Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -Using the estimation results given above, the predicted level of sales in 2014IV is _______ units.

A) 125 B) 127.50 C) 132 D) 133.5 E) none of the above A) 125 B) 127.50 C) 132 D) 133.5 E) none of the above

Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -Using a 5 percent significance level, these estimation results indicate that

A) sales in the first quarter are significantly greater than sales in any other quarter. B) sales in the second quarter are significantly greater than sales in any other quarter. C) sales in the third quarter are significantly greater than sales in any other quarter. D) sales in the fourth quarter are significantly greater than sales in any other quarter. A) sales in the first quarter are significantly greater than sales in any other quarter. B) sales in the second quarter are significantly greater than sales in any other quarter. C) sales in the third quarter are significantly greater than sales in any other quarter. D) sales in the fourth quarter are significantly greater than sales in any other quarter.

Refer to the following: A consulting firm estimates the following quarterly sales forecasting model: $Q _ { t } = a + b t + c D$ The equation is estimated using quarterly data from 2003I-2013III (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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { QT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ONF } \\ \text { OBSERVATIONS: } & 43 & 0.8644 & 127.5 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & \\ &\text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 22.5 & 9.32 & 2.41 & 0.0201 \\ \text { T } & 1.86 & 0.55 & 3.38 & 0.0016 \\ \text { D } & 2.0 & 0.71 & 2.82 & 0.0075 \end{array}$ -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. 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.

Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -Using the estimation results given above, the predicted level of sales in 2014III is _______ units.

A) 141.5 B) 156 C) 172 D) 173.5 E) none of the above A) 141.5 B) 156 C) 172 D) 173.5 E) none of the above

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { PT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OBSERVATIONS: } & 36 & 0.9078 & 76.34 & 0.0001 \end{array}$ $\begin{array}{lllll} \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & T-RATIO&P-VALUE \\ \text { ESTERCEPT } & 24.0 & 6.20 & 3.87 & 0.0005 \\ \text { T } & 0.800 & 0.240 & 3.33 & 0.0022 \\ \text { D1 } & -8.0 & 2.60 & -3.08 & 0.0043 \\ \text { D2 } & -6.00 & 1.80 & -3.33 & 0.0022 \\ \text { D3 } & -4.0 & 0.60 & -6.67 & 0.0001 \end{array}$ -Using the estimated time-series regression, predicted price in the 2nd quarter of 2014 is

A) $48.40 B) $54.40 C) $40.40 D) $51.40 E) none of the above A) $48.40 B) $54.40 C) $40.40 D) $51.40 E) none of the above

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & Q & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUEONF } \\ \text { OBSERVATIONS: } 32 & 0.7984 & 36.14 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & & \\ & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 846.30 & 76.70 & 11.03 & 0.0001 \\ \text { P } & -8.60 & 2.60 & -3.31 & 0.0026 \\ \text { M } & 0.0184 & 0.0048 & 3.83 & 0.0007 \\ \text { PR }& -4.3075 & 1.230 & -3.50 & 0.0016 \end{array}$ -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 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

Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -What is the estimated intercept of the trend line in the fourth quarter?

A) 0 B) 40 C) 55 D) 70 E) none of the above A) 0 B) 40 C) 55 D) 70 E) none of the above

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { PT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OBSERVATIONS: } & 36 & 0.9078 & 76.34 & 0.0001 \end{array}$ $\begin{array}{lllll} \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & T-RATIO&P-VALUE \\ \text { ESTERCEPT } & 24.0 & 6.20 & 3.87 & 0.0005 \\ \text { T } & 0.800 & 0.240 & 3.33 & 0.0022 \\ \text { D1 } & -8.0 & 2.60 & -3.08 & 0.0043 \\ \text { D2 } & -6.00 & 1.80 & -3.33 & 0.0022 \\ \text { D3 } & -4.0 & 0.60 & -6.67 & 0.0001 \end{array}$ -Using the estimated time-series regression, predicted price in the 1st quarter of 2014 is

