ࡱ> )xxx bjbj ̟̟,Nr#U$:$,&&&$+&P?3P+&XwGf (   "<& vvvvvvvy||v-&(^((v2$$  w222($ & v2(v22Wl%^&\pJD-Z$/e(w0Xw[8}28}H\2\<&e(((+&+&Ċ+&+& #:    Analysis of private returns to vocational education and training Wang-Sheng Lee Michael Coelli Melbourne Institute of Applied Economic and Social Research  The views and opinions expressed in this document are those of the author/project team and do not necessarily reflect the views of the Australian Government, state and territory governments or ϲʿ¼ Any interpretation of data is the responsibility of the author/project team. . Publisher's note Additional information relating to this research is available in Analysis of private returns to vocational education and training: Support document. It can be accessed from ϲʿ¼'s website . To find other material of interest, search VOCED (the UNESCO/ϲʿ¼ international database < HYPERLINK "http://www.voced.edu.au/" http://www.voced.edu.au>) using the following keywords: vocational education, employment, outcome of education, qualifications, data analysis. Commonwealth of Australia, 2010 This work has been produced by the ϲʿ¼ (ϲʿ¼) under the National Vocational Education and Training Research and Evaluation (NVETRE) Program, which is coordinated and managed by ϲʿ¼ on behalf of the Australian Government and state and territory governments. Funding is provided through the Department of Education, Employment and Workplace Relations. Apart from any use permitted under the Copyright Act 1968, no part of this publication may be reproduced by any process without written permission. Requests should be made to ϲʿ¼. The NVETRE program is based upon priorities approved by ministers with responsibility for vocational education and training (VET). This research aims to improve policy and practice in the VET sector. For further information about the program go to the ϲʿ¼ website <HYPERLINK "http://www.ncver.edu.au"http://www.ncver.edu.au>. The author/project team was funded to undertake this research via a grant under the NVETRE program. These grants are awarded to organisations through a competitive process, in which ϲʿ¼ does not participate. The views and opinions expressed in this document are those of the author/project team and do not necessarily reflect the views of the Australian Government, state and territory governments or ϲʿ¼. ISBN 978 1 921413 60 5 print edition 978 1 921413 59 9 web edition TD/TNC 98.05 Published by ϲʿ¼ ABN 87 007 967 311 Level 11, 33 King William Street, Adelaide SA 5000 PO Box 8288 Station Arcade, Adelaide SA 5000, Australia ph +61 8 8230 8400 fax +61 8 8212 3436 email ncver@ncver.edu.au About the research Analysis of private returns to vocational education and training Wang-Sheng Lee and Michael Coelli, Melbourne Institute of Applied Economic and Social Research In 2008 as part of a national push to increase Australias skill levels, the Council of Australian Governments agreed on targets that would see, by 2020, a doubling of diploma and advanced diploma completions and a halving of the proportion of 20 to 64-year-old Australians without at least a certificate III. Such targets assume there is a financial return as a result of undertaking vocational education and training (VET). Using data from the Australian Bureau of Statistics (ABS) Surveys of Education and Training (19932005), this study investigated this assumption by looking at the employment and earnings for individuals who had completed a VET course and how these may have changed over time. This work examines the effect of field of education on the returns from VET for individuals, as well as the returns from VET for mature-age students (defined here as persons between 30 and 64years). It also compares these with higher educational qualifications. This study differs from previous research on returns from VET in that it does not determine the individual rate of return from investing in a VET course. Rather, the authors determine the effects of educational qualification on employment and earnings outcomes, and how these have changed over time. Key messages Compared with those who have completed Year 12, employment and earnings benefits are only gained by completing a VET course at the diploma level. This result differs from some previous studies (for example, Long & Shah 2008). However, by comparison with individuals who do not complete Year 12, both employment and earnings benefits can be gained from completion of a VET qualification at any level, an outcome which accords with previous research. Undertaking courses in the area of business, engineering, architecture, building and automotive provides the greatest benefits relative to those who did not complete Year 12. For mature-age students, those who have not completed Year 12 and undertake a VET course at the certificate III level or higher gain the greatest employment and earnings benefits. However, there is a lag of several years before these benefits materialise. The study covers the period 1993 to 2005 to assess whether VET qualifications have continued to attract similar returns relative to Year 12 and non-school completers. The earning benefits from completing a diploma were shown to be relatively stable during this period. At the sub-diploma level there were more fluctuations but, relative to non-school completers, returns from these qualifications were positive. This was not the case when comparisons were made to Year 12 completers. The difference in findings between this and previous studies highlights the complexity of measuring private returns from education. Decisions made about the comparison groups, the degree of disaggregation of educational levels, data sets and the statistical techniques used all impact on the results. So too does the influence of variables such as prior educational achievement, ability, opportunity or motivationvariables which are not present in the Survey of Education and Training. Nevertheless, this study makes it clear that we cannot assume VET has a financial return to the individual; it all depends on educational background and the level and field of the qualification being undertaken. Tom Karmel Managing Director, ϲʿ¼ Contents  TOC \o "1-2" Tables  PAGEREF _Toc125534809 \h 6 Executive summary  PAGEREF _Toc125534810 \h 10 Introduction  PAGEREF _Toc125534811 \h 12 Previous research on returns from VET  PAGEREF _Toc125534812 \h 13 Methodology and data  PAGEREF _Toc125534813 \h 15 Defining the treatment and comparison groups  PAGEREF _Toc125534814 \h 16 Descriptive statistics  PAGEREF _Toc125534815 \h 19 Results  PAGEREF _Toc125534816 \h 25 Returns by aggregate level of qualifications, Year 12 as comparison group  PAGEREF _Toc125534817 \h 27 Returns by aggregate level of qualifications, less than Year 12 as comparison group  PAGEREF _Toc125534818 \h 34 Conditioning on school completion status  PAGEREF _Toc125534819 \h 40 Returns by field of education, Year 12 as comparison group  PAGEREF _Toc125534820 \h 49 Returns by field of education, less than Year 12 as comparison group  PAGEREF _Toc125534821 \h 60 Outcomes for mature-age students  PAGEREF _Toc125534822 \h 71 Returns for mature-age students, Year 12 as comparison group  PAGEREF _Toc125534823 \h 72 Returns for mature-age students, less than Year 12 as comparison group  PAGEREF _Toc125534824 \h 75 Conclusion  PAGEREF _Toc125534825 \h 79 References  PAGEREF _Toc125534826 \h 81 Support document details  PAGEREF _Toc125534827 \h 83 Appendices A: How propensity-score matching works  PAGEREF _Toc125534828 \h 84 B: The two-step matching/ regression approach  PAGEREF _Toc125534829 \h 86 C: Sample sizes of treatment and comparison groups in the 1993, 1997, 2001 and 2005 SET data  PAGEREF _Toc125534830 \h 88  Tables  TOC \t "tabletitle" \c 1 Imputation rules for top category values of weekly earnings  PAGEREF _Toc124575576 \h 19 2 Covariate means for the treatment and comparison groups  PAGEREF _Toc124575577 \h 20 3 Unadjusted mean outcomes for the treatment and comparison groups  PAGEREF _Toc124575578 \h 25 4 Aggregate returns from education for the 1993 SET (ABSCQ) relative to Year 12 completers, males  PAGEREF _Toc124575579 \h 29 5 Aggregate returns from education for the 1993 SET (ABSCQ) relative to Year 12 completers, females  PAGEREF _Toc124575580 \h 29 6 Aggregate returns from education for the 1997 SET (ABSCQ) relative to Year 12 completers, males  PAGEREF _Toc124575581 \h 30 7 Aggregate returns from education for the 1997 SET (ABSCQ) relative to Year 12 completers, females  PAGEREF _Toc124575582 \h 30 8 Aggregate returns from education for the 2001 SET (ABSCQ) relative to Year 12 completers, males  PAGEREF _Toc124575583 \h 31 9 Aggregate returns from education for the 2001 SET (ABSCQ) relative to Year 12 completers, females  PAGEREF _Toc124575584 \h 31 10 Aggregate returns from education for the 2001 SET (ASCED) relative to Year 12 completers, males  PAGEREF _Toc124575585 \h 32 11 Aggregate returns from education for the 2001 SET (ASCED) relative to Year 12 completers, females  PAGEREF _Toc124575586 \h 32 12 Aggregate returns from education for the 2005 SET (ASCED) relative to Year 12 completers, males  PAGEREF _Toc124575587 \h 33 13 Aggregate returns from education for the 2005 SET (ASCED) relative to Year 12 completers, females  PAGEREF _Toc124575588 \h 33 14 Aggregate returns from education for the 1993 SET (ABSCQ) relative to less than Year 12, males  PAGEREF _Toc124575589 \h 35 15 Aggregate returns from education for the 1993 SET (ABSCQ) relative to less than Year 12, females  PAGEREF _Toc124575590 \h 35 16 Aggregate returns from education for the 1997 SET (ABSCQ) relative to less than Year 12, males  PAGEREF _Toc124575591 \h 36 17 Aggregate returns from education for the 1997 SET (ABSCQ) relative to less than Year 12, females  PAGEREF _Toc124575592 \h 36 18 Aggregate returns from education for the 2001 SET (ABSCQ) relative to less than Year 12, males  PAGEREF _Toc124575593 \h 37 19 Aggregate returns from education for the 2001 SET (ABSCQ) relative to less than Year 12, females  PAGEREF _Toc124575594 \h 37 20 Aggregate returns from education for the 2001 SET (ASCED) relative to less than Year 12, males  PAGEREF _Toc124575595 \h 38 21 Aggregate returns from education for the 2001 SET (ASCED) relative to less than Year 12, females  PAGEREF _Toc124575596 \h 38 22 Aggregate returns from education for the 2005 SET (ASCED) relative to less than Year 12, males  PAGEREF _Toc124575597 \h 39 23 Aggregate returns from education for the 2005 SET (ASCED) relative to less than Year 12, females  PAGEREF _Toc124575598 \h 39 24 Aggregate returns from education for the 1997 SET (ABSCQ), males, conditioning on school completion  PAGEREF _Toc124575599 \h 41 25 Aggregate returns from education for the 1997 SET (ABSCQ), females, conditioning on school completion  PAGEREF _Toc124575600 \h 41 26 Aggregate returns from education for the 2001 SET (ABSCQ), males, conditioning on school completion  PAGEREF _Toc124575601 \h 42 27 Aggregate returns from education for the 2001 SET (ABSCQ), females, conditioning on school completion  PAGEREF _Toc124575602 \h 42 28 Aggregate returns from education for the 2001 SET (ASCED), males, conditioning on school completion  PAGEREF _Toc124575603 \h 43 29 Aggregate returns from education for the 2001 SET (ASCED), females, conditioning on school completion  PAGEREF _Toc124575604 \h 43 30 Aggregate returns from education for the 2005 SET (ASCED), males, conditioning on school completion  PAGEREF _Toc124575605 \h 44 31 Aggregate returns from education for the 2005 SET (ASCED), females, conditioning on school completion  PAGEREF _Toc124575606 \h 44 32 Aggregate returns from education for the 1997 SET (ABSCQ), males, conditioning on less than Year 12  PAGEREF _Toc124575607 \h 45 33 Aggregate returns from education for the 1997 SET (ABSCQ), females, conditioning on less than Year 12  PAGEREF _Toc124575608 \h 45 34 Aggregate returns from education for the 2001 SET (ABSCQ), males, conditioning on less than Year 12  PAGEREF _Toc124575609 \h 46 35 Aggregate returns from education for the 2001 SET (ABSCQ), females, conditioning on less than Year 12  PAGEREF _Toc124575610 \h 46 36 Aggregate returns from education for the 2001 SET (ASCED), males, conditioning on less than Year 12  PAGEREF _Toc124575611 \h 47 37 Aggregate returns from education for the 2001 SET (ASCED), females, conditioning on less than Year 12  PAGEREF _Toc124575612 \h 47 38 Aggregate returns from education for the 2005 SET (ASCED), males, conditioning on less than Year 12  PAGEREF _Toc124575613 \h 48 39 Aggregate returns from education for the 2005 SET (ASCED), females, conditioning on less than Year 12  PAGEREF _Toc124575614 \h 48 40 Returns from education for the 1993 SET (ABSCQ) by field of study relative to Year 12 completers, males  PAGEREF _Toc124575615 \h 50 41 Returns from education for the 1993 SET (ABSCQ) by field of study relative to Year 12 completers, females  PAGEREF _Toc124575616 \h 51 42 Returns from education for the 1997 SET (ABSCQ) by field of study relative to Year 12 completers, males  PAGEREF _Toc124575617 \h 52 43 Returns from education for the 1997 SET (ABSCQ) by field of study relative to Year 12 completers, females  PAGEREF _Toc124575618 \h 53 44 Returns from education for the 2001 SET (ABSCQ) by field of study relative to Year 12 completers, males  PAGEREF _Toc124575619 \h 54 45 Returns from education for the 2001 SET (ABSCQ) by field of study relative to Year 12 completers, females  PAGEREF _Toc124575620 \h 55 46 Returns from education for the 2001 SET (ASCED) by field of education relative to Year 12 completers, males  PAGEREF _Toc124575621 \h 56 47 Returns from education for the 2001 SET (ASCED) by field of education relative to Year 12 completers, females  PAGEREF _Toc124575622 \h 57 48 Returns from education for the 2005 SET (ASCED) by field of education relative to Year 12 completers, males  PAGEREF _Toc124575623 \h 58 49 Returns from education for the 2005 SET (ASCED) by field of education relative to Year 12 completers, females  PAGEREF _Toc124575624 \h 59 50 Returns from education for the 1993 SET (ABSCQ) by field of study relative to less than Year12, males  PAGEREF _Toc124575625 \h 61 51 Returns from education for the 1993 SET (ABSCQ) by field of study relative to less than Year12, females  PAGEREF _Toc124575626 \h 62 52 Returns from education for the 1997 SET (ABSCQ) by field of study relative to less than Year12, males  PAGEREF _Toc124575627 \h 63 53 Returns from education for the 1997 SET (ABSCQ) by field of study relative to less than Year12, females  PAGEREF _Toc124575628 \h 64 54 Returns from education for the 2001 (ABSCQ) SET by field of study relative to less than Year12, males  PAGEREF _Toc124575629 \h 65 55 Returns from education for the 2001 (ABSCQ) SET by field of study relative to less than Year12, females  PAGEREF _Toc124575630 \h 66 56 Returns from education for the 2001 (ASCED) SET by field of education relative to less than Year 12, males  PAGEREF _Toc124575631 \h 67 57 Returns from education for the 2001 (ASCED) SET by field of education relative to less than Year 12, females  PAGEREF _Toc124575632 \h 68 58 Returns from education for the 2005 SET (ASCED) by field of education relative to less than Year 12, males  PAGEREF _Toc124575633 \h 69 59 Returns from education for the 2005 SET (ASCED) by field of education relative to less than Year 12, females  PAGEREF _Toc124575634 \h 70 60 Mature-age returns from education for the 1993 SET (ABSCQ) relative to Year 12 completers  PAGEREF _Toc124575635 \h 73 61 Mature-age returns from education for the 1997 SET (ABSCQ) relative to Year 12 completers  PAGEREF _Toc124575636 \h 73 62 Mature-age returns from education for the 2001 SET (ABSCQ) relative to Year 12 completers  PAGEREF _Toc124575637 \h 74 63 Mature-age returns from education for the 2001 SET (ASCED) relative to Year 12 completers  PAGEREF _Toc124575638 \h 74 64 Mature-age returns from education for the 2005 SET (ASCED) relative to Year 12 completers  PAGEREF _Toc124575639 \h 75 65 Mature-age returns from education for the 1993 SET (ABSCQ) relative to less than Year 12  PAGEREF _Toc124575640 \h 76 66 Mature-age returns from education for the 1997 SET (ABSCQ) relative to less than Year 12  PAGEREF _Toc124575641 \h 76 67 Mature-age returns from education for the 2001 SET (ABSCQ) relative to less than Year 12  PAGEREF _Toc124575642 \h 77 68 Mature-age returns from education for the 2001 SET (ASCED) relative to less than Year 12  PAGEREF _Toc124575643 \h 77 69 Mature-age returns from education for the 2005 SET (ASCED) relative to less than Year 12  PAGEREF _Toc124575644 \h 78 C1 Sample sizes of treatment and comparison groups in the 1993 SET data (ABSCQ)  PAGEREF _Toc124575645 \h 88 C2 Sample sizes of treatment and comparison groups in the 1997 SET data (ABSCQ)  PAGEREF _Toc124575646 \h 88 C3 Sample sizes of treatment and comparison groups in the 2001 SET data (ABSCQ)  PAGEREF _Toc124575647 \h 89 C4 Sample sizes of treatment and comparison groups in the 2001 SET data (ASCED)  PAGEREF _Toc124575648 \h 89 C5 Sample sizes of treatment and comparison groups in the 2005 SET data (ASCED)  PAGEREF _Toc124575649 \h 89  Executive summary This report provides estimates of the effects of completing a vocational education and training (VET) qualification on employment and earnings outcomes. Having explicit estimates of the returns from VET is important because such information allows individuals to weigh the potential benefits of acquiring these qualifications. The methodology we use is one based on matched comparisons of persons at each level of VET qualification with Year 12 completers and those who did not complete Year 12. The data we use for the analysis come from four waves of the Survey of Education and Training (SET)1993, 1997, 2001 and 2005conducted by the Australian Bureau of Statistics (ABS). These are national household surveys which collect detailed information on socio-demographic characteristics, employment characteristics and educational qualifications obtained. Part of the analysis of the effects of VET qualifications over the period 1993 to 2005 is complicated by the fact that in the late 1990s, the Australian Qualifications Framework (AQF) was introduced and this completely changed the types of educational qualifications that were awarded. With the introduction of AQF, basic vocational, skilled vocational, and associate diplomas were superseded by certificates IIV, diplomas and advanced diplomas. In this report, we make our best attempt to provide concordance between the pre-AQF credentials and AQF credentials using the Survey of Education and Training data. This report builds on the existing Australian literature by providing a comprehensive analysis of the effects of VET qualifications relative to Year 12 completers and those who did not complete Year 12. The analysis of returns from VET is of high policy relevance because it is precisely people who completed Year 12 or less who would be most interested in the potential benefits from obtaining VET qualifications. In addition, and an important extension to the previous research in this area, results by field of education are provided, as well as empirical estimates of the effects of VET qualifications for mature-age students. This study builds on the existing literature on returns from VET qualifications by expanding the scope of coverage to the period 19932005 (the period where Survey of Education and Training data from ABS are available), and by using a statistical procedure known as matching, where emphasis is placed on creating the most appropriate comparison groups for VET participants. In this study, to take into consideration the returns from VET within a broad education framework, VET qualifications