Evaluation of the Australian Wage Subsidy Special Youth ...

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134 In general, all the results pass the usual checks for performance of the matching. There is a reasonable, low total bias (the mean standardized bias statistic is defined fully in section 4.9.2). The various calipers do not differ dramatically in terms of the mean standardized bias statistic. In general, the average difference in propensity was very low too, although this rises with greater caliper width as expected. The number of SYETP for which a match can be found within the caliper width chosen rises with caliper width as expected. The largest caliper width of 0.05 allows all 104 SYETP cases to be matched. Frölich et al. (1999) p41 point out that the advantage of replacement is clear as a matching algorithm that only uses a comparison case once can face difficulties when there is very low density for the comparison group compared to the treatment group. Replacement is not problematic as long as there is overlap in the propensity distributions. As shown in Figure 5, the propensity distributions overlap greatly, and there is no common support problem, as discussed earlier no cases are lost in the imposition of common support. The caliper also imposes a restriction that can act to impose the common support condition. A drawback of the replacement method can arise if the same observation may be used too often. The result of over-reliance on single observations can be a great loss in precision. The number of times a comparison case is used with replacement is shown in Table 4.6 to help assess this. The percentage of matched comparison cases used more than once remains less than 10 per cent, for all calipers. For example, for caliper 0.001 only 6 of the 79 comparison cases are used more than once. All the mean differences in employment are significant, so efficiency is not considered problematic.
135 Table 4.6 Matching results, Single nearest neighbour with replacement, within caliper Match with caliper width 0.001 Match with caliper width 0.005 Match with caliper width 0.01 Match with caliper width 0.02 Match with caliper width 0.05 Difference in employment 88 for 0.18 0.18 0.18 0.17 0.17 matched treated and comparisons Student’s t statistic (2.74) (2.68) (2.68) (2.66) (2.63) Number of SYETP matched 87 101 102 103 104 Number of comparison which satisfy 79 88 89 89 89 the caliper rule Number of times used 1 73 79 80 79 79 2 5 8 8 9 8 More than 2 1 1 1 1 2 Mean difference in propensity score 0.0002 0.0005 0.0006 0.0007 0.001 between single nearest neighbour matched treated and comparisons Standard deviation 0.0002 0.0009 0.004 0.002 0.003 Mean Standardized bias calculation after matching 9.66 9.90 9.74 9.45 9.58 88 Ever employed in 1986 survey.
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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
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 and 128: 111 4: Study 2 Propensity score mat
Page 129 and 130: 113 Propensity score matching provi
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: 133 Table 4.5, that the variance of
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
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
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185 3 years + -0.35 -0.47 -0.34 -0.
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187 5.7 Multivariate analysis of ef
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189 proportion of time spent unempl
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191 post-school qualification, and
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193 Generally, those variables foun
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195 longj0 Longest job by 1984 < 1
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197 adopted in order to maintain co
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199 6: Study 4 Weighting to counter
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201 Table 6.1, part A Employment eq
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203 Methodist 0.133 0.261 (0.77) (1
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205 CEP referrals 1984 0.143* 0.128
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207 6.2 Results of weighting the PS
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209 The distribution of the propens
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211 Table 6.3 Weighted probit used
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213 (0.76) Tradesperson mtrad 0.20
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215 Table 6.5 Summary statistics fo
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217 Table 6.7 Matching results, sin
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219 6.3 Discussion The comparison o
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221 the selection into SYETP and th
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223 Heteroskedasticity is a violati
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225 Table 7.1, Part A Employment eq
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227 (1.26) (1.28) (1.16) Mothers oc
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229 Other Post-School qualification
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231 7.1.2 Exclusion restriction in
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233 Finally, the third panel of new
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235 Table 7.2 summary of changes to
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237 schooling that was statisticall
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239 (0.25) (0.21) 3 years + -0.50 -
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241 Table 7.4 Summary of distributi
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243 7.2.2 Propensity score matching
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245 original model, but with the pe
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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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