A) $53.60. B) $45.60. C) $56.00. D) $37.60. E) none of the above A) $53.60. B) $45.60. C) $56.00. D) $37.60. E) none of the above

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & Q & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUEONF } \\ \text { OBSERVATIONS: } 32 & 0.7984 & 36.14 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & & \\ & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 846.30 & 76.70 & 11.03 & 0.0001 \\ \text { P } & -8.60 & 2.60 & -3.31 & 0.0026 \\ \text { M } & 0.0184 & 0.0048 & 3.83 & 0.0007 \\ \text { PR }& -4.3075 & 1.230 & -3.50 & 0.0016 \end{array}$ -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 A) 32; 0.7984 B) 32; 36.14 C) 32; 4.57 D) 30; 2.750 E) 28; 2.763

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & Q & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUEONF } \\ \text { OBSERVATIONS: } 32 & 0.7984 & 36.14 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & & \\ & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 846.30 & 76.70 & 11.03 & 0.0001 \\ \text { P } & -8.60 & 2.60 & -3.31 & 0.0026 \\ \text { M } & 0.0184 & 0.0048 & 3.83 & 0.0007 \\ \text { PR }& -4.3075 & 1.230 & -3.50 & 0.0016 \end{array}$ 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 A) 342 B) 600 C) 724 D) 864 E) 872

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & Q & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUEONF } \\ \text { OBSERVATIONS: } 32 & 0.7984 & 36.14 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & & \\ & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 846.30 & 76.70 & 11.03 & 0.0001 \\ \text { P } & -8.60 & 2.60 & -3.31 & 0.0026 \\ \text { M } & 0.0184 & 0.0048 & 3.83 & 0.0007 \\ \text { PR }& -4.3075 & 1.230 & -3.50 & 0.0016 \end{array}$ -At the 1% level of significance, which estimates are statistically significant?

A) All are statistically significant B) All but $\hat { a }$ are statistically significant C) Only $\hat { a } , \hat { b } \text {, and } \hat { c }$ are statistically significant D) Only $\hat { a }$ is statistically significant E) All but $\hat { b } \text { and } \hat { d }$ are statistically significant A) All are statistically significant B) All but $\hat { a }$ are statistically significant C) Only $\hat { a } , \hat { b } \text {, and } \hat { c }$ are statistically significant D) Only $\hat { a }$ is statistically significant E) All but $\hat { b } \text { and } \hat { d }$ are statistically significant

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { PT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OBSERVATIONS: } & 36 & 0.9078 & 76.34 & 0.0001 \end{array}$ $\begin{array}{lllll} \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & T-RATIO&P-VALUE \\ \text { ESTERCEPT } & 24.0 & 6.20 & 3.87 & 0.0005 \\ \text { T } & 0.800 & 0.240 & 3.33 & 0.0022 \\ \text { D1 } & -8.0 & 2.60 & -3.08 & 0.0043 \\ \text { D2 } & -6.00 & 1.80 & -3.33 & 0.0022 \\ \text { D3 } & -4.0 & 0.60 & -6.67 & 0.0001 \end{array}$ -At the 2 percent level of statistical significance, the estimation results indicate that price in the ________ quarter is significantly higher than in any other quarter.

A) 1st B) 2nd C) 3rd D) 4th A) 1st B) 2nd C) 3rd D) 4th

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { PT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OBSERVATIONS: } & 36 & 0.9078 & 76.34 & 0.0001 \end{array}$ $\begin{array}{lllll} \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & T-RATIO&P-VALUE \\ \text { ESTERCEPT } & 24.0 & 6.20 & 3.87 & 0.0005 \\ \text { T } & 0.800 & 0.240 & 3.33 & 0.0022 \\ \text { D1 } & -8.0 & 2.60 & -3.08 & 0.0043 \\ \text { D2 } & -6.00 & 1.80 & -3.33 & 0.0022 \\ \text { D3 } & -4.0 & 0.60 & -6.67 & 0.0001 \end{array}$ -What is the estimated intercept of the trend line in the 1st quarter?

