in participation in adult learning, this report will draw upon four sources of data. First, the 2012 OECD Survey of Adult Skills (PIAAC) provides international comparative data on adult participation in learning activities. Second, the Household Income and Labour Dynamics in Australia (HILDA) survey is a longitudinal survey of Australian households which has collected data on participation in work-related training annually since 2007. Third, the Australian Bureau of Statistics’ Work-Related Training and Adult Learning (WRTAL) survey provides data on participation in formal, non-formal and work-related non-formal learning and was conducted in 2013 and 20172. Fourth, annual programme enrolment statistics from higher education (HE) and vocational educational and training (VET) are also used.

According to PIAAC, 49% of adults participated in job-related adult learning in Australia in 2012, above the OECD average of 40%. Training intensity is also higher than in other countries, with a median of 36 hours per year compared to 30.5 hours in OECD countries.

Figure 1.6. Participation in formal or non-formal job-related training, adults aged 25-64, OECD countries, 2012/2015
Share of adults aged 25-64 who participated in formal or non-formal job-related training over the previous 12 months
Figure 1.6. Participation in formal or non-formal job-related training, adults aged 25-64, OECD countries, 2012/2015

Note: Data refer to 2012 for most countries, except Chile, Greece, Israel, Lithuania, New Zealand, Slovenia and Turkey where they refer to 2015.

Source: OECD Survey of Adult Skills (PIAAC).

That being said, participation has declined considerably in the past decade, based on national data sources. While not directly comparable to the PIAAC measure as only employed workers are polled regarding their participation in job-related adult learning, Figure 1.7 (Panel A) shows that according to the HILDA survey, the share of employed adults participating in job-related training (formal or non-formal) declined from 35% in 2008 to 31% in 20173. Training intensity also declined, with a median of 24 hours in 2017 compared with 28 hours in 2007.

Similar declines are observed from the WRTAL survey, produced by the Australian Bureau of Statistics (ABS), which polls all adults about their training behaviour (not only employed adults, as in HILDA). The share of adults who participated in formal or non-formal learning declined from 43% in 2013 to 37% in 2017 (Figure 1.7, Panel B). This six percentage point decline is almost entirely due to a drop in participation in non-formal learning, and in particular, to a drop in job-related non-formal learning. Participation in formal training remained stable at 13% of the adult population.

But while the share of adults who report participating in formal training remained stable since 2013 according to the WRTAL, enrolment in formal training declined by two percentage points over this period (from 11% of adults aged 25 to 64 to 9%) (Figure 1.8). Enrolment in HE increased modestly since 2008, supported by Australia’s shift in 2012 (until 2017) to a demand-driven system in HE (during which the Australian Government removed caps on its financial support for most domestic undergraduate students). However, VET enrolment declined since 2012 (Figure 1.8). Declines in VET enrolment may be tied in part to tightening of rules in 2012 and 2013 in the use of employer apprenticeship incentives (see Section 1.4.2 for more details), which led to a drop in non-trade apprenticeship starts.

Overall, these trends suggest that while Australia had above-average performance in terms of adult learning coverage in 2012 at the time of the PIAAC survey, this may no longer be the case. Declining participation in adult learning runs opposite to the general increase in participation observed across OECD countries (OECD, 2019[6]). With fewer and fewer Australian adults taking part in adult learning, particularly in job-related non-formal learning, actions are needed to boost participation and reverse these trends.

Figure 1.7. Declining participation in job-related training
Figure 1.7. Declining participation in job-related training

Note: Panel A: Share of employed adults aged 25-64 who participated in formal or non-formal job-related training over the past 12 months. Panel B: Share of adults aged 25-64 who participated in training over the past 12 months.

Source: Panel A: OECD calculations based on the Household Income and Labour Dynamics in Australia (HILDA) survey. Panel B: OECD calculations based on the ABS’ Work-Related Training and Adult Learning (WRTAL) survey.

Figure 1.8. Declining enrolment in formal training
Share of population 25-64 enrolled in formal training by programme type
Figure 1.8. Declining enrolment in formal training

Source: DET, Higher Education Statistics collection, unpublished (accessed 18 June 2019); NCVER, VOCSTATS, Government-funded VET program enrolments 2003-2017 (accessed 18 June 2019); NCVER Apprentice and trainee collection, December quarter 2018.

1.3.2. Under-represented groups

Declining participation may exacerbate gaps in coverage between those with high and low participation rates. Several groups who are under-represented in training participation are also those who are most vulnerable to changing skills demand.

The OECD’s Employment Outlook (2019[8])notes that while changes in skills requirements due to technological change have the potential to affect all workers, the growing demand for high-level cognitive skills and complex social interaction skills suggest that low-skilled workers in jobs that are intensive in repetitive or manual task are likely to bear the brunt of these changes. But while low-skilled workers arguably have a greater need for upskilling opportunities, they tend to receive less training than higher-skilled workers. Employers favour investing in higher-skilled workers when it comes to training, expecting the return to be higher. Older workers, too, are likely to experience significant skills obsolescence, particularly in the context of technological change, unless they upgrade the skills they acquired in initial education. Given the shorter period of time that older workers have to recoup this investment before retirement, they also tend to receive less training than younger workers.

