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Chapter 7: DEMAND ESTIMATION AND FORECASTING
Chapter 7: DEMAND ESTIMATION AND FORECASTING
Multiple Choice
7-1 Demand equations derived from actual market data are
a. empirical demand functions.
b. never estimated using consumer interviews.
c. generally estimated using regression analysis.
d. both a and c
e. all of the above
7-2 A representative sample
a. eliminates the problem of response bias.
b. reflects the characteristics of the population.
c. is frequently a random sample.
d. both b and c
e. all of the above
7-3 One problem with consumer interviews is that
a. the sample may not be a representative sample.
b. response bias.
c. interviews allow for rapid turnaround.
d. both a and b
e. all of the above
7-4 The estimated demand for a good is
ˆ
Q=25-5P+0.32M+12P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. The coefficient on P
Chapter 7: DEMAND ESTIMATION AND FORECASTING
a. does not have the expected sign.
b. is negative as expected.
c. should have the same sign as the coefficient on
P
R
.
d. should not be greater than one (in absolute value).
e. both b and d
7-5 The estimated demand for a good is
ˆ
Q=25-5P+0.32M+12P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. The good is
a. an inferior good since the coefficient on
P
R
is positive.
b. a normal good since the coefficient on
P
R
is positive.
c. an inferior good since the coefficient on M is greater than one.
d. a normal good since the coefficient on M is positive.
e. none of the above
7-6 The estimated demand for a good is
ˆ
Q=25-5P+0.32M+12P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. This good and the related good R are
a. complements since the coefficient on M is positive.
b. substitutes since the coefficient on M is positive.
c. complements since the coefficient on
P
R
is positive.
d. substitutes since the coefficient on
P
R
is positive.
7-7 The estimated demand for a good is
ˆ
Q=25-5P+0.32M+12P
R
Chapter 7: DEMAND ESTIMATION AND FORECASTING
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. If income decreases by $1,000, all else constant, quantity demanded
will ________ by _________ units.
a. decrease; 320 units
b. increase; 3.2 units
c. decrease; 1200 units
d. increase; 500 units
e. decrease; 500 units
7-8 The estimated demand for a good is
ˆ
Q=25-5P+0.32M+12P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. If the price of the good falls by $4, the quantity demanded will
________ by ________ units.
a. increase; 5 units
b. increase; 20 units
c. increase; 50 units
d. increase; 48 units
e. decrease; 12 units
7-9 The estimated demand for a good is
ˆ
Q=4,800 -16P-0.65M-1.5P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. The coefficient on P
a. violates the law of demand.
b. is negative as dictated by the law of demand.
c. should not be greater than one (in absolute value).
d. should have the same sign as the coefficient on
P
R
.
e. both c and d
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-10 The estimated demand for a good is
ˆ
Q=4,800 -16P-0.65M-1.5P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. The good is
a. an inferior good since the coefficient on
P
R
is negative.
b. a normal good since the coefficient on
P
R
is negative.
c. a normal good since the coefficient on M is greater than one (in absolute value).
d. an inferior good since the coefficient on M is negative.
e. none of the above
7-11 The estimated demand for a good is
ˆ
Q=4,800 -16P-0.65M-1.5P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. This good and good R are
a. complements since the coefficient on M is negative.
b. substitutes since the coefficient on M is negative.
c. complements since the coefficient on
P
R
is negative.
d. substitutes since the coefficient on
P
R
is negative.
e. none of the above
7-12 The estimated demand for a good is
ˆ
Q=4,800 -16P-0.65M-1.5P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. If income decreases by $2,000, all else constant, quantity demanded
will ________ by _________ units.
a. increase; 1.30 units
b. decrease; 6.5 units
c. increase; 1,300 units
d. decrease; 65 units
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-13 The estimated demand for a good is
ˆ
Q=4,800 -16P-0.65M-1.5P
R
where Q is the quantity demanded of the good, P is the price of the good, M is income, and
P
R
is
the price of related good R. If the price of the good rises by $10, all else constant, the quantity
demanded will ________ by ________ units.
a. increase; 16 units
b. decrease; 160 units
c. decrease; 1.5 units
d. increase; 150 units
7-14 If demand is estimated using the empirical specification
lnQ=ln a+bln P+cln M+dln P
R
, then
an equivalent expression for demand is
a.
lnQ=a+bP +cM +dP
R
.
b.
