Evaluation of the Australian Wage Subsidy Special Youth ...

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232 the employment equation, and the final panel considers the effect of including both age and CEP referrals in the employment equation as well as the participation equation. Table A2.6 in the appendix shows the effect on the weighted model of changing the specification by including age in the employment equation. The first column in the first new results panels in Table 7.2 gives the lack of results for the unweighted equation – it proved impossible to estimate the unweighted equation with age in the employment equation. This is interpreted as indicative that because the selection arising from data loss is unaccounted for, there is misspecification when age is included in the unweighted equation. In the second column of this panel is shown the weighted Heckman bivariate probit results where age is in the employment equation and participation equation, but CEP referrals remains as an exclusion restriction. The weighted specification is estimable. However, age does not have a reasonably sized coefficient nor is it statistically significant in the employment equation. The size of the SYETP coefficient is slightly affected by this alteration to the specification – with the size increased, although remaining statistically insignificant at conventional test levels. Now, the same form of specification change is shown in panel 2 of Table 7.2, with CEP referrals dropped from the exclusion restriction and included in the employment equation as well as the participation equation. Again, Table A2.7 in the appendix shows the effect on the weighted model of changing the specification by including CEP referrals in the employment equation. The first column of the second panel again shows no results for the unweighted model, as again this specification proved impossible to estimate for the unweighted data. In the second column is shown the weighted Heckman results where CEP referrals are in the employment equation and participation equation, but age remains as an exclusion restriction entered only in the participation equation. The consequences are similar to those found for age – the equation is estimable, and the coefficient of CEP referrals is not of reasonable size and it is not statistically significant, but the change to specification raises the size of the SYETP coefficient although there is no gain in statistical significance.
233 Finally, the third panel of new results in Table 7.2 considers reintroduction of both age and CEP referrals to the employment equation, with no exclusion restriction operation. Once more, Table A2.8 in the appendix shows the effect on the weighted model of changing the specification by including both age and CEP referrals in the employment equation. The results are very similar to those already discussed. The unweighted equation is inestimable in this specification, and the same interpretation is given as before. Again, although introducing these variables to the employment specification raises the size of the SYETP coefficient it does not gain statistical significance, and neither variable age or CEP referrals is of significant size or statistical significance. Overall, the results shown for varying the specification of the exclusion restriction in both the weighted and unweighted data indicate a number of helpful conclusions. In the weighted data, the alteration of the exclusion restriction shows that age was not particularly important to the exclusion restriction, but that it had no independent effect in the employment equation specification. However, including CEP referrals is likely to be a mis-specification as it has no independent effect in the equation and also dramatically reduces the SYETP coefficient. On the other hand, in the unweighted data, age and CEP referrals provided a useful exclusion restriction, and accounted for selection in the data. Once selection due to sample reduction from non-response, sample attrition, and sample design effects was accounted for using the weights, the selection problem in the data appears to have been reduced. The hypothesis tests indicate that the weighted equation does not have evidence for selection. It is further concluded that the original Heckman specification was not greatly improved by any of these specification changes, as evidenced by the only slightly lower AIC. The goodness of fit assessment shows not strong basis for preferring one model over the other. The SYETP coefficient increased in size slightly but there was no improvement in statistical significance. There is a suggestion that the unweighted model is particularly sensitive to the variables in the exclusion restriction, since only when they are excluded is the equation estimable. The weighted equation is more robust to changes in these variables, but it is posited that
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i Evaluation of the Australian Wage
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v Declaration I hereby declare that
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in method and assumptions. The orth
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3.3 Data and variables used for est
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List of Tables and Figures Figure 1
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Table A2.0b Univariate Probit of pa
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xv Abstract The job subsidy Special
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1 1: Wage subsidy theory and evalua
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3 programs of providing benefits an
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5 The empirical methods used for th
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7 how the outcomes from these metho
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9 employment effect could be mainly
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11 Real Wage Employment Figure 1.1:
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13 are two types of unemployment, s
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15 Real wages are predetermined whe
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17 Vella (1998), Heckman, Lalonde a
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19 Each individual has two potentia
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21 this case, if there was no data
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23 correlation for the error of the
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25 Table 1.3 collects together some
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27 Table 1.3 Brief overview of rece
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29 necessarily brief. Then, the evi
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31 limited applications, such as fo
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33 who participated. It was conclud
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35 term unemployed for over 12 of t
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37 importance of the subsidy second
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39 differences in characteristics t
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41 Matching methods are theoretical
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43 2.2 SYETP implementation As SYET