are split into a four-level qualification classification: bachelor degree and above; associate diploma (advanced diploma/diploma); skilled vocational qualifications (certificates IIIIV); and basic vocational qualifications (certificates III), where the qualifications in parentheses are the post-AQF equivalents. In addition, three broad fields of education are considered: business (including management and commerce); engineering and related technologies; architecture, building and construction; and other. The following are the main findings of our analysis: Relative to Year 12 completers, there are no benefits from obtaining basic/skilled vocational (pre-AQF) or certificate IIV (post-AQF) qualifications. However, there are positive employment and earnings outcomes associated with advanced diploma/diploma qualifications. For example, in 2005, males with advanced diplomas/diplomas were 4.7 percentage points more likely to be employed than males with a Year 12 qualification. They were also earning on average 6.9% more per week. Relative to persons who did not complete Year 12, there are benefits to be obtained from obtaining any kind of VET qualification, including the lower-level certificate III qualifications. In all the years examined, people with VET qualifications had relatively higher average weekly earnings and a higher likelihood of being in permanent employment. The finding that, relative to Year 12 completers, there are no employment or earnings benefits from completing a certificate IIIIV qualification differs from the findings in some previous research but are consistent with the findings in several others. Perhaps an important issue to consider in assessing the value of certificate IIIIV qualifications is whether school completers or non-completers are more appropriate as a comparison group. Estimation of the effects of VET mentioned so far are not conditional on school completion status. In other words, they do not account for the fact that there are individuals with VET qualifications who might or might not have completed Year 12. Alternatively, it would be possible to only compare Year 12 completers with VET completers who have also completed Year 12, and similarly to only compare persons with less than Year 12 with VET completers who have also less than Year 12. Estimates of the returns from VET using this alternative approach find that in general, for comparisons relative to Year 12 completers, removing non-completers from the VET group increases the estimated size of the returns; for comparisons relative to people with less than Year 12, removing Year 12 completers from the VET group reduces the estimated size of the impact. Relative to persons who did not complete Year 12, the fields of education that provide the largest effects on earnings and employment outcomes appear to be business, engineering, architecture, building, and automotive. For mature-age students contemplating whether or not to undertake education to obtain a VET qualification, it appears that it is only worthwhile to do so if individuals have fewer than 12 years of schooling, and are intending to enrol in VET courses at the certificate III level or higher. Furthermore, in such instances, it might take a year or two before any positive effects of the investment in education materialise. There have been no dramatic changes over time in the returns from VET qualifications. Between 1993 and 1997, the earnings premium of associate diploma holders relative to both Year 12 completers and non-school completers was positive and of a similar magnitude. Similarly, between 2001 and 2005, the earnings premium of advanced diploma/diploma holders relative to both Year 12 completers and non-school completers was somewhat constant. It is harder to compare changes that took place pre- and post-1997 because of the introduction of AQF and the subsequent re-labelling of credentials. There were more fluctuations over time in the earnings premium to the sub-diploma VET qualifications. But relative to non-school completers, it is clear that over the entire period, 1993 to 2005, there were statistically significant returns from having such VET qualifications. Introduction Ongoing feedback on the performance of participants in the vocational education and training system is important in justifying existing levels of public expenditure. If positive employment and earnings outcomes are found, this would serve to encourage future participation by others. Positive returns might also encourage former participants to return to VET to upgrade their skills and/or develop new ones. VET plays an important role according to the 1999 Adelaide Declaration on National Goals for Schooling in the Twenty-First Century. In particular, VET can be helpful in developing employment-related skills and an understanding of the work environment, providing foundation-building pathways for alternative career options, and providing opportunities for lifelong learning. If we are to motivate individuals to participate in VET and convince them that it is worth their while investing their time and resources in acquiring a VET qualification, then reliable estimates of the returns from VET must be well known and explicit. This is similar to how many people with bachelor degrees in the workforce decide whether or not to invest in a Masters in Business Administration (MBA) degree. The returns from this degree are well known because of frequent salary surveys that publicise the average salaries of individuals with bachelor degrees and those with MBAs. Likewise, if it is clear to individuals what the expected returns are to acquiring certain types of VET qualifications (by comparison with the counterfactual state of not acquiring a VET qualification), informed decisions can be made by young people and those who offer them career guidance on what courses to undertake. Such key decisions can be pivotal in helping them achieve success later in life. This report aims to assess the effects of completing a VET qualification on employment and earnings outcomes. It focuses on estimating the effects of VET for those who have left secondary school. Specifically, this report will address the following questions: How do returns from VET qualifications in Australia vary by level of qualification and field of education? What are the returns from VET qualifications in Australia for more mature-age students who obtain their qualifications later in life? How do they compare with the returns to students who obtain their qualifications when they are younger? Have the returns from VET qualifications in Australia changed over time during the period 1993 to 2005, the period where the Survey of Education and Training data from the ABS were available? The issue of estimating returns from VET by level of qualification is not new and has been addressed by many Australian researchers in the past. However, the methodology we adopt in this report is new. Given the data available, we attempt to estimate the returns from a VET qualification in the most rigorous fashion possible using program-evaluation techniques. In addition, estimating returns by field of education and for mature-age students are relatively unexplored areas. Estimates of such returns can be helpful in shedding more light on the nature of returns from VET for different sub-populations. Note that returns in this report refers to employment and earnings outcomes. They are not true returns in the sense that costs of undertaking education are not taken into account. The next section briefly places our current study in the context of the Australian literature. The methodology and data used in this report are described in the following section; this is followed by a description of how we set up the data to form treatment and comparison groups in order to estimate returns from VET. Such an approach attempts to mimic a randomised experiment, in which differences in outcomes between the two groups can be viewed as the impact of VET and not dependent on covariates of VET participation. The following chapter describes the employment and earnings outcomes we focus on in this report, while the next provides some descriptive statistics of the variables that are used in the multivariate analysis. Estimates of returns from VET by level of qualification and field of education are then given, followed by estimates of returns from VET for mature-age students. There is a final concluding chapter. Previous research on returns from VET In general, two main approaches have been used to provide estimates of the returns from VET in Australia. The first approach is based on calculating an internal rate of return (IRR) from investing in education. This essentially involves obtaining estimates of the stream of costs and benefits of making an investment in education over an individuals lifetime. The internal rate of return is then constructed by determining the interest or discount rate that equates to the present discounted value of the costs and benefits. Australian research based on this approach of estimating the returns from VET include Ryan (2002a) and Long and Shah (2007). Borland (2002) constructed internal rate of return measures at university level for Australia. Overviews of Australian research on returns from VET qualifications conducted prior to these studies are provided in Ryan (2002a, 2002b) and Long and Shah (2007), and will not be repeated here. The second main approach to estimating the returns from education is to estimate a Mincer equation for labour market earnings. This approach involves estimating some variation of a log earnings regression on years of schooling and years of post-school work experience, and interpreting the coefficient on schooling as the returns from schooling. Over the years, many variations of the Mincer equation approach have been employed. These focus on identifying the average relationship between earnings and schooling and not on constructing an internal rate of return. For example, in estimating the economic return from various levels of education in Australia, Leigh (2008) first identified appropriate comparison groups for individuals with certain educational qualifications and restricted his sample accordingly before proceeding with his analysis. In addition, as standard linear ordinary least squares (OLS) regression estimates of the coefficient on schooling are likely to be biased because of self-selection into schooling (that is, individuals do not choose their level of schooling at random), Australian researchers have attempted to circumvent the potential endogeneityof the schooling issue by using instrumental variable techniques (for example, Leigh & Ryan 2008), or by using a sample of twins (for example, Miller, Mulvey & Martin 1995, 2005, 2006). Card (1999, 2001) provides a review of the literature and an overview of the econometric challenges in attempting to estimate the causal returns from education. The general finding in the Australian literature is that the labour market benefits of VET participation are larger for early school leavers than when compared with the outcomes of those who complete school without undertaking further study. In other words, selection of an appropriate comparison group is important in estimating returns. In this report, we build on the previous literature and Ryan (2002b) by providing a comprehensive analysis of the effects of VET qualifications relative to Year 12 completers and those who did not complete Year 12. Overall, Ryan (2002b) found that there was a positive effect of completion of a VET qualification on full-time employment outcomes for individuals, when using individuals who did not complete Year 12 as the basis for comparison. In particular, he found that for males, skilled vocational qualifications and associate diplomas had larger effects on the probability of being employed full-time than basic vocational qualifications. He also found that business courses provided better employment outcomes for both males and females than did other fields. There have been several Australian studies of changes in the labour market returns from education over time in the past few decades. Coelli and Wilkins (2008) construct estimates of earnings and income differences by education attained over the period 198182 to 200304. The authors find that the percentage gap in weekly full-time earnings between individuals with non-university post-secondary qualifications (certificates I to IV and undergraduate diplomas) and those with no post-secondary qualifications has remained stable for males (at around 13 %) but have fallen for females over this period from 21% to 8%. This study updated earlier work by Borland (1999), Gregory (1995), Karmel (1994) and others. The earlier work found that earnings gaps for both males and females had fallen over the period from 196869 to 198182. These studies did not, however, break down the earnings gap by field of education, age of education or even level of education within the broad group of non-university post-secondary education. Kennedy and Hedley (2003) examine movements over time in labour force participation rates by educational attainment category. The authors find that labour force participation rates of prime-age males fell for all educational attainment groups between 1981 and 2001, but the fall for males with no post-school qualifications was particularly dramatic. Female participation rose over this period for all educational attainment categories, though at a slower rate in the 1990s than in the 1980s. Karmel and Woods (2004) project that, as current relatively well-educated cohorts age, there will be a positive education effect over the next few decades, leading to higher engagement rates with the labour force. If the labour market continues to increase its demand for educated workers, VET qualifications can play an important role in providing lifelong learning and training that are important for maintaining and increasing labour force participation. Methodology and data The data used for this report are from the ABS Surveys of Education and Training (SET) for 1993, 1997, 2001 and 2005. The surveys employ very large, nationally representative, population samples and were dwelling-based surveys collected through personal interviews. This report is concerned with estimating a causal return to VET qualifications. It extends the analysis in Ryan (2002b) by examining more waves of SET data (four vs two) and using an alternative statistical procedure known as matching, with the emphasis placed on the creation of appropriate comparison groups. The strength of these data sets for the purposes of this analysis lies in the extensive information they contain on individual educational attainment. Individuals report details of their three highest post-school qualifications, as well as the age at which they left school and whether they had completed the highest level of schooling possible. The qualification details include the VET provider type (for example, university, technical and further education (TAFE), adult/community education centre etc.), when the qualification was completed, and its field and level. The main disadvantage of these data sets is that they are independent cross-section surveys with no linking of individuals over time. However, the presence of four consecutive data sets with considerable similarities in their scope and collection will allow us to estimate changes over time that are representative of the Australian population. Since we aim to estimate the outcomes of the VET system, for the purposes of our analysis for each of the SET data sets we limit the data to samples of individuals who actually were or conceivably could have been its graduates. For the 1993 SET data, we: exclude any full-time/part-time students in the survey year exclude anyone with highest qualifications obtained overseas exclude those not born in Australia, or aged < 18 on arrival in Australia For the 1997, 2001 and 2005 Survey of Education and Training data, we: exclude any full-time/part-time students in the survey year exclude anyone with highest qualifications obtained overseas exclude those not born in Australia, or aged < 15 on arrival in Australia. Unfortunately, the change in the categories for age of immigration after the 1993 survey did not allow us to continue to use less than age 18 years as the cut-off. It is also worth noting that these later years of survey data expanded the scope of the population surveyed, and include, for example, those not in the labour force. In order to make the survey sample in the 1997, 2001 and 2005 SET data comparable with the 1993 SET data, for these three data sets we only include: wage or salary earner in past 12 months employers, self-employed at survey date individuals unemployed or marginally attached to the labour force. Note also that the surveys cover members of private dwellings only, not members of group dwellings (hotels, hostels etc.). The analysis in this report is performed for each of the four years of survey data listed above. By attempting to estimate returns from VET in each of the four years using a comparable sample of the population, we hope to determine if there have been changes over time in the returns from VET. No attempts will be made to provide estimates of the costs of obtaining educational qualifications and internal rates of return. Our empirical strategy for estimating the returns from VET is to use the method of propensity-score-matching to pre-process the data before applying standard regression analysis, in order to make less model-dependent causal inferences (for example, see Hoet al. 2007). This involves conducting a two-stage analysis rather than matching in a single step on a single set of covariates. This approach is necessary because our treatment comparison group assignment variable in the Survey of Education and Training data (VET vs no VET) is retrospective and we cannot use variables measured after the decision on whether to undertake VET has been made (for example, current marital status) to predict the probability of undertaking VET. In the first step, matching is done using covariates that can plausibly affect the decision to undertake VET. In the second step, we use an augmented set of variables for the regression analysisvariables from the first step, the weights obtained from matching in the first step, and variables that might plausibly affect the outcome of interest (but not the decision to undertake VET). This combination of matching and regression using appropriate comparison groups helps us to obtain estimates of the effects of VET qualifications. The two-step statistical procedure we undertake is best explained using a simple example. Suppose there are 2000 people with certificate III/IV (the treatment group) and 8000 people with no qualifications (the comparison group). While ordinary regression analysis will simply use the entire sample of 10000 to estimate the effect of having certificate III/IV qualifications, matching in the first step will first help to eliminate the least comparable comparison group members. Suppose in this case that with nearest neighbour matching, only 1500 of the 8000 comparison group members are kept in the sample (with some being paired with more than one treatment group member; this technique is known as matching with replacement). In other words, the total sample size now is not 10000 but 3500 (that is, 2000 + 1500). The second stage regression is then performed for this smaller sample, with some comparison group members having weights greater than one if they are paired with more than one treatment group member. Comparison group members who are not used are essentially given weights of zero. The