Homework SourseThe following table presents the estimates of the Labor Forc
The following table presents the estimates of the Labor Force Participation of women in a developing country. The standard errors are in parentheses. All estimates are significant in a=5% level. The number of observations are 753.
Where:
inlf: woman in the labor force, with inlf=1 the woman works, 0 otherwise
nwifeinc: husband’s earnings
educ: years of education of woman
exper: labor market experience of woman
age: age of woman
kidslt6: dummy variable, presents number of children less than 6 years old, with value 1 having children, value 0 otherwise kidsge6: dummy variable, presents number of children between 6 and 18 years old, with value 1 having children, value 0 otherwise
Write each model in estimated regression form and describe each model separately, i.e. describe the effects of each independent variable to the dependent variable. Each variable tells a story. - Do the estimates of each model tell a consistent story? Why? - Can you elaborate by stating the differences between these models? Which model would you prefer and why?
Dependent Variable: inlf Independent Variables nwifeinc LPM (OLS) Logit (MLE Probi (MLE) .0034 .0015) 038 (.007) 039 (.006) -,00060 -021 221 206 .012 .005) 131 .025) 123 (.019) .0019 educ ns exper age kidslt6 0032 (.0010) -088 .00018) (.0006) -,016 (.002) -.262 142 013 (.013) 586 (.151) 3.4 -1.443 (.204) ·060 (075) 425 (.860) 73.6 401.77 .053 (008) -868 (.119 036 043) 270 (.509) 73.4 kidsge6 constant Percentage correctly predicted Log-likelihood value Pseudo R-squared -401.30 264 .220 221Solution
Given that the table presents the estimates of the Labor Force Participation of women in a developing country. The standard errors are in parentheses. All estimates are significant in a=5% level. The number of observations are 753
Here dependent variable is inlf and dependent variables are nwifeinc, educ, exper, exper2, age, kidslt6, kidsge6.
These all are dependent variables.
where,
inlf: woman in the labor force, with inlf=1 the woman works, 0 otherwise
nwifeinc: husband’s earnings
educ: years of education of woman
exper: labor market experience of woman
age: age of woman
kidslt6: dummy variable, presents number of children less than 6 years old, with value 1 having children, value 0 otherwise
kidsge6: dummy variable, presents number of children between 6 and 18 years old, with value 1 having children, value 0 otherwise
Write each model in estimated regression form and describe each model separately, i.e. describe the effects of each independent variable to the dependent variable.
The regression equation is,
Y = 0 + 1X1 + 2X2 + 3X3
There are three independent variables for nwifeinc.
X1 is the LPM for nwifeinc
X2 is the Logit for nwifeinc
and X3 is the Probit for nwifeinc
From the table constant is the value of 0 in the regression equation.
and 1, 2 and 3 are the slope which is in front of OLS.
For the first independent variable that is nwifeinc
0 = 0.586
1 = - 0.0034
2 = -0.021
3 = - 0.012
Thus the regression equation is,
Y = 0.586 + - 0.0034 * X1 + -0.021 * X2 + - 0.012 * X3
where Y is the response variable(dependent) that is inlf. and
There are three independent variables for educ.
X1 is the LPM for educ
X2 is the Logit for educ
and X3 is the Probit for educ
From the table constant is the value of 0 in the regression equation.
and 1, 2 and 3 are the slope which is in front of OLS.
For the first independent variable that is educ
0 = 0.425
1 = 0.038
2 = 0.221
3 = 0.131
Thus the regression equation is,
Y = 0.425 + 0.038 * X1 + 0.221 * X2 + 0.131 * X3
Now for exper,
There are three independent variables for exper.
X1 is the LPM for exper
X2 is the Logit for exper
and X3 is the Probit for exper
From the table constant is the value of 0 in the regression equation.
and 1, 2 and 3 are the slope which is in front of OLS.
For the first independent variable that is exper
0 = 0.270
1 = 0.039
2 = 0.206
3 = 0.123
Thus the regression equation is,
Y = 0.270 + 0.039 * X1 + 0.206 * X2 + 0.0.123 * X3
