Evaluation of the Australian Wage Subsidy Special Youth ...

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calculation for age is very low, ranging from 2.34 for 0.001 caliper but only 0.92 for 0.05
caliper. Prior to matching, the standardized bias figure for age was much worse at 49.85,
which is a suitable example of the improved balance after the propensity score matching.
Widening the caliper improved the balance score of this variable, which would be partly
due to the number of times a comparison was used with replacement, and also partly due
to the new comparison cases available for matching to additional SYETP cases as the
caliper was widened. Duration of pre-programme unemployment was also well balanced
after matching, with a standardized bias of 2.58. This did not change with caliper size,
but the sampling of the survey design for the data, where only those of specific
unemployment duration formed the sample frame, would be the key factor in this.
Qualification to year 12 was badly balanced, even after matching, with the means
showing the SYETP group remaining more likely to have this. Frölich et al. (2000) point
out that sometimes poor standardized bias can be due to small probabilities and hence
small standard deviation used in standardizing the standard bias. In this study, the number
of cases of SYETP is quite small, and the variables are not continuous, so this would
contribute to the lower balance scores.
One step to counter poor bias, i.e. balance of the covariates, is to re-specify the
propensity model (Larsson (2000): 54). This will be treated later in Chapter 7.
A final consideration is how to choose between the matching results presented in Table
4.6. The mean difference hardly varies in size, and is always significant, which means
that the effectiveness of the match is the main criterion for selecting between the results.
The model is identical, merely the precision of the match is adjusted in Table 4.6. The
difference in propensity scores is smallest for the 0.001 caliper, indicating this gave the
closest match in this sense. But in terms of the standardized bias the resulting match is
better for the calipers 0.02 and 0.05, although the difference in bias statistics is overall
small. As the estimate is being selected for comparison with the earlier replication
Heckman bivariate probit result of Chapter 3, it might be said that to make the
comparison most similar, all the SYETP cases should be included. This would favour the
result for 0.05 caliper. However, it is claimed that the main advantage of propensity score