idea of using only comparable people in the statistical analysis is an attempt to mimic a randomised experiment. The manner in which matching attempts to eliminate selection bias is explained in more detail in appendix A. Details on the variables used in the first and second stages are provided in appendix B. Defining the treatment and comparison groups In attempting to estimate the returns from different levels of VET qualifications, different treatment/comparison group pairs will be assembled in the Survey of Education and Training data. These are based on information regarding the highest level of qualification obtained. The comparisons are partly driven by the categories are available in the data. For example, even though it would be interesting to split up certificate III and IV qualifications, this is not possible as both qualifications were recorded as one category in the Survey of Education and Training data. For the 1993 and 1997 Surveys of Education and Training, prior to the introduction of the Australian Qualifications Framework, four different treatment groups (D = 1) will be created: bachelor degree and above associate diploma skilled vocational qualifications basic vocational qualifications. Individuals with undergraduate diplomas in the 1993 and 1997 Surveys of Education and Training are excluded from our analyses in order to use a consistent definition of the highest level of educational attainment for the period 19932005. These treatment groups will each be compared with two comparison groups (D = 0): school completers (= Year 12) did not complete schooling (< Year 12). For the 2001 and 2005 Surveys of Education and Training, after the Australian Standard Classification of Education (ASCED) replaced the Australian Bureau of Statistics Classification of Qualifications (ABSCQ), the following different treatment groups will be created: bachelor degree and above advanced diploma/diploma certificate III/IV certificate I/II. As with the 1993 and 1997 Surveys of Education and Training, these treatment groups will be compared against Year 12 completers and non-school completers. The 2001 Survey of Education and Training data are unique in that they report education level using both the Australian Bureau of Statistics Classification of Qualifications and Australian Standard Classification of Education. This allows the returns from VET to be estimated in 2001 using both classification schemes and enables some inferences to be made regarding the differences the change in classification makes (for example, from skilled vocational qualifications to certificate III/IV) In addition, returns from VET will also be estimated separately by fields of study. For the 1993 SET, these fields are: business engineering, architecture, building, automotive other. For the 1997, 2001 and 2005 Surveys of Education and Training, these fields are: business engineering, architecture, building other. The logic driving the use of these field of education categories is that it separates out the traditional trades from other fields. Sample sizes At the most basic level and abstracting from more complicated econometric issues, an ability to make reliable statistical inferences from a sample of a population is highly dependent on whether appropriately large sample sizes are available. The raw sample sizes of each treatment and comparison group used in the analysis are provided in appendix C. These sample sizes are derived after the restrictions described earlier in this section are imposed on the Survey of Education and Training data. Note that the sample sizes here and those used in the multivariate analysis in the Defining the outcome variables section might differ slightly, depending on the number of missing values in outcomes and covariates. Groups that have fewer than 100 people (n < 100) are denoted in italics, indicating that the resulting impact estimates for those groups should be interpreted with caution. In general, engineering/construction is male-dominated, other fields (for example, health, education, creative arts, hospitality etc.) are female-dominated, while business tends to have a roughly equal representation of both genders. Defining the outcome variables With the statistical approach taken for this analysis, careful attention was first placed on defining the appropriate treatment and comparison groups and the set of covariates to be used. This has been deliberate and is an advantage of the statistical approach used in this study. In this way, no systematic biases on outcomes should result, as we do not repeatedly experiment with different regression specifications and samples in attempts to find the set of results that most suits our priors. The four outcomes we examine in the Survey of Education and Training data are: 1 employment (1 = employed, 0 = unemployed or marginally attached to the labour force) 2 working full-time (conditional on working full-time or part-time, 1 = worked 35 or more hours per week with main period employer, 0 = worked less than 35 hours per week with main period employer) 3 permanent vs casual employee (conditional on working, 1 = permanent employee, 0 = casual employee) 4 weekly earnings (conditional on working full-time, using mid-points of the intervals of reported weekly wages so it can be analysed in the same manner as a continuous variable). For weekly earnings, it was necessary to impute values for the top category because the ABS top-coded high values of earnings for confidentiality purposes. Based on assuming a log-normal distribution of wages for each of the Survey of Education and Training years, we used the following imputations. Table 1 Imputation rules for top category values of weekly earnings 1993 SETMales> $1160 = $1401Females> $1160 = $13381997 SETMales> $1160 = $1430Females> $1160 = $13232001 SETMales> $1160 = $1468Females> $1160 = $13802005 SETMales> $2000 = $2422Females> $2000 = $2291Descriptive statistics The means of the covariates for the various treatment and comparison groups for each of the Survey of Education and Training data sets are assembled in table 2. Covariate means for the four treatment groups (bachelor degree and above, associate diploma, skilled vocational qualifications or certificate III/IV, basic vocational qualifications or certificate I/II) are provided in the first four columns of each panel, while covariate means for the two comparison groups (Year 12 and less than Year 12) are given in the last two columns. A cursory glance at any of the panels in table 2 would be sufficient to make clear that there are many differences in characteristics across groups of persons with different educational qualifications. For example, when comparing individuals with a bachelor degree and above (the treatment group) with individuals with a Year 12 education (the comparison group) in the 1993 Survey of Education and Training, it becomes clear that the age distribution in the two groups is quite different. The treatment group is older on average as there is a significantly smaller proportion of individuals with a bachelor degree and above in the 20 to 24 years age group (0.095 vs 0.214). This difference is not unexpected, given that most people graduate with a bachelors degree in their early twenties. The treatment groups are more likely to reside in a capital city and more likely to be married than the comparison groups. Persons with the lowest educational qualifications (Year 12, less than Year12) have slightly higher proportions of individuals with English as the first language, when compared with those with higher qualifications. This could be an indication that language is not a huge barrier with regards to educational attainment in the Australian context, and also perhaps reflects the notion that children of immigrants tend to place a high priority on education. In all of the Survey of Education and Training years, there is a smaller proportion of native English speakers in the bachelor degree and above group than in the less than Year 12 group. In addition, it is also apparent that there is a natural kind of gender sorting into the sub-diploma VET qualifications. In all of the Survey of Education and Training years, males are more likely to have skilled vocational or certificate III/IV qualifications, whereas females are more likely to have basic vocational or certificate I/II qualifications. Differences in covariates for each of the Survey of Education and Training years could be driven by differences in the core characteristics of persons with different educational qualifications. They could also be the result of the sampling scheme. As a persons chance of selection in the survey varied depending on the state or territory or, in some cases, area of state/territory in which they lived, differences in characteristics of survey respondents could therefore also be related to educational qualifications if certain areas had a higher proportion of people with certain qualifications. If we were solely interested in describing differences in the characteristics across these groups, it would be important to take into account the method of sample selection and to use the corresponding sample weights to adjust for this. However, for our purposes, as we are primarily interested in using multivariate statistical techniques to make the treatment and comparison groups similar on average, such weighting is not necessary. The covariate differences across groups in table2 therefore should not be interpreted as representing the average characteristics of persons with each educational qualification in the Australian population. Its primary purpose is simply to document the fact that the groups are quite different before we perform any statistical adjustment. Table 2 Covariate means for the treatment and comparison groups 1993 SET (ABSCQ)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Age 20240.0950.0950.1160.1540.2140.110Age 25290.1330.1390.1470.1560.1520.120Age 30340.1760.1570.1560.1370.1290.132Age 35390.2020.1530.1460.1540.1290.123Age 40440.1440.1490.1350.1390.1030.126Age 45490.1080.1290.1130.0930.0770.126Age 50540.0750.0800.0860.0680.0410.093Age 55640.0670.0910.0960.0540.0460.117Male0.5290.6880.8360.2130.5030.478Capital city0.7700.6910.5920.6480.6820.581Non-English speaking country0.0790.0770.0620.0610.0870.087English is first language0.8920.9040.9240.9100.8910.901NSW0.2310.2600.2530.3000.1850.198Vic.0.2140.2180.2010.1600.2280.209QLD0.1330.1570.1940.1630.1720.205SA0.1140.1190.1090.1230.1310.123WA0.1240.1060.1140.1230.1260.136Married0.6740.7310.7290.6630.5330.674Child aged 020.1630.1280.1420.1340.1260.117Child aged 340.0570.0620.0550.0570.0500.053Child aged 590.1010.1060.1030.1130.0810.101Child aged 10140.0810.1100.0950.0920.0630.096Union member0.3670.2580.2740.2140.2440.231Note: ABSCQ = Australian Bureau of Statistics Classification of Qualifications. 1997 SET (ABSCQ)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Age 20240.0990.1600.0990.1400.2340.075Age 25290.1510.1660.1360.1410.1640.122Age 30340.1340.1460.1690.1380.1220.125Age 35390.1640.1390.1620.1470.1210.141Age 40440.1660.1240.1250.1360.1000.137Age 45490.1280.1150.1110.1140.0700.131Age 50540.0940.0860.0940.0800.0440.108Age 55640.0430.0380.0670.0480.0200.068Male0.0210.0220.0300.0210.0120.034Capital city0.5010.5140.8790.3960.5220.486Non-English speaking country0.8980.8860.9300.9190.8970.927English is first language0.0650.0540.0410.0450.0580.048NSW0.2300.2670.2050.2710.2000.184Vic.0.2340.2000.1910.1670.2200.184QLD0.1660.1680.2140.1880.2110.219SA0.0960.1280.1190.1200.0960.139WA0.1050.1120.1290.1290.1230.132Married0.6790.6160.7370.6560.5250.676Child aged 020.1390.1410.1700.1240.1290.114Child aged 340.0530.0540.0520.0520.0340.057Child aged 590.1040.0650.0930.1140.0800.110Child aged 10140.1160.0940.0950.1090.0670.101Union member0.3110.2540.2330.2060.2110.207Has disability0.1440.2140.2290.2350.1600.245Note: ABSCQ = Australian Bureau of Statistics Classification of Qualifications. 2001 SET (ABSCQ)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Age 20240.0840.0880.0880.1100.1770.066Age 25290.1400.1820.1330.1310.1900.087Age 30340.1470.1230.1470.1270.1570.113Age 35390.1420.1330.1440.1350.1190.149Age 40440.1450.1460.1610.1500.1060.143Age 45490.1360.1390.1170.1110.0730.133Age 50540.1240.0790.0950.1130.0500.122Age 55640.0550.0740.0780.0620.0270.086Male0.0270.0310.0300.0300.0080.043Capital city0.4840.5480.8110.3300.5160.484Non-English speaking country0.9150.8940.9270.9200.9100.931English is first language0.0520.0670.0420.0450.0550.050NSW0.2200.2520.2020.2360.1820.190Vic.0.2350.2010.2000.1750.2210.191QLD0.1560.1700.2020.1910.2240.206SA0.1140.1000.1250.1430.1090.143WA0.1160.1190.1400.1320.1300.138Father born overseas0.3090.3040.2890.2790.2890.256Mother born overseas0.2680.2770.2460.2480.2740.232Married0.6920.7180.7180.6770.5800.668Child aged 020.1310.1310.1290.1110.1400.103Child aged 340.0460.0560.0600.0620.0570.054Child aged 590.1000.1010.1250.1100.0970.112Child aged 10140.0970.0900.0870.1060.0630.107Union member0.2730.1900.1940.1350.1570.162Has disability0.1780.2590.2700.2750.2120.320Note: ABSCQ = Australian Bureau of Statistics Classification of Qualifications. 2001 SET (ASCED)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Age 20240.0820.0670.0870.1010.1750.065Age 25290.1380.1310.1380.1390.1890.085Age 30340.1450.1290.1380.1330.1570.113Age 35390.1410.1160.1470.1350.1190.149Age 40440.1470.1590.1610.1400.1080.143Age 45490.1370.1330.1210.1110.0730.134Age 50540.1270.1260.0940.1180.0510.123Age 55640.0550.0940.0760.0650.0280.087Male0.0270.0380.0300.0320.0090.043Capital city0.4760.4560.7600.3310.5160.485Non-English speaking country0.9160.9040.9230.9100.9110.931English is first language0.0520.0580.0460.0530.0550.049NSW0.2200.2370.2080.2390.1830.190Vic.0.2350.2030.2040.1730.2230.190QLD0.1570.1770.1960.1960.2220.206SA0.1130.1120.1250.1320.1080.143WA0.1140.1410.1380.1360.1300.137Father born overseas0.3070.2900.2890.2880.2860.256Mother born overseas0.2680.2550.2490.2540.2720.232Married0.6930.7230.7190.6820.5790.670Child aged 020.1300.1120.1260.1190.1390.103Child aged 340.0450.0610.0600.0600.0570.053Child aged 590.1010.0960.1250.1080.0980.112Child aged 10140.0970.1050.0900.1070.0630.108Union member0.2760.2040.1950.1220.1580.162Has disability0.1820.2170.2720.2770.2100.320Note: ASCED = Australian Standard Classification of Education. 2005 SET (ASCED)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Age 20240.0630.0640.0920.0750.1610.070Age 25290.1130.0900.1150.0740.1570.066Age 30340.1600.1340.1380.1320.1540.081Age 35390.1390.1350.1390.1470.1200.137Age 40440.1320.1600.1340.1500.0900.147Age 45490.1600.1480.1440.1520.0850.141Age 50540.1140.1010.1050.1050.0610.130Age 55640.0800.1080.0840.0910.0420.109Male0.0390.0580.0390.0410.0160.067Capital city0.4560.4620.6970.3740.5460.511Non-English speaking country0.9300.9340.9620.9360.9290.960English is first language0.0660.0590.0410.0560.0610.045NSW0.2040.2310.2180.2870.1830.208Vic.0.2410.2120.1870.1840.2130.184QLD0.1780.1930.2300.1690.2280.208SA0.1070.1240.1240.1180.1210.142WA0.1170.1240.1210.1250.1310.125Father born overseas0.3060.3110.2640.2730.3030.244Mother born overseas0.2700.2900.2260.2400.2740.221Married0.7310.7270.7130.6910.5680.656Child aged 020.1440.1000.1150.0960.1260.083Child aged 340.0490.0380.0490.0480.0540.043Child aged 590.1050.1220.1030.1120.0850.103Child aged 10140.0970.1060.0960.1150.0670.098Union member0.2780.2110.1970.1570.1590.170Has disability0.1650.2230.2700.2720.1830.322Notes: ASCED = Australian Standard Classification of Education. Omitted groups in the covariates are age 1519, ACT, NT and Tas., and have no children. Results Because assignment to either the treatment or comparison group is random in a randomised experiment, characteristics of both groups will be on average very similar. Both groups would be similar in age, have a similar proportion of males, a similar proportion from each state etc. The only difference is that one group is exposed to the treatment, and the other is not. As a result of this similarity, taking the simple difference in outcomes between the two groups without any adjustments for covariates can be interpreted as an average effect of the treatment (which in our context, would be the higher educational qualification). However, in the case of non-experimental data like the Survey of Education and Training, as seen in the previous section, it is unlikely that the two groups will be similar in terms of characteristics. As such differences in group characteristics exist, it is therefore not likely that a simple comparison in group outcomes can be meaningfully interpreted as a causal effect. Any differences in group outcomes could be the result of the treatment, or due to differences in characteristics of the groups and how this affects the way they respond to the treatment. The role of the multivariate approach used in this section (discussed in the previous section) is to statistically control for differences in such characteristics, so that the remaining differences in outcomes are purged of any bias resulting from these differences in characteristics. Before proceeding to the results of the multivariate analysis, we first provide the raw or unadjusted mean values of the outcome variables for each of the treatment and comparison groups (table 3). Across all the years where Survey of Education and Training data are available (table 3), it is clear that persons with a bachelor degree and above are more likely than all other groups to be employed, more likely to be in permanent employment, and to have relatively higher earnings. It is not always the case, however, that persons with a bachelor degree and above are more likely to be working full-time. In 1993, 1997 and 2001, for example, a higher proportion of persons with associate diploma qualifications were more likely to be working full-time. Table 3 Unadjusted mean outcomes for the treatment and comparison groups 1993 SET (ABSCQ)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Employment0.9340.9040.8930.8080.8200.747Full-time/part-time employment0.8160.8630.8840.6330.7710.727Permanent/casual employment0.8530.8260.8220.7170.7380.703Weekly earnings804.892665.684587.315516.663539.961500.827Note: ABSCQ = Australian Bureau of Statistics Classification of Qualifications. 1997 SET (ABSCQ)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Employment0.9390.8880.9180.8340.8720.778Full-time/part-time employment0.6850.7550.6620.5930.6430.572Permanent/casual employment0.8580.8140.8100.7100.7210.670Weekly earnings908.168725.376693.750622.964624.914579.719Note: ABSCQ = Australian Bureau of Statistics Classification of Qualifications. 2001 SET (ABSCQ)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Employment0.9460.9070.9180.8220.8700.778Full-time/part-time employment0.6540.6620.6120.5230.6430.549Permanent/casual employment0.8590.7830.7790.6860.7330.660Weekly earnings1050.574874.203791.066691.535746.026679.282Note: ABSCQ = Australian Bureau of Statistics Classification of Qualifications. 2001 SET (ASCED)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Employment0.9440.9040.9140.8110.8700.779Full-time/part-time employment0.6510.6050.6050.5270.6430.548Permanent/casual employment0.8570.8160.7740.6760.7350.662Weekly earnings1047.992917.076793.095689.913748.234680.820Note: ASCED = Australian Standard Classification of Education. 