Managerial Economics, 7e (Keat)
Chapter 5 Demand Estimation and Forecasting (Appendices 5A and 5B)
Multiple-Choice Questions
1) Regression analysis can best be described as
A) a statistical technique for estimating the best relationship between one variable and a set of
other selected variables.
B) a statistical technique for determining the true values of variables.
C) a statistical technique for creating functional relationships among variables.
D) None of the above
2) If a regression coefficient passes the t-test, it means that
A) the regression equation is valid.
B) the regression coefficient is significantly different from zero.
C) the regression coefficient can be used for forecasting.
D) the regression coefficient should be included in the regression equation.
3) The coefficient of a linear regression equation indicates
A) the change in the dependent variable relative to a unit change in the independent variable.
B) the change in the independent variable relative to a unit change in the dependent variable.
C) the percentage change in the dependent variable relative to a unit change in the independent
variable.
D) the percentage change in the independent variable relative to a unit change in the dependent
variable.
4) Which of the following is a test of the statistical significance of the entire regression equation?
A) t-test
B) R2
C) F-test
D) Durbin-Watson test
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5) Which of the following is a test of the statistical significance of a particular regression
coefficient?
A) t-test
B) R2
C) F-test
D) Durbin-Watson test
6) Which of the following is a measure of the explanatory power of the regression model?
A) t-test
B) R2
C) F-test
D) Durbin-Watson test
7) R2 is a statistical measure which
A) determines how important one variable is in explaining the value of another variable.
B) tests the true value of a variable.
C) determines how well an equation can estimate the relationship between one variable and a set
of other variables.
D) All of the above
8) When the R2 of a regression equation is very high, it indicates that
A) all the coefficients are statistically significant.
B) the intercept term has no economic meaning.
C) a high proportion of the variation in the dependent variable can be accounted for by the
variation in the independent variables.
D) there is a good chance of serial correlation and so the equation must be discarded.
9) Which of the following indicators will always improve when more variables are added to a
regression equation?
A) the magnitudes of the coefficients
B) the t-test
C) R2
D) the standard errors of the coefficients
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10) Which indicator shows how well a regression line fits through the scatter of data points?
A) F-test
B) R2
C) t-test
D) Durbin-Watson test
11) When a regression coefficient is significant at the .05 level, it means that
A) there is only a five percent chance that there will be an error in a forecast.
B) there is 95 percent chance that the regression coefficient is the true population coefficient.
C) there is a five percent chance or less that the estimated coefficient is zero.
D) there is a five percent chance or less that the regression coefficient is not the true population
coefficient.
12) The t-test is a statistical measure which
A) tests the true value of a variable.
B) tests the statistical significance of a regression coefficient.
C) tests the statistical significance of a regression equation.
D) None of the above
13) The t-statistic is computed by
A) dividing the regression coefficient by the standard error of the estimate.
B) dividing the regression coefficient by the standard error of the coefficient.
C) dividing the standard error of the coefficient by the regression coefficient.
D) dividing the R2 by the F-statistic.
14) A one-tail test of significance would be used to determine whether
A) demand for a good is price elastic.
B) two goods are substitutes for each other in supply.
C) two goods are unrelated to each other in demand.
D) supply of a good is price inelastic.
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15) The F-test is used to determine if
A) a regression coefficient is significant.
B) multicollinearity exists.
C) a regression equation significantly accounts for the variation in the value of a dependent
variable.
D) an identification problem is present.
Answer the following question(s) based on the following regression equation (Standard errors in
parentheses, n = 150):
QD = 1000 – 50PA + 10PB + .05I, (20) (7) (.04)
where QD = quantity demanded of good A, PA = price of good A, PB = price of a competing
good B, and I = per capita income.
16) Using the “rule of 2,” which of the following variables can be deemed statistically
significant?
A) PA
B) PB
C) I
D) All of the above
E) None of the above
17) For which of the following variables should a “two tail” t-test be applied?
A) PA
B) I
C) PB
D) Should be applied for all.
18) For the regression equation Q = 100 – 10X + 0.25X2, which of the following statements is
true?
A) X2 is the more important variable because it is positive.
B) When X decreases by one unit, Q decreases by 10 units.
C) When X increases by 10 units, Q decreases by 1 unit.
D) The change in Q associated with a one unit increase in X depends on the initial level of X.
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19) When using regression analysis for forecasting, the confidence interval indicates
A) the degree of confidence that one has in the equation’s R2.
B) the range in which the value of the dependent variable is expected to lie with a given degree
of probability.
C) the degree of confidence that one has in the regression coefficients.
D) the range in which the actual outcome of a forecast is going to lie.
20) The use of a dummy variable in regression analysis indicates
A) that a researcher does not really know what to include in the equation.
B) that a categorical variable is expected to have an impact on a dependent variable.
C) that insufficient data is available for the analysis.
D) the use of hypothetical data.
21) In using regression analysis to estimate demand, which of the following problems is most
directly a result of insufficient data?
