The Palestinian Economy. Theoretical and Practical Challenges

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Makhool
The chi- square value of 173727.133 with 62 df is highly significant, this means that
the null hypothesis that all effects of the independent variable are zero can be rejected.
Table 8: Likelihood Ratio Tests(b)
Effect -2 Log Likelihood of Reduced Model Chi-Square df Sig.
Intercept 292366.246(a) .000 0 .
yerschol2 314269.314 21903.068 8 .000
id07 292920.796 554.551 4 .000
age1 299186.321 6820.075 14 .000
industry 386015.399 93649.154 10 .000
marital 294275.128 1908.882 4 .000
wbgs 292366.246(a) .000 0 .
id06 331169.241 38802.995 20 .000
sex 302724.043 10357.797 2 .000
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.
a. This reduced model is equivalent to the final model because omitting the effect does not
increase the degrees of freedom.
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 9: West Bank: 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
Sex
Male 1.437 .022 4.209 4442.286 .000
Female 0(b) . . . .
Age
15-19 .596 .038 1.816 250.540 .000
20-24 1.165 .031 3.206 1398.425 .000
25-29 1.099 .028 3.000 1493.254 .000
's coefficient Standard error E( ) Wald test Significance