Evaluation of the Australian Wage Subsidy Special Youth ...

186
professional
(0.60) (0.83) (0.78) (1.11)
Not employed 0.08 -0.00 0.03 -0.10
(0.46) (0.03) (0.13) (0.45)
Mother post-school qualification 0.21 0.19 0.25 0.24
when resp 14
Religion brought up in (1.64) (1.45) (1.55) (1.40)
Catholic 0.16 0.12 0.05 -0.02
(1.27) (0.97) (0.32) (0.11)
Presbyterian 0.28 0.21 0.32 0.25
(1.46) (1.05) (1.31) (1.05)
Methodist 0.12 0.24 0.11 0.23
(0.60) (1.11) (0.44) (0.96)
Other Christian -0.06 -0.11 0.09 0.10
(0.26) (0.52) (0.34) (0.36)
Other religion 0.16 0.22 0.14 0.13
(0.94) (1.16) (0.63) (0.54)
No religion 0.14 0.17 0.17 0.16
(0.94) (1.08) (0.84) (0.83)
missing fathers qualifications -0.49 -0.55
(1.60) (1.69)
missing Mothers qualifications 0.01 0.10
(0.02) (0.42)
missing proportion of time spent -0.07 -0.08
unemployed
(0.12) (0.16)
missing number of siblings 0.20 0.17
(0.79) (0.68)
Constant -0.01 -0.33 0.66 0.39
(0.03) (0.60) (0.86) (0.59)
Observations 2368 2368 1283 1283
Log likelihood -503.74 -500.54 -307.52 -307.63
LR chi 2 (59) 134 137.31 150.58 106.91 126.23
Mcfadden’s Pseudo R 2 135
0.1199 0.1284 0.1481 0.1553
Akaike Information Criterion 0.48 0.48 0.57 0.57
Coefficient with t statistic in brackets. Absolute value of z statistics in parentheses * significant at 5%, **
significant at 1%. Base categories: European ethnic origin, state interviewed in 1984 NSW/ACT,
government school, highest qualification in 1984 year 10 at school, longest job by 1984 is 1 year, lived
mostly in state capital city until respondent aged 14, English is first language, father clerical worker when
respondent aged 14, mother clerical worker when respondent aged 14, religion brought up in is Anglican.
Notes: Variables miss 1 (mothers occupation missing) and miss 2 (fathers occupation missing) predict
failure perfectly, and cannot be added to the regression.
134 This is the likelihood ratio test of the hypothesis that all coefficients except the intercept are equal to
zero. It is defined as LR = 2 (log likelihood M full – 2 log likelihood M intercept ). The degrees of freedom of this
chi squared distributed statistic are equal to the number of constrained parameters i.e. the number of
coefficients being tested.
135 This measure of fit is also known as the likelihood ratio index. It compares the full model of parameters
(M full ) to a model with just the intercept (M intercept ). It is defined as R 2 = 1 – (log likelihood M full / log
likelihood M intercept ) . The value of Mcfadden’s Pseudo R 2 increases as new variables are added.