Regressions of Tobin's Q (the ratio of market value to book value) on measures of female...

 

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Regressions of Tobin's Q (the ratio of market value to book value) on measures of female participation in top management. FEMSUBCEO is a dummy variable taking the value 1 if a firm has a female executive below the CEO level listed in EXECUCOMP. FEMCEO is a dummy variable taking the value 1 if a firm has a female CEO. FIRMAGE is the age of the firm. BOOKLEV is book leverage. RDINT is the ratio of the firm's R&D expense to assets, with a value of zero imputed if R&D expense is not reported. NUMEXEC is the total number of executives listed in EXECUCOMP. Regressions include fixed effects for the year and industry at the 4-digit SIC code level. Observations where the value of Tobin's Q is more than 3 standard deviations away from the mean are excluded. All standard errors are robust to heteroskedasticity and arbitrary within-firm serial correlation. *, **, *** denote significance at the 10%, 5%, and 1% levels respectively. (1) (2) FEMSUBCEO FEMCEO LNASSETS FIRMAGE BOOKLEV RDINT NUMEXEC Observations R² 0.0625 -0.0269 -0.0023 -0.8794 3.2998 -0.0225 19,509 0.36 *** 0.0625 -0.0004 -0.0269 -0.0023 -0.8795 3.2998 -0.0225 19,509 0.36 *** *** *** Does having a female CEO reduce firm performance? . What are three ways to increase firm performance? . • Does the model explain most of the variance in firm performance? . . Can you tell which variable decreases firm performance the most? (If so, which one? If not, why not? Hint: This is a tricky question.) NOTE- The coefficients with a *** are statistically significant and the coefficients without a are not statistically significant. *** Regressions of Tobin's Q (the ratio of market value to book value) on measures of female participation in top management. FEMSUBCEO is a dummy variable taking the value 1 if a firm has a female executive below the CEO level listed in EXECUCOMP. FEMCEO is a dummy variable taking the value 1 if a firm has a female CEO. FIRMAGE is the age of the firm. BOOKLEV is book leverage. RDINT is the ratio of the firm's R&D expense to assets, with a value of zero imputed if R&D expense is not reported. NUMEXEC is the total number of executives listed in EXECUCOMP. Regressions include fixed effects for the year and industry at the 4-digit SIC code level. Observations where the value of Tobin's Q is more than 3 standard deviations away from the mean are excluded. All standard errors are robust to heteroskedasticity and arbitrary within-firm serial correlation. *, **, *** denote significance at the 10%, 5%, and 1% levels respectively. (1) (2) FEMSUBCEO FEMCEO LNASSETS FIRMAGE BOOKLEV RDINT NUMEXEC Observations R² 0.0625 -0.0269 -0.0023 -0.8794 3.2998 -0.0225 19,509 0.36 *** 0.0625 -0.0004 -0.0269 -0.0023 -0.8795 3.2998 -0.0225 19,509 0.36 *** *** *** Does having a female CEO reduce firm performance? . What are three ways to increase firm performance? . • Does the model explain most of the variance in firm performance? . . Can you tell which variable decreases firm performance the most? (If so, which one? If not, why not? Hint: This is a tricky question.) NOTE- The coefficients with a *** are statistically significant and the coefficients without a are not statistically significant. *** Regressions of Tobin's Q (the ratio of market value to book value) on measures of female participation in top management. FEMSUBCEO is a dummy variable taking the value 1 if a firm has a female executive below the CEO level listed in EXECUCOMP. FEMCEO is a dummy variable taking the value 1 if a firm has a female CEO. FIRMAGE is the age of the firm. BOOKLEV is book leverage. RDINT is the ratio of the firm's R&D expense to assets, with a value of zero imputed if R&D expense is not reported. NUMEXEC is the total number of executives listed in EXECUCOMP. Regressions include fixed effects for the year and industry at the 4-digit SIC code level. Observations where the value of Tobin's Q is more than 3 standard deviations away from the mean are excluded. All standard errors are robust to heteroskedasticity and arbitrary within-firm serial correlation. *, **, *** denote significance at the 10%, 5%, and 1% levels respectively. (1) (2) FEMSUBCEO FEMCEO LNASSETS FIRMAGE BOOKLEV RDINT NUMEXEC Observations R² 0.0625 -0.0269 -0.0023 -0.8794 3.2998 -0.0225 19,509 0.36 *** 0.0625 -0.0004 -0.0269 -0.0023 -0.8795 3.2998 -0.0225 19,509 0.36 *** *** *** Does having a female CEO reduce firm performance? . What are three ways to increase firm performance? . • Does the model explain most of the variance in firm performance? . . Can you tell which variable decreases firm performance the most? (If so, which one? If not, why not? Hint: This is a tricky question.) NOTE- The coefficients with a *** are statistically significant and the coefficients without a are not statistically significant. *** Regressions of Tobin's Q (the ratio of market value to book value) on measures of female participation in top management. FEMSUBCEO is a dummy variable taking the value 1 if a firm has a female executive below the CEO level listed in EXECUCOMP. FEMCEO is a dummy variable taking the value 1 if a firm has a female CEO. FIRMAGE is the age of the firm. BOOKLEV is book leverage. RDINT is the ratio of the firm's R&D expense to assets, with a value of zero imputed if R&D expense is not reported. NUMEXEC is the total number of executives listed in EXECUCOMP. Regressions include fixed effects for the year and industry at the 4-digit SIC code level. Observations where the value of Tobin's Q is more than 3 standard deviations away from the mean are excluded. All standard errors are robust to heteroskedasticity and arbitrary within-firm serial correlation. *, **, *** denote significance at the 10%, 5%, and 1% levels respectively. (1) (2) FEMSUBCEO FEMCEO LNASSETS FIRMAGE BOOKLEV RDINT NUMEXEC Observations R² 0.0625 -0.0269 -0.0023 -0.8794 3.2998 -0.0225 19,509 0.36 *** 0.0625 -0.0004 -0.0269 -0.0023 -0.8795 3.2998 -0.0225 19,509 0.36 *** *** *** Does having a female CEO reduce firm performance? . What are three ways to increase firm performance? . • Does the model explain most of the variance in firm performance? . . Can you tell which variable decreases firm performance the most? (If so, which one? If not, why not? Hint: This is a tricky question.) NOTE- The coefficients with a *** are statistically significant and the coefficients without a are not statistically significant. ***

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1 Based on the regression results provided the coefficient for the variable FEMCEO which takes the value of 1 if a firm has a female CEO is not statis... View the full answer