Use the data in CEOSAL2 to answer this question. (i) Estimate the model lsalary = 0

Use the data in CEOSAL2 to answer this question.

(i) Estimate the model

lsalary = β₀ + β₁lsales + β₂lmktval + β₃ceoten + β₄ceoten² + u

by OLS using all of the observations, where lsalary, lsales, and lmktval are all naturallogarithms. Report the results in the usual form with the usual OLS standard errors. (You may verify that the heteroskedasticity-robust standard errors are similar.)

(ii) In the regression from part (i) obtain the studentized residuals; call these stri. How many studentized residuals are above 1.96 in absolute value? If the studentized residuals were independent draws from a standard normal distribution, about how many would you expect to be above two in absolute value with 177 draws?

(iii) Reestimate the equation in part (i) by OLS using only the observations with |str_i| ≤ 1.96. How do the coefficients compare with those in part (i)?

(iv) Estimate the equation in part (i) by LAD, using all of the data. Is the estimate of b1 closer to the OLS estimate using the full sample or the restricted sample? What about for b3?

(v) Evaluate the following statement: “Dropping outliers based on extreme values of studentized residuals makes the resulting OLS estimates closer to the LAD estimates on the full sample.”