Consider the logit/probit model with the dependent variable Y receiving the value 1 if the household decides to invest on high-techonogy in agriculture production; and 0 otherwise; the independent variables age, edu, female and urban are age, education (number of years of schooling), gender (female=1 if the head of household is female, 0 otherwise) of the household head, urban = 1 if household lives in urban areas, 0 otherwise. The estimated results and marginal effects are as follows: Logistic regression Log likelihood = -94.991141 Number of obs LR chi2 (3) Prob chi2 Pseudo R2 190 = 20.35 = 0.0001 = 0.0967
Consider the logit/probit model with the dependent variable Y receiving the value 1 if the household decides to invest on high-techonogy in agriculture production; and 0 otherwise; the independent variables age, edu, female and urban are age, education (number of years of schooling), gender (female=1 if the head of household is female, 0 otherwise) of the household head, urban = 1 if household lives in urban areas, 0 otherwise. The estimated results and marginal effects are as follows: Logistic regression Log likelihood = -94.991141 Number of obs LR chi2 (3) Prob chi2 Pseudo R2 190 = 20.35 = 0.0001 = 0.0967
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Please help me with the question in the image, possibly provide detail answer, i want to understand and learn before the test. Thank you in advanced!
Transcribed Image Text:3. Consider the logit/probit model with the dependent variable Y receiving the value 1 if the
household decides to invest on high-techonogy in agriculture production; and 0 otherwise; the
independent variables age, edu, female and urban are age, education (number of years of
schooling), gender (female = 1 if the head of household is female, 0 otherwise) of the household
head, urban = 1 if household lives in urban areas, 0 otherwise.
The estimated results and marginal effects are as follows:
Logistic regression
Log likelihood = -94.991141
Number of obs
LR chi2 (3)
Prob chi2
Pseudo R2
190
= 20.35
= 0.0001
= 0.0967
=
![Y Coefficient
edu | .6286031
age
.3812022
female |
1.21768
urban |
0.81768
_cons | . 7147315
Average marginal effects
dy/dx
.0202377
- .045245
Std. err.
.1874322
.2005924
.3858659
.3858659
.2287764
Delta-method
std. err.
Z
P> |Z|
2.29 0.022
-2.90 0.004
3.16 0.002
3.02 0.012
3.12
0.002
z P> |z|
[95% conf. interval]
2.38 0.317
-3.11 0.002
3.37 0.001
3.37 0.001
.0612428
-.9743561
.4613966
.4613966
.266338
.7959634
-.1880483
1.973963
1.973963
1.163125
Number of obs = 190
[95% conf. interval]
edu |
age I
female |
. 0295193
.0306121
.0593228
.0698944
urban | .1198944 .0593228
Explain the effect of education, age, gender on the probability of household' decision.
.012381
-.1552437
.0836237
.0836237
.1280944
-.0352464
.316165
.316165](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F24889542-b63c-4fff-b5fe-0ef576c8ef2c%2F4c620e29-0382-42a0-8594-10180a5c143a%2Fh827e8_processed.png&w=3840&q=75)
Transcribed Image Text:Y Coefficient
edu | .6286031
age
.3812022
female |
1.21768
urban |
0.81768
_cons | . 7147315
Average marginal effects
dy/dx
.0202377
- .045245
Std. err.
.1874322
.2005924
.3858659
.3858659
.2287764
Delta-method
std. err.
Z
P> |Z|
2.29 0.022
-2.90 0.004
3.16 0.002
3.02 0.012
3.12
0.002
z P> |z|
[95% conf. interval]
2.38 0.317
-3.11 0.002
3.37 0.001
3.37 0.001
.0612428
-.9743561
.4613966
.4613966
.266338
.7959634
-.1880483
1.973963
1.973963
1.163125
Number of obs = 190
[95% conf. interval]
edu |
age I
female |
. 0295193
.0306121
.0593228
.0698944
urban | .1198944 .0593228
Explain the effect of education, age, gender on the probability of household' decision.
.012381
-.1552437
.0836237
.0836237
.1280944
-.0352464
.316165
.316165
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