Evaluation of the Australian Wage Subsidy Special Youth ...
Evaluation of the Australian Wage Subsidy Special Youth ... Evaluation of the Australian Wage Subsidy Special Youth ...
236 7.2 Varying the Propensity Score specification, effects on the match The specification of the propensity score estimated by probit is vital to the propensity score matching outcome. Some variation to this specification is now examined. In this section, the variable CEP referrals is excluded from the model for the propensity score, and the effect on the matching outcome examined. Additionally, a more concise specification for the probit is estimated, using only those variables thought to have most plausible economic influence on SYETP participation and employment. The combined weighting for sample reduction due to attrition and non-response and survey design is applied in all models, with the weighting protocol for the propensity score matching as shown in the earlier chapter. 7.2.1 Propensity score matching and the effect of excluding CEP referrals Recall that the originally estimated propensity specification was designed to be as similar as possible to the Heckman modelling of Richardson (1998), as the aim had been to discover what the result would have been if propensity score matching had been used. It was earlier noted, that at least one variable in the propensity score then estimated might not satisfy the requirement that it influence both employment and participation in SYETP: namely CEP referrals. Table 7.3 shows the full results for the weighted probit when the variable CEP referrals is excluded from the model. The first column shows the former results with the original specification, while the second column is for the specification when CEP referrals is excluded. The predicted fit of the model, calculated as before 160 , shows 85 per cent of cases are predicted correctly. Thus the predictive power of the model remains acceptable, although lower than for the former weighted specification. Other scalar fit measures presented all indicate the new model to be similarly acceptable as the former model. Most changes to the coefficients and t statistics are very slight. Only the variable private 160 A fitted probability exceeding 0.5 is taken to indicate a predicted response to the survey; these predicted responses are compared to the actual participants/non-participants in SYETP to check which cases the model correctly predicted.
237 schooling that was statistically significant in the former model changes with a move to non-significance at conventional levels when CEP referrals is excluded. The distribution of the estimated propensity score prior to matching is shown in Table 7.4. It is useful to compare this distribution to that found for the weighted results using the original specification (see Table 6.5 in the previous chapter). The distribution of the estimated propensity for those in the SYETP treatment group appears only a little changed by the altered specification. In the SYETP treatment group, the limits of the distribution are very similar to those for the former specification, with only very small adjustments to the size of the largest and smallest observed propensities. The mean propensity for the SYETP treatment group is also very similar; however the median had fallen in size from roughly 0.143 to 0.135, which would indicate a slight shift down in the central peak of the distribution. The standard deviation of the propensity for the SYETP treatment group is hardly changed by the new specification. The propensity score distribution for the comparison group is also only changed slightly overall. The greatest effect appears for the lower tail of the distribution for the comparisons, where the smallest estimated propensities have greater size in the altered specification. The mean propensity, median and standard deviation for the comparisons remains very similar to that found for the former specification.
- Page 201 and 202: 185 3 years + -0.35 -0.47 -0.34 -0.
- Page 203 and 204: 187 5.7 Multivariate analysis of ef
- Page 205 and 206: 189 proportion of time spent unempl
- Page 207 and 208: 191 post-school qualification, and
- Page 209 and 210: 193 Generally, those variables foun
- Page 211 and 212: 195 longj0 Longest job by 1984 < 1
- Page 213 and 214: 197 adopted in order to maintain co
- Page 215 and 216: 199 6: Study 4 Weighting to counter
- Page 217 and 218: 201 Table 6.1, part A Employment eq
- Page 219 and 220: 203 Methodist 0.133 0.261 (0.77) (1
- Page 221 and 222: 205 CEP referrals 1984 0.143* 0.128
- Page 223 and 224: 207 6.2 Results of weighting the PS
- Page 225 and 226: 209 The distribution of the propens
- Page 227 and 228: 211 Table 6.3 Weighted probit used
- Page 229 and 230: 213 (0.76) Tradesperson mtrad 0.20
- Page 231 and 232: 215 Table 6.5 Summary statistics fo
- Page 233 and 234: 217 Table 6.7 Matching results, sin
- Page 235 and 236: 219 6.3 Discussion The comparison o
- Page 237 and 238: 221 the selection into SYETP and th
- Page 239 and 240: 223 Heteroskedasticity is a violati
- Page 241 and 242: 225 Table 7.1, Part A Employment eq
- Page 243 and 244: 227 (1.26) (1.28) (1.16) Mothers oc
- Page 245 and 246: 229 Other Post-School qualification
- Page 247 and 248: 231 7.1.2 Exclusion restriction in
- Page 249 and 250: 233 Finally, the third panel of new
- Page 251: 235 Table 7.2 summary of changes to
- Page 255 and 256: 239 (0.25) (0.21) 3 years + -0.50 -
- Page 257 and 258: 241 Table 7.4 Summary of distributi
- Page 259 and 260: 243 7.2.2 Propensity score matching
- Page 261 and 262: 245 original model, but with the pe
- Page 263 and 264: 247 maintained, then the Heckman bi
- Page 265 and 266: 249 Table 7.6 Weighted Probit used
- Page 267 and 268: 251 Table 7.7 Summary of distributi
- Page 269 and 270: 253 8: Summary and Conclusions The
- Page 271 and 272: 255 over which it ran, the review m
- Page 273 and 274: 257 the Heckman and PSM methods wer
- Page 275 and 276: 259 posited that that such sensitiv
- Page 277 and 278: 261 Description Derivation and deta
- Page 279 and 280: Appendix 2 Tables 263
- Page 281 and 282: 2 years 0.28 0.07 (1.70) (1.70) 3 y
- Page 283 and 284: 267 Table A2.0b Univariate Probit o
- Page 285 and 286: 269 Religion brought up in (1.52) (
- Page 287 and 288: 271 hq9_84 Year 9 of school or less
- Page 289 and 290: 273 Table A2.1 Continued Means and
- Page 291 and 292: 275 mtrad Tradesperson 0.04 0.04 0.
