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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & Q & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUEONF } \\ \text { OBSERVATIONS: } 32 & 0.7984 & 36.14 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & & \\ & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 846.30 & 76.70 & 11.03 & 0.0001 \\ \text { P } & -8.60 & 2.60 & -3.31 & 0.0026 \\ \text { M } & 0.0184 & 0.0048 & 3.83 & 0.0007 \\ \text { PR }& -4.3075 & 1.230 & -3.50 & 0.0016 \end{array}$ 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 A) -0.24 B) -0.43 C) -0.87 D) -1.00 E) -1.26

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. $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { PT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OBSERVATIONS: } & 36 & 0.9078 & 76.34 & 0.0001 \end{array}$ $\begin{array}{lllll} \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & T-RATIO&P-VALUE \\ \text { ESTERCEPT } & 24.0 & 6.20 & 3.87 & 0.0005 \\ \text { T } & 0.800 & 0.240 & 3.33 & 0.0022 \\ \text { D1 } & -8.0 & 2.60 & -3.08 & 0.0043 \\ \text { D2 } & -6.00 & 1.80 & -3.33 & 0.0022 \\ \text { D3 } & -4.0 & 0.60 & -6.67 & 0.0001 \end{array}$ -What is the estimated intercept of the trend line in the 4th quarter?

A) 22.8 B) 16 C) 18 D) 20 E) none of the above A) 22.8 B) 16 C) 18 D) 20 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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & Q & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUEONF } \\ \text { OBSERVATIONS: } 32 & 0.7984 & 36.14 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & & \\ & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 846.30 & 76.70 & 11.03 & 0.0001 \\ \text { P } & -8.60 & 2.60 & -3.31 & 0.0026 \\ \text { M } & 0.0184 & 0.0048 & 3.83 & 0.0007 \\ \text { PR }& -4.3075 & 1.230 & -3.50 & 0.0016 \end{array}$ 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 A) -0.43 B) -0.86 C) -1.00 D) -1.43 E) -2.40

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. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -The estimated QUARTERLY increase in sales is ______ units, and the estimated ANNUAL increase in sales is ______ units.

A) 1.5; 6 B) 1.4; 4 C) 30; 4 D) 1.5; 40 E) none of the above A) 1.5; 6 B) 1.4; 4 C) 30; 4 D) 1.5; 40 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. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -At the 5 percent level of significance, is there a statistically significant trend in sales?

A) Yes, because 0.0362 0.01. C) Yes, because 0.700 > 0.05. D) Yes, because 2.14 >0.05. E) both c and d A) Yes, because 0.0362 0.01. C) Yes, because 0.700 > 0.05. D) Yes, because 2.14 >0.05. E) both c and d

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 2014I is _______ units.

A) 137.5 B) 139 C) 133.5 D) 132 E) none of the above A) 137.5 B) 139 C) 133.5 D) 132 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. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -In any given year, quarterly sales tend to vary as follows:

A) QI > QII > QIII > QIV B) QI > QII > QIV > QIII C) QII > QIII > QIV > QI D) QIII > QII > QI > QIV E) QIII > QIV > QII > QI A) QI > QII > QIII > QIV B) QI > QII > QIV > QIII C) QII > QIII > QIV > QI D) QIII > QII > QI > QIV E) QIII > QIV > QII > QI

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, is there a statistically significant trend in the price of dolls?

A) Yes, because 0.0022 0.02. C) Yes, because 0.800 > 0.02. D) Yes, because 0.240 > 0.02. E) Yes, because 3.33 > 0.02. A) Yes, because 0.0022 0.02. C) Yes, because 0.800 > 0.02. D) Yes, because 0.240 > 0.02. E) Yes, because 3.33 > 0.02.

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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { QT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ONF } \\ \text { OBSERVATIONS: } & 43 & 0.8644 & 127.5 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & \\ &\text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 22.5 & 9.32 & 2.41 & 0.0201 \\ \text { T } & 1.86 & 0.55 & 3.38 & 0.0016 \\ \text { D } & 2.0 & 0.71 & 2.82 & 0.0075 \end{array}$ -Using the estimated trend line, what is the predicted level of sales in 2013IV ?

A) 110.06 B) 106.20 C) 104.34 D) 102.2 E) none of the above A) 110.06 B) 106.20 C) 104.34 D) 102.2 E) none of the above

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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { QT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ONF } \\ \text { OBSERVATIONS: } & 43 & 0.8644 & 127.5 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & \\ &\text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 22.5 & 9.32 & 2.41 & 0.0201 \\ \text { T } & 1.86 & 0.55 & 3.38 & 0.0016 \\ \text { D } & 2.0 & 0.71 & 2.82 & 0.0075 \end{array}$ -What is the estimated intercept of the trend line in the second quarter?

A) 22.50 B) 24.50 C) 24.36 D) 2.00 E) none of the above A) 22.50 B) 24.50 C) 24.36 D) 2.00 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 the estimation results given above, the predicted level of sales in 2014II is _______ units.

