Evaluation of the Australian Wage Subsidy Special Youth ...
Evaluation of the Australian Wage Subsidy Special Youth ... Evaluation of the Australian Wage Subsidy Special Youth ...
242 The magnitude of the employment effect falls, but only slightly. The dramatic changes to the statistical significance of the employment effect when CEP referrals is dropped might be attributed to the relatively large fall in the number of comparison cases used to match against the SYETP. This has a role in reducing the efficiency that in turn causes the fall in statistical significance. However, further discussion of the results is now deferred until after the estimation of a new specification. Table 7.5 Matching results, Single nearest neighbour with replacement, within caliper, weighting the propensity with combined weights: vary specification Match with caliper width 0.001 Original specification Match with caliper width 0.001 Original specification, Don’t include cep referrals Match with caliper width 0.001 New reduced specification Difference in employment 163 for 0.08 0.06 0.18 matched treated and comparisons t statistic 1.57 164 0.53 4.72** Total SYETP available 104 104 109 Number of SYETP matched 87 85 104 % SYETP matched 84% 82% 95% Number of comparison which satisfy 80 75 93 the caliper rule Number of times used 1 73 68 83 2 7 5 9 More than 2 2 1 Mean difference in propensity score 0.0002 0.0002 0.0002 between single nearest neighbour matched treated and comparisons Standard deviation 0.0002 0.0003 0.0002 Mean standardized bias 11.04 16.15 14.48 Common support cases dropped from syetp before matching 1 1 0 Number of observations 1283 1283 1389 Weighting protocol: weight propensity, weight the match using the treated weight only. The weighted mean bias is calculated using svymean in Stata. * significant at 10 % l.o.s., ** 5% l.o.s. 163 Ever employed in 1986 survey. 164 Probability of (0.22).
243 7.2.2 Propensity score matching and the effect of reduced specification Augurzky and Schmidt (2001) argue that although all available variables that rule the selection process are usually included in the participation equation, it may be better to remove variables of lesser importance from the specification. Their analysis showed that only including variables that were strongly significant could help combat the unnecessary effort of trying to balance these variables, which they found came at the expense of balance of the most relevant variables. In light of this, variables with low significance, or with only a theoretically minor role in employment, are candidates for exclusion from the probit for participation. Heckman, Ichimura and Todd (1997) also suggest that it is useful to compare the matching results from a reduced model of participation to that of the fuller model, in order to better assess the different approach to modelling entailed. In light of this a reduced specification of the probit for the propensity is proposed. The new matching results are shown in column 3 of Table 7.5, already shown. Only those variables with a potentially strong role in both employment and programme participation are included in the probit. Labour market outcomes for programmes are most often based on gender, age and unemployment experience which are included in the reduced model. The human capital effects of education, represented by highest qualification, and work experience are added. Marital status, children and partner’s labour market behaviour are included as variables that usually influence labour supply. Health, ethnicity and location are other factors commonly entered as constraints to labour supply or demand. The variation by location (state) was found to strongly influence SYETP participation [see section 2.2.6]. The rural/urban location is based on background prior to programme entry, retained from the former specification, because it is highly related to location in 1984 and later surveys. But this variable might act as a better instrument for the influences of personal background on labour market behaviour because location for young people is mostly due to parental choice. All of these variables form a subgroup of the fuller original specification. Note that CEP referrals is not included. Only one variable that was formerly statistically significant in the full model was excluded: nature of schooling (private, government, overseas, Roman Catholic). All other variables excluded from the reduced model were not statistically significant in the estimated probit.
- 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 and 252: 235 Table 7.2 summary of changes to
- Page 253 and 254: 237 schooling that was statisticall
- Page 255 and 256: 239 (0.25) (0.21) 3 years + -0.50 -
- Page 257: 241 Table 7.4 Summary of distributi
- 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
- Page 303 and 304: 3 years + -0.04 (2.13)* CEP referra
- Page 305 and 306: 289 Table A2.6 Part A Employment eq
- Page 307 and 308: 291 Table A2.6 Part B Selection/par
242<br />
The magnitude <strong>of</strong> <strong>the</strong> employment effect falls, but only slightly. The dramatic changes to<br />
<strong>the</strong> statistical significance <strong>of</strong> <strong>the</strong> employment effect when CEP referrals is dropped might<br />
be attributed to <strong>the</strong> relatively large fall in <strong>the</strong> number <strong>of</strong> comparison cases used to match<br />
against <strong>the</strong> SYETP. This has a role in reducing <strong>the</strong> efficiency that in turn causes <strong>the</strong> fall<br />
in statistical significance. However, fur<strong>the</strong>r discussion <strong>of</strong> <strong>the</strong> results is now deferred until<br />
after <strong>the</strong> estimation <strong>of</strong> a new specification.<br />
Table 7.5 Matching results, Single nearest neighbour with replacement, within caliper,<br />
weighting <strong>the</strong> propensity with combined weights: vary specification<br />
Match with<br />
caliper width<br />
0.001<br />
Original<br />
specification<br />
Match with<br />
caliper width<br />
0.001<br />
Original<br />
specification,<br />
Don’t include<br />
cep referrals<br />
Match with<br />
caliper width<br />
0.001<br />
New reduced<br />
specification<br />
Difference in employment 163 for 0.08 0.06 0.18<br />
matched treated and comparisons<br />
t statistic 1.57 164 0.53 4.72**<br />
Total SYETP available 104 104 109<br />
Number <strong>of</strong> SYETP matched 87 85 104<br />
% SYETP matched 84% 82% 95%<br />
Number <strong>of</strong> comparison which satisfy 80 75 93<br />
<strong>the</strong> caliper rule<br />
Number <strong>of</strong> times used<br />
1 73 68 83<br />
2 7 5 9<br />
More than 2 2 1<br />
Mean difference in propensity score 0.0002 0.0002 0.0002<br />
between single nearest neighbour<br />
matched treated and comparisons<br />
Standard deviation 0.0002 0.0003 0.0002<br />
Mean standardized bias 11.04 16.15 14.48<br />
Common support cases dropped from<br />
syetp before matching<br />
1 1 0<br />
Number <strong>of</strong> observations 1283 1283 1389<br />
Weighting protocol: weight propensity, weight <strong>the</strong> match using <strong>the</strong> treated weight only. The weighted mean<br />
bias is calculated using svymean in Stata. * significant at 10 % l.o.s., ** 5% l.o.s.<br />
163 Ever employed in 1986 survey.<br />
164 Probability <strong>of</strong> (0.22).