The Palestinian Economy. Theoretical and Practical Challenges

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Makhool
Table 13: Likelihood Ratio Tests
Effect -2 Log Likelihood of Reduced Model Chi-Square df Sig.
Intercept 111949.4 0 0 .
yerschol2 119835.6 7886.237 8 0
id07 112592.2 642.8202 4 8.4E-138
age1 113440.5 1491.161 14 0
Industry 155571 43621.66 10 0
Marital status 114264.3 2314.91 4 0
Wbgs 111949.4 0 0 .
id06 112988.5 1039.121 8 5.4E-219
sex 112107.9 158.5276 2 3.77E-35
The chi-square statistic is the difference in -2 log-likelihoods between the final model and a
reduced model. The reduced model is formed by omitting an effect from the final model. The null
hypothesis is that all parameters of that effect are 0.
The likelihood ratio test shows that there are statistically significant relationships between
the independent variable (years of schooling, sex, age at last birthday, district, locality
type, marital status, and industry group, and the dependent variable (labour force status).
Table 14: Gaza Strip: Parameter estimates for the log odds of
underemployed respondents relative to fully employed:
The values under B’s coefficient indicate log odds ratio associated with
each effect, while the values under E (B) indicate the odds- ratio.
Independent
variables
’s
coefficient
Standard
error
E( )
Wald
test
Significance
sex
Male .335 .047 1.399 50.229 .000
Female 0(b) . . . .
age
15-19 1.350 .072 3.858 350.940 .000
20-24 1.062 .063 2.891 280.831 .000
25-29 .953 .058 2.593 274.355 .000
30-34 1.030 .057 2.800 327.959 .000
35-39 .947 .058 2.577 269.717 .000
40-44 .480 .063 1.616 57.898 .000
45-49 .302 .072 1.352 17.761 .000
50 and over 0(b) . . . .