The following model can be used to study whether campaign expenditures affect election outcomes voteA = β0 + β1log(expendA) + β2log(expendB) + β3prtystrA + u , where voteA is the percentage of the vote received by Candidate A, expendA and expendB are campaign expenditures by Candidate A and B, and prtystrA is a measure of party strength for Candidate A (the percentage of the most recent presidential vote that went to A’s party).(i) In terms of the parameters, state the null hypothesis that a 1% increase in A’s expenditures is exactly offset by a 1% increase in B’s expenditures. (ii) In terms of the parameters, state the null hypothesis that campaign expenditures do not affect the outcome of the election, vs. the alternative hypothesis that they do matter. Download the data in the Excel file VOTE1, available on Canvas. Import it into Stata (File - Import - Excel spreadsheet). (iii) Estimate the given model using the data in VOTE1. Do A’s expenditures affect the outcome? What about B’s expenditures? Can you use these results to test the hypothesis in part (ii)? (iv) Stata can conduct a test on a linear combination of parameters using the command "lincom." Conduct the test in part (i) against the two-sided alternative at a test size of 5%. Report the result and the conclusion of your test. 1 (v) Stata can conduct an F test using the command "test." Conduct the test in part (ii), against the alternative that H0 is not true, at a test size of 5%. Report the results and the conclusion of your test. (vi) Report the F-statistic for the overall significance of the regression. What are the null and alternative hypotheses of this test, and how do you interpret the result?
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