Casual workers, own-account workers, those in part-time work or with temporary contracts are potentially vulnerable groups who face challenges in maintaining and upgrading their skills. As training is often provided by employers, workers with less attachment to the labour market have more difficulty accessing it. Some OECD countries have seen a rise in non-standard contractual working arrangements in recent years, and in Australia, the share of adult workers (age 25-64) in at least one of these types of contractual arrangements increased from 42% of total employment in 2007 to 43% in 2017 (Table 1.2). The share of temporary work (fixed-term contracts) in employment increased (from 8% to 9% between 2007 and 2017), and the share of part-time work in employment increased by half of a percentage point to 27.5%. There has been a rise in part-time work among those who would prefer to work full-time: involuntary part-time employment increased from 7% to 9% of employment over this period (OECD, 2019[9]). The share of casual employees – those who receive a “loading” on their wage in compensation for a lack of leave entitlements, including paid holiday and sick leave, redundancy pay and notice of termination – was stable over this period. Gilfillan (2018[10]) documents a steep rise in casual work in Australia from the mid-1980s to early-1990s before it levelled out. The share of own account workers – self-employed workers with no employees, including gig or platform workers–declined from 8% to 7% over this period. While the share of own account workers includes those in gig or platform work, it does not capture those who use platform work to complement their primary job and may therefore underestimate the extent of such work in the Australian labour market (OECD, 2019[11]).

Table 1.2. Share of non-standard working arrangements in total employment
Share of employment, aged 25-64, 2007 and 2017

 

2007

2017

 

%

%

Part-time workers

27.0

27.5

Casual workers

12.5

12.8

Fixed-term contract

7.6

8.8

Own-account workers

8.2

7.2

Workers who are part of at least one of the above groups

41.8

43.3

Note: Due to overlap between groups, the rows do not add up to the total.

Source: OECD calculations based on the HILDA survey.

Figure 1.9. Participation in formal or non-formal job-related training by group
Share of employed adults (25-64)* in each group, 2017**
Figure 1.9. Participation in formal or non-formal job-related training by group

Note: Ranked in order of the gap in participation rates between groups. Share of employed adults who participated in formal or non-formal job-related training over the previous 12 months.

*The exception is the comparison based on labour force status, which includes unemployed adults. **Data for risk of automation and labour demand are for 2016.

Source: OECD calculations based on the HILDA survey; Skills for Jobs database (labour demand); the ABS’ WRTAL survey (labour force status); and risk of automation as computed by Edmonds and Bradley (2015[2]).

An overview of differences in participation rates across groups is provided in Figure 1.9. The largest differences are observed between full-time permanent workers and own-account self-employed workers and between highly-educated and low-educated workers. Casual workers also have much lower training participation than full-time permanent workers, and workers in SMEs train less than workers in large firms. Employed workers on fixed-term temporary contracts have comparable (even slightly higher) training participation rates to workers with full-time permanent contracts.

As of 2017, young and older employed workers in Australia have similar participation rates, unlike in most OECD countries where older workers receive less training. The gap between young and older employed workers has declined since 2007 when young workers were eight percentage points more likely to participate in adult learning. The gap closed due to a simultaneous decline in the participation of younger workers (2.8 percentage points) and a rise in the participation of older workers (3.3 percentage points).

As the HILDA survey only polls employed workers about their training behaviour, it is necessary to consult the ABS’ WRTAL survey to understand differences in training participation between the employed and unemployed. Figure 1.9 shows that unemployed workers are far less likely to participate in work-related training (for the unemployed, this might include training in employability skills or skills related to a particular occupation) than employed workers (21 percentage points less).

Australia is one of the only OECD countries where workers in surplus occupations train more than workers in shortage occupations. Australia’s policies to intervene early to retrain displaced workers in declining industries may have contributed to this positive outcome. On the other hand, workers in occupations with a high risk of automation [based on the calculation by Edmonds and Bradley (2015[2])] train less than those with a low risk of automation. Only 26% of workers in occupations with a high risk of automation participated in job-related training in 2017, compared with 40% of workers in occupations with a low risk of automation. This suggests that workers in occupations with a high risk of automation may be vulnerable to poorer employment prospects and lower wages in the future unless they retrain.

Many of the groups in Figure 1.9 are overlapping. Running a pooled cross-sectional regression using HILDA data of participation in job-related training from 2007 to 2017 on a set of individual, job and firm characteristics provides a way of isolating the effect of each characteristic. Even when controlling for individual, job and firm characteristics, there is a negative time trend on the probability of participating in job-related training which amounts to a total decline of 2.1 percentage points over the 10-year period (Table 1.3, Column 2). This is a larger decline than the one registered in the descriptive statistics, suggesting that declining participation in adult learning cannot be explained by compositional changes in individual or job characteristics. Instead, external conditions in the labour market or policy changes are more likely the cause of the decline. Given the rise in unemployment over this period, employers may have taken advantage of looser labour market conditions to recruit external candidates with needed skills, rather than train existing employees. Higher unemployment goes hand in hand with reduced consumer demand, which may constrain the ability of employers to invest in training.

The regression results presented in Table 1.3 confirm many of the descriptive relationships highlighted in Figure 1.9. Casual workers, own-account workers, and those in part-time work or with temporary contracts receive significantly less training than employees with a permanent contract, even after controlling for other characteristics. Educational attainment also increases the likelihood of participating in training for adults. Employed workers in large firms train significantly more than workers in SMEs. This represents a real challenge in Australia where 68% of all Australian employees work in firms with fewer than 250 employees (OECD, 2019[12]), the highest share of SME employment across OECD countries, along with Greece.

