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You have been presented with the following data and asked to fit statisti­cal demand functions: REGION SALES (Y) (‘000 gallons) ADVERTISING EXPENSES (A) ($’000) SELLING PRICE (P) ($/gallon) DISPOSABLE...

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You have been presented with the following data and asked to fit statisti­cal demand functions:

REGION

SALES (Y)

(‘000 gallons)

ADVERTISING EXPENSES (A)

($’000)

SELLING PRICE (P)

($/gallon)

DISPOSABLE INCOME (M)

($’000)

1

160

150

15.00

19.0

2

220

160

13.50

17.5

3

140

50

16.50

14.0

4

190

190

14.50

21.0

5

130

90

17.00

15.5

6

160

60

16.00

14.5

7

200

140

13.00

21.5

8

150

110

18.00

18.0

9

210

200

12.00

18.5

10

190

100

15.50

20.0

Use any multiple regression packages to estimate a linear relationship between the dependent variable and the independent variables.

a. Linear Relationship

i. Identify the dependent and independent variables.

ii. Estimate a linear relationship between the dependent variable and all the independent variables.

iii. What are the tests that you would use to determine the ‘goodness-of-fit’ of the estimated demand function? Conduct the tests and explain the results.

iv. Discuss the economic implications of the various coefficients.

b. Non-linear relationship.

i. Estimate a logarithmic form of the demand function.

ii. Is the estimated demand function ‘good’? Explain your answer.

iii. Compare with the linear form above. Elaborate.

Answered Same Day Aug 07, 2022

Solution

Shakeel answered on Aug 07 2022
63 Votes
(a)
i.    The dependent variable is ‘Sales’ and independent variables are ‘Advertising expenses’, ‘Selling price’ and Disposable income.
ii.    To establish the linear relationship, the multiple regression is run. According to the result, the relationship is defined by the following equation:
    Y = 310.24 + 0.008*A – 12.20*P + 2.677*M
iii.    The goodness of fit can be determined by the F-statistic...
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