) Demographic data from 126 countries is obtained for the year 2017. It is hypothesized that life expectancy (Y) is dependent on number of under five deaths (X2), polio immunization coverage (D), Per capita Govt. Exp. on Health Care (X3) (in Rs crores), Per Capita GNI (in Rs crores) (X4) and Average number of years of Schooling (Xs). Polio immunization coverage = 1 if yes and 0 otherwise. Following regressions were %3D estimated:

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Q5 a) Demographic data from 126 countries is obtained for the year 2017. It is hypothesized
that life expectancy (Y) is dependent on number of under five deaths (X2) , polio
immunization coverage (D), Per capita Govt. Exp. on Health Care (X3) (in Rs crores),
Per Capita GNI (in Rs crores) (X4) and Average number of years of Schooling (Xs).
Polio immunization coverage =1 if yes and 0 otherwise. Following regressions were
estimated:
MODEL 1:
= 0.903 – 0.561X2¡ + 2.008 X3i + 0.553X4¿ + 0.778 X5i + 3.638 D
(0.405)
se =
(1.280)
(0.765)
(0.712)
(0.491)
R? = 0.787
RSS = 1339.8
MODEL 2:
P, = 1.379 + 0.594 X31 + 2.139 D
se =
(0.406) (0.465)
R? = 0.677
RSS = 1567.28
i. Is it a time series or a cross sectional data
ii. Show model 2 is a restricted version of model 1 and what is the restriction?
iii. Test for the statistical significance of the restriction at 5% level.
iv. Construct a 95% confidence interval for true per capita government health
expenditure in model II and check whether it is statistically significant.
v. In a CLRM what will be the effect on estimates of slope coefficient and intercept if:
Y is multiplied by a constant c
X is multiplied by a constant c?
Transcribed Image Text:Q5 a) Demographic data from 126 countries is obtained for the year 2017. It is hypothesized that life expectancy (Y) is dependent on number of under five deaths (X2) , polio immunization coverage (D), Per capita Govt. Exp. on Health Care (X3) (in Rs crores), Per Capita GNI (in Rs crores) (X4) and Average number of years of Schooling (Xs). Polio immunization coverage =1 if yes and 0 otherwise. Following regressions were estimated: MODEL 1: = 0.903 – 0.561X2¡ + 2.008 X3i + 0.553X4¿ + 0.778 X5i + 3.638 D (0.405) se = (1.280) (0.765) (0.712) (0.491) R? = 0.787 RSS = 1339.8 MODEL 2: P, = 1.379 + 0.594 X31 + 2.139 D se = (0.406) (0.465) R? = 0.677 RSS = 1567.28 i. Is it a time series or a cross sectional data ii. Show model 2 is a restricted version of model 1 and what is the restriction? iii. Test for the statistical significance of the restriction at 5% level. iv. Construct a 95% confidence interval for true per capita government health expenditure in model II and check whether it is statistically significant. v. In a CLRM what will be the effect on estimates of slope coefficient and intercept if: Y is multiplied by a constant c X is multiplied by a constant c?
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