Evaluation of the Australian Wage Subsidy Special Youth ...
Evaluation of the Australian Wage Subsidy Special Youth ... Evaluation of the Australian Wage Subsidy Special Youth ...
112 4.1 Differences between the treatment and comparison group An important problem for evaluation of programme effects is whether the treated are compared to an adequate reference group. This is the issue of selection distortion, where those treated have a very different profile to those in the comparison group. Selective recruitment onto subsidy would make the treated have a different profile than the larger group of those eligible. Controls for selection distortion can be made on observable characteristics, such as those variables shown in Table 4.1. The Table 4.1 gives the mean and standard deviation from the mean for a set of characteristics, with column 1 and 2 showing these for the SYETP treated group, and columns 3 and 4 showing the comparison group characteristics. The absolute difference between the means is in column 5, with the results of the t-test at one percent level of significance indicated by an asterisk to show statistically significant differences. Richardson (1998) p6 commented that the contrast between those who took part in SYETP and those in the comparison group was “striking”. Indeed, column 1 and column 3 of Table 4.1, of which the means were also presented by Richardson (1998), shows that the profile of the treatment and comparison groups differs strongly. In most cases, means were quite different for the SYETP relative to the comparisons, and in some cases the variation from the mean, as represented by the standard deviation was also very different for each group. As Richardson (1998) highlights, SYETP participants had a different educational attainment profile where post-school qualifications were less common, they were about a year younger, and had poorer labour market experiences than those in the comparison group. However, how different the SYETP group was from the comparisons is related more clearly here by the addition of the test of the statistical significance of the mean difference. Almost all variables have a significant divergence between the means for the SYETP group and the comparisons. Consideration of the many statistically significant differences in Table 4.1 makes the selection distortion for SYETP in the ALS data apparent. The literature review also highlights other evidence that it was generally the case for SYETP entrants to be younger than the eligible group as a whole – mostly teenagers. Thus it is possible that the ALS sample reflects differences that existed between the SYETP and comparison populations.
113 Propensity score matching provides a method of analysis that controls for the lack of correspondence between the treatment and comparison group. As discussed in Chapter 1, evaluation methods seek to maximize the similarity of the comparison and treated groups, in order to return to a quasi-experimental situation where effects can be usefully attributed to the programme. The propensity score matching method is now further discussed and applied. The outcomes of the propensity score matching are then compared to that of the bivariate probit. The relevance of each approach to the case at hand is considered, and the result for the SYETP programme effect is discussed.
- Page 77 and 78: 61 restriction was used. If there w
- Page 79 and 80: 63 to the end of the 1980’s. An o
- Page 81 and 82: 65 for teens overall had risen, emp
- Page 83 and 84: 67 for Australia using data from th
- Page 85 and 86: 69 training, can provide a form of
- Page 87 and 88: 71 employer survey estimates were t
- Page 89 and 90: 73 provisions for SYETP and extende
- Page 91 and 92: 75 withdrawals occurred at similar
- Page 93 and 94: 77 Table 2.17 State usage of progra
- Page 95 and 96: 79 2.3.1 Stretton (1982, 1984) 53 S
- Page 97 and 98: 81 Stretton attributed the success
- Page 99 and 100: 83 included in the employment model
- Page 101 and 102: 85 completers. Their argument was t
- Page 103 and 104: 87 was an issue for the data. Unlik
- Page 105 and 106: 89 Table 2.21 Richardson (1998) Est
- Page 107 and 108: 91 2.3.5 General discussion Some ge
- Page 109 and 110: 93 Controlling for differences in i
- Page 111 and 112: 95 taken by a previous researcher a
- Page 113 and 114: 97 If employability is assumed to b
- Page 115 and 116: 99 suitability of the underlying as
- Page 117 and 118: 101 Heckman, Lalonde and Smith (199
- Page 119 and 120: 103 effect on employment relative t
- Page 121 and 122: 105 Table 3.1, Part A Employment eq
- Page 123 and 124: 107 (-1.80) (-1.80) Tradesperson -0
- Page 125 and 126: 109 duration of Pre-June 1984 unemp
- Page 127: 111 4: Study 2 Propensity score mat
- Page 131 and 132: 115 4.2 Propensity score matching m
- Page 133 and 134: 117 covariates that influence the a
- Page 135 and 136: 119 (7) E(Y c | D=1) = E P(X) {E[Y
- Page 137 and 138: 121 For CIA to be plausible, a ‘r
- Page 139 and 140: 123 employment and programme partic
- Page 141 and 142: Highest qualification in 1984 (1.56
- Page 143 and 144: 127 4.6 Distribution of the propens
- Page 145 and 146: 129 Figure 4.3 Histograms of estima
- Page 147 and 148: 131 Table 4.5 Summary statistics fo
- Page 149 and 150: 133 Table 4.5, that the variance of
- Page 151 and 152: 135 Table 4.6 Matching results, Sin
- Page 153 and 154: 137 Table 6.3 using Swedish data wi
- Page 155 and 156: 139 matching is the ability to weed
- Page 157 and 158: 141 Table 4.7 Matching results, All
- Page 159 and 160: 143 the unobserved component. If th
- Page 161 and 162: 145 5: Study 3 Attrition and non-re
- Page 163 and 164: 147 occur by design, because the mi
- Page 165 and 166: 149 (1990) extended and improved th
- Page 167 and 168: 151 (10) A* = δ 0 + δ 1 x +δ 2 z
- Page 169 and 170: 153 again from September to Novembe
- Page 171 and 172: 155 5.5.2 Univariate examination of
- Page 173 and 174: 157 lower, the job lengths are only
- Page 175 and 176: 159 Work limited by health 1984 0.1
- Page 177 and 178: 161 The characteristics of the SYET
113<br />
Propensity score matching provides a method <strong>of</strong> analysis that controls for <strong>the</strong> lack <strong>of</strong><br />
correspondence between <strong>the</strong> treatment and comparison group. As discussed in Chapter 1,<br />
evaluation methods seek to maximize <strong>the</strong> similarity <strong>of</strong> <strong>the</strong> comparison and treated groups,<br />
in order to return to a quasi-experimental situation where effects can be usefully<br />
attributed to <strong>the</strong> programme. The propensity score matching method is now fur<strong>the</strong>r<br />
discussed and applied. The outcomes <strong>of</strong> <strong>the</strong> propensity score matching are <strong>the</strong>n compared<br />
to that <strong>of</strong> <strong>the</strong> bivariate probit. The relevance <strong>of</strong> each approach to <strong>the</strong> case at hand is<br />
considered, and <strong>the</strong> result for <strong>the</strong> SYETP programme effect is discussed.
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