finding a skilled job after training. It illustrates the presence of a gender gap of about 9 per cent between males and females at all levels of training. Figure : Estimated relationship between age and probability of getting a skilled job by VET training and gender The next figure shows the extent to which Certificate IV and Diplomas set themselves apart with regard to the probability of getting a skilled job after training. It shows that Certificate III is not significantly different to a lower level of training with respect to this probability. Figure : Estimated relationship between age and probability of getting a skilled job by VET training level The final figure in this part illustrates the gap that exists between ADF stayers and leavers at all level of training in favour of the leavers. Leavers are more likely to find a skilled job upon leaving than ADF stayers who return to their former job. Figure : Estimated relationship between age and probability of getting a skilled job by VET training level and transition type Predicting Labour Market Outcomes for ADF (ex-) Personnel Box 11: Deriving predictions of individuals’ outcomes We use the results of the underlying statistical that we presented in the previous section to build policy-relevant predictions. The principle is simple and powerful. The model allows us to derive an estimated prediction for each outcome of interest and for each individual in the sample. These individual predictions can be summed up for different subgroups to allow us to focus the results of the model on people and circumstances that are at the forefront of policy relevance. This section focuses on the ‘typical’ DVA client with a claim under the Military Rehabilitation and Compensation Act 2004 (MRCA). The next two sections use the estimation results of the underlying econometric model in order to build specific predictions for DVA clients who leave the ADF (this section) and to build scenarios for DVA clients who lodged a claim under the Military Rehabilitation and Compensation Act 2004 (MRCA) since 1 July 2004 (the next section).
Table A : Correlations between explanatory variables used in multivariate regression Age Male Disability Below Year 12 before training Study certificate III/IV Study diploma or above Module completer for employment reason Reason for study achieved Not satisfied with training Further study Skilled job before training Casual job before training Part-time job before training Age 1 Male 0.02 1 Disability 0.09 0.03 1 Below Year 12 before training 0.18 0.06 0.06 1 Study certificate III/IV 0.00 -0.04 -0.01 0.00 1 Study diploma or above -0.04 -0.05 -0.02 -0.15 -0.42 1 Module completer 0.16 0.07 0.03 0.01 -0.31 -0.11 1 Study for employment reason 0.08 0.06 -0.01 0.02 0.11 -0.01 -0.05 1 Reason for achieved 0.06 0.06 -0.04 0.04 0.03 -0.07 -0.06 -0.04 1 Not satisfied with training -0.05 -0.01 0.00 -0.03 0.02 0.05 -0.03 -0.00 -0.22 1 Further study -0.17 -0.07 0.00 -0.07 0.01 0.04 -0.18 -0.10 -0.03 0.01 1 Skilled job before training 0.25 0.14 -0.01 -0.08 -0.02 0.02 0.11 0.04 0.07 -0.01 -0.06 1 Casual job before training -0.25 -0.08 0.02 -0.01 -0.06 0.01 -0.06 -0.11 -0.08 0.02 0.10 -0.21 1 Part-time job before training -0.21 -0.30 0.028 -0.02 -0.02 0.02 -0.09 -0.12 -0.08 0.01 0.12 -0.27 0.50 1