The data set consists of information on 4200 full-time full-year workers. The hi

Question

The data set consists of information on 4200 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma ora 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 college, O if high school) Female = binary variable (1 if female, 0 if male) Age- age (in years) Ntheas binary variable (1 if Region = Northeast, 0 otherwise) Midwest binary variable (1 if Region Midwest, 0 otherwise) South = binary variable (1 if Region = South, 0 otherwise) Wests binary variable (1 if Region = West, 0 otherwise) Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using Data from the Current Population Survey Dependent Variable: average h hourly earnings (AHE Regressor College (%) Female (X2) Age (%) Northeast (X4 5.04 (0.19) -2.41 (0.18) 0.27 (0.04) 5.02 5.00 -2.43 0.18) 2.41 (0.18) 0.27 (0.04) 0.63

Explanation / Answer

t statistic of college - high school earnings difference = (Coefficient of College - 0) / Standard error of college
= 5.02 / 0.19 = 26.42

Critical value of t for 90% confidence is 1.64

Since the absolute value of the t-statistic is greater than the critical value of 90% , the college - high school earnings difference estimated from the regression is statistically significant at the 10% level.

Estimated college - high school earnings difference = Coefficient of College = 5.02
90% confidence interval is
(5.02 - 1.64*0.19, 5.02 + 1.64*0.19)
(4.71, 5.33)

t statistic of male - female earnings difference = (0 - Coefficient of Female) / Standard error of Female
= 2.43 / 0.18 = 13.5

Critical value of t for 90% confidence is 1.64

Since the absolute value of the t-statistic is greater than the critical value of 90% , the male - female earnings difference estimated from the regression is statistically significant at the 10% level.

Estimated male - female earnings difference = 0 - Coefficient of Female = 2.43
90% confidence interval is
(2.43 - 1.64*0.18, 2.43 + 1.64*0.18)
(2.13, 2.73)

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