Suppose you are given the following regression equation for Sony's laptop computers
(standard errors in parentheses.)
Q = 8,400 - 10 P + 5 A + 4 Px + 0.05 I
(1,732) (2.29) (1.36) (1.75) ( 0.15)
R2 = 0.65
N = 120
F = 35.25
Standard error of estimate = 34.3
Q = Quantity demanded
P = Price of Sony Laptop computers = $1,000
A = monthly advertising expenditures (in thousands) = 40
PX = price of a related good = $800
I = average monthly income of buyers = $4,000
Answer the following questions based on the above equation and the data provided. (Show all work to receive full / partial credit)
How many units can Sony expect to sell in a month?
Using the information given above, calculate the own price elasticity? Given your calculations, should Sony increase or reduce the price to maximize revenues
Calculate the advertising elasticity and show the impact of advertising on sales
Calculate the cross-price elasticity of demand for Sony laptops? Is the related good a substitute or complement? Why?
Calculate the income elasticity of demand. What and how much impact will a recession have on sales of this product? Why? Explain.