Women are more likely to participate in job-related training than men, but this gap disappears when industry, occupation, and region differences are accounted for. Similarly, being married and being born in Australia both increase one’s likelihood of participating in job-related training, but these effects are no longer significant once region, occupation and industry controls are included. Occupations with a low risk of automation (including managers, professionals, and information and communications technology technicians) train significantly more than workers in occupations with a high risk of automation (including food preparation assistants; agricultural, forestry and fishery labourers; and cleaners and helpers). Workers in the manufacturing industry are significantly less likely to receive job-related training than workers in most other industries.

Table 1.3. Probability of participating in training, by socio-demographic characteristics
Marginal effects from probit regression

 

Participation in job-related training

Participation in job-related training

Participation in formal training

 

Employed population, 25-64

Employed population, 25-64

Employed population, 25-64

 

2007-2017

2007-2017

2007-2017

 

Marginal effect

p-value

Marginal effect

p-value

Marginal effect

p-value

Year

-0.027

***

-0.021

***

-0.011

***

Female

0.166

***

-0.016

 

-0.018

 

Age

-0.001

 

-0.001

 

-0.022

***

Married

0.051

***

0.004

 

-0.098

***

With dependent children

0.019

 

0.016

 

-0.070

***

Non-native

-0.149

***

-0.035

 

0.017

 

Education (years)

0.041

***

0.018

***

0.012

***

Firm size (ref=1 employee)

 

 

 

 

 

 

2-19

0.105

 

0.128

*

-0.087

 

20 - 199

0.374

***

0.294

***

-0.038

 

200 +

0.466

***

0.357

***

-0.001

 

Part-time job

-0.145

***

-0.226

***

0.092

***

Contract type (ref=permanent contract)

 

 

 

 

 

Fixed-term contract

0.020

 

-0.065

*

0.035

 

Casual

-0.338

***

-0.295

***

0.084

**

Other

-0.099

 

-0.109

 

0.001

 

Own account worker

-0.405

***

-0.321

***

-0.062

 

Self-employed with employees

-0.507

***

-0.430

***

-0.210

***

Tenure (years)

0.003

**

-0.002

 

-0.014

***

Region dummies

No

 

Yes

 

Yes

 

Industry dummies

No

 

Yes

 

Yes

 

Occupation dummies

No

 

Yes

 

Yes

 

Observations

65592

 

64972

 

77641

 

Psuedo R2

0.051

 

0.109

 

0.075

 

Note: For the first two panels, the dependent variable takes a value of 1 if the employed worker participated in job-related training (formal or non-formal) over the past 12 months, and 0 otherwise. In the third panel, the dependent variable takes a value of 1 if the employed worker participated in formal training (job-related or not) over the past 12 months, and 0 otherwise. Occupation dummies are at 2-digit ISCO, and industry dummies are at 1-digit ANZSIC. *** p<0.001 ** p<0.01 * p<0.05.

Source: OECD calculations based on the HILDA survey.

Participation trends vary depending on the type of training in question. Fialho, Quintini and Vandeweyer (2019[13]) find opposite relationships between contract type and non-formal training versus contract type and formal training. In particular, fixed term and temporary agency workers are less likely to receive non-formal training but more likely to receive formal training than their counterparts with permanent contracts. The job-related training variable in the HILDA includes both formal and non-formal training, and it is not possible to separate these two. However, a different variable asks respondents whether they participated in formal training (job-related or not). The final column of Table 1.3 restricts the analysis to formal training, controlling for the same individual, job, and firm characteristics as before. There is no significant relationship between fixed term contract and own-account workers and the likelihood of participating in formal training. On the other hand, while part-time and casual workers participate less in job-related training (formal or non-formal), they tend to participate more in formal training than their full-time permanent counterparts. Pursuing full formal qualifications is not easily compatible with working full-time, likely explaining these differences.

Age is also a much more important factor in predicting participation in formal training than job-related (formal or non-formal) training: older adults and those with longer tenure are significantly less likely to participate in formal training than younger adults and those with less work experience, probably due to the reluctance of older workers to return to learning in a classroom setting. This is despite evidence (Coelli and Tabasso, 2015[14]) showing that older workers (age 40 to 54) have similar labour market outcomes (employment, hours, wage rates) from formal training as younger adults.

1.3.3. Employer provision

Employer provision of adult learning influences its coverage and inclusiveness. PIAAC finds that 78% of adult learning participants received funding from their employer for at least one learning activity in the previous 12 months. This is in line with the OECD average but 10 percentage points below top-performing countries such as the Netherlands, France or Denmark (Figure 1.10).

Figure 1.10. Share of participants who received funding from their employer for at least one learning activity in the last 12 months
Figure 1.10. Share of participants who received funding from their employer for at least one learning activity in the last 12 months

Source: OECD Survey of Adult Skills (PIAAC).

