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Problem solving

  1. a) Write down the population model. You also know that literature suggests that the relationship between the CEO's salary and years with the company has inverse U shape. (HINT: When writing down the population model make sure to use the rules of thumb to determine if the variables should be in logs or not.) (3pts) b) Estimate the regression that you have specified in a) using STATA and report the results. You will be graded on the formatting of your table. A screen-shot of output from STATA will score 0. (2pts) c) Interpret all coefficients including the intercept. (7pts) d) Determine if ALL variables have a jointly significant effect on the CEO's salary. (It is sufficient to write the outcome of your test and associated F-stat and critical F-stat.) (1 pts) e) Test if the coefficients on college and grad are jointly significant. (It is sufficient to write the outcome of your test and associated F-stat and critical F-stat.) Should these variable be dropped from the regression? Why? (lpts) f) Test if the effect of sales and the market value of the firm on the CEO's salary is statistically the same. (It is sufficient to write the outcome of your test and associated F-stat and critical F-stat.) (1 pts) g) Estimate your model from part a. and include also variable cubic term for ceoten. Should you keep this new variable in your regression? What is the cost of keeping this variable? What is the benefit of including this variable? (HINT: Examine what happens to the effects of other variables when you include this variable.) 2. on the screenshot

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