Q=a+bP +cM +dP
R
.
c.
Q=ea+bP +cM +dP
R
.
d.
Q=abPcMdP
R
.
e. none of the above
7-15 Possible problems with consumer interviews include:
a. a non-random sample
b. the identification problem
c. response bias
d. both a and b
e. both a and c
7-16 For a linear demand function,
Q=a+bP +cM +dP
R
, the income elasticity is
a. c.
b. c(M/Q).
c. c(Q/M).
d. −c.
e. −c(Q/
P
).
7-17 For a nonlinear demand function of the form ,
Q=aPbMcP
R
d
, the estimated cross-price elasticity
of demand is
a. d.
b. −d.
c. d(
P
R
/P).
d. −d(P/
P
R
).
e. d(Q/
P
).
7-18 Build-Right Concrete Products produces specialty cement used in construction of highways.
Build-Right is a price-setting firm and estimates the demand for its cement by the State Highway
Department using a demand function in the nonlinear form:
Q=aPbMcP
R
d
where Q = yards of cement demanded monthly, P = the price of Build-Right’s cement per yard,
M = state tax revenues per capita, and
P
R
= the price of asphalt per yard. The manager at Build-
Right transforms the nonlinear relation into a linear relation for estimation. The estimation results
are presented below:
DEPENDENT VARIABLE:
LNQ
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
34
0.678
14.323
0.02311
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
4.00
1.50
2.67
0.0122
LNP
–0.800
0.25
–3.20
0.0032
LNM
0.750828
0.1816
4.13
0.0003
LNPR
0.600
0.200
3.00
0.0054
Given the above, the estimated demand for cement is
a. elastic because
ˆ
E
= −4.0.
b. elastic because
ˆ
E
= −2.0.
c. elastic because
ˆ
E
= −1.5.
d. inelastic because
ˆ
E
= −0.32.
e. inelastic because
ˆ
E
= −0.8.
7-19 Build-Right Concrete Products produces specialty cement used in construction of highways.
Build-Right is a price-setting firm and estimates the demand for its cement by the State Highway
Department using a demand function in the nonlinear form:
Q=aPbMcP
R
d
where Q = yards of cement demanded monthly, P = the price of Build-Right’s cement per yard,
M = state tax revenues per capita, and
P
R
= the price of asphalt per yard. The manager at Build-
Right transforms the nonlinear relation into a linear relation for estimation. The estimation results
are presented below:
DEPENDENT VARIABLE:
LNQ
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
34
0.678
14.323
0.02311
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
4.00
1.50
2.67
0.0122
LNP
–0.800
0.25
–3.20
0.0032
LNM
0.750828
0.1816
4.13
0.0003
LNPR
0.600
0.200
3.00
0.0054
Given the above, at the 1 percent level of significance, the number of degrees of freedom for a
t
−
test is _____, and the critical value of the t−statistic is ________. 0Only parameter estimate(s)
________ is (are) NOT statistically significant at the 1 percent level of significance.
a. 30; 2.457;
ˆ
a
b. 30; 2.750;
ˆ
a
c. 34; 2.042;
ˆ
c
d. 34; 2.042,
ˆ
a
and
ˆ
c
7-20 Build-Right Concrete Products produces specialty cement used in construction of highways.