The National Centre for Vocational Education and Research (NCVER) Survey of Employer Use and Views (SEUV) polls employers about their use of VET (the survey does not ask about their use of HE). According to SEUV, the share of firms providing VET or unaccredited training has declined since 2005 (Figure 1.11). Meanwhile the share of firms reporting that their employees are engaged in informal learning has increased, suggesting that employees are turning to informal opportunities to compensate for declining employer provision of structured training. New digital and online tools, including massive open online courses (MOOCs), have likely facilitated this rise in informal learning. While not asked why they stopped using structured training, employers reported a decline in satisfaction with unaccredited training between 2007 and 2017. Employer satisfaction with nationally-recognised accredited training remained stable over this period.

Still, the main strategy which employers report using to address skills gaps is training existing staff (87% of employers), followed by recruitment of new staff (57%) and internal reorganisation (57%). Similarly, using a less representative sample of mainly large firms, the Workforce Development Needs Survey (AIG, 2018[15]) finds that retraining existing staff on the job is the strategy favoured by most employers (68%) followed by employing experienced employees (64%). This stated preference for training existing staff stands in contrast to employer practices reported in Europe’s Continuous Vocational Training Survey (CVTS): among employers that did not train, over 50% reported a preference for recruiting over training existing employees.

Figure 1.11. Employer provision of training, 2005, 2007, 2013, 2017
Share of firms providing training, by type of vocational education or training
Figure 1.11. Employer provision of training, 2005, 2007, 2013, 2017

Source: NCVER, Survey of Employer Use and Views (database).

As shown in the regression results in Table 1.3, firm size is a strong predictor of participation in job-related learning. Findings from the SEUV confirm that for every type of training, small firms are less likely to provide training than large firms. This gap is largest for unaccredited training (42 percentage points lower), followed by VET (38 percentage points lower), and then informal learning (19 percentage points lower). These gaps reduced between 2015 and 2017 but remain substantial.

Declining employer provision of VET and unaccredited training may be tied in part to reductions in financial incentives, including the removal in 2012 and 2013 of incentives under the Australian Apprenticeships Incentives programme for certain apprentices and trainees4, and the 2016 closure of the Industry Skills Fund. External conditions in the labour market or other policy changes may also have played a role.

1.4. Existing financial incentives for promoting adult learning in Australia

Financial incentives have an important role to play as they can promote participation in adult learning when training cost is a barrier, and can also help to overcome time constraints by compensating the opportunity costs of training. If designed with some degree of co-funding they can encourage individuals and employers to financially contribute to the system and achieve a sustainable mix of contributions from the government, employers, and individuals. Finally, when appropriately targeted or differentiated, they can help steer training towards occupations and skills that are in demand on the labour market.

This section provides a brief description of the overall governance of the adult learning system in Australia and then summarises the existing financial incentives for encouraging participation in adult learning.

1.4.1. Governance and public investment in adult learning in Australia

Adult learning systems tend to be complex as they encompass programmes designed to pursue a variety of policy objectives and reach different target groups, such as basic skills courses for the low-skilled, second chance programmes for adults who did not complete initial education, professional training for workers, training for the unemployed, or language classes for migrants (OECD, 2019[6]). As a result, responsibility for adult learning policy is often split across several ministries, levels of government, and other actors (e.g. social partners, training providers, non-governmental organisations). Often the different actors do not perceive themselves as being part of a joint adult learning system, in view of their separate objectives, responsibilities, and budgets.

This complexity is reflected in Australia’s adult learning system. It consists of a school sector that includes public and private schools, an HE sector consisting of mostly public universities, and a VET sector that includes many private providers and a small number of large public providers (Technical and Further Education, TAFE) (Keating, 2004[16]). While HE is generally funded and administered by the national government, VET is generally administered by the states and territories, but funding is shared between the national, state and territory governments. In 2017, state and territory governments contributed AUS 3.3 billion (52% of total funding) to VET, while the national government contributed the remaining 3.0 billion (48% of total funding) (NCVER, 2019[17]). The Australian Government also provided AUS 756 million in loans for VET in 2017 (NCVER, 2019[17]). Provision and financial support for adult learning in VET varies by state and territory. This federated approach has the advantage that policies and programmes can be targeted to the needs of learners in the state or territory. The disadvantage is that programmes and policies differ across the country, which can lead to inequities in adult learning opportunities.

Non-formal adult education is provided by an array of bodies. Most employers providing or paying for unaccredited training for their employees choose to perform such training in-house (54.5% did not use an external training provider in 2017, according to the SEUV). Of those employers who did opt to use external training providers, 41% used a private training provider, 29% used a professional or industry association, 22% used a supplier or manufacturer, 6% used other providers, and only 3% used a TAFE.

The National Foundation Skills Strategy for Adults was launched in September 2012 and is a collaborative ten-year framework to build foundation skills (language, literacy, numeracy, and employability skills) for adults over 2012-2022. All Australian governments have committed to an aspirational target that by 2022, 66% of working age Australians will have literacy and numeracy skills at Level 3 or above (this is relative to the 2012 OECD Survey of Adult Skills benchmark, with 56% of working-age Australians at Level 3 literacy or above, and 46% at Level 3 numeracy or above). There is no funding specifically attached to this agreement. The adult learning sector (also called “ACE”, adult community education) provides adult basic education programmes in language, literacy and numeracy skills to low-skilled adults but ACE does not receive national funding and is funded to varying degrees by states and territories. Migrants are eligible for subsidised training in language and literacy skills through the nationally-funded Australian Migrant Education Programme (AMEP). The national government used to subsidise language and literacy skills training in the workplace (Workplace English Language and Literacy, WELL) but closed this programme in 2014 (NCVER, 2018[18]). Job seekers are eligible for subsidised accredited language, literacy and numeracy training through the Skills for Education and Employment programme.

