Interpreting Regression and Elasticity Coefficients
We believe that the quantity of hamburger (Qh) purchased within a market is a function of its own price (Ph), the price of chicken (Pc), advertising expenditures (A) and household disposable income (I). Using data available to the research team, we have estimated the following linear regression relationship:
Qh = 205.2 – 200*Ph + 100*Pc + 0.023*A + 0.0005*I
(a) How might we interpret the coefficients in the estimated regression?
(b) What is the forecasted demand for hamburger when Ph is $1.00, Pc is $1.20, A is $5,000 and I is $20,000?
(c) Calculate the own price elasticity for hamburger. If price were to decrease by 1% would the total revenue for hamburger increase or decrease? Explain.
(d) Calculate the cross price elasticity with respect to chicken price, the advertising elasticity and the income elasticity using the information listed and calculated in (b). Interpret the economic meaning of these measures.
(e) Which of the explanatory variable has the greatest impact on hamburger demand? Explain.