Evaluation of the Australian Wage Subsidy Special Youth ...

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A series of empirical studies was presented, forming an evaluation of the employment
gains attributable to SYETP. The central aims of the analysis were threefold: to examine
the results of the Heckman selection modelling against those of propensity score
matching, and so relax the specification from fully parameterised to semi-parametric; to
account for attrition and non-response in the data; and to compare the employment
impact of SYETP under the different modelling assumptions. The analysis has produced
new results for the employment gains of SYETP. The new results account for potential
bias due to survey attrition, and provide more evidence as to the robustness of the
employment gains to varying the modelling assumptions. The new evaluation evidence
for SYETP thus improves the knowledge relating to the employment gains for SYETP.
The Richardson (1998) evaluation using the Heckman selection probit was first replicated
successfully. The propensity score matching (PSM) methods were applied using the
nearest-neighbour-within-caliper-with-replacement protocol. The choice of caliper width
was explored by the application of several plausible caliper widths. To examine the
sensitivity of the results to the choice of Propensity Score Matching protocol, all-incaliper
matching was also applied, and it was concluded that the results were not strongly
affected by the choice of matching protocol. The PSM results reduce the size and
significance of the employment effect found when compared to the Heckman modelling.
It was concluded that potential attrition bias might affect the results by introducing
selection bias.
Sample reduction in the Australian Longitudinal Survey data was explored. The effects of
survey design, initial non-response, and subsequent panel attrition were examined and
found to have substantial impacts on the participant and comparison group characteristics,
introducing potential bias. This was then accounted for, and the impact on evaluation
assessed. Weights were constructed to deal with attrition, non-response and complex
survey design in the ALS data. The weighted results were found to be smaller and to have
low statistical significance. Accounting for attrition in both the Heckman bivariate probit
and PSM models reduces the size of the employment effect found, and results have low
significance. However, after accounting for attrition, the employment effect found using