2005 SET (ASCED)Bachelors degree and aboveAssociate diplomaSkilled vocational qualificationsBasic vocational qualificationsYear 12Less than Year 12Employment0.9480.9170.9300.8440.8910.830Full-time/part-time employment0.6390.5810.6200.5630.6200.551Permanent/casual employment0.8490.8010.7670.7430.7120.695Weekly earnings1271.7551052.036937.946853.945878.638807.583Note: ASCED = Australian Standard Classification of Education. We now present treatment/comparison group differences after statistically adjusting for differences in characteristics. These results are the main results from this report and are our estimates of the returns from education based on the Survey of Education and Training data. Note that the estimates of returns in this section are based on cross-sectional data represent average returns. This is because these estimates are derived from individuals of various ages who might have obtained their qualifications a long time ago or only more recently. For example, the earnings premium of persons with diplomas over Year 12 completers should not be interpreted as the immediate effect on earnings one should expect from obtaining a diploma. Instead, it should be interpreted as an average earnings premium over an individuals working life. Returns by aggregate level of qualifications, Year 12 as comparison group Tables 4 to 13 provide estimates of the private returns from education in terms of employment and earnings outcomes, using individuals who completed 12 years of schooling as the comparison group. The estimates are provided separately by Survey of Education and Training year and gender. At this point, the focus is on educational qualifications prior to being broken down by field of education. The more disaggregated results by field of education using individuals who completed 12 years of schooling as the comparison group are presented later. The estimates in these tables are the mean differences in outcomes between the respective treatment and comparison groups after accounting for differences in their characteristics. For the three outcomesemployment, full-time/part-time employment, and permanent/casual employmentsuch differences can simply be interpreted as the percentage point increase or decrease in outcomes one would expect as a result of experiencing the treatment. For the fourth outcome that is examinedweekly earningsthe outcome is first transformed by taking logs, a conventional practice in the education literature that has theoretical justifications. For example, in table 4, in the first row, average log weekly earnings of persons with a bachelor degree and above is 0.292 log points higher than persons with a Year 12 qualification. As the log earnings specification allows an interpretation of returns in percentage terms using a simple re-transformation, it can also be more usefully inferred that persons with a bachelor degree or more earned 33.9% more than persons with only Year 12 qualifications. When comparisons are made relative to having a Year 12 qualification, the results in tables 4 to 13 make it clear that by obtaining a bachelors degree or higher, and to a lesser extent an associate diploma (ABSCQ) or an advanced diploma/diploma (ASCED), individuals can generally expect to be more likely to be employed, to be in full-time employment, to be in permanent employment, and to have higher weekly earnings. For example, looking at the results based on the 1997 SET for males in table 6, persons with associate diplomas are 12.9 percentage points more likely to be employed than persons with a Year 12 qualification. They are also earning on average 0.068 log points more (7.0%). On the other hand, there is no evidence to suggest in tables 4 to 13 that obtaining basic and skilled vocational qualifications (ABSCQ) or certificate I/II and III/IV qualifications (ASCED) confers any positive labour market outcomes, relative to having a Year 12 qualification. In most cases, the estimated impacts are negative, which suggests that such qualifications actually lead to relatively worse outcomes. For example, in the 2001 Survey of Education and Training in table 10, males with certificate I/II qualifications earned 10.0% less per week on average than males with Year 12 qualifications. For females in the 2001 Survey of Education and Training (table 11) with certificateI/II qualifications, their earnings were 9.1% less per week on average than females with Year 12 qualifications. Returns under the ABSCQ and ASCED frameworks Recall that the 2001 Survey of Education and Training data are unique in that they report education level using both the ABSCQ and the ASCED. According to the former, released in 2001, the following correspondence levels between the two exist: ABSCQASCEDBachelor degreeBachelor (honours) degreeBachelor (pass) degreeUndergraduate diplomaAdvanced diplomaAssociate diplomaDiplomaCertificate IVSkilled vocational qualificationsCertificate IIIBasic vocational qualificationsCertificate IIDue to the way educational categories are grouped together in the Survey of Education and Training (refer to Defining the treatment and comparison groups in the methodology section), we are not able to precisely use the correspondence proposed by ABS in our analysis. A comparison of the impact estimates based on ABSCQ and ASCED classification schemes should therefore take this into consideration. For bachelor degrees and above, both schemes essentially use a similar definition, and this is reflected in that fact that the sample sizes and impact estimates on the four outcomes are similar under either ABSCQ or ASCED. As our advanced diploma/diploma grouping under ASCED is of a higher qualification level than the associate diploma grouping under ABSCQ (because we include advanced diploma holders in ASCED grouping), we would expect the impacts to be relatively higher when we use our ASCED definition. Indeed, looking at the comparative results in tables 8 to 11, where the impacts are significant, one can see that the impacts on permanent employment and average weekly earnings are higher in table 10 than they are in table 8. Similarly, as our certificate III/IV grouping under ASCED is of a higher qualification level than the skilled vocation qualification grouping under ABSCQ (because certificate IV is of a higher level than skilled vocational qualifications), we also expect impacts to be larger when ASCED is used. However, the results in tables 8 to 11 do not provide strong evidence that this is the case, and the impacts appear to be very similar. This could possibly be an indication that the labour market does not sufficiently distinguish certificate IV qualifications from certificate III qualifications. Turning to the lowest qualification level, the basic vocational qualification grouping under ABSCQ is comparatively superior to the certificate I/II grouping we use under ASCED because it omits individuals with certificate I qualifications. Comparing the results in tables 8 to 11, although the impacts are all negative relative to Year 12 completers, it can be seen that under the ABSCQ scheme, they are slightly less negative. Returns over time Have the returns from VET qualifications changed over time from 1993 to 2005? Focusing first on the group with bachelor degrees and above to establish a benchmark, it can be seen that the average weekly earnings premium relative to Year 12 completers has remained somewhat stable. For males (females), the premium was 33.9% (25.7%) in 1993, 27.5% (31.8%) in 1997, 29.3% (30.1%) in 2001 and 32.0% (37.9%) in 2005, where the premium is expressed relative to the average earnings of matched Year 12 completers. The earnings premium for male associate diploma holders relative to Year 12 completers in 1993 was 7.8% and 7.0% in 1997. The earnings premium for females in both 1993 and 1997 was not significantly different from zero. With the introduction of ASCED, which replaced the ABSCQ, and our grouping of diploma and advanced diploma holders into one category, we find that there is an increase in the earnings premium. In 2001, for males (females), the premiums were 13.4% (2.9%) and in 2005, they were 7.4% (12.0%). Some of these increases are most likely to be due to the effects of the credential re-labelling and our method of grouping (see the earlier discussion comparing the 2001 results in tables 8 to 11 under the alternative classification schemes, ABSCQ or ASCED). Table 4 Aggregate returns from education for the 1993 SET (ABSCQ) relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.036***0.0060.032**0.292***(0.002)(0.617)(0.046)(0.000)Number of observations1787174014651204Associate diploma0.032*0.0180.0240.075***(0.051)(0.238)(0.263)(0.008)Number of observations10851044812664Skilled vocational qualifications-0.0050.016**0.010-0.028*(0.547)(0.046)(0.421)(0.053)Number of observations4294406230292380Basic vocational qualifications-0.0210.003-0.0250.069(0.462)(0.931)(0.515)(0.157)Number of observations425399349240Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 5 Aggregate returns from education for the 1993 SET (ABSCQ) relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.105***0.0330.047**0.299***(0.000)(0.163)(0.025)(0.000)Number of observations159014851425858Associate diploma0.065*0.042-0.040-0.036(0.056)(0.325)(0.350)(0.490)Number of observations493430398222Skilled vocational qualifications0.058**-0.013-0.0100.057*(0.029)(0.713)(0.771)(0.098)Number of observations844724615278Basic vocational qualifications0.030-0.045*0.0180.003(0.124)(0.074)(0.463)(0.916)Number of observations157412941240554Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 6 Aggregate returns from education for the 1997 SET (ABSCQ) relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.039***0.066***0.077***0.243***(0.000)(0.000)(0.000)(0.000)Number of observations2036196816421423Associate diploma0.0250.129***0.050*0.068**(0.265)(0.000)(0.098)(0.041)Number of observations570550496438Skilled vocational qualifications0.015*-0.0020.021-0.072***(0.090)(0.904)(0.170)(0.000)Number of observations3491338624462186Basic vocational qualifications-0.039**0.013-0.010-0.041(0.010)(0.558)(0.665)(0.107)Number of observations155714441142982Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 7 Aggregate returns from education for the 1997 SET (ABSCQ) relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.046***0.046**0.049**0.276***(0.001)(0.030)(0.011)(0.000)Number of observations2019188817971116Associate diploma-0.0100.0600.0030.022(0.737)(0.148)(0.929)(0.507)Number of observations535484483292Skilled vocational qualifications-0.030-0.115**-0.070-0.142***(0.356)(0.013)(0.147)(0.001)Number of observations480411348166Basic vocational qualifications-0.043***-0.002-0.032-0.051***(0.003)(0.907)(0.120)(0.001)Number of observations237120141883970Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 8 Aggregate returns from education for the 2001 SET (ABSCQ) relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.025***-0.0100.058***0.254***(0.006)(0.577)(0.000)(0.000)Number of observations2284224217891591Associate diploma-0.0060.027-0.0210.055*(0.778)(0.424)(0.498)(0.094)Number of observations670633521474Skilled vocational qualifications-0.004-0.072***-0.026*-0.074***(0.580)(0.000)(0.083)(0.000)Number of observations3534341624102145Basic vocational qualifications-0.056***-0.068**-0.079**-0.095***(0.005)(0.025)(0.011)(0.002)Number of observations952862687545Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 9 Aggregate returns from education for the 2001 SET (ABSCQ) relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.067***0.0270.065***0.274***(0.000)(0.161)(0.000)(0.000)Number of observations2407227621411308Associate diploma0.050*0.0290.0590.049(0.072)(0.455)(0.146)(0.148)Number of observations549500472268Skilled vocational qualifications-0.029-0.044-0.067*-0.143***(0.233)(0.191)(0.060)(0.000)Number of observations826706635339Basic vocational qualifications-0.024-0.013-0.023-0.071***(0.150)(0.555)(0.344)(0.004)Number of observations191815931432713Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 10 Aggregate returns from education for the 2001 SET (ASCED) relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.027***-0.0080.044***0.257***(0.002)(0.664)(0.002)(0.000)Number of observations2290224718011591Advanced diploma/diploma-0.0160.0340.045*0.126***(0.327)(0.230)(0.070)(0.000)Number of observations992938780687Certificate III/IV0.000-0.093***-0.042***-0.074***(0.957)(0.000)(0.003)(0.000)Number of observations3878375426552361Certificate I/II-0.068***-0.042-0.056-0.105***(0.002)(0.201)(0.103)(0.002)Number of observations825741600478Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 11 Aggregate returns from education for the 2001 SET (ASCED) relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.067***0.041**0.067***0.263***(0.000)(0.033)(0.000)(0.000)Number of observations2488234422031338Advanced diploma/diploma0.0260.0200.045*0.029(0.168)(0.456)(0.095)(0.269)Number of observations11741068957490Certificate III/IV-0.013-0.040-0.048*-0.096***(0.502)(0.142)(0.091)(0.000)Number of observations12321065979505Certificate I/II-0.031*-0.017-0.045*-0.095***(0.085)(0.498)(0.079)(0.000)Number of observations165613641213612Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 12 Aggregate returns from education for the 2005 SET (ASCED) relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.035***0.056***0.059***0.278***(0.000)(0.003)(0.000)(0.000)Number of observations2262221319051578Advanced diploma/diploma0.047***0.0170.0300.071**(0.002)(0.551)(0.270)(0.017)Number of observations1022990833649Certificate III/IV0.036***-0.005-0.009-0.036**(0.000)(0.720)(0.564)(0.030)Number of observations3586348227292228Certificate I/II-0.0110.0540.021-0.070**(0.616)(0.103)(0.522)(0.050)Number of observations788742582527Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 13 Aggregate returns from education for the 2005 SET (ASCED) relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.038***0.039**0.091***0.321***(0.000)(0.029)(0.000)(0.000)Number of observations2706257623361417Advanced diploma/diploma0.0130.0200.054**0.113***(0.472)(0.464)(0.049)(0.000)Number of observations11951080932511Certificate III/IV0.030*0.0030.066**-0.036(0.069)(0.901)(0.011)(0.119)Number of observations155314081205672Certificate I/II-0.041**-0.0120.035-0.021(0.030)(0.674)(0.219)(0.481)Number of observations13251116960481Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Returns by aggregate level of qualifications, less than Year 12 as comparison group In this section, instead of using persons with Year 12 qualifications as the comparison group, we use persons with less than a Year 12 qualification. The motivation for using this alternative comparison group is to highlight what differences in labour market outcomes persons with less than 12 years of schooling might expect if they obtained VET qualifications or obtained other higher qualifications. Tables 14 to 23 provide the corresponding estimates for each of the Survey of Education and Training years. These tables correspond directly with tables 4 to 13, the only difference being that a different comparison group is being used. Not surprisingly, we see that when comparisons are made to a relatively less educated group, the expected returns from VET and other higher qualifications are higher. Unlike before, it now appears that obtaining sub-diploma VET qualifications also leads to beneficial outcomes. For example, in the 1997 Survey of Education and Training in table 16, it can be seen that persons with either skilled or basic vocational qualifications have average weekly earnings that are higher by about 12% to 13%. Furthermore, in all Survey of Education and Training years, persons with sub-diploma VET qualifications have statistically significant higher probabilities of being employed. An analysis of the effects of using either ABSCQ or ASCED scheme can also be made using tables 18 to 21. These are similar to the findings in the previous section, when a similar analysis was done using tables 8 to 11 with the alternative comparison group. The results in tables 14 to 23 therefore suggest that, in terms of labour market outcomes, any person who has only less than 12 years of formal schooling could stand to benefit by enrolling in VET. However, as results in the previous section suggest, for persons who have completed high school, obtaining sub-diploma VET qualifications is of little or no benefit. Returns over time Relative to non-school completers, the earnings premium of persons with at least a bachelors degree remained consistently high over the period 1993 to 2005. For males (females), the premium was 54.8% (57.0%) in 1993, 53.1% (52.3%) in 1997, 56.5% (50.1%) in 2001 and 57.5% (54.7%) in 2005. Similar to the results in tables 4 to 13 using Year 12 completers as the comparison group, we also find that for associate diploma holders, the credential re-labelling and change in grouping used resulted in higher premiums in 2001 and 2005, by comparison with 1993 and 1997. For example, in 1993, for males (females), the earnings premium for associate diploma holders over non-school completers was 24.6% (6.9%); in 2005, it was 33.0% (27.1%). Recall that earlier in tables 8 to 11 using an alternative comparison group, we saw that the change from ABSCQ to ASCED played a much less important role in the returns from the sub-diploma VET qualifications. This is also the case using non-school completers as the comparison group (tables 18 to 21). Abstracting from this change in framework allows us to discuss more concretely the trends in the earnings premiums to holders of sub-diploma VET qualifications. For males, the earnings premium for skilled vocational qualifications or certificate III/IV qualifications during the period 1993 to 2005 ranged between 10% and 15%. For females, the earnings premium was over 12% in both 1993 and 2005, but not significantly different from zero in 1997 and 2001. The returns from basic vocational qualifications or certificate I/II qualifications fluctuated a little over time but remained consistently positive relative to non-school completers. In 1993, for males (females) the premium was 15.3% (7.8%); in 1997, it was 13.4% (9.2%). It fell to 7.6% (4.2%) in 2001. In 2005, the earnings premium for males dropped further to 5.1%. However, it went back up to 9.6% for females. Table 14 Aggregate returns from education for the 1993 SET (ABSCQ) relative to less than Year 12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.127***0.0080.066***0.437***(0.000)(0.500)(0.000)(0.000)Number of observations1783174014661203Associate diploma0.105***0.0190.057**0.220***(0.000)(0.214)(0.015)(0.000)Number of observations10871043810663Skilled vocational qualifications0.098***0.021***0.047***0.093***(0.000)(0.007)(0.000)(0.000)Number of observations4294406130292375Basic vocational qualifications0.079**-0.015-0.0120.142***(0.021)(0.591)(0.774)(0.002)Number of observations426399349246Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 15 Aggregate returns from education for the 1993 SET (ABSCQ) relative to less than Year 12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.149***0.078***0.109***0.451***(0.000)(0.001)(0.000)(0.000)Number of observations158914861423856Associate diploma0.097***0.090**0.0310.067(0.006)(0.037)(0.487)(0.218)Number of observations494429397222Skilled vocational qualifications0.115***0.0200.0280.167***(0.000)(0.550)(0.444)(0.000)Number of observations843721613277Basic vocational qualifications0.082***-0.0160.074***0.075***(0.000)(0.539)(0.004)(0.007)Number of observations156712871261547Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 16 Aggregate returns from education for the 1997 SET (ABSCQ) relative to less than Year 12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.105***0.059***0.130***0.426***(0.000)(0.002)(0.000)(0.000)Number of observations2035197616421424Associate diploma0.086***0.116***0.095***0.256***(0.001)(0.001)(0.003)(0.000)Number of observations569549499436Skilled vocational qualifications0.090***-0.0230.049***0.118***(0.000)(0.114)(0.002)(0.000)Number of observations3491338624782206Basic vocational