Build-Right is a price-setting firm and estimates the demand for its cement by the State Highway
Department using a demand function in the nonlinear form:
Q=aPbMcP
R
d
where Q = yards of cement demanded monthly, P = the price of Build-Right’s cement per yard,
M = state tax revenues per capita, and
P
R
= the price of asphalt per yard. The manager at Build-
Right transforms the nonlinear relation into a linear relation for estimation. The estimation results
are presented below:
DEPENDENT VARIABLE:
LNQ
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
34
0.678
14.323
0.02311
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
4.00
1.50
2.67
0.0122
LNP
–0.800
0.25
–3.20
0.0032
LNM
0.750828
0.1816
4.13
0.0003
LNPR
0.600
0.200
3.00
0.0054
Given the above, if tax revenue per capita (M) increases 5%, the estimated quantity of cement
demanded will
a. increase by less than 1%.
b. increase more than 1% but less than 5%.
c. increase more than 5% but less than 10%.
d. increase more than 10%.
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-21 Build-Right Concrete Products produces specialty cement used in construction of highways.
Build-Right is a price-setting firm and estimates the demand for its cement by the State Highway
Department using a demand function in the nonlinear form:
Q=aPbMcP
R
d
where Q = yards of cement demanded monthly, P = the price of Build-Right’s cement per yard,
M = state tax revenues per capita, and
P
R
= the price of asphalt per yard. The manager at Build-
Right transforms the nonlinear relation into a linear relation for estimation. The estimation results
are presented below:
DEPENDENT VARIABLE:
LNQ
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
34
0.678
14.323
0.02311
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
4.00
1.50
2.67
0.0122
LNP
–0.800
0.25
–3.20
0.0032
LNM
0.750828
0.1816
4.13
0.0003
LNPR
0.600
0.200
3.00
0.0054
Given the above, the estimated cross-price elasticity of demand for cement relative to the price of
asphalt is
a. 0.3
b. 0.6
c. 1.2
d. 3.0
e. none of the above
7-22 Build-Right Concrete Products produces specialty cement used in construction of highways.
Build-Right is a price-setting firm and estimates the demand for its cement by the State Highway
Department using a demand function in the nonlinear form:
Q=aPbMcP
R
d
where Q = yards of cement demanded monthly, P = the price of Build-Right’s cement per yard,
M = state tax revenues per capita, and
P
R
= the price of asphalt per yard. The manager at Build-
Right transforms the nonlinear relation into a linear relation for estimation. The estimation results
are presented below:
Chapter 7: DEMAND ESTIMATION AND FORECASTING
DEPENDENT VARIABLE:
LNQ
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
34
0.678
14.323
0.02311
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
4.00
1.50
2.67
0.0122
LNP
–0.800
0.25
–3.20
0.0032
LNM
0.750828
0.1816
4.13
0.0003
LNPR
0.600
0.200
3.00
0.0054
Given the above, if the price of asphalt (
P
R
) decreases 20%, the estimated quantity of cement
demanded will:
a. increase 12%
b. increase 6%
c. increase 1.2%
d. decrease 12%.
e. decrease 1.2%.
7-23 Build-Right Concrete Products produces specialty cement used in construction of highways.
Build-Right is a price-setting firm and estimates the demand for its cement by the State Highway
Department using a demand function in the nonlinear form:
Q=aPbMcP
R
d
where Q = yards of cement demanded monthly, P = the price of Build-Right’s cement per yard,
M = state tax revenues per capita, and
P
R
= the price of asphalt per yard. The manager at Build-
Right transforms the nonlinear relation into a linear relation for estimation. The estimation results
are presented below:
DEPENDENT VARIABLE:
LNQ
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
34
0.678
14.323
0.02311
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
4.00
1.50
2.67
0.0122
LNP
–0.800
0.25
–3.20
0.0032
LNM
0.750828
0.1816
4.13
0.0003
LNPR
0.600
0.200
3.00
0.0054
Given the above, if Build-Right decides to charge the State Highway Department $55 per yard for
its cement when tax revenues per capita are $3,200 and the price of asphalt is $35 per yard, the
expected quantity demanded is
a. 1,000 yards of cement.
b. 2,000 yards of cement.
c. 4,000 yards of cement.
d. 6,000 yards of cement.
e. 8,000 yards of cement.