A) 24 B) -8 C) 32 D) 16 E) none of the above A) 24 B) -8 C) 32 D) 16 E) none of the above

Exam 7: Demand Estimation and Forecasting

forecaster used the following regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data during 2005II-2013IV (t = 1, ..., 35) for an appliance manufacturer to obtain the estimation results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ ,and $D _ { 3 }$ are seasonal dummy variables for quarters I, II, and III. DEPENDENTVARIAELE: QT R-SQUARE F-RATIO P-VALUE ON F OESERVATIONS: 35 0.9219 88.54 PARAMETER STANDARD VARIAELE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 21.0 T D9 - - D2 - 1.80 - D3 -4.0 a. At the 2 percent level of significance, the critical value of the t-statistic is _. The parameter estimate of a (is, is not) statistically significant. The parameter estimate of b __ (is, is not) statistically significant. The parameter estimate of $c _ { 1 }$ ________ (is, is not) statistically significant. The parameter estimate of $c _ { 2 }$ ________ (is, is not) statistically significant. The parameter estimate of $c _ { 3 }$ __ (is, is not) statistically significant. b. The statistical estimates indicate a(n) _ (upward, downward) trend in sales of _ units per quarter year. c. The estimated intercepts for each of the four quarters are: Intercept for quarter 1 is . Intercept for quarter 2 is . Intercept for quarter 3 is . Intercept for quarter 4 is . d. The forecasted sales for the 1^st quarter of 2014 are _ units. The forecasted sales for the 2^nd quarter of 2014 are _ units. The forecasted sales for the 3^rd quarter of 2014 are _ units. The forecasted sales for the 4^th quarter of 2014 are _____ units.

(Short Answer)

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Question 21

Refer to the following: The estimated demand for a good is $\hat { Q } = 4,800 - 16 P - 0.65 M - 1.5 P _ { R }$ 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

(Multiple Choice)

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Question 22

Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. DEPENDENTVARIAELE: aT R-SQUARE F-RATIO P-VALUE ON F OESERVATIONS: 64 0.8768 107.982 0.0001 PARAMETER STANDARD VARIAELE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 30.0 12.8 2.34 0.0224 T 1.5 0.70 2.14 0.0362 D1 10.0 3.0 3.33 0.0015 D2 25.0 7.2 3.47 0.0010 D3 40.0 15.8 2.53 0.0140 -Using the estimation results given above, the predicted level of sales in 2014IV is _______ units.

(Multiple Choice)

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Question 23

Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. DEPENDENTVARIAELE: aT R-SQUARE F-RATIO P-VALUE ON F OESERVATIONS: 64 0.8768 107.982 0.0001 PARAMETER STANDARD VARIAELE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 30.0 12.8 2.34 0.0224 T 1.5 0.70 2.14 0.0362 D1 10.0 3.0 3.33 0.0015 D2 25.0 7.2 3.47 0.0010 D3 40.0 15.8 2.53 0.0140 -Using a 5 percent significance level, these estimation results indicate that

(Multiple Choice)

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Question 24

Refer to the following: A consulting firm estimates the following quarterly sales forecasting model: $Q _ { t } = a + b t + c D$ The equation is estimated using quarterly data from 2003I-2013III (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 ONF OBSERVATIONS: 43 0.8644 127.5 0.0001 VARIABLE PARAMETER STANDARD ESTIMATE 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 -These estimates indicate that the second quarter change in sales is

(Multiple Choice)

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Question 25

Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. DEPENDENTVARIAELE: aT R-SQUARE F-RATIO P-VALUE ON F OESERVATIONS: 64 0.8768 107.982 0.0001 PARAMETER STANDARD VARIAELE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 30.0 12.8 2.34 0.0224 T 1.5 0.70 2.14 0.0362 D1 10.0 3.0 3.33 0.0015 D2 25.0 7.2 3.47 0.0010 D3 40.0 15.8 2.53 0.0140 -Using the estimation results given above, the predicted level of sales in 2014III is _______ units.