qualifications0.032*0.0030.0150.126***(0.056)(0.898)(0.516)(0.000)Number of observations1557144311751009Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 17 Aggregate returns from education for the 1997 SET (ABSCQ) relative to less than Year 12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.142***0.120***0.176***0.421***(0.000)(0.000)(0.000)(0.000)Number of observations2028189318141134Associate diploma0.103***0.129***0.129***0.141***(0.002)(0.002)(0.002)(0.000)Number of observations539485488299Skilled vocational qualifications0.111***-0.0360.0630.028(0.002)(0.434)(0.219)(0.575)Number of observations479411349166Basic vocational qualifications0.090***0.037*0.074***0.088***(0.000)(0.075)(0.000)(0.000)Number of observations237620221908971Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 18 Aggregate returns from education for the 2001 SET (ABSCQ) relative to less than Year 12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.079***0.037**0.134***0.451***(0.000)(0.045)(0.000)(0.000)Number of observations2281224217941596Associate diploma0.046**0.080**0.0530.301***(0.048)(0.020)(0.110)(0.000)Number of observations666632521474Skilled vocational qualifications0.072***-0.044***0.044***0.139***(0.000)(0.003)(0.006)(0.000)Number of observations3536341824102154Basic vocational qualifications0.023-0.034-0.0220.084***(0.305)(0.270)(0.501)(0.007)Number of observations945857684549Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 19 Aggregate returns from education for the 2001 SET (ABSCQ) relative to less than Year 12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.165***0.098***0.164***0.413***(0.000)(0.000)(0.000)(0.000)Number of observations2433230521871329Associate diploma0.197***0.0630.136***0.197***(0.000)(0.127)(0.001)(0.000)Number of observations552497475266Skilled vocational qualifications0.101***-0.0060.053-0.011(0.000)(0.868)(0.145)(0.745)Number of observations826705641344Basic vocational qualifications0.095***0.0280.102***0.058**(0.000)(0.227)(0.000)(0.020)Number of observations193016021448712Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 20 Aggregate returns from education for the 2001 SET (ASCED) relative to less than Year 12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.079***0.040**0.143***0.448***(0.000)(0.028)(0.000)(0.000)Number of observations2287224817981599Advanced diploma/diploma0.033*0.088***0.106***0.350***(0.074)(0.002)(0.000)(0.000)Number of observations991937778694Certificate III/IV0.066***-0.050***0.036**0.129***(0.000)(0.000)(0.017)(0.000)Number of observations3894375926622374Certificate I/II0.017-0.0090.0010.073**(0.479)(0.793)(0.986)(0.032)Number of observations821738595483Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 21 Aggregate returns from education for the 2001 SET (ASCED) relative to less than Year 12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.166***0.094***0.165***0.406***(0.000)(0.000)(0.000)(0.000)Number of observations2516237522511360Advanced diploma/diploma0.143***0.048*0.170***0.181***(0.000)(0.073)(0.000)(0.000)Number of observations11861082980498Certificate III/IV0.125***-0.0070.057**0.035(0.000)(0.796)(0.047)(0.179)Number of observations12341065984507Certificate I/II0.089***0.043*0.106***0.041(0.000)(0.082)(0.000)(0.131)Number of observations166813771226616Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 22 Aggregate returns from education for the 2005 SET (ASCED) relative to less than Year 12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.051***0.046**0.101***0.454***(0.000)(0.014)(0.000)(0.000)Number of observations2266221819091581Advanced diploma/diploma0.053***0.0180.066**0.285***(0.001)(0.531)(0.019)(0.000)Number of observations10301002842652Certificate III/IV0.050***-0.033**0.0190.125***(0.000)(0.027)(0.220)(0.000)Number of observations3584347927292268Certificate I/II-0.0030.0480.0470.050(0.870)(0.125)(0.173)(0.144)Number of observations794742581527Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 23 Aggregate returns from education for the 2005 SET (ASCED) relative to less than Year 12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.125***0.143***0.151***0.436***(0.000)(0.000)(0.000)(0.000)Number of observations2684257423241390Advanced diploma/diploma0.087***0.103***0.122***0.240***(0.000)(0.000)(0.000)(0.000)Number of observations12001078934499Certificate III/IV0.123***0.070***0.105***0.110***(0.000)(0.005)(0.000)(0.000)Number of observations155314061208647Certificate I/II0.0330.069**0.100***0.092***(0.107)(0.014)(0.001)(0.008)Number of observations13271118959487Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Conditioning on school completion status In this section, additional analysis that uses definitions of both the treatment and comparison groups which conditions on school completion status is performed. Up to now, qualifications for the treatment group have been defined using the highest level of qualification variable. Two comparison groups were used for the various treatment groupsYear 12 completers and persons with less than Year 12. These comparisons essentially reflect the returns for the highest level of educational qualifications, and not the total package of qualifications (or the route used to get there). For instance, it would be of interest if employers regard any VET qualification (with or without Year 12 qualifications) as being of more value than terminal Year 12 completions. Ryan (2002b) notes that, since completion of Year 12 or of Year 10, in conjunction with a related certificate course, are common prerequisites for entry into associate diploma courses, school completers would be the obvious comparison group for associate diploma graduates. On the other hand, the outcomes of individuals with basic and skilled vocational qualifications are more appropriately compared with individuals who did not complete their schooling. This is because school completion is not a prerequisite for these qualifications and most of those in the Survey of Education and Training data with those qualifications would not have completed the highest level of school. For the estimates provided so far, emphasis should therefore focus on using the comparisons that are most relevant. For example, comparing persons with skilled vocational qualifications with persons who have completed Year 12 might lead to a downward bias on the effects of skilled vocational qualifications because there will be persons in the group with skilled vocational qualifications who have less than Year 12 qualifications (and who are likely to be of lower ability). There is an important alternative to the approach used in Ryan (2002b) in choosing the most appropriate comparison groups for the various VET qualifications. At the moment, estimation of the average treatment effect does not account for the fact that there are individuals in the treatment group with VET qualifications who might or might not have completed Year 12. However, it would be possible to estimate the average treatment effect of VET for Year 12 completers and non-completers separately. In other words, when Year 12 completers are used as the comparison group, Year 12 completers are only compared with VET completers who have also completed Year 12. Similarly, when persons with less than Year 12 are used as the comparison group, persons with less than Year 12 are only compared with VET completers who have also less than Year 12. Estimates of the returns from VET using this alternative way of defining the treatment group are provided in tables 2439. In general, for comparisons relative to Year 12 completers, removing non-completers from the treatment group increases the estimated size of the returns; for comparisons relative to persons with less than Year 12, removing Year 12 completers from the treatment group reduces the estimated size of the impact. Conditioning on Year 12 completion in the treatment and comparison groups Table 24 Aggregate returns from education for the 1997 SET (ABSCQ), males, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.044***0.064***0.076***0.252***(0.000)(0.001)(0.000)(0.000)Number of observations1836178214881293Associate diploma0.0170.145***0.0560.086*(0.554)(0.002)(0.161)(0.051)Number of observations302290270242Skilled vocational qualifications0.0330.0020.0450.043(0.126)(0.953)(0.240)(0.240)Number of observations515503395359Basic vocational qualifications0.004-0.0140.011-0.009(0.889)(0.749)(0.811)(0.859)Number of observations381364294261Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 25 Aggregate returns from education for the 1997 SET (ABSCQ), females, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.052***0.069***0.056***0.272***(0.000)(0.002)(0.006)(0.000)Number of observations1791167516071032Associate diploma0.0050.026-0.0070.059(0.885)(0.627)(0.896)(0.183)Number of observations329296298178Skilled vocational qualifications0.022-0.0200.109-0.098(0.775)(0.854)(0.287)(0.230)Number of observations92867648Basic vocational qualifications-0.0150.0600.0470.010(0.576)(0.113)(0.205)(0.696)Number of observations681594565361Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 26 Aggregate returns from education for the 2001 SET (ABSCQ), males, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.038***-0.0100.048***0.263***(0.000)(0.595)(0.002)(0.000)Number of observations2033200115971431Associate diploma0.0080.0090.0040.132***(0.785)(0.845)(0.931)(0.003)Number of observations327313269246Skilled vocational qualifications0.020-0.0140.0390.022(0.290)(0.692)(0.279)(0.509)Number of observations574566452410Basic vocational qualifications-0.0200.0270.020-0.054(0.563)(0.621)(0.702)(0.299)Number of observations277266226198Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 27 Aggregate returns from education for the 2001 SET (ABSCQ), females, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.063***0.038*0.073***0.280***(0.000)(0.060)(0.000)(0.000)Number of observations2134202119221189Associate diploma0.0580.0280.158***0.028(0.131)(0.593)(0.004)(0.541)Number of observations303280266161Skilled vocational qualifications-0.0110.113*0.065-0.080(0.808)(0.058)(0.283)(0.133)Number of observations251220210156Basic vocational qualifications0.017-0.0500.021-0.005(0.593)(0.237)(0.632)(0.897)Number of observations511444409224Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 28 Aggregate returns from education for the 2001 SET (ASCED), males, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.036***-0.0130.048***0.268***(0.000)(0.502)(0.001)(0.000)Number of observations2037200516071433Advanced diploma/diploma0.0160.0480.0190.165***(0.416)(0.194)(0.558)(0.000)Number of observations595575484420Certificate III/IV0.016-0.0160.0370.039(0.348)(0.619)(0.249)(0.206)Number of observations693678547497Certificate I/II-0.0210.0420.0080.006(0.603)(0.482)(0.895)(0.918)Number of observations234220195166Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 29 Aggregate returns from education for the 2001 SET (ASCED), females, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.068***0.047**0.066***0.263***(0.000)(0.020)(0.001)(0.000)Number of observations2178205919531205Advanced diploma/diploma0.043*0.0130.091***0.024(0.073)(0.691)(0.007)(0.443)Number of observations716669610330Certificate III/IV0.0260.0620.090**-0.040(0.433)(0.159)(0.049)(0.298)Number of observations429384368247Certificate I/II-0.001-0.0500.052-0.051(0.985)(0.313)(0.286)(0.270)Number of observations407340314182Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 30 Aggregate returns from education for the 2005 SET (ASCED), males, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.039***0.067***0.062***0.279***(0.000)(0.001)(0.000)(0.000)Number of observations2063202517421440Advanced diploma/diploma0.052***0.0120.062*0.142***(0.001)(0.738)(0.065)(0.000)Number of observations634623547421Certificate III/IV0.042***0.0210.0390.050(0.007)(0.505)(0.225)(0.121)Number of observations831816676573Certificate I/II0.0070.0650.0360.015(0.844)(0.244)(0.504)(0.811)Number of observations275265224186Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 31 Aggregate returns from education for the 2005 SET (ASCED), females, conditioning on school completion EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.048***0.040**0.092***0.320***(0.000)(0.029)(0.000)(0.000)Number of observations2450234021181299Advanced diploma/diploma0.0230.0130.084**0.117***(0.292)(0.684)(0.011)(0.000)Number of observations790728632358Certificate III/IV0.0330.0100.107***-0.008(0.190)(0.796)(0.007)(0.807)Number of observations607560509310Certificate I/II-0.0310.0520.099*0.035(0.373)(0.296)(0.053)(0.447)Number of observations410347314184Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Conditioning on less than Year 12 in the treatment and comparison groups Table 32 Aggregate returns from education for the 1997 SET (ABSCQ), males, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.0640.0440.0930.357***(0.125)(0.516)(0.120)(0.000)Number of observations199190154130Associate diploma0.0460.112**0.0800.244***(0.219)(0.030)(0.115)(0.000)Number of observations268259230197Skilled vocational qualifications0.084***-0.027*0.040**0.107***(0.000)(0.082)(0.016)(0.000)Number of observations2976288120821852Basic vocational qualifications0.022-0.0000.0000.112***(0.257)(0.995)(0.992)(0.000)Number of observations11751079878747Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 33 Aggregate returns from education for the 1997 SET (ABSCQ), females, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.061-0.0360.0870.374***(0.218)(0.619)(0.194)(0.000)Number of observations22720919298Associate diploma0.0670.216***0.155**0.088(0.244)(0.002)(0.020)(0.159)Number of observations209188190120Skilled vocational qualifications0.095**-0.0530.0250.043(0.017)(0.313)(0.667)(0.497)Number of observations387325273118Basic vocational qualifications0.079***0.0110.0350.059**(0.000)(0.662)(0.171)(0.011)Number of observations169414221334610Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 34 Aggregate returns from education for the 2001 SET (ABSCQ), males, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above-0.0050.0610.079**0.320***(0.859)(0.128)(0.023)(0.000)Number of observations535498393340Associate diploma0.0230.0330.0170.223***(0.488)(0.506)(0.720)(0.000)Number of observations342322256230Skilled vocational qualifications0.057***-0.054***0.033*0.116***(0.000)(0.001)(0.066)(0.000)Number of observations2961285219581746Basic vocational qualifications-0.005-0.065*-0.0500.067*(0.848)(0.079)(0.218)(0.083)Number of observations671593462353Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 35 Aggregate returns from education for the 2001 SET (ABSCQ), females, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.071**0.0290.143***0.258***(0.011)(0.448)(0.000)(0.000)Number of observations697618564272Associate diploma0.148***0.0510.0940.177***(0.002)(0.427)(0.150)(0.002)Number of observations242215210100Skilled vocational qualifications0.080**-0.045-0.030-0.058(0.015)(0.271)(0.496)(0.213)Number of observations574485430188Basic vocational qualifications0.073***0.0360.078***0.056*(0.001)(0.187)(0.007)(0.077)Number of observations140911621041484Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 36 Aggregate returns from education for the 2001 SET (ASCED), males, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.0060.0400.104**0.333***(0.862)(0.500)(0.030)(0.000)Number of observations251241196162Advanced diploma/diploma-0.0100.118**0.102**0.322***(0.745)(0.011)(0.014)(0.000)Number of observations397364298272Certificate III/IV0.058***-0.057***0.0240.114***(0.000)(0.000)(0.160)(0.000)Number of observations3203307721131876Certificate I/II-0.003-0.046-0.0310.045(0.905)(0.252)(0.472)(0.313)Number of observations591522404317Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 37 Aggregate returns from education for the 2001 SET (ASCED), females, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.098**0.0270.184***0.406***(0.020)(0.648)(0.001)(0.000)Number of observations321295267140Advanced diploma/diploma0.089**0.0660.129***0.172***(0.011)(0.142)(0.006)(0.001)Number of observations465407370171Certificate III/IV0.083***-0.0380.0060.003(0.002)(0.268)(0.880)(0.943)Number of observations803681620260Certificate I/II0.076***0.0370.052*0.049(0.001)(0.198)(0.088)(0.154)Number of observations12541030922434Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 38 Aggregate returns from education for the 2005 SET (ASCED), males, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above-0.0070.0530.0870.364***(0.862)(0.429)(0.147)(0.000)Number of observations199192163138Advanced diploma/diploma0.0190.0110.0430.298***(0.503)(0.827)(0.365)(0.000)Number of observations395374293232Certificate III/IV0.036***-0.032*0.0010.113***(0.000)(0.063)(0.977)(0.000)Number of observations2751266020391691Certificate I/II-0.0100.066*0.0110.038(0.696)(0.096)(0.792)(0.389)Number of observations510469357330Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 39 Aggregate returns from education for the 2005 SET (ASCED), females, conditioning on less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsBachelor degree and above0.0300.0940.107*0.415***(0.449)(0.153)(0.077)(0.000)Number of observations256238219118Advanced diploma/diploma0.0260.0550.100*0.171***(0.448)(0.290)(0.054)(0.004)Number of observations403356299152Certificate III/IV0.084***0.0470.104***0.102**(0.000)(0.143)(0.003)(0.010)Number of observations952849699349Certificate I/II0.0300.0360.068*0.066(0.214)(0.295)(0.063)(0.120)Number of observations918769646303Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Returns by field of education, Year 12 as comparison group In this section, as discussed in the methodology section, each VET-related educational qualification is broadly grouped into one of three groups: business; engineering, architecture and building; and other. Examining returns for these smaller subgroups by field of education is useful in helping to provide a sense of the heterogeneity of returns associated with different levels of qualifications. The results in tables 40 to 49 suggest that relative to having a Year 12 qualification, only advanced diploma/diploma qualifications result in positive labour market outcomes. In 2001, males with business advanced diplomas/diplomas had the relatively largest impacts, with an expected earnings premium of 18.8%. The corresponding premium for females in 2001 was 9.9%. In 2005, although the premium for males dropped slightly to 15.3%, females with business advanced diplomas/diplomas saw a growth in their premium to 17.4%. Note that these results are consistent with the aggregate results in tables 10, 12 and 13, where it was suggested that there were positive benefits associated with obtaining advanced diplomas/diplomas, relative to a Year 12 completion. Here, it is further suggested that among the courses available for diplomas, business studies is the field of education that appears to provide the highest return. Table 40 Returns from education for the 1993 SET (ABSCQ) by field of study relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.0280.029-0.0280.152**(0.503)(0.508)(0.615)(0.043)Number of observations164156122106Associate diploma engineering0.039*0.0340.0210.050(0.082)(0.105)(0.513)(0.215)Number of observations550532402320Associate diploma other0.014-0.0080.0550.061(0.641)(0.756)(0.118)(0.227)Number of observations373356287237Skilled vocational qualifications business-0.0220.0370.0730.095(0.556)(0.252)(0.124)(0.165)Number of observations224210170140Skilled vocational qualifications engineering-0.0060.020**-0.003-0.027(0.578)(0.029)(0.868)(0.105)Number of observations3082292321491692Skilled vocational qualifications other0.0060.0080.022-0.046(0.748)(0.640)(0.396)(0.138)Number of observations988927709546Basic vocational qualifications