Evaluation of the Australian Wage Subsidy Special Youth ...

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In finding a counterfactual match for the participant, it is possible that there is no
comparison group individual with a similar propensity score. This is termed the common
support problem. The crux of common support is the identification and removal of treated
individuals for which the propensity indicates no close match is available in the
comparison group. Imposing common support ensures that the observed characteristics of
the participants are close to that of the non-participants.
4.5 Estimating the probability of participation for SYETP
Initially, the main aim is to repeat the formulation of the Richardson (1998) specification
as much as possible. In consideration of what variables to include in the propensity score
estimation, it is then deemed appropriate to apply the probit modelling of SYETP in as
much as possible the same specification used by Richardson (1998).
The results for the probit analysis, which is unweighted 80 , are shown in Table 4.2. The
variables, which are all constructed using 1984 data, are: gender, age, marital status,
children, partner’s employment, ethnicity, location, type of schooling, qualification level,
longest job held, CEP referrals, proportion of time spent unemployed prior to June 1984,
urban/rural area grew up in, number of siblings had, standard of spoken English, attitude
towards women in work, parental occupation and whether parent held a post-school
qualification, and religion brought up in. These are all the variables in the participation
equation of the bivariate probit estimated in chapter 3.
The variables in the model are central to the credibility of the CIA. In regard to labour
market evaluation, pre-programme labour market history is considered the most
important explanatory variable, and this is part of the model applied here. In addition, the
family background and attitudinal variables might be considered useful to help capture
otherwise unobservable characteristics such as motivation that could influence
80 The aim here is to find equivalent estimates for the bivariate probit model of Richardson (1998) using
PSM. Weighting is applied to both models in chapter 6.