Job seekers registered with the Australian Government’s mainstream employment service, ‘jobactive’, also have access to funding for learning opportunities through the Employment Fund and other subsidised training programmes. Depending on individual circumstances and needs, jobactive providers can use the Employment Fund to help build a participant’s skills and experience and improve their chances of finding and retaining work. This includes providing access to accredited training, employer-required unaccredited training (where this is a job requirement), or unaccredited training to address employability and foundation skills.

Public investment for adult learning in Australia is above average. Total funding for adult learning is estimated to amount to AUS 7.5 billion (0.4% of GDP) though this estimate does not include support which varies by states and territories, nor support for training via employment services (Table 1.4). Due to the cross-cutting nature of the adult learning sector, national spending on adult learning is not accounted for under a single budget line, but usually across a range of budget lines (Andriescu et al., 2019[19]). The complex nature of governance and funding of adult learning precludes consistent and direct comparisons across countries. A European Commission study (FiBS and DIE, 2013[20]) provides the most comprehensive comparative data on funding for adult learning available. It finds that in most countries, the public sector investment in adult learning equates to 0.1% of national GDP. Australia, at 0.4% of GDP, stands with Scandinavian countries like Denmark (0.4%), Norway (0.6%) and Sweden (0.5%) which have above average public investment in adult learning.

Table 1.4. Annual public investment in adult learning in Australia

 

Share of 25-64 year olds

Total spending (AUS millions)

Prorated amount allocated to 25-64 year olds (AUS millions)

VET loans and subsidies

54%

5 914

3 194

Loans

756

408

Subsidies 1

5 158

2 785

HE loans and subsidies

27%

12 466

3 366

Loans 2

5 473

1 478

Subsidies 3

6 993

1 888

Tax incentive 4

80%

1 200

960

Total

 

 

7 519

Notes: This table does not include state or territory-specific support for adult learning or financial support for employment services. Loans do not take into account loan costs. Adults aged 25-64 represented 54% of enrolments in government-funded VET in 2018 (NCVER, 2019[21]). Adults aged 25 and older represented 27% of domestic students enrolled in undergraduate courses in 2016 (Department of Education, 2017[22]).

1 Includes both government grants and general programme funding.

2 Based on 2017 Higher Education Finance Statistics report.

3 Includes government subsidies for university places in the Commonwealth Grant Scheme in 2017-18, based on the Portfolio Budget Statement for Department of Education and Training.

4 Can be applied towards formal training either in VET or HE.

Source: NCVER (2019[17]), Government funding of VET 2017; Productivity Commission (2019[23]), Report on Government Services; Australian Taxation Office, Taxation statistics 2014-15 Individuals: Selected items for 1978-79 to 2014-15 income years (database).

1.4.2. Existing financial incentives

The national and state and territory governments in Australia currently provide financial incentives to individuals and employers to engage in adult learning via subsidies, loans, and tax incentives. This section will discuss each of these briefly, and Table 1.6 summarises the financial incentives currently in place in Australia to promote adult learning.

Subsidies

Subsidies are the most common type of financial incentive used in Australia to promote adult learning. Provided they meet eligibility requirements and study with an approved provider, most domestic undergraduate HE and VET students benefit from government subsidies. The states and territories are responsible for setting and providing the subsidy rates in VET qualifications, while the Australian Government sets the subsidy rates in HE for the Commonwealth Grant Scheme. Subsidy rates vary by discipline. For example, in 2019 the average subsidy rate for a national government-supported place in HE was 58% (AUS 13 363), but ranged from 72% in agriculture (AUS 23 590) to only 16% in law, accounting, commerce, economics, and administration (AUS 2 160) (DET, 2018[24]).

Employers can access subsidies to offset wages and other costs associated with apprenticeships through the Australian Apprenticeships Incentives programme. Employer incentives are designed to support completion of apprenticeships and traineeships (i.e. non-trade apprenticeships) and range in value from AUS 750 to AUS 4 000 per apprentice (Atkinson and Stanwick, 2016[25]). An econometric evaluation of the programme commissioned by the Australian Government found that employer incentive payments resulted in an increase in commencements of apprenticeships, but also a decrease in the probability of completing (Deloitte Access Economics, 2012[26]). The government reformed the system in 2012: commencement incentives for existing worker apprenticeships and traineeships not on the National Skills Needs List (NSNL), in other priority occupations, or those working part-time, were removed (NCVER, 2018[18]). In 2013, completion incentives for existing apprenticeships and traineeships not on the NSNL were also removed. All occupations on the NSNL are trade occupations. Apprentice and trainee starts in non-trade occupations declined significantly since 2012, including for 25-64 year olds (Hargreaves, Stanwick and Skujins, 2017[27]), and this decline has been linked to reductions in employer incentives (Atkinson and Stanwick, 2016[25]).

