ker's age ranged from 25 to 34 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. West is the omitted region. A detailed description of the variables used in the data set is available here Results of Regressions of Average Hourly Eamings on Gender and Education Binary Variables and Other Characteristics Using 1998 Data from the Curren Population Survey. Dependent variable: average hourly earnings (AHE). Regressor (1) 5.42 (0.26) -2.18 (021) (2) 5.44 (0.26) (3) 5.32 (0.26) -239 (0.21) College (X,) Female (X2) -2.39 (0.21) 0.14 0.14 Age (X3) (0.01) (0.01) 0.52 (0.27) 0.53 (0.29) -0.23 (0.25) Northeast (X4) Midwest (Xs) South (X) 12.43 4.49 3.13 Intercept (0.15) (1.02) (1.01) Summary Statistics and Joint Tests F-statistic for regional effects = 0 6.11 SER 6.27 6.22 621 0.137 3628 Note: The numbers in parentheses below each estimated coefficient are the estimated 0.104 0.176 3628 3628 standard errors. regression shown in column (2) was estimated again, this time using data from 1992 (3628 observations selected at random from the March 1993 CPS, converted into 1998 dollars using the consumer price index). The results are AHE = 0.77 +5.29College - 259Female +0.40Age. SER = 5.85, R = 0.21 (0.98) (0.20) (0.18) (0.03) numbers in parentheses are the estimated standard errors. culate the t-statistic for the change in the College coefficient between 1992 and 1998. The fstatistic for the channe int officient bet 1992 and 1998 Rn
ker's age ranged from 25 to 34 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. West is the omitted region. A detailed description of the variables used in the data set is available here Results of Regressions of Average Hourly Eamings on Gender and Education Binary Variables and Other Characteristics Using 1998 Data from the Curren Population Survey. Dependent variable: average hourly earnings (AHE). Regressor (1) 5.42 (0.26) -2.18 (021) (2) 5.44 (0.26) (3) 5.32 (0.26) -239 (0.21) College (X,) Female (X2) -2.39 (0.21) 0.14 0.14 Age (X3) (0.01) (0.01) 0.52 (0.27) 0.53 (0.29) -0.23 (0.25) Northeast (X4) Midwest (Xs) South (X) 12.43 4.49 3.13 Intercept (0.15) (1.02) (1.01) Summary Statistics and Joint Tests F-statistic for regional effects = 0 6.11 SER 6.27 6.22 621 0.137 3628 Note: The numbers in parentheses below each estimated coefficient are the estimated 0.104 0.176 3628 3628 standard errors. regression shown in column (2) was estimated again, this time using data from 1992 (3628 observations selected at random from the March 1993 CPS, converted into 1998 dollars using the consumer price index). The results are AHE = 0.77 +5.29College - 259Female +0.40Age. SER = 5.85, R = 0.21 (0.98) (0.20) (0.18) (0.03) numbers in parentheses are the estimated standard errors. culate the t-statistic for the change in the College coefficient between 1992 and 1998. The fstatistic for the channe int officient bet 1992 and 1998 Rn
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text:Refer to the table of estimated regressions below, computed using data for 1998 from the CPS, to answer the following question. The data set consists of information on 4000 full-time full-year workers. The highest educational achievement of each worker was either a high school diploma or a bachelor's degree. The
worker's age ranged from 25 to 34 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. West is the omitted region. A detailed description of the variables used in the data set is available here
Results of Regressions of Average Hourly Earnings on Gender and Education Binary
Variables and Other Characteristics Using 1998 Data from the Curren Population Survey.
Dependent variable: average hourly earnings (AHE).
Regressor
(1)
(2)
(3)
5.42
5.44
5.32
College (X,)
(0.26)
- 2.18
(0.21)
(0.26)
- 2.39
(0.21)
(0.26)
- 2.39
(0.21)
Female (X2)
0.14
0.14
Age (X3)
(0.01)
(0.01)
0.52
Northeast (X4)
(0.27)
0.53
(0.29)
- 0.23
(0.25)
Midwest (X5)
South (X6)
12.43
4.49
3.13
Intercept
(0.15)
(1.02)
(1.01)
Summary Statistics and Joint Tests
F-statistic for regional effects = 0
6.11
SER
6.27
6.22
6.21
R?
0.104
0.176
0.137
3628
3628
3628
Note: The numbers in parentheses below each estimated coefficient are the estimated
standard errors.
The regression shown in column (2) was estimated again, this time using data from 1992 (3628 observations selected at random from the March 1993 CPS, converted into 1998 dollars using the consumer price index). The results are
AHE = 0.77 + 5.29College - 2.59Female + 0.40Age, SER= 5.85, R = 0.21
(0.98) (0.20)
(0.18)
(0.03)
The numbers in parentheses are the estimated standard errors.
Calculate the t-statistic for the change in the College coefficient between 1992 and 1998.
The t-statistic for the change in the College coefficient between 1992 and 1998
(Round your response to three decimal places)
Transcribed Image Text:Was the change in the College coefficient between 1992 and 1998 statistically significant at the 5% significance level?
O A. Yes.
O B. No.
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