(Multiple Choice)

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Question 26

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. DEPENDENT VARIABLE: PT R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 36 0.9078 76.34 0.0001 VARIABLE PARAMETER STANDARD T-RATIO P-VALUE ESTERCEPT 24.0 6.20 3.87 0.0005 T 0.800 0.240 3.33 0.0022 D1 -8.0 2.60 -3.08 0.0043 D2 -6.00 1.80 -3.33 0.0022 D3 -4.0 0.60 -6.67 0.0001 -Using the estimated time-series regression, predicted price in the 2nd quarter of 2014 is

(Multiple Choice)

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Question 27

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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-VALUEONF OBSERVATIONS: 32 0.7984 36.14 0.0001 VARIABLE PARAMETER STANDARD ESTIMATE 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 -Based upon the parameter estimates in the above table

(Multiple Choice)

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Question 28

Refer to the following: A forecaster used the regression equation $Q _ { t } = a + b t + c _ { 1 } D _ { 1 } + c _ { 2 } D _ { 2 } + c _ { 3 } D _ { 3 }$ and quarterly sales data for 1996I-2013IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and $D _ { 1 } , D _ { 2 }$ and $D _ { 3 }$ are dummy variables for quarters I, II, and III. DEPENDENTVARIAELE: aT R-SQUARE F-RATIO P-VALUE ON F OESERVATIONS: 64 0.8768 107.982 0.0001 PARAMETER STANDARD VARIAELE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 30.0 12.8 2.34 0.0224 T 1.5 0.70 2.14 0.0362 D1 10.0 3.0 3.33 0.0015 D2 25.0 7.2 3.47 0.0010 D3 40.0 15.8 2.53 0.0140 -What is the estimated intercept of the trend line in the fourth quarter?

(Multiple Choice)

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Question 29

If demand is estimated using the empirical specification $\ln Q = \ln a + b \ln P + c \ln M + d \ln P _ { R }$ , then an equivalent expression for demand is

(Multiple Choice)

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Question 30

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. DEPENDENT VARIABLE: PT R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 36 0.9078 76.34 0.0001 VARIABLE PARAMETER STANDARD T-RATIO P-VALUE ESTERCEPT 24.0 6.20 3.87 0.0005 T 0.800 0.240 3.33 0.0022 D1 -8.0 2.60 -3.08 0.0043 D2 -6.00 1.80 -3.33 0.0022 D3 -4.0 0.60 -6.67 0.0001 -Using the estimated time-series regression, predicted price in the 1st quarter of 2014 is

(Multiple Choice)

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Question 31

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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-VALUEONF OBSERVATIONS: 32 0.7984 36.14 0.0001 VARIABLE PARAMETER STANDARD ESTIMATE 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 -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 ____.

(Multiple Choice)

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Question 32

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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-VALUEONF OBSERVATIONS: 32 0.7984 36.14 0.0001 VARIABLE PARAMETER STANDARD ESTIMATE 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.

(Multiple Choice)

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Question 33

Possible problems with consumer interviews include:

(Multiple Choice)

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Question 34

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

(Multiple Choice)

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Question 35

Refer to the following: The following linear demand specification is estimated for Conlan Enterprises, a price-setting firm: $Q = a + b P + c M + d P _ { R }$ 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-VALUEONF OBSERVATIONS: 32 0.7984 36.14 0.0001 VARIABLE PARAMETER STANDARD ESTIMATE 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 -At the 1% level of significance, which estimates are statistically significant?

(Multiple Choice)

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Question 36

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. DEPENDENT VARIABLE: PT R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 36 0.9078 76.34 0.0001 VARIABLE PARAMETER STANDARD T-RATIO P-VALUE ESTERCEPT 24.0 6.20 3.87 0.0005 T 0.800 0.240 3.33 0.0022 D1 -8.0 2.60 -3.08 0.0043 D2 -6.00 1.80 -3.33 0.0022 D3 -4.0 0.60 -6.67 0.0001 -At the 2 percent level of statistical significance, the estimation results indicate that price in the ________ quarter is significantly higher than in any other quarter.

