Previously expendA and expendB are measured in thousand dollars.

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1. Previously expendA and expendB are measured in thousand dollars. Now create two additional variables eA and eB which measure expenditures in dollar amounts instead. Regress voteA on eA, eB, and prtystrA. Compare the estimated coefficients of eA and eB with those of expendA and expendB you got in the last lab. 2. Now regress voteA on log(eA), log(eB), and prtystrA. Compare the estimated coefficients of log(eA) and log(eB) with those of log(expendA) and log(expendB) you got in the last lab. What happens to the estimate of the constant term compared to the one you got in the last lab? Figure out the mathematical relationship between the intercepts of the two models.

3. Regress voteA on log(expendA), log(expendB), and prtystrA. Store the regression result in a temporary SAS data set. Print it out using print procedure and submit the output.

4. Regress voteA on log(expendA), log(expendB), and prtystrA. Store the predicted value of voteA in a temporary SAS data set. Print it out using print procedure and submit the output.

5. In the previous regression model, test whether the coefficient of log(expendA) equals the negative of that of log(expendB). Report the p-value along with your conclusion.

6. Create a new variable diff, with diff being the difference between log(expendB) and log(expendA). Regress vote on log(expendA), diff, and prtystrA. Is the coefficient of log(expendA) significant? And what is its p-value?

 

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