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book Introduction to Econometrics 3rd Edition by James Stock, Mark Watson cover

Introduction to Econometrics 3rd Edition by James Stock, Mark Watson

النسخة 3الرقم المعياري الدولي: 978-9352863501
book Introduction to Econometrics 3rd Edition by James Stock, Mark Watson cover

Introduction to Econometrics 3rd Edition by James Stock, Mark Watson

النسخة 3الرقم المعياري الدولي: 978-9352863501
تمرين 20
This problem is inspired by a study of the "gender gap" in earnings in top corporate jobs [Bertrand and Hallock (2001)]. The study compares total compensation among top executives in a large set of U.S. public corporations in the 1990s. (Each year these publicly traded corporations must report total compensation levels for their top five executives.)
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
This problem is inspired by a study of the gender gap in earnings in top corporate jobs [Bertrand and Hallock (2001)]. The study compares total compensation among top executives in a large set of U.S. public corporations in the 1990s. (Each year these publicly traded corporations must report total compensation levels for their top five executives.) 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     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, in millions of dollars) and stock return (a measure of firm performance, in percentage points), are added to the regression:     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.
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, in millions of dollars) and stock return (a measure of firm performance, in percentage points), are added to the regression:
This problem is inspired by a study of the gender gap in earnings in top corporate jobs [Bertrand and Hallock (2001)]. The study compares total compensation among top executives in a large set of U.S. public corporations in the 1990s. (Each year these publicly traded corporations must report total compensation levels for their top five executives.) 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     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, in millions of dollars) and stock return (a measure of firm performance, in percentage points), are added to the regression:     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.
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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a) The estimation of earnings for given ...

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Introduction to Econometrics 3rd Edition by James Stock, Mark Watson
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