Problem 1 Hypotheses Testtly InsignificantroblemsLAIM 1 Which of the following can cause the usual OLS t statistics to be invalid (that is, not to have t distribu-tions under Ho)?(i)(ii) A sample correlation coefficient of .95 between two independent variables that are in the model.(iii) Omitting an important explanatory variable.2 Consider an equation to explain salaries of CEOs in terms of annual firm sales, return on equity (roe.ipercentage form), and return on the firm's stock (ros, in percentage form):log(salary)= Bo + Blog(sales) + B₂roe + Bros + u.(i)In terms of the model parameters, state the null hypothesis that, after controlling for sales androe, ros has no effect on CEO salary. State the alternative that better stock market performanceincreases a CEO's salary.(ii) Using the data in CEOSAL1, the following equation was obtained by OLS:p-Value(Heteroskedasticity.log(salary) = 4.32 + .280 log(sales) + .0174 roe +.00024 ros(.32) (.035)(.0041)(.00054)n = 209, R² = .283.By what percentage is salary predicted to increase if ros increases by 50 points? Does ros havea practically large effect on salary?(iii)Test the null hypothesis that ros has no effect on salary against the alternative that ros has apositive effect. Carry out the test at the 10% significance level.(iv)Would you include ros in a final model explaining CEO compensation in terms of firm perfor-mance? Explain.renovee3 The variable rdintens is expenditures on research and development (R&D) as a percentage of sale=Sales are measured in millions of dollars. The variable profmarg is profits as a percentage of sales.Using the data in RDCHEM for 32 firms in the chemical industry, the following equatiois estimated:(i)rdintens = .472 + .321 log(sales) + .050 profmarg(.046)(1.369) (216)n = 32, R2 = .099.Interpret the coefficient on log(sales). In particular, if sales increases by 10%, what is the esti-mated percentage point change in rdintens? Is this an economically large effect?

The ordinary least square (OLS) estimation refers to the establishment of a linear relationship…

ems 1 Which of the following can cause the usual OLS t statistics to be invalid (that is, not to have t distribu tions under Ho)? (i) Heteroskedasticity. (ii) A sample correlation coefficient of .95 between two independent variables that are in the model_ (iii) Omitting an important explanatory variable. CEOs in terms of annual firm sales, return on equity (roe,

ems 1 Which of the following can cause the usual OLS t statistics to be invalid (that is, not to have t distribu tions under Ho)? (i) Heteroskedasticity. (ii) A sample correlation coefficient of .95 between two independent variables that are in the model_ (iii) Omitting an important explanatory variable. CEOs in terms of annual firm sales, return on equity (roe,

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4: Estimating Demand

Section: Chapter Questions

Problem 1E

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Regression Statistics Multiple R 0.971 R-Square A Adjusted R-Square .942 Standard Error 30.462 Observations 51 ANOVA df SS MS F Significance F Regression C 747851.57 373925.79 402.98 9.89E-31 Residual 48 D 927.91 Total 50 792391.11 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept E 62.13 26.79 1.60E-30 1539.66 1789.51 Price of Roses −6.68 F −1.41 1.64E-01 −16.16 2.81 Disposable Income (M) 9.73 0.34 G 1.23E-31 9.04 10.42…
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