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 second quarter?

A) 25 B) 26.6 C) 55 D) 65 E) none of the above A) 25 B) 26.6 C) 55 D) 65 E) none of the above C

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 -statistic is equal to __________.

A) 0.7984 B) 4.57 C) 36.14 D) 2.763 E) -3.50 A) 0.7984 B) 4.57 C) 36.14 D) 2.763 E) -3.50

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 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

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. $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { PT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OBSERVATIONS: } & 36 & 0.9078 & 76.34 & 0.0001 \end{array}$ $\begin{array}{lllll} \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & T-RATIO&P-VALUE \\ \text { ESTERCEPT } & 24.0 & 6.20 & 3.87 & 0.0005 \\ \text { T } & 0.800 & 0.240 & 3.33 & 0.0022 \\ \text { D1 } & -8.0 & 2.60 & -3.08 & 0.0043 \\ \text { D2 } & -6.00 & 1.80 & -3.33 & 0.0022 \\ \text { D3 } & -4.0 & 0.60 & -6.67 & 0.0001 \end{array}$ -The estimated QUARTERLY increase in price is ______, and the estimated ANNUAL increase in price is ______ .

A) $1.50; $6.00 B) $1.40; $4.00 C) $0.60; $2.40 D) $0.80; $3.20 E) none of the above A) $1.50; $6.00 B) $1.40; $4.00 C) $0.60; $2.40 D) $0.80; $3.20 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. $\begin{array}{rllll} \text { DEPENDENT VARIABLE: } & \text { PT } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\ \text { OBSERVATIONS: } & 36 & 0.9078 & 76.34 & 0.0001 \end{array}$ $\begin{array}{lllll} \text { VARIABLE } & \text { PARAMETER } & \text { STANDARD } & T-RATIO&P-VALUE \\ \text { ESTERCEPT } & 24.0 & 6.20 & 3.87 & 0.0005 \\ \text { T } & 0.800 & 0.240 & 3.33 & 0.0022 \\ \text { D1 } & -8.0 & 2.60 & -3.08 & 0.0043 \\ \text { D2 } & -6.00 & 1.80 & -3.33 & 0.0022 \\ \text { D3 } & -4.0 & 0.60 & -6.67 & 0.0001 \end{array}$ -In any given year price tends to vary from quarter to quarter as follows:

A) PI > PII > PIII > PIV B) PI > PIV > PIII > PII C) PII > PIII > PIV > PI D) PIII > PI > PII > PIV E) PIV > PIII > PII > PI A) PI > PII > PIII > PIV B) PI > PIV > PIII > PII C) PII > PIII > PIV > PI D) PIII > PI > PII > PIV E) PIV > PIII > PII > PI

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 or cyclical variation at the same time. D) both a and b E) both a and c 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 or cyclical variation at the same time. D) both a and b E) both a and c