National subsidies for training are offered for vulnerable adults with specific skills needs. For instance, older adults are eligible for the Skills and Training Incentive (introduced in January 2019), a training voucher which subsidises the cost of any training that is identified as part of their Skills Checkpoint assessment and which would help them build skills to remain in the workforce longer. The Australian Government provides up to AUS 2 200 towards the cost of training, and either the individual or their employer must match this amount. The Skills for Education and Employment (SEE) programme for job seekers and the AMEP for migrants subsidise foundation skills (literacy and numeracy) training. Other subsidised training programmes are offered to displaced workers, older workers, parents re-entering the labour market, low-skilled adults, and job seekers (see Table 1.6 for a list of subsidised training programmes, along with eligibility requirements).

There have been no national subsidies for the development of foundation skills for employed individuals since the WELL programme closed in 2014. The Industry Skills Fund (closed in 2016) offered grants to certain SMEs to subsidise accredited and unaccredited training (Box 1.2) and went some way to meeting employed individuals’ foundation skills needs following the closure of WELL.

Each state offers its own set of subsidies for adult learning, and the type of learning that is eligible for subsidy varies by state. New South Wales, for instance, is the only state to subsidise skill sets (i.e. bundles of units of competency). Many states subsidise a mixture of formal and non-formal learning, and most target subsidies on qualifications deemed to be priority areas for the state or territory (OECD, 2018[7]).

Box 1.2. Industry Skills Fund

The Industry Skills Fund (ISF), which ran in Australia from January 2015 to December 2016, was a grant programme to support the training needs of enterprises. It was targeted at growth-oriented SMEs and operated under a co-financing model with the amount contributed by firms based on a sliding scale depending on the size and location of the firm. The grant supported both accredited and unaccredited training provided it met certain conditions, including that the training provided a significant return on investment, was fit-for-purpose to meet a specific need related to the growth opportunity, and was not already eligible for funding under other government programs. In addition to the subsidy, SMEs could also receive free and tailored advice to assist them in identifying skills to boost their workforce and overall productivity. Businesses could apply to grants to cover the costs of recommended training based on the skills advice. SMEs who received skills advice and completed a funding agreement were overwhelmingly positive about the value added by Skills Advisers, based on survey findings.

An innovative feature of the ISF was that it covered unaccredited training in addition to accredited training. Skills Advisers who were consulted for a review of the programme thought that this feature filled an important gap, as other government assistance already covered formal qualifications, and the direct and opportunity costs associated with qualification-based training support could outweigh the possible benefit to business and its staff. Feedback from stakeholders suggests that unaccredited training was custom-designed to meet business needs and delivery was generally flexible and timely. Moreover, in some fields accredited training was either not available or not up to date, or no accredited provider was available.

The ISF was closed after two years, as part of a redirection of funding within the education and training portfolio. However, survey results suggest that close to 90% of micro and SMEs agreed or strongly agreed that the training outcome had been positive for their business, and an equivalent percentage reported that the training adequately addressed the skills needs of their business. While the grant helped overcome the cost-related barriers to training for SMEs, the tailored skills advice was effective at addressing barriers to training related to the identification of skills needs: 97% of firms who received an ISF grant agreed that the support they received helped their business to better identify skills needs and training solutions. Only 15% of firms reported that they would have funded this training anyway, while 37% reported that they would have sought other public support if the ISF grant had not been available. These survey results suggest low deadweight losses (Box 1.3). A common criticism regarding the programme was that the process of filling in the grant application was too complex, and could have been streamlined for efficiency.

Source: ACIL Allen Consulting (2016[28]), “Industry Skills Fund and the Youth Stream Pilot Programs”.

Income-contingent loans

Loans are available to help individuals overcome liquidity constraints associated with investing in education and training. As with subsidies, provided they meet eligibility requirements and study with an approved provider, most domestic undergraduate HE and VET students are eligible for income-contingent interest-free loans that go towards tuition fees. Students may obtain loans for multiple qualifications; however, there is a lifetime limit to the amount that can be borrowed (AUS 104 440 in 2019 for most students). Apprentices at Certificate III or IV qualification levels leading to specific priority qualifications and occupations are also eligible for income-contingent loans (Trade Support Loans) that cover the costs of everyday expenses (e.g. tools) while undertaking apprenticeship training. All of these loans are repayable only once the student earns above a threshold income (for the 2018-19 income year, the compulsory repayment threshold was AUS 51 957), helping to overcome barriers related to cost. The Australian Government determines the rules for both the HE and VET loan schemes.

Variation in funding models across VET and HE has led some groups (BCA, 2017[29]) to argue that the system creates an uneven playing field which distorts individual incentives in favour of HE. For instance, while there are caps on loans and a 20% loan fee for all VET student loans, the HECS-HELP loans (which represents a large proportion of HE loans) do not have caps or loan fees. The Australian Government also regulates the price of course fees in HE, but does not currently have the authority to do so in VET. Specific consideration of funding arrangements in VET and HE sectors remains outside the scope of this review.

The National Centre for Student Equity in Higher Education (NCSEHE) assesses how well represented disadvantaged groups are in HE, which provides a sense for the capacity of the entire package of financial support (subsidies and loans) to target under-represented groups as well as the size of deadweight losses (Box 1.3). In 2017, 17% of domestic undergraduate enrolments were made up of students of low socio-economic status – defined as those from the poorest 25% of Australian postcodes. Their participation continues to be below their population share (25%) but has been increasing since 2012 when only 16% of students with low socio-economic status were enrolled in HE (Koshy, 2018[30]). Representation of students from low socio-economic status tends to be much higher in TAFEs than in HE institutions (in Victoria: 40% in VET, compared with only 14% in HE) (The Senate, 2018[31]; KPMG, 2018[32]). This suggests that deadweight losses may be higher for subsidies and loans in HE than for VET.