7-24 The estimated demand for a good X is
ˆ
Q=70 -3.5P-0.6M+4P
Z
, where
ˆ
Q
= units of the good,
P = price of the good, M = income, and
P
Z
= price of related good Z. All parameter estimates are
statistically significant. Which of the following statements is correct?
a. X is a normal good.
b. X is an inferior good.
c. X and Z are substitutes.
d. X and Z are complements.
e. both b and c
7-25 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
Given the above, at the 1% level of significance, the critical value of the t−statistic used by
Conlan to test for statistical significance has _____ degrees of freedom and is equal to ________.
a. 32; 0.7984
b. 32; 36.14
c. 32; 4.57
d. 30; 2.750
e. 28; 2.763
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-27 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
Given the above, at the 1% level of significance, which estimates are statistically significant?
a. All are statistically significant
b. All but
ˆ
a
are statistically significant
c. Only
ˆ
a,ˆ
b,and ˆ
c
are statistically significant
d. Only
ˆ
a
is statistically significant
e. All but
ˆ
band ˆ
d
are statistically significant
7-28 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
Given the above, based upon the parameter estimates in the above table
a. this good is a normal good.
b. the related good is a substitute.
c. the related good is a complement.
d. a and b
e. a and c
7-29 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
Assume that the income is $10,000, the price of the related good is $40, and Conlan chooses to
set the price of this product at $30. At the prices and income given above, Conlan can expect to
sell _________units.
a. 342
b. 600
c. 724
d. 864
e. 872
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-30 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
Assume that the income is $10,000, the price of the related good is $40, and Conlan chooses to
set the price of this product at $30. At the prices and income given above, what is the price
elasticity of demand?
a. −0.43
b. −0.86
c. −1.00
d. −1.43
e. −2.40
7-31 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
Chapter 7: DEMAND ESTIMATION AND FORECASTING
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
Assume that the income is $10,000, the price of the related good is $40, and Conlan chooses to
set the price of this product at $30. At the prices and income given above, what is the income
elasticity?
a. −1.62
b. −0.87
c. 0.21
d. 0.31
e. 1.50
7-32 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
For the next 2 questions suppose income remains at $10,000 but the price of the related good
increases to $60 and Conlan decides to raise the price of its product to $50. At the prices and
income given above, Conlan can expect to sell _________units.
a. 342
b. 600
c. 724
d. 864
e. 872
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-33 The following linear demand specification is estimated for Conlan Enterprises, a price-setting
firm:
Q=a+bP +cM +dP
R
where Q is the quantity demanded of the product Conlan Enterprises sells, P is the price of that
product, M is income, and
P
R
is the price of a related product. The results of the estimation are
presented below:
DEPENDENT VARIABLE:
Q
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS:
32
0.7984
36.14
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T-RATIO
P-VALUE
INTERCEPT
846.30
76.70
11.03
0.0001
P
–8.60
2.60
–3.31
0.0026
M
0.0184
0.0048
3.83
0.0007
PR
–4.3075
1.230
–3.50
0.0016
For the next 2 questions suppose income remains at $10,000 but the price of the related good
increases to $60 and Conlan decides to raise the price of its product to $50.What is the new own
price elasticity of demand?
a. −0.24
b. −0.43
c. −0.87
d. −1.00
e. −1.26
7-34 A market-determined price
a. is determined by the manager of a firm.
b. is determined by the intersection of demand and supply curves.
c. is an endogenous variable
d. both a and b
e. both b and c
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-35 Manager-determined prices are
a. not determined by the forces of demand and supply.
b. exogenous variables in a demand equations.
c. associated with price-taking firms.
d. both a and b
e. both b and c
7-36 Qualitative forecasting methods
a. use higher quality data than statistical methods.
b. are often the result of expert opinion.
c. cannot be replicated by another researcher.
d. both b and c
e. all of the above
7-37 Time-series models
a. cannot be replicated by another researcher.
b. use dummy variables to control for cyclical variation.
c. use dummy variables to control for time trend.
d. both a and b
e. both b and c
7-38 Time-series data
a. show the behavior of a particular variable over time.
b. may exhibit trend or cyclical variation, but not both at the same time.
c. may exhibit trend and cyclical variation at the same time.
