MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Question
Read the box "The Return to Education and the Gender Gap."
The Return to Education and the Gender Gap
Dependent variable: logarithm of Hourly Earnings.
*
Regressor
Years of education
Female
Female x Years of education
Potential experience
Potential experience²
Midwest
South
West
Intercept
(1)
0.1035**
(0.0009)
1.533"
(0.012)
0.208
(2)
0.1050**
(0.0009)
-0.263**
(0.004)
1.629"
(0.012)
0.1001"
(0.0011)
0.258
-0.432**
(0.024)
0.0121"
(0.0017)
1.697**
(0.016)
(4)
0.1013**
(0.0012)
0.258
-0.451"
(0.024)
0.0134"
(0.0017)
0.0136**
(0.0012)
-0.000184**
(0.000021)
-0.095"
(0.006)
-0.092**
(0.006)
-0.028"*
(0.007)
1.328"
R²
The sample size is 52,970 observations for each regression. Female is an indicator variable that equals 1 for
women and 0 for men. Midwest, South, and West are indicator variables denoting the region of the United States
(0.023)
0.267
expand button
Transcribed Image Text:Read the box "The Return to Education and the Gender Gap." The Return to Education and the Gender Gap Dependent variable: logarithm of Hourly Earnings. * Regressor Years of education Female Female x Years of education Potential experience Potential experience² Midwest South West Intercept (1) 0.1035** (0.0009) 1.533" (0.012) 0.208 (2) 0.1050** (0.0009) -0.263** (0.004) 1.629" (0.012) 0.1001" (0.0011) 0.258 -0.432** (0.024) 0.0121" (0.0017) 1.697** (0.016) (4) 0.1013** (0.0012) 0.258 -0.451" (0.024) 0.0134" (0.0017) 0.0136** (0.0012) -0.000184** (0.000021) -0.095" (0.006) -0.092** (0.006) -0.028"* (0.007) 1.328" R² The sample size is 52,970 observations for each regression. Female is an indicator variable that equals 1 for women and 0 for men. Midwest, South, and West are indicator variables denoting the region of the United States (0.023) 0.267
Female
Female x Years of education
Potential experience
Potential experience
Midwest
South
West
Intercept
1.533"
(0.012)
0.208
-0.263"
(0.004)
1.629"
(0.012)
-0.432**
0,024)
0.258
00121"*
(0.0017)
1.697**
(0.016)
-0.451**
(0.024)
0.258
0.0134"
(0.0017)
0.0136**
(0.0012)
-0.000184"
(0.000021)
-0.095"
(0.006)
-0.092
(0.006)
-0.028"*
(0.007)
1.328"
R²
The sample size is 52,970 observations for each regression. Female is an indicator variable that equals 1 for
women and 0 for men. Midwest, South, and West are indicator variables denoting the region of the United States
in which the worker lives: For example, Midwest equals 1 if the worker lives in the Midwest and equals 0
otherwise (the omitted region is Northeast). Standard errors are reported in parentheses below the estimated
coefficients. Individual coefficients are statistically significant at the "5% or 1% significance level.
(0.023)
0.267
Scenario A
Consider a man with 18 years of education and 4 years of experience who is from a western state. Use the results from column (4) of the table and the method in Key Concept 8.1 to estimate t
expected change in the logarithm of average hourly earnings (AHE) associated with an additional year of experience.
The expected change in the logarithm of average hourly earnings (AME) associated with an additional year of experience is % (Round your response to two decimal places.)
expand button
Transcribed Image Text:Female Female x Years of education Potential experience Potential experience Midwest South West Intercept 1.533" (0.012) 0.208 -0.263" (0.004) 1.629" (0.012) -0.432** 0,024) 0.258 00121"* (0.0017) 1.697** (0.016) -0.451** (0.024) 0.258 0.0134" (0.0017) 0.0136** (0.0012) -0.000184" (0.000021) -0.095" (0.006) -0.092 (0.006) -0.028"* (0.007) 1.328" R² The sample size is 52,970 observations for each regression. Female is an indicator variable that equals 1 for women and 0 for men. Midwest, South, and West are indicator variables denoting the region of the United States in which the worker lives: For example, Midwest equals 1 if the worker lives in the Midwest and equals 0 otherwise (the omitted region is Northeast). Standard errors are reported in parentheses below the estimated coefficients. Individual coefficients are statistically significant at the "5% or 1% significance level. (0.023) 0.267 Scenario A Consider a man with 18 years of education and 4 years of experience who is from a western state. Use the results from column (4) of the table and the method in Key Concept 8.1 to estimate t expected change in the logarithm of average hourly earnings (AHE) associated with an additional year of experience. The expected change in the logarithm of average hourly earnings (AME) associated with an additional year of experience is % (Round your response to two decimal places.)
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