You have beenpresented with the following data and asked to fit statisti­cal demandfunctions: 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 DayAug 07, 2022

Answer To: You have beenpresented with the following data and asked to fit statisti­cal demandfunctions:...

Shakeel answered on Aug 07 2022
14 Votes
(a)
i.    The dependent variable is ‘Sales’ and independent variables are ‘Advertising expenses’, ‘Sel
ling 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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