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Help asap! 2. (2 points) Rachel is a graduate student at Mac who is interested in issues related to labor market discrimination. As such, she

Help asap!

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2. (2 points) Rachel is a graduate student at Mac who is interested in issues related to labor market discrimination. As such, she plans to write a term paper regarding the male-female wage gap for one of her graduate courses. As a starting point, she performs a simple Oaxaca decomposition using a public dataset that she acquired online. First, she starts with the simplest specification as follows: Specification 1: In(hourly wage) = a + b x (years of education) Using a statistical software, she gets the following Oaxaca decomposition results: . oaxaca Inwage educ, by(female) weight(@) Blinder-Oaxaca decomposition Number of obs 1,434 1: female = 0 2: fomale = 1 Inwage Conf. Std. Irr. [95% Conf. Interval] Differential Prediction_1 3.4-40221 .6174724 196.89 J.463977 J.474447 Prediction_2 3.246761 .0218257 140.64 0.060 3. 223984 Difference .1734607 .0279579 6.20 0.041 -1104642 .2282573 Decomposition Explained .0457839 .0112163 4.04 0.040 .0473734 Unexplained .1276708 .0266498 4.70 0.001 0753594 .1799418 Next, she tries a different specification with additional controls: Specification 2: In(hourly wage) = a + b x (years of education) + c x (years of labor market experience) + d x (years of job tenure) With the second specification, she gets the following decomposition results: . oaxaca Inwage educ exper tenure, by(female) weight(0) Blinder Oaxaca decomposition Number of obs 1,454 1: female = d 2: female = 1 Inware Coof Std. Err. Pylal (95% Conf. Interval] Differential Prediction_1 3.440222 . 0174874 196.73 3. 405947 3.474497 Prediction 2 3.266761 0210523 149.49 3. 223932 3. 109591 Difference -1734607 027958 6.30 0.900 1186052 .3283163 Decomposition Explained 6852798 015643 0545322 . 1160375 Unexplained 0881809 026692 0.001 .0358655 .140-4963 Based on these results, choose two of the following interpretations that are the least reasonable. a) On average, the hourly wage of men is approximately 17.3% higher than that of women. b) Under Specification 1, about 0.046 log points are due to average differences in education years between men and women

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