A) 127.5 B) 137.5 C) 154 D) 155.5 E) none of the above A) 127.5 B) 137.5 C) 154 D) 155.5 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. \[\begin{array} { | l l l l l l } \hline \text { DEPENDENTVARIAELE: } & \text { aT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OESERVATIONS: } & 64 & \text { 0.8768 } & 107.982 & 0.0001 & \\ & & \text { PARAMETER } & \text { STANDARD } & & \\ \text { VARIAELE } & & \text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & & 30.0 & 12.8 & 2.34 & 0.0224 \\ \text { T } & & 1.5 & 0.70 & 2.14 & 0.0362 \\ \text { D1 } & & 10.0 & 3.0 & 3.33 & 0.0015 \\ \text { D2 } & & 25.0 & 7.2 & 3.47 & 0.0010 \\ \text { D3 } & & 40.0 & 15.8 & 2.53 & 0.0140 \\ \hline \end{array}\] -At the 5 percent level of significance, is there a statistically significant trend in sales?

A) No, because 1.5 2.00. E) none of the above A) No, because 1.5 2.00. E) none of the above

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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { QT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ONF } \\ \text { OBSERVATIONS: } & 43 & 0.8644 & 127.5 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & \\ &\text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 22.5 & 9.32 & 2.41 & 0.0201 \\ \text { T } & 1.86 & 0.55 & 3.38 & 0.0016 \\ \text { D } & 2.0 & 0.71 & 2.82 & 0.0075 \end{array}$ -At the 1 percent level of significance, is there a statistically significant trend in sales?

A) No, since 1.86 0.55 E) Yes, since 3.38 > 2.704 A) No, since 1.86 0.55 E) Yes, since 3.38 > 2.704

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: $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { QT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ONF } \\ \text { OBSERVATIONS: } & 43 & 0.8644 & 127.5 & 0.0001\\\\ \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & \\ &\text { ESTIMATE } & \text { ERROR } & \text { T-RATIO } & \text { P-VALUE } \\ \text { INTERCEPT } & 22.5 & 9.32 & 2.41 & 0.0201 \\ \text { T } & 1.86 & 0.55 & 3.38 & 0.0016 \\ \text { D } & 2.0 & 0.71 & 2.82 & 0.0075 \end{array}$ -Using the estimated trend line, what is the predicted level of sales in 2014I ?

A) 110.06 B) 106.20 C) 104.34 D) 102.2 E) none of the above A) 110.06 B) 106.20 C) 104.34 D) 102.2 E) none of the above

Exam 7: Demand Estimation and Forecasting

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 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?

(Multiple Choice)

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Question 41

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 4th quarter?

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Question 42

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, what is the price elasticity of demand?

(Multiple Choice)

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Question 43

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 -The estimated QUARTERLY increase in sales is units, and the estimated ANNUAL increase in sales is units.

(Multiple Choice)

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Question 44

Problems in forecasting include:

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Question 45

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 -At the 5 percent level of significance, is there a statistically significant trend in sales?

(Multiple Choice)

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Question 46

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 2014I is _______ units.

(Multiple Choice)

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Question 47

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 -In any given year, quarterly sales tend to vary as follows:

(Multiple Choice)

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Question 48

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, is there a statistically significant trend in the price of dolls?

(Multiple Choice)

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Question 49

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 -Using the estimated trend line, what is the predicted level of sales in 2013IV ?

(Multiple Choice)

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Question 50

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. -If the price of the good falls by $4, the quantity demanded will by units.

(Multiple Choice)

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Question 51

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 -What is the estimated intercept of the trend line in the second quarter?

(Multiple Choice)

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Question 52

A representative sample

(Multiple Choice)

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Question 53

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 2014II is _______ units.

(Multiple Choice)

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Question 54

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 . Only parameter estimate(s) ____ is (are) NOT statistically significant at the 1 percent level of significance.

(Multiple Choice)

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Question 55

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 -At the 5 percent level of significance, is there a statistically significant trend in sales?

(Multiple Choice)

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Question 56

The estimated cross-price elasticity of demand for cement relative to the price of asphalt is

(Multiple Choice)

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Question 57

If tax revenue per capita (M) increases 5%, the estimated quantity of cement demanded will

(Multiple Choice)

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Question 58

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 -At the 1 percent level of significance, is there a statistically significant trend in sales?

(Multiple Choice)

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Question 59

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 -Using the estimated trend line, what is the predicted level of sales in 2014I ?

(Multiple Choice)

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Question 60

Problems in forecasting include:

A representative sample

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 . Only parameter estimate(s) ____ is (are) NOT statistically significant at the 1 percent level of significance.

The estimated cross-price elasticity of demand for cement relative to the price of asphalt is

If tax revenue per capita (M) increases 5%, 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

Exam 7: Demand Estimation and Forecasting

Problems in forecasting include:

A representative sample

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 ________. Only parameter estimate(s) ________ is (are) NOT statistically significant at the 1 percent level of significance.

The estimated cross-price elasticity of demand for cement relative to the price of asphalt is

If tax revenue per capita (M) increases 5%, 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

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 . Only parameter estimate(s) ____ is (are) NOT statistically significant at the 1 percent level of significance.