Box 1.3. Economic rationale for policy intervention in the presence of deadweight loss

Deadweight loss is a reduction in net economic benefits resulting from an inefficient allocation of resources, and is often considered when assessing government interventions and programmes. In the context of adult learning, deadweight loss might occur following the introduction of a government policy aimed at raising participation in training, where the desired training participation might have occurred (at least to some extent) in the absence of government intervention. A related concept, additionality, refers to the change in behaviour (e.g. higher participation in training) that is specifically induced by the government intervention and which would not have occurred in the absence of such intervention.

Most public policy interventions have some degree of deadweight loss and it is up to policy makers to decide whether the expected economic benefits warrant the intervention. Intervention in the presence of deadweight loss is often justified on the basis of distributional advantages or positive externalities associated with learning. In the absence of government intervention, adults with higher levels of qualifications tend to receive more training from employers than adults with lower level or no qualifications. The introduction of a financial incentive aimed at those with lower level qualifications may improve the distribution of training provision, generating significant economic value. An intervention that leads to more training may also bring about positive externalities, whereby the enhanced training provided to one worker increases not only their own productivity, but also the productivity levels of co-workers through knowledge transfer, imitation, and learning by doing. Financial incentives that target firms can capture significant external benefits, as without government intervention firms may under-invest in training out of a fear that the trained employee will go to another firm.

Source: Adapted from BIS (2012[33]), “Assessing the Deadweight Loss Associated with Public Investment in Further Education and Skills”, http://www.bis.gov.uk/.

Tax incentives

When claiming their annual taxes, individuals can deduct expenses related to self-education for a course that relates directly to their current work activities. Individuals may not claim this deduction for a course that relates only in a general way to their current employment or occupation or which would enable them to retrain for new employment or a new occupation. This financial incentive covers both the self-employed and employees.

In 2014-15, 616 000 individuals (nearly 5% of all tax filers) claimed AUS 1.2 billion in self-education expenses (Figure 1.12). The average claim was AUS 1 950 and there is no cap on claim amounts, though there is a floor (AUS 450). The tax incentive tends to be used more by younger tax filers (aged 25-39) than by those age 40 and over (Table 1.5). The tax deduction is not income-tested, and is used to a greater degree by tax filers earning between AUS 25 000 to 150 000 than by those earning less than AUS 25 000. It has particularly high use among individuals earning AUS 100 000 to 150 000.

The Australian Government also allows employers who provide or pay for work-related training for an employee freedom from paying the Fringe Benefits Tax (FBT) under certain circumstances, since their employees would could claim these expenses as part of the self-education expenses tax deduction if they paid for the training themselves. However, if an employer chooses to provide or pay for training for an employee and that training does not have a sufficient connection to the employee’s current employment, then the employer must still pay the FBT.

The next chapter will provide evidence on what the current barriers are to further engagement in adult learning by individuals and employers in Australia. It will discuss the capacity of various financial incentives to boost engagement in adult learning, and will provide Australian and international examples for illustration.

Figure 1.12. Use of self-education expenses tax deduction, 1991-2013
Number of claims and total value of expenses claimed
Figure 1.12. Use of self-education expenses tax deduction, 1991-2013

Source: Australian Taxation Office, Taxation statistics 2014-15 Individuals: Selected items for 1978-79 to 2014-15 income years (database).

Table 1.5. Distribution of self-education tax deduction by age and income level, 2014-15

 

Number of claims

Taxfilers

Share of taxfilers who claimed

Total

615 904

13 213 816

4.7

Age

 

 

 

25-29

122 768

1 478 576

8.3

30-34

109 596

1 468 114

7.5

35-39

79 556

1 304 319

6.1

40-44

63 294

1 366 974

4.6

45-49

47 711

1 281 344

3.7

50-54

35 802

1 268 198

2.8

55-59

21 897

1 125 540

1.9

60-64

9 476

885 803

1.1

25-64

490 100

10 178 868

4.8

Income Level

 

 

 

Less than 25 000

81 605

3 724 000

2.2

25 001 to 50 000

212 965

3 864 081

5.5

50 001 to 70 000

130 543

2 167 175

6.0

70 001 to 100 000

111 733

1 830 305

6.1

100 001 to 150 000

66 189

982 701

6.7

150 001 to 500 000

12 869

645 554

2.0

Source: Australian Taxation Office, Taxation statistics 2014-15 Individuals: Selected items for 1978-79 to 2014-15 income years (database).