d. both a and b
e. both a and c
Chapter 7: DEMAND ESTIMATION AND FORECASTING
7-39 Seasonal or cyclical variation in a time series model
a. is regular in nature and can be accounted for by dummy variables.
b. can decrease the accuracy of a forecast if not accounted for by dummy variables.
c. exhibits irregular variation that can be accounted for by dummy variables.
d. both a and b
e. both b and c
7-40 Dummy variables are used in time-series forecasting models
a. to change the intercept of a regression in selected periods.
b. to account for random variation in the data.
c. to account for seasonal variation in the data.
d. both a and b
e. both a and c
7-41 A consulting firm estimates the following quarterly sales forecasting model:
Qt=a+bt +cD
The equation is estimated using quarterly data from 2005I–2015III (t = 1,..., 43). The variable D
is a dummy variable for the second quarter where:
D = 1 in the second quarter, and 0 otherwise.
The results of the estimation are:
DEPENDENT VARIABLE:
QT
R−SQUARE
F−RATIO
P−VALUE ON F
OBSERVATIONS:
43
0.8644
127.5
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T−RATIO
P−VALUE
INTERCEPT
22.5
9.32
2.41
0.0201
T
1.86
0.55
3.38
0.0016
D
2.0
0.71
2.82
0.0075
Chapter 7: DEMAND ESTIMATION AND FORECASTING
Give the above, at the 1 percent level of significance, is there a statistically significant trend in
sales?
a. No, since 1.86 < 2.704
b. No, since 0.55 < 1.86
c. No, since 1.02 < 2.704
d. Yes, since 1.86 > 0.55
e. Yes, since 3.38 > 2.704
7-42 A consulting firm estimates the following quarterly sales forecasting model:
Qt=a+bt +cD
The equation is estimated using quarterly data from 2005I–2015III (t = 1,..., 43). The variable D
is a dummy variable for the second quarter where:
D = 1 in the second quarter, and 0 otherwise.
The results of the estimation are:
DEPENDENT VARIABLE:
QT
R−SQUARE
F−RATIO
P−VALUE ON F
OBSERVATIONS:
43
0.8644
127.5
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T−RATIO
P−VALUE
INTERCEPT
22.5
9.32
2.41
0.0201
T
1.86
0.55
3.38
0.0016
D
2.0
0.71
2.82
0.0075
Given the above, at the 1 percent level of significance, is there a statistically significant trend in
sales?
a. Yes, because 0.0016 < 0.01.
b. No, because 0.0016 < 0.01.
c. Yes, because 0.55 > 0.01.
d. Yes, because 1.86 > 0.01.
7-43 A consulting firm estimates the following quarterly sales forecasting model:
Chapter 7: DEMAND ESTIMATION AND FORECASTING
Qt=a+bt +cD
The equation is estimated using quarterly data from 2005I–2015III (t = 1,..., 43). The variable D
is a dummy variable for the second quarter where:
D = 1 in the second quarter, and 0 otherwise.
The results of the estimation are:
DEPENDENT VARIABLE:
QT
R−SQUARE
F−RATIO
P−VALUE ON F
OBSERVATIONS:
43
0.8644
127.5
0.0001
VARIABLE
PARAMETER
ESTIMATE
STANDARD
ERROR
T−RATIO
P−VALUE
INTERCEPT
22.5
9.32
2.41
0.0201
T
1.86
0.55
3.38
0.0016
D
2.0
0.71
2.82
0.0075
Given the above, these estimates indicate that the second quarter change in sales is
a. 22.5 units higher in the second quarter than in the other three quarters.
b. 1.86 units higher in the second quarter than in the other three quarters.
c. 2.00 units higher in the second quarter than in the other three quarters.
d. 24.5 units higher in the second quarter than in the other three quarters.
7-44 A consulting firm estimates the following quarterly sales forecasting model:
Qt=a+bt +cD
The equation is estimated using quarterly data from 2005I–2015III (t = 1,..., 43). The variable D
is a dummy variable for the second quarter where:
D = 1 in the second quarter, and 0 otherwise.
The results of the estimation are:
