Exam 2

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Apr 3, 2024

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ECON 5370 Exam 2: Chapter 4, 5, & 6 Study online at https://quizlet.com/_cce1vv QUESTION 1 In a regression equation, one may measure the accuracy of the estimation by: a. estimating the standard deviation of the errors of prediction b. calculating the standard deviation of the errors of prediction c. all of the above d. calculating the standard error of the estimate e. a and b only (b and d only) E: a and b only (calculating the standard deviation of the errors of prediction & calculating the standard error of the estimate) QUESTION 2 In addition to prediction, one purpose of regression analysis is: a. to measure the overall "fit" of the model to the sample obser- vations b. to test whether the slope parameter ² is equal to some particular value c. to test whether the slope parameter ² is equal to zero d. b and c e. none of the above D:b and c (to test whether the slope parameter ² is equal to some particular value & to test whether the slope parameter ² is equal to zero) QUESTION 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 a one-percent increase in family size increases food expenditures .224%. b. that a one-percent increase in family size increases food expenditures .693%. c. that as total expenditures on goods and services rises, food expenditures falls. d. that a one-percent increase in total expenditures increases food expenditures 1%. e. that as family size increases, food expenditures go down. A: that a one-percent increase in family size increases food ex- penditures .224%. QUESTION 4 Appendix: In regression analysis, the existence of a high degree of inter- correlation among some or all of the explanatory variables in the regression equation constitutes: a. a simultaneous equation relationship b. heteroscedasticity c. multicollinearity d. nonlinearities e. autocorrelation C: multicollinearity QUESTION 5 Appendix: In regression analysis, the existence of a significant pattern in successive values of the error term constitutes: a. autocorrelation b. nonlinearities c. multicollinearity d. a simultaneous equation relationship e. heteroscedasticity A: autocorrelation QUESTION 6 Appendix: The Identification Problem in the development of a demand func- tion 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 D: the simultaneous relationship between the demand and supply functions 1 / 12

ECON 5370 Exam 2: Chapter 4, 5, & 6 Study online at https://quizlet.com/_cce1vv QUESTION 7 Appendix: When two or more "independent" variables are highly correlated, then we have: a. the identification problem b. complementary products c. heteroscedasticity d. autocorrelation e. multicollinearity E: multicollinearity QUESTION 8 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. reciprocal b. double-logarithmic c. cubic d. semilogarithmic e. polynomial B: double-logarithmic QUESTION 9 Caution must be exercised in using regression models for predic- tion 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 B: the value of the independent variable lies outside the range of observations from which the model was estimated QUESTION 10 Consider the following linear demand function where Q D = quan- tity demanded, P = selling price, and Y = disposable income: Q D = 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 B: for a one unit increase in price, quantity demanded would decline by 2.1 units QUESTION 11 Consider the following multiplicative demand function where Q D = quantity demanded, P = selling price, and Y = disposable income: QD = 1.6P-1.5 Y.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 demand- ed 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 demand- A: for a one percent increase in disposable income, quantity demanded would increase by .2 percent 2 / 12

ECON 5370 Exam 2: Chapter 4, 5, & 6 Study online at https://quizlet.com/_cce1vv ed would increase by .2 percent e. none of the above QUESTION 12 Demand functions in the multiplicative form are most common for all of the following reasons except: a. exponents of parameters are the elasticities of those variables b. elasticities are constant over a range of data c. marginal impact of a unit change in an individual variable is constant d. c and d e. ease of estimation of elasticities C: marginal impact of a unit change in an individual variable is constant QUESTION 13 Even though insignificant explanatory variables can raise the ad- justed R 2 of a demand function, one should not interpret their effects on the regression when a. planning for capital budgets b. sales revenue reaches its peak c. forecasting unit sales for operations planning d. analyzing inventory relative to capacity requirements e. testing marketing hypotheses about the determinants of de- mand E: testing marketing hypotheses about the determinants of de- mand QUESTION 14 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 Error t Stat 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. As price rises for soda, people tend to drink less of it b. Price is insignificant c. All of the coefficients are significant d. Temp is significant e. Income is significant A: As price rises for soda, people tend to drink less of it QUESTION 15 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 C: t-test QUESTION 16 In which of the following econometric problems do we find Durbin-Watson statistic being far away from 2.0? a. heteroscedasticity b. agency problems c. the identification problem d. multicollinearity e. autocorrelation E: autocorrelation QUESTION 17 Novo Nordisk A/S, a Danish firm, sells insulin and other drugs 3 / 12

