At how many average weekly hours worked is the marginal effect of hours on predicted wage equal to zero? What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
At how many average weekly hours worked is the marginal effect of hours on predicted wage equal to zero? What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
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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At how many average weekly hours worked is the marginal effect of hours on predicted wage equal to zero?
-
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What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
-
![Consider the following OLS regression output which is estimated with Wage2.dta (see
tutorial folder on Blackboard)
Source
df
MS
Number of obs
935
F (4, 930)
36.82
Model
22.6467366
4
5.66168416
Prob > F
0.0000
%3D
Residual
143.009547
930
.153773706
R-squared
Adj R-squared
0.1367
%3D
0.1330
%3D
Total
165.656283
934
.177362188
Root MSE
.39214
%3D
lwage
Сoef.
Std. Err.
P>|t|
[95% Conf. Interval]
educ
.0400982
.0068351
5.87
0.000
.0266843
.0535122
IQ
.005914
.0009967
5.93
0.000
.0039579
.0078701
hours
.0035899
.013037
0.28
0.783
-.0219954
.0291752
hours2
-.0000842
.0001298
-0.65
0.517
-.0003389
.0001706
cons
5.649044
.3240363
17.43
0.000
5.013117
6.284971
where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ
is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is
experience squared (hours * hours). Assume that MLR 1-6 hold.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb2d5f33c-ae78-41ed-81b8-d30f18a3c571%2F3efe89fe-8733-472e-90a2-b19b54aab86e%2Favlz8qk_processed.png&w=3840&q=75)
Transcribed Image Text:Consider the following OLS regression output which is estimated with Wage2.dta (see
tutorial folder on Blackboard)
Source
df
MS
Number of obs
935
F (4, 930)
36.82
Model
22.6467366
4
5.66168416
Prob > F
0.0000
%3D
Residual
143.009547
930
.153773706
R-squared
Adj R-squared
0.1367
%3D
0.1330
%3D
Total
165.656283
934
.177362188
Root MSE
.39214
%3D
lwage
Сoef.
Std. Err.
P>|t|
[95% Conf. Interval]
educ
.0400982
.0068351
5.87
0.000
.0266843
.0535122
IQ
.005914
.0009967
5.93
0.000
.0039579
.0078701
hours
.0035899
.013037
0.28
0.783
-.0219954
.0291752
hours2
-.0000842
.0001298
-0.65
0.517
-.0003389
.0001706
cons
5.649044
.3240363
17.43
0.000
5.013117
6.284971
where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ
is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is
experience squared (hours * hours). Assume that MLR 1-6 hold.
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