ECON 5370 Exam 2 | Questions with 100% Correct Answers

ECON 5370 Exam 2 | Questions with 100% Correct Answers 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 (should be b and d only) 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 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. 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. a simultaneous equation relationship b. heteroscedasticity c. multicollinearity d. nonlinearities e. autocorrelation 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 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 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 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 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 Consider the following linear demand function where Q D = quantity 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 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 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 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 Even though insignificant explanatory variables can raise the adjusted 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 demand 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 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 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 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. 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. 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 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 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 The coefficient of determination ranges in value between 0.0 and 1.0. a. true b. false 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 All of the following are criteria used to select a forecasting technique 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 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. e. data is created from a random number generation program. Consumer expenditure plans is an example of a forecasting method. Which of the general categories best described this example? a. time-series forecasting techniques b. survey techniques and opinion polling c. econometric techniques d. input-output analysis e. barometric techniques 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 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 or seasonal adjustments e. a cubic functional form For studying demand relationships for a proposed new product that no one has ever used before, what would be the best method to use? a. ordinary least squares regression on historical data b. market experiments, where the price is set differently in two markets c. consumer surveys, where potential customers hear about the product and are asked their opinions d. double log functional form regression model e. all of the above are equally useful in this case If two alternative economic models are offered, other things equal, we would a. tend to pick the one with the lowest R2. b. select the model that is the most expensive to estimate. c. pick the model that was the most complex. d. select the model that gave the most accurate forecasts e. all of the above In the first-order exponential smoothing model, the new forecast is equal to a weighted average of the old forecast and the actual value in the most recent period. a. true b. false Mr. Geppetto uses exponential smoothing to predict revenue in his wood carving business. He uses a weight of ω = .4 for the naïve forecast and (1- ω) = .6 for the past forecast. What revenue did he predict for March using the data below? Select closet answer. MONTH REVENUE FORECAST Nov 100 100 Dec 90 100 Jan 115 ---- Feb 110 ---- MARCH ? ? a. 101.7 b. 102.1 c. 104.7 d. 103.2 e. 106.2 Regarding forecasting, which of the following statements is NOT true? a. Operations managers need sales forecasts to plan future production. b. Financial managers need estimates of future sales revenues, disbursements and capital expenditures in order to plan effectively. c. Forecasts of credit conditions are needed to plan the cash needs of the firm. d. Public administrators and managers of NFP corporations need not forecast, since they need not make a profit. e. Both c and d are false Seasonal variations can be incorporated into a time-series model in a number of different ways, including: a. ratio-to-trend method b. a and e only c. a, b, and c d. root mean squared error method e. use of dummy variables Select the correct statement. a. Qualitative forecasts give the direction of change. b. Quantitative forecasts give the exact amount or exact percentage change. c. Diffusion forecasts use the proportion of the forecasts that are positive to forecast up or down. d. Surveys are a form of qualitative forecasting. e. all of the above are correct. Simplified trend models are generally appropriate for predicting the turning points in an economic time series. a. true b. false Smoothing techniques are a form of ____ techniques which assume that there is an underlying pattern to be found in the historical values of a variable that is being forecast.