Table 6

Regression analysis of discretionary bonus weight

Discretionary Bonus Weight
(1)(2)
Intercept−0.016−0.747***
(0.349)(<0.001)
Big4it−0.027***−0.096***
(<0.001)(<0.001)
Earning Predict CFit−0.027***−0.141***
(0.003)(0.004)
Abnormal Accrualsit0.121***0.628***
(<0.001)(<0.001)
ROA Volatilityit−0.186**−0.891**
(0.018)(0.045)
Return Volatilityit0.235***0.982***
(<0.001)(<0.001)
CEO Tenureit0.002***0.011***
(<0.001)(<0.001)
CEO Dualityit−0.010***−0.045***
(0.002)(0.009)
R&D to Salesit0.001*0.002**
(0.030)(0.011)
B/M Ratioit0.0020.016
(0.179)(0.132)
Lossit0.005−0.024
(0.391)(0.400)
Sizeit0.004***0.004
(<0.001)(0.534)
Leverageit−0.013−0.144***
(0.162)(0.002)
Annual Returnit0.009***0.044***
(<0.001)(<0.001)
ROAit0.074***0.284***
(<0.001)(0.002)
Year indicatorsYesYes
Industry indicatorsYesYes
Number of observations9,5109,510
R20.0880.095

Note(s): Column 1 of this table presents the results of ordinary least square regression of Discretionary (Formula) Bonus Weight on the test variables of accounting quality. Column 2 presents the result of Tobit regression model, in which the dependent variable, Discretionary Bonus Weight, is censored below zero. The regressions control for year and 2-digit SIC code industry effects. All variables are defined in Appendix. *, **, and *** indicate that the estimated coefficients are statistically significant at 0.10, 0.05, and 0.01 level, respectively. P-values in brackets are from two-tailed t-tests

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