business-0.0100.0450.0600.177*(0.862)(0.403)(0.396)(0.097)Number of observations1141119876Basic vocational qualifications engineering-0.1020.095-0.149-0.103(0.258)(0.192)(0.164)(0.417)Number of observations72626644Basic vocational qualifications other0.002-0.034-0.0210.035(0.963)(0.437)(0.715)(0.586)Number of observations240226186126Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 41 Returns from education for the 1993 SET (ABSCQ) by field of study relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.0730.080-0.107-0.104(0.275)(0.326)(0.211)(0.314)Number of observations13211511266Associate diploma engineering0.1020.3410.235-0.251....Number of observations11986Associate diploma other0.076*0.025-0.001-0.020(0.062)(0.629)(0.978)(0.758)Number of observations350304277146Skilled vocational qualifications business0.0890.0490.0990.061(0.104)(0.513)(0.173)(0.357)Number of observations19317214789Skilled vocational qualifications engineering0.1220.0560.0520.167(0.607)(0.803)(0.847)(0.624)Number of observations26242416Skilled vocational qualifications other0.058*-0.038-0.0210.053(0.070)(0.351)(0.621)(0.215)Number of observations624527444172Basic vocational qualifications business0.014-0.0350.0060.007(0.587)(0.284)(0.863)(0.807)Number of observations936763746344Basic vocational qualifications engineering0.049-0.425-0.496-0.455....Number of observations9894Basic vocational qualifications other0.059*-0.0600.045-0.066(0.065)(0.144)(0.246)(0.144)Number of observations625522507202Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 42 Returns from education for the 1997 SET (ABSCQ) by field of study relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.0260.0950.0810.067(0.567)(0.169)(0.159)(0.344)Number of observations149144128112Associate diploma engineering0.0380.141***0.0680.095*(0.211)(0.006)(0.143)(0.053)Number of observations250248212196Associate diploma other0.0030.127**-0.0050.039(0.946)(0.046)(0.936)(0.550)Number of observations169158152128Skilled vocational qualifications business0.076-0.0420.0730.040(0.272)(0.732)(0.709)(0.795)Number of observations64623432Skilled vocational qualifications engineering0.014-0.0020.015-0.071***(0.130)(0.887)(0.368)(0.000)Number of observations3072298621231905Skilled vocational qualifications other0.0050.0580.048-0.081*(0.858)(0.208)(0.307)(0.087)Number of observations355338288248Basic vocational qualifications business-0.0040.104**0.0710.065(0.918)(0.042)(0.179)(0.293)Number of observations278260218196Basic vocational qualifications engineering-0.045*-0.0030.006-0.055(0.050)(0.926)(0.882)(0.176)Number of observations591560422369Basic vocational qualifications other-0.047*-0.005-0.067*-0.077**(0.055)(0.885)(0.064)(0.049)Number of observations687624520428Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 43 Returns from education for the 1997 SET (ABSCQ) by field of study relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.0110.166***0.032-0.033(0.798)(0.006)(0.566)(0.462)Number of observations235213220156Associate diploma engineering-0.3420.2800.1920.233(0.167)(0.442)(0.466).Number of observations28232615Associate diploma other-0.014-0.004-0.0730.050(0.750)(0.945)(0.216)(0.362)Number of observations271243239118Skilled vocational qualifications business0.1000.1740.0930.005(0.446)(0.357)(0.643)(0.981)Number of observations46433824Skilled vocational qualifications engineering-0.027-0.028-0.007-0.305(0.831)(0.882)(0.972)(0.321)Number of observations54453921Skilled vocational qualifications other-0.044-0.149***-0.092-0.127**(0.224)(0.004)(0.102)(0.012)Number of observations380319269118Basic vocational qualifications business-0.0290.040-0.003-0.037**(0.109)(0.107)(0.892)(0.043)Number of observations153513201254693Basic vocational qualifications engineering-0.007-0.054-0.039-0.086(0.940)(0.722)(0.800)(0.699)Number of observations68585222Basic vocational qualifications other-0.067**-0.087**-0.142***-0.093***(0.011)(0.018)(0.000)(0.002)Number of observations772640586254Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 44 Returns from education for the 2001 SET (ABSCQ) by field of study relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.0350.0260.0380.054(0.376)(0.707)(0.539)(0.436)Number of observations180174144132Associate diploma engineering-0.017-0.0080.0000.126**(0.612)(0.883)(0.994)(0.017)Number of observations270261200190Associate diploma other-0.0350.045-0.0570.032(0.374)(0.478)(0.337)(0.610)Number of observations216197181152Skilled vocational qualifications business-0.019-0.223-0.046-0.048(0.818)(0.120)(0.855)(0.863)Number of observations62582925Skilled vocational qualifications engineering0.003-0.085***-0.026-0.064***(0.692)(0.000)(0.114)(0.000)Number of observations2945286519851804Skilled vocational qualifications other-0.009-0.061-0.033-0.163***(0.692)(0.134)(0.411)(0.000)Number of observations505480377315Basic vocational qualifications business-0.0270.035-0.011-0.083(0.483)(0.589)(0.855)(0.200)Number of observations216199165144Basic vocational qualifications engineering-0.077*-0.086-0.022-0.016(0.054)(0.135)(0.738)(0.779)Number of observations274245186156Basic vocational qualifications other-0.063**-0.081*-0.103**-0.110**(0.032)(0.075)(0.029)(0.020)Number of observations457401320248Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 45 Returns from education for the 2001 SET (ABSCQ) by field of study relative to Year 12 completers, females EmploymentFull-time/part-time employmentPermanent/casual employmentLog weekly earningsAssociate diploma business0.0640.131**0.117**0.050(0.136)(0.020)(0.047)(0.241)Number of observations262235228142Associate diploma engineering0.1510.0870.093-0.072(0.383)(0.786)(0.738)(0.891)Number of observations29272615Associate diploma other0.061-0.122**-0.0170.024(0.140)(0.040)(0.787)(0.701)Number of observations258236218103Skilled vocational qualifications business-0.0070.139**0.024-0.111*(0.892)(0.045)(0.739)(0.069)Number of observations184162160115Skilled vocational qualifications engineering-0.0180.027-0.048-0.068(0.838)(0.841)(0.785)(0.646)Number of observations68584427Skilled vocational qualifications other-0.040-0.124***-0.109**-0.183***(0.180)(0.002)(0.011)(0.000)Number of observations571483431196Basic vocational qualifications business-0.0210.0460.018-0.092***(0.323)(0.104)(0.547)(0.004)Number of observations11761000856473Basic vocational qualifications engineering-0.154-0.018-0.366-0.336(0.482)(0.968)(0.552).Number of observations3324236Basic vocational qualifications other-0.034-0.078**-0.080**-0.048(0.210)(0.041)(0.044)(0.219)Number of observations703569527232Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 46 Returns from education for the 2001 SET (ASCED) by field of education relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.0020.0370.0390.172***(0.958)(0.511)(0.388)(0.001)Number of observations289271220202Advanced diploma/diploma engineering0.0080.0800.0230.138***(0.769)(0.107)(0.568)(0.002)Number of observations326313256238Advanced diploma/diploma other-0.0270.050-0.0020.086*(0.343)(0.299)(0.965)(0.060)Number of observations368344293246Certificate III/IV qualifications business-0.014-0.069-0.028-0.059(0.753)(0.382)(0.688)(0.467)Number of observations16014610090Certificate III/IV qualifications engineering0.005-0.082***-0.037**-0.063***(0.557)(0.000)(0.019)(0.000)Number of observations3131304920971910Certificate III/IV qualifications other-0.019-0.044-0.064*-0.150***(0.373)(0.236)(0.088)(0.000)Number of observations571539441364Certificate I/II qualifications business-0.126-0.145-0.029-0.369(0.518)(0.702)..Number of observations2724148Certificate I/II qualifications engineering-0.155-0.406***-0.505**-0.130(0.170)(0.010)(0.013)(0.803)Number of observations66504522Certificate I/II qualifications other-0.053**-0.020-0.025-0.113***(0.020)(0.562)(0.479)(0.001)Number of observations730665535442Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 47 Returns from education for the 2001 SET (ASCED) by field of education relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.065*0.118**0.125***0.094**(0.073)(0.027)(0.008)(0.043)Number of observations310292276182Advanced diploma/diploma engineering0.0260.0680.1020.105(0.830)(0.742)(0.668)(0.836)Number of observations40383122Advanced diploma/diploma other0.002-0.0490.045-0.027(0.920)(0.129)(0.191)(0.468)Number of observations814733641285Certificate III/IV qualifications business-0.0140.135***0.082-0.020(0.703)(0.006)(0.113)(0.632)Number of observations339294290198Certificate III/IV qualifications engineering-0.0070.0870.033-0.073(0.922)(0.449)(0.793)(0.531)Number of observations90786242Certificate III/IV qualifications other-0.014-0.123***-0.109***-0.144***(0.552)(0.000)(0.002)(0.000)Number of observations800675607263Certificate I/II qualifications business-0.077-0.025-0.192**-0.032(0.270)(0.804)(0.046)(0.757)Number of observations1241008846Certificate I/II qualifications engineering-0.000-0.114-0.3560.129....Number of observations1610102Certificate I/II qualifications other-0.029-0.010-0.026-0.090***(0.118)(0.709)(0.342)(0.002)Number of observations152212541115559Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 48 Returns from education for the 2005 SET (ASCED) by field of education relative to Year 12 completers, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.0430.0800.0270.142***(0.125)(0.131)(0.598)(0.008)Number of observations322312267217Advanced diploma/diploma engineering0.0430.0080.0110.064(0.166)(0.877)(0.815)(0.265)Number of observations272270244181Advanced diploma/diploma other0.037-0.0620.0150.065(0.102)(0.173)(0.722)(0.199)Number of observations427413323253Certificate III/IV qualifications business0.067**0.0700.0840.030(0.028)(0.230)(0.125)(0.656)Number of observations245243202174Certificate III/IV qualifications engineering0.042***-0.0180.000-0.029(0.000)(0.294)(0.979)(0.128)Number of observations2713263820301633Certificate III/IV qualifications other0.0100.046-0.013-0.112***(0.656)(0.210)(0.725)(0.004)Number of observations625600494426Certificate I/II qualifications business0.0610.121*0.0860.007(0.152)(0.073)(0.146)(0.925)Number of observations199192158138Certificate I/II qualifications engineering0.0120.0640.054-0.121**(0.717)(0.224)(0.321)(0.045)Number of observations309297222212Certificate I/II qualifications other-0.095**0.025-0.078-0.039(0.014)(0.670)(0.202)(0.522)Number of observations275249201175Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 49 Returns from education for the 2005 SET (ASCED) by field of education relative to Year 12 completers, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.0500.092*0.160***0.160***(0.182)(0.076)(0.002)(0.002)Number of observations313285253171Advanced diploma/diploma engineering0.0110.382-0.0360.194(0.979)(0.593)(0.942).Number of observations25262617Advanced diploma/diploma other0.010-0.0180.064*0.128***(0.644)(0.587)(0.053)(0.001)Number of observations857764652316Certificate III/IV qualifications business0.051*0.161***0.173***0.019(0.059)(0.000)(0.000)(0.527)Number of observations551511461330Certificate III/IV qualifications engineering0.061-0.020-0.010-0.053(0.370)(0.849)(0.935)(0.763)Number of observations94908034Certificate III/IV qualifications other0.004-0.096***-0.016-0.087**(0.869)(0.003)(0.659)(0.018)Number of observations910804667294Certificate I/II qualifications business-0.0220.0050.061*0.023(0.315)(0.878)(0.067)(0.504)Number of observations933806698355Certificate I/II qualifications engineering0.007-0.234-0.040-0.707(0.966)(0.517)(0.925).Number of observations3125225Certificate I/II qualifications other-0.085**-0.063-0.001-0.084(0.026)(0.269)(0.988)(0.158)Number of observations354280236119Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Returns by field of education, less than Year 12 as comparison group We repeat the empirical exercise conducted in the previous section, but this time using persons with less than 12 years of schooling as the comparison group. Recall that earlier we found that obtaining any kind of VET qualification (even basic vocational qualifications [ABSCQ] or certificate I/II [ASCED]) led to relatively better labour market outcomes by comparison with those who had less than Year 12. The results in tables 50 to 59 aim to provide more information regarding the returns associated with different fields of study at each level of qualification. In 1993, business studies dominated all fields in terms of providing the largest earnings impacts, regardless of whether the VET qualification in question was an associate diploma, skilled or basic vocational qualification (tables 50 and 51). However, in 1997, engineering, architecture, building and automotive studies led to the highest returns on earnings for males with associate diplomas (table 52). Returns for both these fields of study similarly dominated the other field of education category in 2001 and 2005. Overall, it therefore appears that, for persons with less than a Year 12 qualification, positive returns can be expected from undertaking business studies or specific trade studies (engineering, architecture, building and automotive). In the most recent year when Survey of Education and Training data are available (2005), for qualifications below the diploma level, there were no positive labour market returns from obtaining qualifications in the non-trade fields of study (for example, agriculture, creative arts, education, health, hospitality, society and culture etc.) for males. However, for females, it appears that certificate I/II business qualifications led to an earnings premium of 13.0%; the associated impact of full-time/part-time employment was also a positive 12.1%. Table 50 Returns from education for the 1993 SET (ABSCQ) by field of study relative to less than Year12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.116**0.0200.0470.297***(0.025)(0.649)(0.478)(0.000)Number of observations163155121106Associate diploma engineering0.103***0.0240.0410.210***(0.000)(0.224)(0.226)(0.000)Number of observations552533401319Associate diploma other0.112***-0.0020.088**0.202***(0.001)(0.936)(0.021)(0.000)Number of observations374355287237Skilled vocational qualifications business0.071*0.0290.0630.181***(0.099)(0.370)(0.202)(0.008)Number of observations224209169140Skilled vocational qualifications engineering0.098***0.020**0.045***0.082***(0.000)(0.028)(0.004)(0.000)Number of observations3081292421501691Skilled vocational qualifications other0.098***0.0130.045*0.084***(0.000)(0.445)(0.092)(0.009)Number of observations987928710548Basic vocational qualifications business0.0950.0160.0450.223**(0.163)(0.747)(0.550)(0.028)Number of observations1131119876Basic vocational qualifications engineering-0.0450.087-0.0970.035(0.662)(0.195)(0.397)(0.797)Number of observations72626644Basic vocational qualifications other0.099**-0.053-0.0250.145**(0.031)(0.205)(0.667)(0.034)Number of observations240225185126Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 51 Returns from education for the 1993 SET (ABSCQ) by field of study relative to less than Year12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.0850.103-0.0310.096(0.227)(0.208)(0.732)(0.375)Number of observations13111611270Associate diploma engineering0.0700.3210.2500.142....Number of observations111075Associate diploma other0.105**0.0670.0450.054(0.012)(0.204)(0.396)(0.406)Number of observations350304278146Skilled vocational qualifications business0.132**0.0680.0970.223***(0.018)(0.352)(0.190)(0.004)Number of observations19317214890Skilled vocational qualifications engineering0.1510.1940.0700.258(0.550)(0.471)(0.808).Number of observations26242215Skilled vocational qualifications other0.112***0.0010.0060.133***(0.001)(0.975)(0.899)(0.004)Number of observations624525441172Basic vocational qualifications business0.075***0.0030.071**0.094***(0.005)(0.922)(0.034)(0.006)Number of observations934762743341Basic vocational qualifications engineering0.080-0.045-0.444-0.085....Number of observations97104Basic vocational qualifications other0.098***-0.0400.087**0.046(0.002)(0.338)(0.030)(0.338)Number of observations628521505204Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 52 Returns from education for the 1997 SET (ABSCQ) by field of study relative to less than Year12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.0810.136*0.122*0.248***(0.115)(0.052)(0.062)(0.000)Number of observations150144130112Associate diploma engineering0.114***0.127**0.109**0.300***(0.002)(0.013)(0.025)(0.000)Number of observations250247216197Associate diploma other0.0600.0830.0670.219***(0.251)(0.197)(0.305)(0.000)Number of observations170158152128Skilled vocational qualifications business0.123-0.0360.1110.209(0.137)(0.790)(0.589)(0.219)Number of observations64623432Skilled vocational qualifications engineering0.089***-0.028*0.042**0.125***(0.000)(0.064)(0.011)(0.000)Number of observations3072298521551932Skilled vocational qualifications other0.092***0.0410.079*0.072(0.010)(0.356)(0.092)(0.102)Number of observations356337288248Basic vocational qualifications business0.0390.117**0.0550.216***(0.337)(0.029)(0.307)(0.000)Number of observations278259215194Basic vocational qualifications engineering0.035-0.0190.0380.119***(0.197)(0.606)(0.310)(0.002)Number of observations591559441386Basic vocational qualifications other0.027-0.029-0.0260.077**(0.309)(0.395)(0.481)(0.042)Number of observations687623519428Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 53 Returns from education for the 1997 SET (ABSCQ) by field of study relative to less than Year12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.140***0.205***0.168***0.109**(0.006)(0.001)(0.005)(0.038)Number of observations239218219158Associate diploma engineering-0.1040.2700.3080.325(0.707)(0.435)(0.249).Number of observations27242615Associate diploma other0.095*0.0620.0650.152**(0.051)(0.320)(0.294)(0.021)Number of observations271243242122Skilled vocational qualifications business0.1780.2260.1790.115(0.173)(0.234)(0.402)(0.576)Number of observations46434026Skilled vocational qualifications engineering0.1230.0170.1330.018(0.361)(0.927)(0.529)(0.951)Number of observations54484021Skilled vocational qualifications other0.102**-0.0750.0490.015(0.011)(0.147)(0.404)(0.794)Number of observations379320269118Basic vocational qualifications business0.093***0.077***0.100***0.100***(0.000)(0.002)(0.000)(0.000)Number of observations153613221269695Basic vocational qualifications engineering0.126-0.0400.0590.025(0.259)(0.800)(0.707)(0.915)Number of observations68585222Basic vocational qualifications other0.077***-0.0320.0110.041(0.008)(0.394)(0.769)(0.258)Number of observations771638585253Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 54 Returns from education for the 2001 (ABSCQ) SET by field of study relative to less than Year12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.076*0.119*0.0900.298***(0.093)(0.086)(0.210)(0.000)Number of observations182174144132Associate diploma engineering0.0280.0370.0750.330***(0.456)(0.496)(0.135)(0.000)Number of observations272261200189Associate diploma other0.0390.0730.0020.241***(0.390)(0.251)(0.980)(0.000)Number of observations216200182154Skilled vocational qualifications business0.043-0.218*-0.002-0.087(0.645)(0.099)(0.993)(0.808)Number of observations64593025Skilled vocational qualifications engineering0.069***-0.044***0.046***0.150***(0.000)(0.007)(0.009)(0.000)Number of observations2965288020021811Skilled vocational qualifications other0.061**-0.0240.0520.006(0.027)(0.567)(0.234)(0.881)Number of observations507481377316Basic vocational qualifications business0.0490.0680.0430.126*(0.270)(0.293)(0.501)(0.065)Number of observations219206168146Basic vocational qualifications engineering0.024-0.043-0.0140.146**(0.608)(0.447)(0.838)(0.011)Number of observations274245190156Basic vocational qualifications other0.016-0.062-0.0460.037(0.638)(0.173)(0.337)(0.421)Number