Using Econometrics A Practical Guide 7th Edition Studenmund Solutions Manual

Using Econometrics A Practical Guide 7th Edition Studenmund Solutions Manual Instructor’s Manual Answers to Odd-numbered Exercises Chapter 1 1-3. (a) The coefficient of Li represents the change in the percentage chance of making a putt when the length of the putt increases by one foot. In this case, the percentage chance of making the putt decreases by 4.1 for each foot longer the putt is. (b) The equations are identical. To convert one to the other, note that P ˆ i = P i – e i , which is true because e i = P i - P ˆ i (or more generally, e i = Y i – Y ˆ i ). (c) 42.6 percent, yes; 79.5 percent, no (too low); -18.9 percent, no (negative!). (d) One problem is that the theoretical relationship between the length of the putt and the percentage of putts made is almost surely non-linear in the variables; we’ll discuss models appropriate to this problem in Chapter 7. A second problem is that the actual dependent variable is limited by zero and one but the regression estimate is not; we’ll discuss models appropriate to this problem in Chapter 13. 1-5. (a) β ʏ is the change in S caused by a one-unit increase in Y, holding G constant and β G is the change in S caused by a one-unit increase in G, holding Y constant. (b) +, - (c) Yes. Richer states spend at least some of their extra money on education, but states with rapidly growing student populations find it difficult to increase spending at the same rate as the student population, causing spending per student to fall, especially if you hold the wealth of the state constant. (d) Ŝ i = -183 + 0.1422Y i - 59.26G i . Note that 59.26 ∙ 10 = 5926 ∙ 0.10, so nothing in the equation has changed except the scale of the coefficient of G. 1-7. (a) β 2 represents the impact on the wage of the ith worker of a one-year increase in the education of the ith worker, holding constant that worker’s experience and gender. (b) β 3 represents the impact on the wage of the ith worker of being male instead of female, holding constant that worker’s experience and education. (c) There are two ways of defining such a dummy variable. You could define COLOR i = 1 if the ith worker is a person of color and 0 otherwise, or you could define COLOR 1 = 1 if the ith worker is not a person of color and 0 otherwise. (The actual name you use for the variable doesn’t have to be “COLOR.” You could choose any variable name as long as it didn’t conflict with the other variable names in the equation.) (d) We’d favor adding a measure of the quality of the worker to this equation, and answer iv, the number of employee of the month awards won, is the best measure of quality in this group. As tempting as it might be to add the average wage in the field, it would be the same for each employee in the sample and thus wouldn’t provide any useful information.