- Page 293 and 294: 277 Year 9 of school or less -0.19
- Page 295 and 296: 279 Table A2.3 Probit of SYETP part
- Page 297 and 298: 281 (0.22) (0.44) (0.67) (0.89) Tra
- Page 299 and 300: 283 Table A2.5a Univariate probit f
- Page 301 and 302: 285 Manager/professional/para-profe
236<br />
7.2 Varying <strong>the</strong> Propensity Score specification, effects on <strong>the</strong> match<br />
The specification <strong>of</strong> <strong>the</strong> propensity score estimated by probit is vital to <strong>the</strong> propensity<br />
score matching outcome. Some variation to this specification is now examined. In this<br />
section, <strong>the</strong> variable CEP referrals is excluded from <strong>the</strong> model for <strong>the</strong> propensity score,<br />
and <strong>the</strong> effect on <strong>the</strong> matching outcome examined. Additionally, a more concise<br />
specification for <strong>the</strong> probit is estimated, using only those variables thought to have most<br />
plausible economic influence on SYETP participation and employment. The combined<br />
weighting for sample reduction due to attrition and non-response and survey design is<br />
applied in all models, with <strong>the</strong> weighting protocol for <strong>the</strong> propensity score matching as<br />
shown in <strong>the</strong> earlier chapter.<br />
7.2.1 Propensity score matching and <strong>the</strong> effect <strong>of</strong> excluding CEP referrals<br />
Recall that <strong>the</strong> originally estimated propensity specification was designed to be as similar<br />
as possible to <strong>the</strong> Heckman modelling <strong>of</strong> Richardson (1998), as <strong>the</strong> aim had been to<br />
discover what <strong>the</strong> result would have been if propensity score matching had been used. It<br />
was earlier noted, that at least one variable in <strong>the</strong> propensity score <strong>the</strong>n estimated might<br />
not satisfy <strong>the</strong> requirement that it influence both employment and participation in SYETP:<br />
namely CEP referrals.<br />
Table 7.3 shows <strong>the</strong> full results for <strong>the</strong> weighted probit when <strong>the</strong> variable CEP referrals is<br />
excluded from <strong>the</strong> model. The first column shows <strong>the</strong> former results with <strong>the</strong> original<br />
specification, while <strong>the</strong> second column is for <strong>the</strong> specification when CEP referrals is<br />
excluded. The predicted fit <strong>of</strong> <strong>the</strong> model, calculated as before 160 , shows 85 per cent <strong>of</strong><br />
cases are predicted correctly. Thus <strong>the</strong> predictive power <strong>of</strong> <strong>the</strong> model remains acceptable,<br />
although lower than for <strong>the</strong> former weighted specification. O<strong>the</strong>r scalar fit measures<br />
presented all indicate <strong>the</strong> new model to be similarly acceptable as <strong>the</strong> former model. Most<br />
changes to <strong>the</strong> coefficients and t statistics are very slight. Only <strong>the</strong> variable private<br />
160 A fitted probability exceeding 0.5 is taken to indicate a predicted response to <strong>the</strong> survey; <strong>the</strong>se predicted<br />
responses are compared to <strong>the</strong> actual participants/non-participants in SYETP to check which cases <strong>the</strong><br />
model correctly predicted.
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