Evaluation of the Australian Wage Subsidy Special Youth ...

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192 5.8 Model of the probability of attrition To construct the weight for non-response and selection that was provided with the data, administrative data was used to weight back to the population. Only survey data is available to be applied to estimates of the sample attrition weight. As the attrition only occurs after the 1984 survey, it is likely the survey information is the most relevant for describing the characteristics of the respondents, as it is gathered at a more recent juncture while the administrative data would be more dated. One useful piece of relevant information that is not available in the data would be survey collection information about movers. This variable had a central role in describing non-response. However, unavailability means the importance of this item to attrition cannot be assessed. The variables selected for explaining attrition are chosen from amongst those variables measured in the 1984 survey. The model is weighted by the initial nonresponse/design/selection weight in order to represent the 1984 data, so that the estimates which will be used for the attrition weights will only account for the further non-response to the later surveys to 1986. In this following model, it is assumed that the same process as that of attrition to 1986 defines attrition to the 1985 survey. 138 The results of estimation for the probit model of attrition are shown in column 1 of table 5.9. Those who were interviewed in South Australia and the Northern Territory, Western Australia and Tasmania, were more likely to also be interviewed in later years to 1986. Additionally, those in country towns and rural areas, and those with a highest qualification to year 12, had a higher tendency to be interviewed again in later years. Those with longer unemployment prior to June 1984 were less likely to be surveyed again in later years, as were those who were missing the unemployment variable, had held longer jobs in the past, and those who were married. Participants in SYETP were more likely to respond to later surveys. 138 In exploration of this, results for which are not shown, separate modelling of the attrition to each year was not found to have different estimated models, with the same coefficients statistically significant and of similar magnitude, and so common modelling of the attrition was found appropriate.
193 Generally, those variables found to be statistically significant in the multivariate model of attrition reflect those pointed out by the univariate analysis of difference in mean arising from attrition (see section5.5.4 and Table 5.5). As a summary measure of fit for the probit model, the predictions of the model are examined. A fitted probability exceeding 0.5 is taken to indicate a predicted response to the survey. When these predicted responses are compared to the actual interviews in 1986 the model correctly predicted the attrition to 1986 for 72 per cent of the 1984 observations. The other measures of fit indicate no serious problems. These weights are now introduced into a single final weight that can be used for modelling. This combined weight could then be used to reflect the total effect due to nonresponse, survey design, and survey attrition.
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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
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
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: 191 post-school qualification, and
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 and 258: 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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