1. Completions of VET qualifications in Australia and implications for national and state VET planning Tom Karmel NCVER 20-21 May 2012

2. The value of completion  VET qualification rates are terrible  But, does it matter...... ► yes it does

3. Outline  Model the pay-off to completion  Identify the groups with the highest pay-offs  Relate the pay-offs to intention to complete and completion  Think about the implications

4. Outcome variables  employed after training  further study after training  employed or further study after training  improved employment circumstances after training  occupational status after training  wages after training

5. Methodology  Run separate models for graduates and module completers  Predict outcomes for every individual, assuming that they are graduate/module completer  Pay-off=graduate outcome/module completer outcome

6. Simplification  Focus on ► employment after training ► study after training ► wages for full-time workers (after training)

7. Employed after training

8. Further study

9. Salary full time

10. Summary of pay-offs after training Average pay-off (%)%>0 Employed21.780.8 Further study122.797.7 Employed or further study 28.299.9 Improved employment34.895.1 Salary (FT)0.360.7 Salary (PT)14.373.5 Occupational status2.358.9

11. Employment status after training Population pay-off = 21.7% Employment status before training: Unemployed pay-off = 34% Field of Education Other; Business pay-off = 14.6% Field of Education Other Services; Community Services; Technical pay-off=47.9% Employment status before training: Not in labour force pay-off = 108.3% Prior Education Diploma & Higher; Cert III/IV pay-off = 65.1% Prior Education Year 12 pay-off= 96.9% Prior Education <Year 12 & Cert I/II pay-off= 134.1% Employment status before training: Employed pay-off = 2.8%

12. Further Study Population pay-off =122.7% Employment status before training: Employed pay-off = 99% Qualification level: Diploma & above pay-off = 57.6% Qualification level: Cert III & IV pay-off = 93.9% Qualification level: Cert I & II pay-off= 141.5% Employment status before training Unemployed pay-off = 158.1% Employment status before training Not in labour force pay-off = 217.5% Qualification level: Diploma & above; Cert III & IV pay-off = 72.3% Qualification level: Cert I/II pay-off = 274.7%

13. Salary full time Population pay-off = 0.3% Qualification level: Cert I & II pay-off = -0.6% Qualification level: Cert III & IV pay-off = 1.8% Employment status before training: Employed pay-off = 0.3% Employment status before training: Not in Labour force pay-off = 7.0% Employment status before training: Unemployed pay-off = 8.3% Qualification level: Diploma & above pay-off = 6.6% Employment status before training Employed pay-off = 4.9% Employment status before training: Not in Labour force/ Unemployed pay-off = 13.7%

14. Summary  It pays to complete in respect of employment or further study  For employment, pay-off is highest for those not employed before training  For further study, pay-off is huge, and highest for cert I/II, and depends on employment status before training  Those doing diplomas, or a cert III & not employed before, get higher wages by completing

15. The link with completion  Question. Are those who benefit more from completion more likely to complete?  Answer. No.  Question. Are those who benefit more from completion more likely to intend to complete?  Answer. No.

16. Probability to complete

17. Population 84.9% Part Time 74.9% Personal reasons 69.5% Employment 76.4% Further study 74.0% Full Time 99.6%

18. Probability of intending to complete

19. Population 95% Part Time 91.6% Other 77.2% Other Services 87.1% Business; Technical 93.1% Community Services 95.4% Full Time 97.2%

20. Correlations with prob of completion Pay-off to: Employment after training-.08 Full-time study after training-.23 Salary for full-time employment after training-.08 Intending to complete.58

21. Correlations with intention to complete Pay off to: Employment after training.04 Further study after training-.33 Salary for full-time employment after training0.14

22. Modelling the probability of completion VariableEstimate Intercept-0.16 Probability that student intends to complete1.03 Satisfaction with training0.008

23. Final comments  Our analysis is helpful in specifying groups for performance indicators.  Gives an insight into where public funds should go?  Low completion rates do need to be addressed. ► payment on completions?