5) estimated gender gap =2.12
6) here test statistic =2.12/0.36=5.889
for above test statistic p value =0.0000
7)
as critical value =margin of error/std error =(2.83-1.41)/(2*0.36)=1.972 ~ 1.96
8)
mean wage of women =12.52
QUESTION 5 Suppose that a researcher, using wage data on 250 randomly selected male workers and 2...
2. Exercises: 5.2, part (a), (b), (c), (d) and (e) 5.2 Suppose a researcher, using wage data on 250 randomly selected male workers and 280 female workers, estimates the OLS regression www Wage - 12.52 + 2.12 Male, R? = 0.06, SER = 4.2, (0.23) (0.36) www. where Wage is measured in dollars per hour and Male is a binary variable that is equal to 1 if the person is a male and if the person is a female. Define...
top Suppose that a researcher, using wage data on 230 randomly selected male workers and 258 fermale workers, estimates the OLS regression 4 Wage 11.518 +1.950 x Male, R 0,04, SER = 3.9, (0.2116) (0.3312) where Wage is measured in dollars per hour and Male is a binary variable that is equal to 1 if the person is a male and 0if the person is a female. Define the wage gender gap as the difference in mean earnings between men...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.17 4.26 1.68 0.0991 Education 1.81 0.35 5.17 0.0000 Experience 0.45 0.10 4.50 0.0000 Age −0.01...
Using data from 50 workers, a researcher estimates Wage = ?0 + ?1Education + ?2Experience + ?3Age + ?, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.58 4.42 1.71 0.0931 Education 1.68 0.37 4.54 0.0000 Experience 0.35 0.18 1.94 0.0580 Age ?0.06...
Consider the model yi = β0 +β1X1i +β2X2i +ui . We fail to reject the null hypothesis H0 : β1 = 0 and β2 = 0 at 5% when: a) A F test of H0 : β1 = 0 and β2 = 0 give us a p value of 0.001 b) A t test of H0 : β1 = 0 give us a p value of 0.06 and a t test of H0 : β2 = 0 a p value...
The data set consists of information on 4900 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.73 3.94 1.96 0.0558 Education 1.15 0.39 2.95 0.0050 Experience 0.45 0.11 4.09 0.0002 Age −0.03...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 8.23 4.40 1.87 0.0678 Education 1.23 0.38 3.24 0.0022 Experience 0.53 0.18 2.94 0.0051 Age −0.08...
2 Using data from 50 workers, a researcher estimates Wage BoIEducation + 2Experience B3Age E, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker respectively. The regression results are shown in the following table. 10 points Standard Coefficients t Stat P-Value 0.1310 0.0003 0.0022 Error 4.24 Intercept Education Experience Age 6.52 1.32 1.54 0.34 0.12 3.88 3.25 -0.20 0.39 0.01 0.05...
The data set consists of information on 3700 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if...