ECON 5370 Exam 2: Chapter 4, 5, & 6 Study online at https://quizlet.com/_cce1vv worldwide. Activella, an estrogen and progestin hormone replace- ment therapy sold by Novo-Nordisk, is examined using 33 quar- ters of data Y = -204 + .34X1 - .17X2 (17.0) (-1.71) Where Y is quarterly sales of Activella, X1 is the Novo's adver- tising of the hormone therapy, and X2 is advertising of a similar product by Eli Lilly and Company, Novo-Nordisk's chief com- petitor. 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. Neither X1 nor X2 are statistically significant. b. The Durbin-Watson statistic shows significant problems with autocorrelation c. X1 is statistically significant but X2 is not statistically significant. d. X1 is not statistically significant but X2 is statistically significant. e. Both X1 and X2 are statistically significant. E: Both X1 and X2 are statistically significant QUESTION 18 One commonly used test in checking for the presence of autocor- relation 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 B: Durbin-Watson test QUESTION 19 The assumptions underlying the simple linear regression model are: a. associated with each value of X is a probability distribution b. the disturbance term is assumed to be an independent random variable c. the value of the dependent variable Y is postulated to be a random variable d. a theoretical straight-line relationship exists between X and the expected value of Y e. a through c f. b through d E: a through c QUESTION 20 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 B: False QUESTION 21 The coefficient of determination ranges in value between 0.0 and 1.0. a. true b. false A: True QUESTION 22 The constant or intercept term in a statistical demand study repre- sents 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 D: 0.0 QUESTION 1 All of the following are criteria used to select a forecasting tech- 4 / 12

ECON 5370 Exam 2: Chapter 4, 5, & 6 Study online at https://quizlet.com/_cce1vv nique EXCEPT: a. the time required to complete the model b. the complexity of the relationships being forecast c. the cost associated with developing the forecasting model d. all of these are criteria used to select a forecasting technique e. the accuracy required of the forecasting model A: the time required to complete the model QUESTION 2 An example of a time series data set is one for which the: a. data would be collected for a given firm for several consecutive periods (e.g., months). b. use of regression analysis would impossible in time series. c. data would be collected for several different firms at a single point in time. d. regression analysis comes from data randomly taken from different points in time. d. data is created from a random number generation program. data would be collected for a given firm for several consecutive periods (e.g., months). QUESTION 3 Consumer expenditure plans is an example of a forecasting method. Which of the general categories best described this ex- ample? a. time-series forecasting techniques b. survey techniques and opinion polling c. econometric techniques d. input-output analysis e. barometric techniques survey techniques and opinion polling QUESTION 4 Emma uses a linear model to forecast quarterly same-store sales at the local Garden Center. The results of her multiple regression is: Sales = 2,800 + 200•T - 350•D where T goes from 1 to 16 for each quarter of the year from the first quarter of 2006 ('06I) through the fourth quarter of 2009 ('09 IV). D is a dummy variable which is 1 if sales are in the cold and dreary first quarter, and zero otherwise, because the months of January, February, and March generate few sales at the Garden Center. Use this model to estimate sales in a store for the first quarter of 2010 in the 17th month; that is: {2010 I}. Emma's forecast should be: a. 6,000 b. 5,850 c. 6,200 d. 5,950 e. 6,350 5,850 QUESTION 5 Examine the plot of data. Sales Time It is likely that the best forecasting method for this plot would be: a. a semi-log regression model b. a secular trend upward c. a two-period moving average d. a seasonal pattern that can be modeled using dummy variables a seasonal pattern that can be modeled using dummy variables or seasonal adjustments 5 / 12

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