of observations454407330252Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 55 Returns from education for the 2001 (ABSCQ) SET by field of study relative to less than Year12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAssociate diploma business0.219***0.142**0.171***0.198***(0.000)(0.018)(0.004)(0.000)Number of observations260235227143Associate diploma engineering0.3300.1120.0920.182(0.170)(0.714)(0.794)(0.700)Number of observations30282615Associate diploma other0.158***-0.0500.0530.105*(0.001)(0.411)(0.413)(0.066)Number of observations258235215104Skilled vocational qualifications business0.154**0.167**0.159**0.054(0.010)(0.018)(0.031)(0.313)Number of observations186161162116Skilled vocational qualifications engineering0.106-0.0050.0320.034(0.326)(0.970)(0.864)(0.845)Number of observations68604527Skilled vocational qualifications other0.081**-0.060-0.010-0.083*(0.014)(0.146)(0.826)(0.080)Number of observations571483434196Basic vocational qualifications business0.092***0.081***0.124***0.054*(0.000)(0.005)(0.000)(0.100)Number of observations11871008890478Basic vocational qualifications engineering-0.126-0.066-0.1520.162(0.510)(0.847)(0.691).Number of observations3926257Basic vocational qualifications other0.123***-0.0510.074*0.072*(0.000)(0.180)(0.065)(0.073)Number of observations704580542224Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 56 Returns from education for the 2001 (ASCED) SET by field of education relative to less than Year 12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.0210.144***0.131**0.405***(0.555)(0.010)(0.012)(0.000)Number of observations289271220202Advanced diploma/diploma engineering0.056*0.128**0.120***0.359***(0.083)(0.011)(0.007)(0.000)Number of observations327315262240Advanced diploma/diploma other0.0200.0450.0630.270***(0.535)(0.343)(0.168)(0.000)Number of observations365344292244Certificate III/IV qualifications business0.040-0.0460.0700.154*(0.406)(0.547)(0.412)(0.069)Number of observations16115010090Certificate III/IV qualifications engineering0.073***-0.051***0.038**0.145***(0.000)(0.001)(0.026)(0.000)Number of observations3158306621181915Certificate III/IV qualifications other0.051**-0.0030.0320.009(0.049)(0.930)(0.435)(0.803)Number of observations571539441364Certificate I/II qualifications business0.047-0.0530.252-0.099(0.823)(0.878)..Number of observations27241511Certificate I/II qualifications engineering-0.100-0.282*-0.376**0.279(0.430)(0.090)(0.030)(0.445)Number of observations65504622Certificate I/II qualifications other0.024-0.0030.0090.071**(0.342)(0.940)(0.797)(0.042)Number of observations725662535447Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 57 Returns from education for the 2001 (ASCED) SET by field of education relative to less than Year 12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.203***0.182***0.271***0.219***(0.000)(0.001)(0.000)(0.000)Number of observations309291276182Advanced diploma/diploma engineering0.1290.1040.2830.081(0.483)(0.642)(0.294).Number of observations42383221Advanced diploma/diploma other0.123***-0.0030.113***0.164***(0.000)(0.928)(0.001)(0.000)Number of observations821739662295Certificate III/IV qualifications business0.176***0.163***0.166***0.044(0.000)(0.002)(0.001)(0.304)Number of observations342293294198Certificate III/IV qualifications engineering0.1540.0790.0320.003(0.102)(0.499)(0.822)(0.980)Number of observations90806642Certificate III/IV qualifications other0.096***-0.087**0.031-0.011(0.000)(0.010)(0.389)(0.772)Number of observations800689628263Certificate I/II qualifications business0.0210.137-0.0220.099(0.780)(0.192)(0.833)(0.262)Number of observations1241009050Certificate I/II qualifications engineering-0.0870.2370.257-0.136(0.880)...Number of observations16994Certificate I/II qualifications other0.098***0.0300.114***0.043(0.000)(0.250)(0.000)(0.144)Number of observations152712681126560Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 58 Returns from education for the 2005 SET (ASCED) by field of education relative to less than Year 12, males EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.053*0.101*0.0740.366***(0.077)(0.054)(0.173)(0.000)Number of observations320312267218Advanced diploma/diploma engineering0.0480.0580.0830.282***(0.128)(0.283)(0.111)(0.000)Number of observations278271247182Advanced diploma/diploma other0.072***-0.084*0.0460.209***(0.005)(0.058)(0.321)(0.000)Number of observations430417327252Certificate III/IV qualifications business0.058*0.0620.106*0.130*(0.071)(0.290)(0.062)(0.056)Number of observations246242204172Certificate III/IV qualifications engineering0.048***-0.042**0.0110.157***(0.000)(0.013)(0.530)(0.000)Number of observations2702263220231670Certificate III/IV qualifications other0.045*0.0040.0070.001(0.054)(0.904)(0.863)(0.975)Number of observations625600494425Certificate I/II qualifications business0.0320.0700.167***0.120(0.442)(0.283)(0.007)(0.110)Number of observations200191157136Certificate I/II qualifications engineering0.0330.0600.0420.050(0.313)(0.237)(0.439)(0.386)Number of observations314297221212Certificate I/II qualifications other-0.072*0.047-0.0570.035(0.071)(0.411)(0.365)(0.564)Number of observations280248202174Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 59 Returns from education for the 2005 SET (ASCED) by field of education relative to less than Year 12, females EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earningsAdvanced diploma/diploma business0.152***0.206***0.196***0.236***(0.001)(0.000)(0.000)(0.000)Number of observations314283253168Advanced diploma/diploma engineering0.1620.249-0.0620.072(0.521)(0.463)(0.878).Number of observations26262418Advanced diploma/diploma other0.065***0.0520.091***0.245***(0.007)(0.122)(0.009)(0.000)Number of observations859767653315Certificate III/IV qualifications business0.150***0.236***0.237***0.114***(0.000)(0.000)(0.000)(0.001)Number of observations553505458319Certificate III/IV qualifications engineering0.161**0.0210.0100.092(0.041)(0.851)(0.937)(0.510)Number of observations94887834Certificate III/IV qualifications other0.096***-0.0190.0380.102**(0.000)(0.564)(0.296)(0.026)Number of observations912802664306Certificate I/II qualifications business0.064***0.114***0.106***0.122***(0.008)(0.001)(0.002)(0.002)Number of observations940807700355Certificate I/II qualifications engineering-0.028-0.226-0.165-0.088(0.881)(0.505)(0.706).Number of observations3426227Certificate I/II qualifications other-0.034-0.0140.0140.129(0.407)(0.810)(0.820)(0.107)Number of observations353281238126Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Outcomes for mature-age students The analysis of returns from education thus far has focused on the average person. Most people obtain their educational qualifications early in life, following the standard route of completing high school and then moving onto vocational or higher education. However, there is also a significant proportion of individuals in the Australian population who left school prior to Year 12, or just after completing Year 12, and who immediately joined the workforce. These individuals might at some point consider gaining higher qualifications or re-skilling. Research on the labour market returns from education at mature ages is rather sparse, both in Australia and overseas. Two studies in Australia do attempt to analyse this issue. Headey and Warren (2008) compare changes in earnings of individuals who do and do not undertake some further education over the period 2000 to 2005. They find that those who do undertake some further education have larger earnings gains over this period, particularly those who undertook the education early in that period. They interpret this as some evidence that it may take some time for education to pay off. Karmel and Woods (2004) investigate the effect of obtaining formal qualifications later in life on employment rates and the probability of working full-time. They find that education later in life is associated with as good or even better employment outcomes than those obtaining education earlier in life, particularly for females. Sub-diploma qualifications do not have a positive effect on employment rates, however. The authors employ the 2001 Survey of Education and Training in their analysis. They did not look at earnings, only employment rates and the probability of working full-time. International studies of the returns from mature-age education have found a variety of effects. Studies of delaying post-secondary study from straight after high school until later, but still during the twenties age range in the United States and the United Kingdom found essentially no negative effects of delay. In other words, earnings were just as high at around age 30 years for those who delayed as for those that did not. These studies include Blundell et al. (2000) in the United Kingdom, and Light (1995) and Leigh and Gill (1997) in the United States. Delay of study to the thirties age range, however, resulted in very little earnings benefits of further education in the UK (Jenkins et al. 2003; Silles 2007). Earnings by age 42 years were found to be the same for those who undertook further education as those that did not. Jenkins et al. (2003) did find, however, that education during an individuals thirties did increase the probability of being employed at aged 42 if the individual was not employed at aged 33 years. Jacobson, LaLonde and Sullivan (2005) found that there were earnings returns from undertaking vocational-type education at community colleges in the US among workers who were displaced (made redundant). Zhang and Palameta (2006) found earnings gains for workers who completed qualifications in Canada at mature ages. The results in this section attempt to shed more light on this important policy issue. Specifically, we ask what the returns from VET qualifications in Australia are for individuals who obtained their qualifications later in life. Such training or skills upgrading could be viewed as an attempt to provide a form of employment-protection insurance. In order to empirically implement this using the Survey of Education and Training data, we use information on age and when they obtained qualifications to create different subgroups, and perform matching on those subgroups. For example, using the 1997 Survey of Education and Training data, in order to compute zero to two-year impacts of VET for individuals who are currently aged 3064 years (that is, the time between 1997, when the survey was conducted, and 199597, the period when they obtained their qualifications), we can set the treatment group as 30 to 64-year-olds who completed their VET qualifications some time between 1995 and 1997, with the comparison group as 30 to 64-year-olds who have no qualifications, and estimate differences in outcomes in 1997. Similarly, in order to estimate three-to-seven year impacts of VET for individuals who are currently aged 3064 years (that is, the time between 1997 and 199094), we can set the treatment group as 30 to 64-year-olds who completed their VET qualifications some time between 1990 and 1994, and the comparison group as 30 to 64-year-olds who have no qualifications, and estimate differences in outcomes in 1997. We focus on persons in the 30 to 64 years age group to estimate between one to eight years of follow-up impacts in each of the Survey of Education and Training data sets because of sample size constraints and the way information on the date qualifications was collected in the data (otherwise we would use finer age breakdowns and follow-up periods). In theory, the survey design allows us to obtain long-term impact estimates for a variety of age ranges. But in practice, we are constrained by the sample sizes. When sample sizes are small, any estimates that are obtained are likely to be unreliable. In this section, we only focus on sub-diploma VET qualifications because sample sizes do not permit us to create a large enough sample of mature-age students with diploma qualifications. We also pool males and females together due to sample size constraints. Note that as the sample sizes employed in this section are small, all results should be interpreted with caution. Returns for mature-age students, Year 12 as comparison group Recall that, when examining the average returns for all students, we found that there was no benefit in obtaining a basic or skilled vocational qualification (ABSCQ) or a certificate I to IV qualification (ASCED) if a Year 12 qualification was already held. Similarly, the results in this section suggest that, for mature-age students, there is no benefit to be expected from obtaining sub-diploma VET qualifications. The impact estimates in tables 60 to 69 suggest that, in the majority of outcomes examined, mature-age students can expect a negative outcome relative to the counterfactual scenario of not pursuing any higher education after completing high school. For example, in 2005, the one-to-two year follow-up impact for average log weekly earnings for a certificate III/IV qualification was -10.7% (see table 64). Furthermore, the longer run three-to-five-year follow-up impact was also still negative (-5.5%), although this was not statistically significant. Therefore, for persons with a Year 12 qualification who are considering obtaining sub-diploma VET qualifications, the tentative conclusion appears to be that one should not expect any positive labour market outcomes to arise as a result of obtaining those qualifications. Table 60 Mature-age returns from education for the 1993 SET (ABSCQ) relative to Year 12 completers EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings13 years follow-upSkilled vocational qualifications-0.094-0.082-0.117-0.056(0.235)(0.332)(0.236)(0.678)Number of observations84726437Basic vocational qualifications-0.0960.032-0.0440.056(0.247)(0.780)(0.697)(0.705)Number of observations11078784248 years follow-upSkilled vocational qualifications-0.0290.026-0.016-0.040(0.482)(0.545)(0.752)(0.499)Number of observations242222187130Basic vocational qualifications0.054-0.044-0.0700.091(0.285)(0.495)(0.296)(0.243)Number of observations19017014790Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 61 Mature-age returns from education for the 1997 SET (ABSCQ) relative to Year 12 completers EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings13 years follow-upSkilled vocational qualifications0.0130.1070.048-0.166(0.902)(0.461)(0.763)(0.286)Number of observations48463527Basic vocational qualifications-0.0410.044-0.121*-0.142*(0.372)(0.527)(0.068)(0.055)Number of observations21517917411047 years follow-upSkilled vocational qualifications-0.0220.0790.020-0.084(0.648)(0.320)(0.802)(0.316)Number of observations13613410886Basic vocational qualifications-0.078**0.020-0.042-0.064(0.013)(0.673)(0.361)(0.169)Number of observations429371328209Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 62 Mature-age returns from education for the 2001 SET (ABSCQ) relative to Year 12 completers EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings12 years follow-upSkilled vocational qualifications0.0670.051-0.177-0.328(0.459)(0.729)(0.241)(0.129)Number of observations62605429Basic vocational qualifications-0.050-0.125-0.164-0.072(0.549)(0.215)(0.132)(0.649)Number of observations10486804037 years follow-upSkilled vocational qualifications0.016-0.107-0.102-0.186***(0.700)(0.104)(0.128)(0.008)Number of observations23221117896Basic vocational qualifications-0.021-0.006-0.027-0.130**(0.545)(0.903)(0.603)(0.015)Number of observations371325284172Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 63 Mature-age returns from education for the 2001 SET (ASCED) relative to Year 12 completers EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings12 years follow-upCertificate III/IV0.0370.008-0.130-0.275***(0.587)(0.936)(0.183)(0.003)Number of observations108989456Certificate I/II-0.180-0.227-0.219-0.494(0.335)(0.388)(0.434).Number of observations4230311837 years follow-upCertificate III/IV-0.017-0.076-0.057-0.058(0.634)(0.154)(0.267)(0.308)Number of observations357321286156Certificate I/II-0.0050.014-0.077-0.183***(0.907)(0.824)(0.237)(0.009)Number of observations252218196120Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 64 Mature-age returns from education for the 2005 SET (ASCED) relative to Year 12 completers EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings12 years follow-upCertificate III/IV0.0110.0910.049-0.113(0.808)(0.211)(0.477)(0.143)Number of observations178168158104Certificate I/II-0.2630.265-0.294-0.378(0.194)(0.471)(0.738)(0.602)Number of observations3828212035 years follow-upCertificate III/IV0.049*0.0030.050-0.057(0.071)(0.949)(0.225)(0.234)Number of observations497472386264Certificate I/II-0.019-0.040-0.026-0.113(0.742)(0.658)(0.785)(0.248)Number of observations13312210466Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Returns for mature-age students, less than Year 12 as comparison group When the comparison group used are persons with less than 12 years of schooling (see tables 65 to 69) instead of Year 12 completers, the results change considerably. Specifically, there appear to be some longer-term positive impacts on earnings and employment from obtaining VET qualifications. In 2001 and 2005, for example, the estimated impacts over the longer term (three to seven or three tofive years of follow-up respectively) for average log weekly earnings are positive and statistically significant. In 2001, the premium was 15.6%. In 2005, the return was 10.8%. Furthermore, using theolder ABSCQ classification scheme, in 2001 obtaining basic vocational qualifications led to a 6.4percentage point increase in the probability of being employed and a 9.4 percentage point increase in the probability of being in permanent employment (table 67). However, keep in mind that, given the generally small sample sizes for the estimates obtained in this section, these results should be interpreted with caution. More work on the effects of education and training on mature-age workers in Australia remains to be done before evidence-based policy for this important subgroup of the population can properly be formulated. Table 65 Mature-age returns from education for the 1993 SET (ABSCQ) relative to less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings13 years follow-upSkilled vocational qualifications0.0280.014-0.0140.056(0.757)(0.855)(0.895)(0.696)Number of observations84726438Basic vocational qualifications-0.0210.0490.0020.090(0.810)(0.673)(0.986)(0.458)Number of observations10978804248 years follow-upSkilled vocational qualifications0.0640.0620.0660.135*(0.175)(0.153)(0.239)(0.078)Number of observations242222187130Basic vocational qualifications0.100*0.0130.0480.184**(0.063)(0.836)(0.511)(0.023)Number of observations18917014890Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 66 Mature-age returns from education for the 1997 SET (ABSCQ) relative to less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings13 years follow-upSkilled vocational qualifications0.1260.0750.1010.084(0.308)(0.638)(0.571)(0.638)Number of observations48453627Basic vocational qualifications0.0520.082-0.0080.057(0.311)(0.233)(0.904)(0.433)Number of observations21517917310947 years follow-upSkilled vocational qualifications0.0970.0650.0770.152*(0.116)(0.408)(0.369)(0.066)Number of observations13513410782Basic vocational qualifications0.0220.0320.0500.124***(0.543)(0.500)(0.292)(0.009)Number of observations430371327210Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 67 Mature-age returns from education for the 2001 SET (ABSCQ) relative to less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings12 years follow-upSkilled vocational qualifications0.100-0.039-0.090-0.156(0.350)(0.785)(0.541)(0.437)Number of