Suppose as part of the Public Protectors' inquiry (in South Africa) into gender discrimination and nepotism...
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Suppose as part of the Public Protectors' inquiry (in South Africa) into gender discrimination and nepotism you are asked, as an expert in econometrics, to compare total compensation among top executives in a large set of South African public corporations (a) Let Female be an indicator variable that is equal to 1 for females and 0 for males. A regression of the logarithm of earnings onto Female yields In(Earnings) = 6.48 – 0.44Female, SER = 2.65 (0.01) (0.05) where SER is the Standard Error of the Regression, and standard errors are in parentheses. These scores range from 1 (lowest) to 36 (highest). Question 2 continues on the next page.. EC3741 Introductory Econometrics I Page 3 of 3 (i) The estimated coefficient on Female is -0.44. Explain what this value means. (ii) The SER is 2.65. Explain what this value means. (iii) Does this regression suggest that female top executives earn less than top male executives? Explain. (iv) Does this regression suggest that there is gender discrimination? Explain. (b) Two new variables, the market value of the firm (a measure of firm size, millions dollars) and stock return (a measure of firm performance, in percentage points), are added to the regression: In(Earnings) = 3.86 – 0.28Female + 0.371n(MarketValue) +0.004Return, (0.03) (0.04) (0.004) (0.003) n = 46, 670, R = 0.345 standard errors are in parentheses, n is the sample size. (i) The coefficient on In(MarketValue) is 0.37. Explain what this value means. (ii) The coefficient on Female is now -0.28. Explain why it has changed from the regression in (a). (c) Are large firms more likely to have female top executives than small firms? Explain. Suppose as part of the Public Protectors' inquiry (in South Africa) into gender discrimination and nepotism you are asked, as an expert in econometrics, to compare total compensation among top executives in a large set of South African public corporations (a) Let Female be an indicator variable that is equal to 1 for females and 0 for males. A regression of the logarithm of earnings onto Female yields In(Earnings) = 6.48 – 0.44Female, SER = 2.65 (0.01) (0.05) where SER is the Standard Error of the Regression, and standard errors are in parentheses. These scores range from 1 (lowest) to 36 (highest). Question 2 continues on the next page.. EC3741 Introductory Econometrics I Page 3 of 3 (i) The estimated coefficient on Female is -0.44. Explain what this value means. (ii) The SER is 2.65. Explain what this value means. (iii) Does this regression suggest that female top executives earn less than top male executives? Explain. (iv) Does this regression suggest that there is gender discrimination? Explain. (b) Two new variables, the market value of the firm (a measure of firm size, millions dollars) and stock return (a measure of firm performance, in percentage points), are added to the regression: In(Earnings) = 3.86 – 0.28Female + 0.371n(MarketValue) +0.004Return, (0.03) (0.04) (0.004) (0.003) n = 46, 670, R = 0.345 standard errors are in parentheses, n is the sample size. (i) The coefficient on In(MarketValue) is 0.37. Explain what this value means. (ii) The coefficient on Female is now -0.28. Explain why it has changed from the regression in (a). (c) Are large firms more likely to have female top executives than small firms? Explain.
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required solution of all parts are given below Ans A A i the coefficient on female is 044 this means ... View the full answer
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Business Statistics a decision making approach
ISBN: 978-0133021844
9th edition
Authors: David F. Groebner, Patrick W. Shannon, Phillip C. Fry
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