In this paper, demand estimation will be done through a regression analysis. This analysis will examine the elements that management should look at when determining demand for a product such as: price, competitor’s price, customer income, advertising and the cost of microwave ovens. The main objective of this paper will be to: estimate the demand function using regression analysis, find elasticities of demand with respect to various variables and make forecasting decisions based upon the values of elasticities. The data to compute the equation will be gathered from twenty-six grocery stores throughout the country for the month of April. Compute the Elasticities for Each Independent Variable.
Qd=-5200-42P+20Px+5.2I+.20A+.25M, when P=500, PX=600, I=5,500, A=10,000, and M=5,000.
Price (P)
Ep = (Dq÷Dp) x (P ÷Q)
Ep = -42 x (5÷26,560)
Ep = -.008
Less than 1, inelastic
Competitor Price (PX)
Epx = (Dq÷Dp) x (Px ÷Q)
Epx = 20 x (6÷26,560)
Epx = .005
Less than 1, inelastic
Income (I)
Ei = (Dq÷Dp) x (I÷Q)
Ei = 5.2 x (5500÷26,560)
Ei = 1.08
Greater than 1, elastic
Advertising (A)
Ea = (Dq÷Dp) x (A÷Q)
Ea = .20 x
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