Table 1.6. Existing financial incentives to promote adult learning in Australia

Type

Name

Provided by*

Eligible learners

Eligible training

Allocated to

Subsidy

Commonwealth Grant Scheme

CW

Most domestic students, subject to citizenship and residency requirements

Most accredited undergraduate and some postgraduate courses offered at HE institutions

Individual

VET state-subsidised places

S&T and CW

Most domestic students; eligibility varies by state

Formal training at an approved RTO

Individual

State-subsidised training

S&T

Varies by state

Varies by state, mostly accredited training

Individual

Australian Apprenticeships Incentives programme

CW

Apprentices and trainees

Formal VET training in high demand occupations

Employer

Australian Migrant English Programme

CW

Migrants with less than functional English

Accredited English language tuition

Individual

Skills for Education and Employment

CW

Registered job seekers with literacy and numeracy needs

Accredited language, literacy and numeracy training

Individual

Employment Fund

CW

Registered jobactive job seekers

Accredited training, employer required non-accredited training, or non-accredited training in employability or foundation skills.

Individual

New Enterprise Incentive Scheme

CW

Adults 18+ who are able to work full-time in new business

Accredited small business training at a RTO (Certificate III or IV)

Individual

ParentsNext

CW

Registered participants who are parents of young children

Employment preparation which includes referral to education, training or other activities that lead to employment

Individual

Skills and Training Incentive

CW

Adults who have participated in the Skills Checkpoint Programme (must be age 45-70 and at risk of unemployment or recently unemployed).

Suitable job-related formal or non-formal training, as identified by a Skills Checkpoint assessment

Individual

Stronger Transitions

CW

Displaced workers in regions affected by large-scale redundancies

A range of services are offered including skills assessments, job search assistance, literacy and numeracy support, and digital literacy training.

Individual/Emp

Career Transition Assistance

CW

Available nationally from July 2019 to help job seekers age 45+ become more competitive in the labour market.

Resilience, digital skills, job search assistance

Individual

Loan

Higher Education Loan Programme

CW

Most domestic students, subject to citizenship and residency requirements

Most courses in HE institutions that are accredited or lead to an award

Individual

VET Student Loans

CW

Open to all learners

Formal VET training in approved courses only (high national priority, address skills shortages)

Individual

Trade Support Loans

CW

Apprentices

Loans cover costs while undertaking apprenticeship training in priority occs/quals

Individual

Tax incentive

Self-education expenses deduction

CW

Open to all employed persons

Formal training related to current employment.

Individual

Fringe benefits tax deduction

CW

Open to all employed persons

Formal training related to current employment

Employer

Note: *CW: Commonwealth government; S&T: state and territory governments.

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[30] Koshy, P. (2018), “Equity Student Participation in Australian Higher Education: 2012 – 2017”, National Centre for Student Equity in Higher Education (NCSEHE), Perth, https://www.ncsehe.edu.au/wp-content/uploads/2018/12/Equity-Student-Briefing-Note_2017-18_Final.pdf.

[32] KPMG (2018), “The importance of TAFE to Victoria’s prosperity”, KPMG, https://assets.kpmg/content/dam/kpmg/au/pdf/2018/importance-of-tafe-to-victorias-prosperity-kpmg-final-report-june-2018.pdf.

[21] NCVER (2019), “Australian vocational education and training statistics: Government-funded students and courses - January to September 2018”, National Centre for Vocational Education Research, Adelaide, https://www.ncver.edu.au/__data/assets/pdf_file/0043/4869394/Government-funded-students-and-courses-January-to-September-2018.pdf.

[17] NCVER (2019), “Government funding of VET 2017”, National Centre for Vocational Education Research, Adelaide, https://www.ncver.edu.au/research-and-statistics/publications/all-publications/government-funding-of-vet-2017 (accessed on 26 June 2019).

[18] NCVER (2018), “Timeline of Australian VET policy initiatives 1998-2017”, National Centre for Vocational Education Research, Adelaide, http://www.voced.edu.au/vet-knowledge-bank-timeline-australian-vet-policy-initiatives-1998-2017.

[5] 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.

[6] OECD (2019), Getting Skills Right: Future-Ready Adult Learning Systems, Getting Skills Right, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264311756-en.

[9] OECD (2019), “Labour Market Statistics: Involuntary part time workers”, OECD Employment and Labour Market Statistics (database), https://dx.doi.org/10.1787/data-00307-en (accessed on 7 May 2019).

[11] OECD (2019), “Measuring platform mediated workers”, OECD Digital Economy Papers, No. 282, OECD Publishing, Paris, https://dx.doi.org/10.1787/170a14d9-en.

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

[12] OECD (2019), OECD SME and Entrepreneurship Outlook 2019, OECD Publishing, Paris, https://dx.doi.org/10.1787/34907e9c-en.

[7] OECD (2018), Getting Skills Right: Australia, Getting Skills Right, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264303539-en.

[23] Productivity Commission (2019), “Report on Government Services 2019”, https://www.pc.gov.au/research/ongoing/report-on-government-services.

[31] The Senate (2018), “Select Committee on the Future of Work and Workers”, Commonwealth of Australia.

Notes

← 1. The AIG Workforce Development Needs survey is highly skewed towards larger firms: in the 2018 survey, 63% of the sample was made up of firms with 20 employees or more. This contrasts sharply with the actual enterprise structure in Australia, where only 3% of enterprises have 20 or more employees (OECD, 2019[12]). The vast majority (97%) of enterprises in Australia have fewer than 10 employees.

← 2. The Education and Training Experience survey was an earlier version of the WRTAL.

← 3. Respondents are asked whether they took part in any work-related training in the last 12 months. This question is only asked of employed respondents.

← 4. Incentives were removed for existing worker apprentices and for trainees not in occupations experiencing skills shortages.

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