In terms of the model parameters, state the null hypothesis that, after controlling for sales and roe, ros has no effect on CEO salary. State the alternative that better stock market performance increases a CEO’s salary. Consider an equation to explain salaries of CEOs in terms of annual firm sales, return on equity (roe,in percentage form), and return on the firm's stock (ros, in percentage form):log(salary) = Po + P₁ log(sales) + B₂roe + B3ros + μUsing the data in CEOSAL1, the following equation was obtained by OLS:log(salary) = 4.32 +0.28 log(sales) + 0.0174roe + 0.00024ros(0.0041) (0.00054)(0.32) (0.035)n = 209, R² = 0.283

Solution: The population regression equation is log(Salary)=β0+β1log(sales)+β2roe+β3ros

n terms of the model parameters, state the null hypothesis that, after controlling for sales and roe, ros has no effect on CEO salary. State the alternative that better stock market performance increases a CEO’s salary.

n terms of the model parameters, state the null hypothesis that, after controlling for sales and roe, ros has no effect on CEO salary. State the alternative that better stock market performance increases a CEO’s salary.

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter6: Exponential And Logarithmic Functions

Section6.7: Exponential And Logarithmic Models

Problem 19TI: Does a linear, exponential, or logarithmic model best fit the data in Table 2? Find the model.

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Question

In terms of the model parameters, state the null hypothesis that, after controlling for sales and roe, ros has no effect on CEO salary. State the alternative that better stock market performance increases a CEO’s salary.

Consider an equation to explain salaries of CEOs in terms of annual firm sales, return on equity (roe,
in percentage form), and return on the firm's stock (ros, in percentage form):
log(salary) = Po + P₁ log(sales) + B₂roe + B3ros + μ
Using the data in CEOSAL1, the following equation was obtained by OLS:
log(salary) = 4.32 +0.28 log(sales) + 0.0174roe + 0.00024ros
(0.0041) (0.00054)
(0.32) (0.035)
n = 209, R² = 0.283

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