Evaluation of the Australian Wage Subsidy Special Youth ...

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198 Table 5.10: Performance of attrition weight as measured by unweighted and weighted profile mean 1984 unadjusted profile 1986 unadjusted profile 1986 weighted to 1984 profile 1984 weighted to sampled population profile 1986 adjusted to sampled population Age at 1984 survey 20.13 19.95 20.01 19.88 19.92 Gender=female 0.41 0.41 0.41 0.39 0.39 Work limited by health 0.12 0.11 0.11 0.11 0.11 Aboriginal/Torres Strait 0.03 0.03 0.03 0.04 0.03 Islander Other ethnic minority 0.08 0.08 0.08 0.08 0.08 Married 1984 0.12 0.10 0.11 0.11 0.11 State interviewed in 1984 Victoria 0.24 0.24 0.24 0.24 0.24 Queensland 0.16 0.13 0.14 0.16 0.16 South Australia/Northern 0.11 0.11 0.11 0.10 0.10 Territory Western Australia/Tasmania 0.12 0.13 0.12 0.11 0.11 New South Wales/Australian 0.39 0.38 0.39 0.39 0.39 Capital Territory Area of residence in 1984 Capital city 0.49 0.47 0.49 0.49 0.49 Other city 0.23 0.22 0.23 0.23 0.23 Country town 0.21 0.24 0.21 0.22 0.22 Rural area 0.06 0.07 0.06 0.06 0.06 Highest qualification in 1984 Degree/diploma 0.11 0.11 0.11 0.11 0.11 Apprenticeship 0.08 0.08 0.08 0.07 0.08 Other post-school 0.07 0.07 0.07 0.07 0.07 qualification Year 12 of school 0.16 0.16 0.16 0.15 0.16 Year 11 of school 0.13 0.13 0.13 0.13 0.13 Year 10 of school 0.31 0.30 0.31 0.31 0.31 Year 9 of school 0.14 0.12 0.14 0.14 0.14 Average recorded Pre-June 1984 unemployment 142 0.63 0.61 0.62 0.62 0.61 observations 2368 1687 1687 2368 1687 NOTE 1: for a 0-1 indicator variable, the mean gives the proportion. For example, the mean in the population, column 1, for gender=female is the proportion of females in the population. 142 Average recorded Pre-June 1984 unemployment is missing for 27 observations, and has a base of 2341.
199 6: Study 4 Weighting to counteract attrition and nonresponse in ALS In this chapter the combined weights are applied, which were constructed in the previous chapter to repair the data for loss due to attrition, non-response and to account for the survey design. First the weights are applied to the Heckman bivariate probit modelling, and the effects discussed. Then the weights are applied to the propensity score matching (PSM). The application of weights to PSM is more complex, and the full protocol is first presented and then the weighted results are discussed. Finally, the employment effects found from the Heckman and PSM models in the repaired data are contrasted with those formerly found. The discussion focuses on the limitations to each application. 6.1 Results of weighting Heckman bivariate probit The weights accounting for attrition, non-response and survey design were constructed in the previous section. Table 6.1 shows the effect of applying this sample reduction weight to the bivariate probit of employment and SYETP participation. The first column shows the unweighted replication results to better enable comparison while the final column gives the results for the regression weighted for sample reduction and survey design. Attention is focused on the treatment effect, as indicated by the SYETP variable. An important change brought in by accounting for the sample reduction is the loss of statistical significance for CEP referrals in 1984 in the SYETP participation equation. It is now less significant, although it would pass the t test at the significance level of 10 per cent. In the modelling of the treatment effect of SYETP, this is a key element of the identifying restriction in the bivariate probit. Along with this change, the SYETP treatment dummy loses size and statistical significance in the employment equation. The change introduced by weighting for sample reduction strongly affects the interpretation of SYETP treatment effect. Given the coincident change in the CEP referrals in the participation equation, and it’s role in the identifying restrictions for the bivariate probit, it is highly likely that adjusting for the selection effects due to attrition of the sample, has
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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
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
Page 179 and 180: 163 para-professional Mother not em
Page 181 and 182: 165 comparison group where the shar
Page 183 and 184: 167 5.5.4 Attrition: natural attrit
Page 185 and 186: 169 both sources that impose change
Page 187 and 188: 171 para-professional Father not em
Page 189 and 190: 173 work in later sections, this su
Page 191 and 192: 175 Table 5.6: Effect of selection/
Page 193 and 194: 177 appropriate to discard these fr
Page 195 and 196: 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: 197 adopted in order to maintain co
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 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
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249 Table 7.6 Weighted Probit used
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251 Table 7.7 Summary of distributi
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253 8: Summary and Conclusions The
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255 over which it ran, the review m
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257 the Heckman and PSM methods wer
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259 posited that that such sensitiv
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261 Description Derivation and deta
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Appendix 2 Tables 263
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2 years 0.28 0.07 (1.70) (1.70) 3 y
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267 Table A2.0b Univariate Probit o
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269 Religion brought up in (1.52) (
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271 hq9_84 Year 9 of school or less
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273 Table A2.1 Continued Means and
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275 mtrad Tradesperson 0.04 0.04 0.
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277 Year 9 of school or less -0.19
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279 Table A2.3 Probit of SYETP part
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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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