Evaluation of the Australian Wage Subsidy Special Youth ...

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8: Summary and Conclusions
The underlying motivation for this work is the desire for a closer examination of the
Australian wage subsidy SYETP. The main theoretical rationale for wage subsidies is
that they stimulate a gain in employment. However the review of the theoretical models
of wage subsidies shows they cannot provide unambiguous proof of an increase in
employment. The importance of empirical evaluation of wage subsidies in part stems
from this uncertainty. The central question remains: do wage subsidies improve
employment prospects for the individual?
Microeconomic evaluation evidence can demonstrate whether SYETP has led to a gain in
employment for participants. While the main evaluation interest is the programme
influence on job entry, the processes of participation and job entry can involve both
observable and unobservable components that can introduce selection bias. An evaluation
of the program effect needs to account for this selection. Two evaluation methods are
explored here – the Heckman selection bivariate probit model, and matching methods, in
particular propensity score matching. Both identify a parameter corresponding to the
mean effect of treatment on the treated, which can be used to decide whether the
programme leads to employment gains. However each method uses different assumptions
to achieve this. Selection on unobservables is assumed by the Heckman bivariate probit,
while selection on observables is assumed by matching methods.
The review of recent overseas evidence for wage subsidies shows a variety of positive
and negative impacts. Two key themes are identified. The empirical ambiguity as to
employment gains from wage subsidies remains unresolved. Contributing to this, in many
studies the non-experimental evaluation methods insufficiently test the assumptions,
alternative methods, and data issues. It was noted that meta-analysis might be more
satisfactory in accounting for the deviations in evaluation evidence, since it was hard to