observations62605430Basic vocational qualifications-0.031-0.022-0.0360.146(0.701)(0.844)(0.730)(0.338)Number of observations10685804037 years follow-upSkilled vocational qualifications0.072-0.0750.0160.060(0.106)(0.260)(0.819)(0.426)Number of observations23221117895Basic vocational qualifications0.064*0.0720.094*0.046(0.086)(0.152)(0.067)(0.398)Number of observations373327290172Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 68 Mature-age returns from education for the 2001 SET (ASCED) relative to less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings12 years follow-upCertificate III/IV0.066-0.001-0.049-0.039(0.363)(0.996)(0.627)(0.697)Number of observations107989456Certificate I/II-0.076-0.0060.0030.126(0.672)(0.986)(0.991).Number of observations4230311737 years follow-upCertificate III/IV0.031-0.0300.0450.156***(0.412)(0.570)(0.391)(0.008)Number of observations357321286156Certificate I/II0.082*0.0440.061-0.013(0.085)(0.481)(0.343)(0.841)Number of observations260225199120Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Table 69 Mature-age returns from education for the 2005 SET (ASCED) relative to less than Year 12 EmploymentFull-time/ part-time employmentPermanent/ casual employmentLog weekly earnings12 years follow-upCertificate III/IV0.0730.0660.0480.114(0.128)(0.359)(0.480)(0.124)Number of observations179170160104Certificate I/II-0.1980.1820.111-0.145(0.290)(0.526)(0.789)(0.856)Number of observations3828221935 years follow-upCertificate III/IV0.074***0.0450.091**0.114**(0.009)(0.307)(0.038)(0.022)Number of observations498472388263Certificate I/II-0.0050.060-0.001-0.018(0.931)(0.507)(0.995)(0.873)Number of observations13412210466Note: p-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Conclusion This report assessed the effects of completing a VET qualification on employment and earnings, using four different years of data from the ABS Surveys of Education and Training. To provide useful information to persons with less than 12 years of schooling and school completers who are contemplating the decision to invest in VET qualifications, comparisons in labour market outcomes are made relative to both these groups throughout the report. A short section with estimates of returns from mature-age students was also included to provide guidance to mature-age students deciding whether or not to undertake vocational education and training. The report provided detailed estimated impacts on four outcomes, three of them employment outcomes and one an earnings outcome. By and large, across the four different years of SET data, a consistent finding emerged. This finding is that, if one already is a school completer, then enrolling in vocational education and training to obtain sub-diploma VET (certificate IIV) qualifications is unlikely to be beneficial in terms of labour market outcomes. Only obtaining qualifications at the diploma level and above is likely to provide a positive return. On the other hand, if an individual only has less than 12 years of school education, then there are some concrete benefits to be obtained from all levels of VET qualifications, including the lower-level certificate I/II qualifications. In terms of choosing the field of education that is likely to provide the highest rates of return, it appears that business, engineering, architecture, building, and automotive are all fields that lead to tangible positive returns. The finding that, relative to Year 12 completers, there are no employment or earnings benefits in completing a certificate III/IV qualification differs from the findings in some previous research. See, for example, Karmel and Nguyen (2007), Karmel (2008) and Long and Shah (2008), who find positive benefits when making similar comparisons. On the other hand, these findings are consistent with the findings in Ryan (2002a) and Leigh (2008), who also find that, by comparison with Year 12 completers, skilled vocational qualifications or certificate III/IV qualifications do not result in employment or earnings benefits. Perhaps an important issue to consider in assessing the value of certificate III/IV qualifications is whether school completers or non-completers are more appropriate as a comparison group. An additional complication that needs to be taken into account is that many students undertaking certificate III/IV qualifications are studying part-time and may be working in lower wage stepping stone jobs in order to balance their workstudy routine. If this is the case, there will be a downward bias when attempting to estimate the potential returns from such qualifications. For mature-age students contemplating obtaining a VET qualification, it appears that it is only worthwhile to do so if one has less than 12 years of schooling and one is intending to enrol in VET courses at the certificate III level or higher. Furthermore, in such instances, it might take a year or two before any positive effects of the investment in education might materialise. There have not been dramatic changes over time in the returns from VET qualifications. Between 1993 and 1997 the earnings premium of associate diploma holders relative to both Year 12 completers and non-school completers was positive and of a similar magnitude. Similarly, between 2001 and 2005, the earnings premium of advanced diploma/diploma holders relative to both Year 12 completers and non-school completers were somewhat constant. It is harder to compare changes that took place pre- and post-1997 because of the introduction of AQF and the re-labelling of credentials. There were more fluctuations over time in the earnings premium to the sub-diploma VET (certificate IIV) qualifications. But relative to non-school completers, it is clear that over the entire period 1993 to 2005, there were statistically significant returns from having such VET qualifications. Some caveats to the general findings in this report are worth noting. The statistical approach used in this study is based on the assumption that all measured variables that affect VET participation and the outcomes considered are available and used in our models. However, many unmeasured variables related to ability and motivation are not included in our models (because data are not available), which implies that estimates in this study could be biased. In addition, performing the analysis separately by gender and field of education often results in small sample sizes, implying that some results might not be very robust. 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Cobb-Clark, D & Crossley, T 2003, Econometrics for evaluations: An introduction to recent developments, Economic Record, 247, pp.491511. Coelli, M & Wilkins, R 2008, Credential changes and education earnings premia in Australia, Melbourne Institute of Applied Economic and Social Research, Working paper no.11/08, Melbourne. Gregory, R 1995, Higher education expansion and economic change, Australian Bulletin of Labour, 21, pp.295322. Headey, B & Warren, D 2008, Adult education and job training, 20012005: Who does it? Does it improve future earnings? in Families, incomes and jobs, volume 3: A statistical report on waves 1 to 5 of the HILDA Survey, Melbourne Institute of Applied Economic and Social Research, Melbourne. Heckman, J, Lochner, L & Todd, P 2008, Earnings functions and rates of return, IZA discussion paper no.3310, Bonn. 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Zhang, X & Palamet, B 2006, Participation in adult schooling and its earnings impact in Canada, Analytical Studies Branch research paper series no. 276, Statistics Canada, Ottawa. Support document details Additional information relating to this research is available in Analysis of private returns to vocational education and training: Support document. It can be accessed from ϲʿ¼s website < HYPERLINK "http://www.ncver.edu.au/publications/2221.html" http://www.ncver.edu.au/publications/2221.html> and contains detailed regression results that correspond to tables 4 to 59 of the report. Appendix A: How propensity-score matching works Assume that each individual has two potential outcomes: Y(1) in the case that he or she obtained a VET qualification and Y(0) if the same person did not. The latter is often referred to as the counterfactual in the evaluation literature for those who obtained VET qualifications. The causal effect is then given by the comparison of Y(1) and Y(0). Let D represent the treatment variable, taking a value of 1 if the individual has a VET qualification and 0 otherwise. One parameter of interest for policy-makers is referred to as the average treatment effect on the treated (ATT) and can be expressed as:  EMBED Equation.DSMT4  In our setting, this would be the effect of a VET qualification on labour market outcomes for those who undertook VET studies. However, in reality, only one of these two outcomes is observable for each individual, making a direct comparison impossible. To estimate ATT, one needs to have an estimate of E(Y(0)|D=1). A nave approach uses E(Y(0)|D=0) as an estimate for E(Y(0)|D=1). However, simply comparing people with VET qualifications and those without VET qualifications is a potentially biased approach because it is likely that certain individuals self-select themselves into the vocational education system, while others choose not to obtain any more schooling after a certain point or choose to pursue a university education instead. These groups of individuals are potentially quite different. In the econometrics literature, this is known as the problem of selection bias and exists because  EMBED Equation.DSMT4  One econometric approach to solving the problem of selection bias involves the use of matching methods. Matching estimators is justifiable when an assumption that potential outcomes are independent of treatment receipt conditional on a set of observable characteristics is satisfied. More formally, this important condition is known as the Conditional Independence Assumption (CIA):  EMBED Equation.DSMT4  The fulfilment of this assumption helps solve the problem of selection bias because after conditioning on the covariates,  EMBED Equation.DSMT4  Although exact matching on covariates is possible as an approach to deal with the problem of selection bias, it can sometimes lead to difficulties due to the problem known as the curse of dimensionality. In other words, there could be many empty cells and little overlap in the distribution of covariates between treatment and comparison groups. As an alternative, many researchers have adopted a matching approach known as propensity-score matching that matches individuals based on a single variable, the propensity score. The term propensity score is the terminology used to refer to the probability of being in the treatment group. This is the approach we adopt in our analysis of the returns from VET in this report. For propensity-score matching, a further statistical assumption that is required is that the propensity score is strictly less than one so that matches can be found for all treated individuals. Propensity-score-matching is a semi-parametric alternative to standard linear OLS regression. Although both regression and matching rely on a similar selection on observables assumption for identification of the average treatment effect, matching allows one to relax the implicit linear functional form assumption in regression. Matching also allows an examination of the support condition to determine the extent to which individuals with VET qualifications are similar to those with lower schooling. Regression techniques do not allow easy detection of this problem, sometimes leading to estimating counterfactuals that require too much out-of-sample projection of the available data. Another advantage of matching over standard regression-based techniques is that it provides the researcher with flexibility in choosing how to aggregate heterogeneous impacts by the choice of weights so that policy parameters like the ATT can be estimated. Standard regression models impose a particular weighted average on the assumption of heterogeneous treatment effects, and it is not clear that this weighted average parameter is a parameter a policy-maker would be most interested in. Black and Smith (2004) is a recent application of the propensity-score approach to the related issue of examining the labour market effects of college quality. Cobb-Clark and Crossley (2003) provide a useful discussion of the differences in assumptions underlying standard linear regression, matching and instrumental variable approaches when these methods are used for evaluation purposes. Appendix B: The two-step matching/ regression approach In the first step, matching is done using covariates that can plausibly affect the decision to undertake VET. The propensity score is estimated using a probit model, where the dependent variable is VET participation (the main report discusses in detail how this binary variable denoting the various treatment and comparison groups is defined) and the independent variables are given below. For each of the Survey of Education and Training years, the following variables have been identified: 1993 Age (2024, 2529, 3034, 3539, 4044, 4549, 5054, 5564), gender, area of usual residence (= 1 if capital city), birthplace (= 1 if non-English speaking country), English language background (= 1 if English is first language), and state. 1997 Age (2024, 2529, 3034, 3539, 4044, 4549, 5054, 5564), gender, birthplace (=1 if non-English speaking country), English language background (= 1 if English is first language), and state. 2001 Age (2024, 2529, 3034, 3539, 4044, 4549, 5054, 55-64), gender, birthplace (= 1 if non-English speaking country), English language background (= 1 if English is first language), father born overseas, mother born overseas, and state. 2005 Age (2024, 2529, 3034, 3539, 4044, 4549, 5054, 5564), gender, birthplace (= 1 if non-English speaking country), English language background (= 1 if English is first language), father born overseas, mother born overseas, and state. Although state and area of residence at the time of the survey, and at the time they were deciding whether or not to undertake VET, is likely to be different for some people, we assume they are the same in order to use the area variables as matching variables. In the second step, we use an augmented set of variables for the regression analysisvariables from the first step, the weights obtained from matching in the first step, and variables that might plausibly affect the outcome of interest (but not the decision to undertake VET). 1993 Marital status (= 1 if married), Age of youngest child (02, 34, 59, 1014), and union status. 1997 Marital status (= 1 if married), Age of youngest child (02, 34, 59, 1014), union status, and disability status. 2001 Marital status (= 1 if married), Age of youngest child (02, 34, 59, 1014), union status, and disability status. 2005 Marital status (= 1 if married), Age of youngest child (02, 34, 59, 1014), union status, and disability status. The regression adjustment procedure in the report is based on OLS, regardless of whether the outcome is binary or continuous. This is the standard practice in randomised experiments and matching studies, where the purpose of the regression is purely to soak up any residual variation inthe covariates. One might view it as an augmented two-sample t-test with covariates. This combination of matching and regression using appropriate comparison groups helps us obtain estimates of the effects of VET qualifications. Appendix C: Sample sizes of treatment and comparison groups in the 1993, 1997, 2001 and 2005 SET data Table C1 Sample sizes of treatment and comparison groups in the 1993 SET data (ABSCQ) Treatment groupBusinessEngineering/ constructionOtherTotalBachelor degree and above---1689Assoc diploma148282362792Skilled vocational20915548062569Basic vocational526414341001 Comparison group:Year 122201< Year 12 6788Table C2 Sample sizes of treatment and comparison groups in the 1997 SET data (ABSCQ) Treatment groupBusinessEngineering/ constructionOtherTotalBachelor degree and above---2032Assoc diploma195139221555Skilled vocational5515633681986Basic vocational9073307301967 Comparison group:Year 121807< Year 12 5566 Table C3 Sample sizes of treatment and comparison groups in the 2001 SET data (ABSCQ) Treatment groupBusinessEngineering/ constructionOtherTotalBachelor degree and above---2359Assoc diploma223151237611Skilled vocational12515185402183Basic vocational7041575811442 Comparison group:Year 121660< Year 12 4582Table C4 Sample sizes of treatment and comparison groups in the 2001 SET data (ASCED) Treatment groupBusinessEngineering/ constructionOtherTotalBachelor degree and above---2403Advanced diploma/diploma3001855961090Certificate III/IV25216246862566Certificate I/II764111291247Note: Total is not same as the sum of the fields because a category field not determined was excluded from the other category. The majority of persons with certificate I/II qualifications were classified as being in mixed field programs in the 2001 SET, which have been put into the other category. Comparison group:Year 121635< Year 12 4530Table C5 Sample sizes of treatment and comparison groups in the 2005 SET data (ASCED) Treatment groupBusinessEngineering/ constructionOtherTotalBachelor degree and above---2487Advanced diploma/diploma3181526451115Certificate III/IV40014047692573Certificate I/II5701743171061 Comparison group:Year 121582< Year 12 3534  For example, the Financial Times, a UK-based newspaper, conducts an annual international survey of MBA alumni and reports their average salary. Business schools often also survey their graduating class for information regarding the average starting salary package.  The justification for using such an approach comes from the fact that this type of specification can be derived from a simple model where individual decision-makers choose years of schooling to maximise the present discounted value of lifetime net income.  Heckman, Lochner and Todd (2008) highlight the fact that strong assumptions are required to claim that the coefficient on education from a Mincer model can be interpreted as an internal rate of return. These include: (i) there is no direct or psychic costs of schooling; (ii) there are no income taxes; (iii) there is no loss of working life with additional years of schooling; (iv) earnings functions are multiplicatively separable in experience and schooling; and (v) marginal returns to schooling equal average returns to schooling.  According to the ABS 2006 Census of Population and Housing, less than 0.5% of dwellings were non-private dwellings. The Survey of Education and Training sample restriction to private dwellings should therefore not be expected to significantly affect the generalisation of results in this study to the wider Australian population.  In the 2001 SET, this distinction is made based on whether employees had leave entitlements.  Percentage effects are computed using the standard calculation: 100*(e-1).  It was not possible to do this for the 1993 SET as only information on the highest level of post-school qualifications was available. It was not possible to determine if a person with post-school qualifications such as VET qualifications had completed Year 12.  One-to-two-year follow-up impacts in this case are obtained by comparing earnings outcomes in 2005 between treatment group members that completed their VET qualifications some time in 200405 and comparison group members.  Incidentally, this is often the approach used in most IRR studies.      PAGE 30 Analysis of private returns to vocational education and training ϲʿ¼  PAGE 31  EMBED Word.Picture.8  !BQRal  O `    > ? 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