Question

Use column 2 (8 Kilometer data).

Only need "f" and "g" please show work, thank you.

Q2. In their paper "The Rewards to running: Prize structure and performance in professional road racing", Lynch and Zaxlook at whether races with large prizes record faster times because they attract faster runners, or because they encourage all runners to run faster (the paper can be found on D2L, but you shouldn't need to read it in order to answer this question) They regress thee time taken to finish the race on prize difference (defined as the dollar amount of prize money a runner would lose if he or she finished one place lower than her pre-race ranking relative to other race entrants) and some other controls to see if there is a relationship between prize money at risk, and finishing time. They present the following table, which contains results from two specifications: first where they do not include 1993 points, a variable which is a measure of the runner's ability (the top panel), and second, where they do (the bottom panel). Consider the 8 kilometer race (the second column). Note that the figures in parentheses below the coefficients are t-statistics (and not standard errors) Truncated Regressions Linear Specification One-Time Runners With and Without 1993 Points (dependent variable = time in seconds) TABLE 4 5 8 10 15 10 Нalf Marathon Kilometer Kilometer Marathon Kilometer Kilometer Mile Without 1993 Points Prize difference/ -31.34 (1.650 42.00 502.6** -18.22 1,000 -84.83 -31.3 -26.49*** (2.097) (1.433) (1.740) (1.535) (0.368) (3.277) p value LR test of race dummies 0007285 07203 02185 00000 00000 00005 00000 N 128 100 345 122 199 402 101 With 1993 points 1993 points -0.004769 -0.02226** -0.01449** -0.003016 -0.008837 -0.05023***_0.06393*** (0.687) (1.082) (2.152) (2.507) (0.327) (2.765) (3.351 Prize difference/ -15.60 135.9 1.004 -294.6 0.03186 41.46 46.78 1,000 (1.480 (0.028) (0.002) (1.077) (0.598) (1.418) (1.837) NOTE: Figures in parentheses are t statistics TuMmersTO TUMlaster. e. What is the coefficient on the variable (prize difference/1000) in the regression with 1993 points? a. -294.6. T-statistic 1.480. f. Is this coefficient significant at the 5% level? Why or why not? g. Based on this coefficient (in the regression with 1993 points), would you say that there is good evidence that higher prize difference encourages runners to run faster? Explain.

Answer 1

ans..................

given that,

Truncated Regressions Linear Specification One Time Runners With and Without 1993 Points (dependent variable = time in seconds) TABLE 4 10 15 10 Half Marathon Kilowneter Kilometer Kiloweter Kilowmeter Mile Marathon Without 1993 Points Prize difference 649 -3134502.6 -18.22 1,000 4200 8483 -31.31 (1.650) (2.09) (1433) (1.740) (1535) (0.368) 3.277) p value LR test of race dummies 00000 00000 199 0007285 203 00005 02185 00000 345 128 100 122 101 402 With 1993 points 1993 points -0.004769 00226* _0.01449** -0.003016 0008837 -05023**_0.06393** (2.507 (1.082) (2.152) (0.327) (0.687)(2.765) .351) Prize difference 0.03186 4146 135.9 1,000 1.004 2946 678 -15.60 (1.837 (0.028) (480 (0.002) (1.077) (0.598) (1418)

by using coloum 2

i.e., 8 km data

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