A) the identification problem
B) the problem of a low R2
C) the problem of high standard errors
D) the problem of insignificant F-statistics
22) Which of the following is most likely to indicate a statistically significant regression
coefficient?
A) |t| > R2
B) R2 > .90
C) |t| > 2
D) |t| > 4
23) The F-test is used in forecasting to
A) establish confidence intervals for testing regression coefficients.
B) examine the degree of multicollinearity among independent variables.
C) determine how well a regression equation can account for dependent variable values.
D) determine whether an identification problem exists.
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Answer the following questions on the basis of the following regression equation. (Standard
errors in parentheses, n = 200.)
Q = -6,500 – 100PA + 50PB + .3I + .2A; R2 =.12, (2,500) (50) (30) (.1) (.08)
where Q is the quantity demanded of good A; PA = $10, price of good A; PB = $8, price of good
B; I = $12,000, per capita income; and A = $20,000, monthly advertising expenditures.
24) Which of the variables does not pass the t-test at the .05 level of significance?
A) PA
B) PB
C) A
D) I
E) All the variables pass the t-test.
25) As a researcher, which aspect of the results would be of greatest concern?
A) the negative value of the constant (i.e., -6,500)
B) the relatively low impact of the competitor’s price
C) the fact that not all of the variables are statistically significant
D) the poor fit of the regression line
26) As the manager of good A, which of the following would be of greatest concern (based on
the regression results above)?
A) None of the factors below would be of concern.
B) an impending recession
C) pressure on you by your salespersons to lower the price so that they can boost their sales
D) a price reduction by the makers of good B
27) Which of the following cannot be determined on the basis of the above regression results?
A) the degree of price elasticity of good B
B) whether or not good A is “normal”
C) the degree of competition between A and B
D) All of the above can be determined.
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28) In the estimation of demand, the “identification problem” refers to
A) the problem of selecting the proper level of significance.
B) the problem of deciding whether to use time series or cross-sectional data.
C) the problem of separating out the effects of price on the quantity demanded when supply
cannot be held constant.
D) the problem of having insufficient variation in prices.
29) Which of the following refers to a relatively high correlation among the independent
variables of a regression equation?
A) autocorrelation
B) the identification problem
C) statistically insignificant regression coefficients
D) multicollinearity
30) The problem of autocorrelation refers to
A) independent variables in a regression equation whose values are closely related to each other.
B) insufficient data to estimate regression coefficient values.
C) regression coefficient values which are not significantly different from zero.
D) regression equation variables which exhibit a similar pattern in their values over a number of
time periods.
31) A dummy variable is also called
A) an approximate variable.
B) a discrete variable.
C) a zero-sum variable.
D) an improper variable.
32) A manager will have the least confidence in an explanatory variable that
A) does not pass the F-test.
B) is expressed as a dummy variable.
C) does not pass the t-test.
D) constitutes only a small part of R2.
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33) From a management policy perspective, which regression result is the most useful?
A) a regression equation that passes the F-test
B) a regression equation whose explanatory variables all pass the t-test
C) a regression equation that has the highest R2
D) a regression equation that has the least number of dummy variables
34) The fact that a person with a forceful and persuasive personality but not necessarily the
greatest amount of knowledge and judgment can exercise a disproportionate amount of influence
is a major drawback of
A) the Delphi method of forecasting.
B) the market research method.
C) opinion polling.
D) the jury of executive opinion approach.
35) The forecasting technique, which predicts technological trends and is carried out by a
sequential series of written questions and answers is
A) the Delphi method.
B) the market research method.
C) opinion polling.
D) the jury of executive opinion approach.
36) Average weekly claims for unemployment insurance, money supply and the index of stock
prices are all examples of
A) leading indicators.
B) coincident indicators.
C) lagging indicators.
D) None of the above
37) One of the series included among the lagging indicators is
A) the change in sensitive material prices.
B) the index of industrial production.
C) employees on non-agricultural payrolls.
D) average duration of unemployment.
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38) Which of the following is not one of the leading indicators?
A) index of consumer expectations, U. of Michigan
B) change in consumer price index for services
C) vendor performance, slower deliveries diffusion index
D) manufacturers’ new orders, nondefense capital goods
39) Which of the following is a leading economic indicator?
A) average hours, manufacturing
B) money supply M2
C) stock prices, 500 common stocks
D) All of the above
40) The method of forecasting with leading indicators can be criticized for
A) occasionally forecasting a recession when none ensues.
B) forecasting the direction of the economy but not the size of the change in economic activity.
C) frequent revisions of data after original publication.
D) All of the above
41) A general rule of thumb is that if, after a period of increases, the leading indicator index
sustains ________ consecutive declines, a recession (or at least a slowing of the economy) will
follow.
A) three
B) four
C) five
D) six
42) The forecasting technique which involves the use of the least squares statistical method to
examine trends, and takes into account seasonal and cyclical fluctuations, is known as
A) compound growth rate projection.
B) the Delphi method.
C) time series projection.
D) exponential smoothing projection.
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