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Run a regression using the following variables: price of roses (Rosepr), the price of carnations

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Run a regression using the following variables: price of roses (Rosepr), the price of carnations

 

(CarnatPr), the trend variable (time), Births, Deaths, Wedding, Unemp, Income as well as a

 

constant. Answer questions 1-10 based on this model.

 

1.Which of the following is true of the expected coefficients in the model?

 

A) Births, deaths, wedding, price of carnations, and income are expected to be positive and the

 

price of roses and unemployment are expected to be negative.

 

B) Births, deaths, wedding, and income are expected to be positive and the price of roses, price

 

of carnations, and unemployment are expected to be negative.

 

C) Price of carnations and income are expected to be positive and births, deaths, wedding, the

 

price of roses and unemployment are expected to be negative.

 

D) none of the above

 

2.The price elasticity for roses is approximately

 

A) -10.9

 

B) -3.7

 

C) -1.9

 

D) none of the above

 

3.The cross price elasticity for roses and carnations is approximately

 

A) 2.0

 

B) 3.2

 

C) 4.5

 

D) none of the above

 

4.The coefficient associated with the price of roses can be interpreted as follows: For every $1

 

increase in the price of a dozen roses, there are 2526.23 dozen less sold holding all other

 

variables constant.

 

A) True

 

B) False

 

5.The estimated coefficient for wedding is found to be approximately

 

A) 0.47 and is insignificant.

 

B) 0.12 and is significant at the .01 level.

 

C) -0.29 and is insignificant.

 

 

D) none of the above.

 

6.The estimated coefficient for Deaths is found to be insignificant and therefore should be

 

dropped from the regression model.

 

A) True

 

B) False

 

7.Which of the following pairs of variables exhibits the highest degree of multicollinearity?

 

A) wedding and events

 

B) births and events

 

C) income and unemployment

 

D) none of the above.

 

8.Which of the following statements best represents the interpretation of the R2 for this model?

 

A) The variables included in the model explain 91.9% of the variation in the number of dozens

 

of roses sold.

 

B) The variables included in the model explain 97.9% of the variation in the number of dozens of

 

roses sold.

 

C) The variables included in the model explain 95.5% of the variation in the number of dozens of

 

roses sold.

 

D) none of the above

 

9.Which of the following statements best represents the interpretation of the explanatory power

 

of the R2 for this model?

 

A) The F-critical is greater than the F-statistic so we can reject the null hypothesis of no

 

explanatory power for the model.

 

B) The F-critical is less than the F-statistic so we cannot reject the null hypothesis of no

 

explanatory power for the model.

 

C) The F-critical is greater than the F-statistic so we cannot reject the null hypothesis of no

 

explanatory power for the model.

 

D) none of the above

 

10.According to the coefficient associated with the trend variable, the number of dozens of roses

 

sold was decreasing at a rate of 472.67% per quarter more than could be explained by changes in

 

the other variables.

 

A) True

 

 

B) False

 

Suppose the florists believe that first-quarter sales are greater than sales in any other quarter.

 

Create and define a variable(s) that will allow you to test this hypothesis. Re-estimate the

 

equation with your new variable and answer question 11.

 

11.The florists are correct about the first-quarter sales being greater than sales in any other

 

quarter.

 

A) True

 

B) False

 

12.A potential shortcoming of this model could be

 

A) the high degree of substitutability between the price of roses and the price of carnations

 

B) multicollinearity between sales of roses and the price of carnations

 

C) an omitted variable such as green plant price

 

D) none of the above

 

Paper#60274 | Written in 05-Mar-2016

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