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Wednesday 13 November 2013

Economics problems

Exercise 5
 General Cereals is using a regression model to estimate the demand for Tweetie Sweeties, a whistle-shaped, sugar coated breakfast cereal for children. The following (multiplicative exponential) demand function is being used:
QD = 6,280P −2.15 A1.05 N3.70
where QD = quantity demanded, in 10 oz: boxes
P = price per box, in dollars
A = advertising expenditures on daytime television, in dollars
N = proportion of the population under 12 years old
 a. Determine the point price elasticity of demand for Tweetie Sweeties.
b. Determine the advertising elasticity of demand.
c. What interpretation would you give to the exponent of N?

Exercise 6
            The demand for haddock has been estimated as
log Q = a + b log P + c log I + d log Pm
where Q = quantity of haddock sold in New England
P = price per pound of haddock
I = a measure of personal income in the New England region
Pm = an index of the price of meat and poultry
If b = −2.174, c = 0.461, and d = 1.909,
a. Determine the price elasticity of demand.
b. Determine the income elasticity of demand.
c. Determine the cross price elasticity of demand.
d. How would you characterize the demand for haddock?
e. Suppose disposable income is expected to increase by 5 percent next year.
Assuming all other factors remains constant, forecast the percentage change in the quantity of haddock demanded next year.

Exercise 7
            An estimate of the demand function for household furniture produced the following results:
F = 0.0036Y1.08R0.16P −0.48    r2 = 0.996
where F = furniture expenditures per household
Y = disposable personal income per household
R = value of private residential construction per household
P = ratio of the furniture price index to the consumer price index
 a. Determine the point price and income elasticities for household furniture.
b. What interpretation would you give to the exponent for R? Why do you suppose R was included in the equation as a variable?
c. If you were a supplier to the furniture manufacturer, would you have preferred to see the analysis performed in physical sales units rather than dollars of revenue? How would this change alter the interpretation of the price coefficient, presently estimated as −0.48?

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