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45 In July1978, the subsidy was cal
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47 In January 1979, variations were
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49 benefits were paid at a slightly
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51 2.2.3 SYETP operation Earlier re
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53 ceiling constraints’ applied t
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55 Award Conditions for employment
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57 Harris (2001) claims that during
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59 display boards listed details of
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61 restriction was used. If there w
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63 to the end of the 1980’s. An o
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65 for teens overall had risen, emp
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67 for Australia using data from th
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69 training, can provide a form of
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71 employer survey estimates were t
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73 provisions for SYETP and extende
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75 withdrawals occurred at similar
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77 Table 2.17 State usage of progra
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79 2.3.1 Stretton (1982, 1984) 53 S
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81 Stretton attributed the success
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83 included in the employment model
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85 completers. Their argument was t
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87 was an issue for the data. Unlik
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89 Table 2.21 Richardson (1998) Est
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91 2.3.5 General discussion Some ge
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93 Controlling for differences in i
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95 taken by a previous researcher a
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97 If employability is assumed to b
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99 suitability of the underlying as
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101 Heckman, Lalonde and Smith (199
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103 effect on employment relative t
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105 Table 3.1, Part A Employment eq
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107 (-1.80) (-1.80) Tradesperson -0
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109 duration of Pre-June 1984 unemp
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111 4: Study 2 Propensity score mat
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113 Propensity score matching provi
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115 4.2 Propensity score matching m
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117 covariates that influence the a
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119 (7) E(Y c | D=1) = E P(X) {E[Y
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121 For CIA to be plausible, a ‘r
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123 employment and programme partic
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Highest qualification in 1984 (1.56
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127 4.6 Distribution of the propens
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129 Figure 4.3 Histograms of estima
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131 Table 4.5 Summary statistics fo
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133 Table 4.5, that the variance of
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135 Table 4.6 Matching results, Sin
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137 Table 6.3 using Swedish data wi
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139 matching is the ability to weed
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141 Table 4.7 Matching results, All
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143 the unobserved component. If th
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145 5: Study 3 Attrition and non-re
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147 occur by design, because the mi
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149 (1990) extended and improved th
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151 (10) A* = δ 0 + δ 1 x +δ 2 z
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153 again from September to Novembe
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155 5.5.2 Univariate examination of
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157 lower, the job lengths are only
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159 Work limited by health 1984 0.1
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161 The characteristics of the SYET
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163 para-professional Mother not em
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165 comparison group where the shar
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167 5.5.4 Attrition: natural attrit
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169 both sources that impose change
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171 para-professional Father not em
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173 work in later sections, this su
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175 Table 5.6: Effect of selection/
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177 appropriate to discard these fr
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179 Australia/Tasmania. Amongst tho
Page 197 and 198: 181 Table 5.5a Summary statistics b
Page 199 and 200: 183 5.6.1.2 Effects of the non-resp
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: 231 7.1.2 Exclusion restriction in
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 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
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283 Table A2.5a Univariate probit f
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285 Manager/professional/para-profe
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3 years + -0.04 (2.13)* CEP referra
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289 Table A2.6 Part A Employment eq
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291 Table A2.6 Part B Selection/par
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301
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BLMR Bureau of Labour Market Resear
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Fay, R.G. (1996) "Enhancing the eff
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Heckman J.J. and Smith, J. A. (1998
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Lewis, H.G. (1963) "Unionism and re
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Quandt, R. (1972) "A new approach t
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Stromback, M. and Dockery, A. (2000
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