(Multiple Choice)

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Question 37

Refer to the following: The manufacturer of Beanie Baby dolls used quarterly price data for 2005I - 2013IV (t = 1, ..., 36) and the regression equation $P _ { t } = a + b t + c _ { 1 } D 1 _ { t } + c _ { 2 } D 2 _ { t } + c _ { 3 } D 3 _ { t }$ to forecast doll prices in the year 2014. $P _ { t }$ is the quarterly price of dolls, and $D 1 _ { t } , D 2 _ { t }$ and $D 3 _ { t }$ are dummy variables for quarters I, II, and III, respectively. DEPENDENT VARIABLE: PT R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 36 0.9078 76.34 0.0001 VARIABLE PARAMETER STANDARD T-RATIO P-VALUE ESTERCEPT 24.0 6.20 3.87 0.0005 T 0.800 0.240 3.33 0.0022 D1 -8.0 2.60 -3.08 0.0043 D2 -6.00 1.80 -3.33 0.0022 D3 -4.0 0.60 -6.67 0.0001 -What is the estimated intercept of the trend line in the 1st quarter?

(Multiple Choice)

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Question 38

If the price of asphalt ( $P _ { R }$ ) decreases 20%, the estimated quantity of cement demanded will:

(Multiple Choice)

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Question 39

Refer to the following: The estimated demand for a good is $\hat { Q } = 25 - 5 P + 0.32 M + 12 P _ { R }$ 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

(Multiple Choice)

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Question 40

Refer to the following: The estimated demand for a good is $\hat { Q } = 4,800 - 16 P - 0.65 M - 1.5 P _ { R }$ 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

If demand is estimated using the empirical specification $\ln Q = \ln a + b \ln P + c \ln M + d \ln P _ { R }$ , then an equivalent expression for demand is

Possible problems with consumer interviews include:

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

If the price of asphalt ( $P _ { R }$ ) decreases 20%, the estimated quantity of cement demanded will:

Refer to the following: The estimated demand for a good is $\hat { Q } = 25 - 5 P + 0.32 M + 12 P _ { R }$ 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

Managers, Profits, and Markets

Demand, Supply, and Market Equilibrium

Marginal Analysis for Optimal Decisions

Basic Estimation Techniques

Theory of Consumer Behavior

Elasticity and Demand

Production and Cost in the Short Run

Production and Cost in the Long Run

Production and Cost Estimation

Managerial Decisions in Competitive Markets

Managerial Decisions for Firms With Market Power

Strategic Decision Making in Oligopoly Markets

Advanced Pricing Techniques

Decisions Under Risk and Uncertainty

Government Regulation of Business

Filters

Exam 7: Demand Estimation and Forecasting

If demand is estimated using the empirical specification ln⁡Q=ln⁡a+bln⁡P+cln⁡M+dln⁡PR\ln Q = \ln a + b \ln P + c \ln M + d \ln P _ { R }lnQ=lna+blnP+clnM+dlnPR​ , then an equivalent expression for demand is

Possible problems with consumer interviews include:

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

If the price of asphalt ( PRP _ { R }PR​ ) decreases 20%, the estimated quantity of cement demanded will:

Managers, Profits, and Markets

Demand, Supply, and Market Equilibrium

Marginal Analysis for Optimal Decisions

Basic Estimation Techniques

Theory of Consumer Behavior

Elasticity and Demand

Production and Cost in the Short Run

Production and Cost in the Long Run

Production and Cost Estimation

Managerial Decisions in Competitive Markets

Managerial Decisions for Firms With Market Power

Strategic Decision Making in Oligopoly Markets

Advanced Pricing Techniques

Decisions Under Risk and Uncertainty

Government Regulation of Business

Filters

If demand is estimated using the empirical specification $\ln Q = \ln a + b \ln P + c \ln M + d \ln P _ { R }$ , then an equivalent expression for demand is

If the price of asphalt ( $P _ { R }$ ) decreases 20%, the estimated quantity of cement demanded will: