Managerial Economics Chapter 4
20. Consider the following multiplicative demand function where QD = quantity demanded, P = selling price, and Y = disposable income: QD=1.6P^-13Y^2 The coefficient of Y (i.e., .2) indicates that (all other things being held constant): a. for a one percent increase in disposable income, quantity demanded would increase by .2 percent b. for a one unit increase in disposable income, quantity demanded would increase by .2 units c. for a one percent increase in disposable income quantity demanded would increase by .2 units d. for a one unit increase in disposable income, quantity demanded would increase by .2 percent e. none of the above
ANSWER: a
23. Novo Nordisk A/S, a Danish firm, sells insulin and other drugs worldwide. Activella, an estrogen and progestin hormone replacement therapy sold by Novo-Nordisk, is examined using 33 quarters of data Y = -204 + . 34X1 - .17X2 (17.0) (-1.71) Where Y is quarterly sales of Activella, X1 is the Novo's advertising of the hormone therapy, and X2 is advertising of a similar product by Eli Lilly and Company, Novo-Nordisk's chief competitor. The parentheses contain t-values. Addition information is: Durbin-Watson = 1.9 and R2 = .89. Using the data for Novo-Nordisk, which is correct? a. Both X1 and X2 are statistically significant. b. Neither X1 nor X2 are statistically significant. c. X1 is statistically significant but X2 is not statistically significant. d. X1 is not statistically significant but X2 is statistically significant. e. The Durbin-Watson statistic shows significant problems with autocorrelation
ANSWER: a
28. Even though insignificant explanatory variables can raise the adjusted R2 of a demand function, one should not interpret their effects on the regression when a. testing marketing hypotheses about the determinants of demand b. analyzing inventory relative to capacity requirements c. forecasting unit sales for operations planning d. sales revenue reaches its peak e. planning for capital budgets
ANSWER: a
9. The coefficient of determination ranges in value between 0.0 and 1.0. a. true b. false
ANSWER: a
10. The coefficient of determination measures the proportion of the variation in the independent variable that is "explained" by the regression line. a. true b. false
ANSWER: b
12. The estimated slope coefficient (b) of the regression equation (Ln Y = a + b Ln X) measures the ____ change in Y for a one ____ change in X. a. percentage, unit b. percentage, percent c. unit, unit d. unit, percent e. none of the above
ANSWER: b
15. One commonly used test in checking for the presence of autocorrelation when working with time series data is the ____. a. F-test b. Durbin-Watson test c. t-test d. z-test e. none of the above
ANSWER: b
19. Consider the following linear demand function where QD = quantity demanded, P = selling price, and Y = disposable income: QD = −36 −2.1P + .24Y The coefficient of P (i.e., −2.1) indicates that (all other things being held constant): a. for a one percent increase in price, quantity demanded would decline by 2.1 percent b. for a one unit increase in price, quantity demanded would decline by 2.1 units c. for a one percent increase in price, quantity demanded would decline by 2.1 units d. for a one unit increase in price, quantity demanded would decline by 2.1 percent e. none of the above
ANSWER: b
21. Caution must be exercised in using regression models for prediction when: a. the value of the independent variable lies inside the range of observations from which the model was estimated b. the value of the independent variable lies outside the range of observations from which the model was estimated c. diminishing returns are present d. the existence of saturation levels are present e. none of the above
ANSWER: b
24. In which of the following econometric problems do we find Durbin-Watson statistic being far away from 2.0? a. the identification problem b. autocorrelation c. multicollinearity d. heteroscedasticity e. agency problems
ANSWER: b
25. When there is multicollinearity in an estimated regression equation, a. the coefficients are likely to be small. b. the t-statistics are likely to be small even though the R2 is large. c. the coefficient of determination is likely to be small. d. the problem of omitted variables is likely. e. the error terms will tend to have a cyclical pattern.
ANSWER: b
26. Appendix: When two or more "independent" variables are highly correlated, then we have: a. the identification problem b. multicollinearity c. autocorrelation d. heteroscedasticity e. complementary products
ANSWER: b
5. Appendix: In regression analysis, the existence of a significant pattern in successive values of the error term constitutes: a. heteroscedasticity b. autocorrelation c. multicollinearity d. nonlinearities e. a simultaneous equation relationship
ANSWER: b
7. Appendix: When using a multiplicative power function (Y = a X1b1X2b2X3b3) to represent an economic relationship, estimates of the parameters (a, and the b's) using linear regression analysis can be obtained by first applying a ____ transformation to convert the function to a linear relationship. a. semilogarithmic b. double-logarithmic c. reciprocal d. polynomial e. cubic
ANSWER: b
8. The correlation coefficient ranges in value between 0.0 and 1.0. a. true b. false
ANSWER: b
14. In testing whether each individual independent variables (Xs) in a multiple regression equation is statistically significant in explaining the dependent variable (Y), one uses the: a. F-test b. Durbin-Watson test c. t-test d. z-test e. none of the above
ANSWER: c
27. Which is NOT true about the coefficient of determination? a. As you add more variables, the R-square generally rises. b. As you add more variables, the adjusted R-square can fall. c. If the R-square is above 50%, the regression is considered significant. d. The R-square gives the percent of the variation in the dependent variable that is explained by the independent variables. e. The higher is the R-square, the better is the fit.
ANSWER: c
3. A study of expenditures on food in cities resulting in the following equation: Log E = 0.693 Log Y + 0.224 Log N where E is Food Expenditures; Y is total expenditures on goods and services; and N is the size of the family. This evidence implies: a. that as total expenditures on goods and services rises, food expenditures falls. b. that a one-percent increase in family size increases food expenditures .693%. c. that a one-percent increase in family size increases food expenditures .224%. d. that a one-percent increase in total expenditures increases food expenditures 1%. e. that as family size increases, food expenditures go down.
ANSWER: c
13. The standard deviation of the error terms in an estimated regression equation is known as: a. coefficient of determination b. correlation coefficient c. Durbin-Watson statistic d. standard error of the estimate e. none of the above
ANSWER: d
17. Demand functions in the multiplicative form are most common for all of the following reasons except: a. elasticities are constant over a range of data b. ease of estimation of elasticities c. exponents of parameters are the elasticities of those variables d. marginal impact of a unit change in an individual variable is constant e. c and d
ANSWER: d
18. Appendix: The Identification Problem in the development of a demand function is a result of: a. the variance of the demand elasticity b. the consistency of quantity demanded at any given point c. the negative slope of the demand function d. the simultaneous relationship between the demand and supply functions e. none of the above
ANSWER: d
2. In a cross section regression of 48 states, the following linear demand for per-capita cans of soda was found: Cans = 159.17 - 102.56 Price + 1.00 Income + 3.94Temp Coefficients Standard t Stat Error Intercept 159.17 94.16 1.69 Price -102.56 33.25 -3.08 Income 1.00 1.77 0.57 Temperature 3.94 0.82 4.83 R-Sq = 54.1% R-Sq(adj) = 51.0% From the linear regression results in the cans case above, we know that: a. Price is insignificant b. Income is significant c. Temp is significant d. As price rises for soda, people tend to drink less of it e. All of the coefficients are significant
ANSWER: d
22. The constant or intercept term in a statistical demand study represents the quantity demanded when all independent variables are equal to: a. 1.0 b. their minimum values c. their average values d. 0.0 e. none of the above
ANSWER: d
30. In addition to prediction, one purpose of regression analysis is: a. to measure the overall "fit" of the model to the sample observations b. to test whether the slope parameter β is equal to some particular value c. to test whether the slope parameter β is equal to zero d. b and c e. none of the above
ANSWER: d
1. Using a sample of 100 consumers, a double-log regression model was used to estimate demand for gasoline. Standard errors of the coefficients appear in the parentheses below the coefficients. Ln Q = 2.45 -0.67 Ln P + . 45 Ln Y - .34 Ln Pcars (.20) (.10) (.25) Where Q is gallons demanded, P is price per gallon, Y is disposable income, and Pcars is a price index for cars. Based on this information, which is NOT correct? a. Gasoline is inelastic. b. Gasoline is a normal good. c. Cars and gasoline appear to be mild complements. d. The coefficient on the price of cars (Pcars) is insignificant. e. All of the coefficients are insignificant.
ANSWER: e
11. The presence of association between two variables does not necessarily imply causation for the following reason(s): a. the association between two variables may result simply from pure chance b. the association between two variables may be the result of the influence of a third common factor c. both variables may be the cause and the effect at the same time d. a and b e. a, b, and c
ANSWER: e
16. The assumptions underlying the simple linear regression model are: a. the value of the dependent variable Y is postulated to be a random variable b. a theoretical straight-line relationship exists between X and the expected value of Y c. associated with each value of X is a probability distribution d. the disturbance term is assumed to be an independent random variable e. a through c f. b through d
ANSWER: e
29. In a regression equation, one may measure the accuracy of the estimation by: a. calculating the standard deviation of the errors of prediction b. calculating the standard error of the estimate c. estimating the standard deviation of the errors of prediction d. all of the above e. a and b only
ANSWER: e
4. The principal econometric techniques used in measuring demand relationships are: a. the standard deviation b. regression c. correlation analysis d. the coefficient of determination e. both b and c
ANSWER: e
6. Appendix: In regression analysis, the existence of a high degree of intercorrelation among some or all of the explanatory variables in the regression equation constitutes: a. autocorrelation b. a simultaneous equation relationship c. nonlinearities d. heteroscedasticity e. multicollinearity
ANSWER: e
