Assume Demand equation of a product as Q = 70 -10 P + 4Pr + 50 I Where Q = Quantity of the product demanded, P = Price of the product (in $), Pr = Price of the related product (in $) and I = Per capital income (in ‘000) State the key steps for analyzing the above demand equation and calculate the regression results. What are the implications of the above regression analysis for management decisions?

Assume Demand equation of a product as Q = 70 -10 P + 4Pr + 50 I Where Q = Quantity of the product demanded, P = Price of the product (in $), Pr = Price of the related product (in $) and I = Per capital income (in ‘000) State the key steps for analyzing the above demand equation and calculate the regression results. What are the implications of the above regression analysis for management decisions?

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4: Estimating Demand

Section: Chapter Questions

Problem 2E

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Q. Wilpen Company, a price-setting firm, produces nearly 80 percent of all tennis balls purchased in the United States. Wilpen estimates the U.S. demand for its tennis balls by using the following linear specification: Q = a + bP + cM + dPR. Where Q is the number of cans of tennis balls sold quarterly, P is the wholesale price Wilpen charges for a can of tennis balls, M is the consumers’ average household income, and PR is the average price of tennis rackets. The regression results are as follows: a- Discuss the statistical significance of the parameter estimates a^, b^, c^, and d^ using the p-values. Are the signs of b^, c^, and d^ consistent with the theory of demand? Wilpen plans to charge a wholesale price of $1.65 per can. The average price of a tennis racket is $110, and consumers’ average household income is $24,600. b. What is the estimated number of cans of tennis balls demanded? c) At the values of P, M, and Pr given, what are the estimated values of the price (E^), income…
Q. Wilpen Company, a price-setting firm, produces nearly 80 percent of all tennis balls purchased in the United States. Wilpen estimates the U.S. demand for its tennis balls by using the following linear specification: Q = a + bP + cM + dPR. Where Q is the number of cans of tennis balls sold quarterly, P is the wholesale price Wilpen charges for a can of tennis balls, M is the consumers’ average household income, and PR is the average price of tennis rackets. The regression results are as follows: a. Discuss the statistical significance of the parameter estimates a^, b^, c^, and d^ using the p-values. Are the signs of b^, c^, and d^ consistent with the theory of demand? Wilpen plans to charge a wholesale price of $1.65 per can. The average price of a tennis racket is $110, and consumers’ average household income is $24,600. b. What is the estimated number of cans of tennis balls demanded? c) At the values of P, M, and Pr given, what are the estimated values of the price (E^), income…
Suppose that an economist has been able to gather data on the relationship between demand and price for a particular product. After analyzing scatterplots and using economic theory, the economist decides to estimate an equation of the form Q= aPb, where Q is quantity demanded and P is price. An appropriate regression analysis is then performed, and the estimated parameters turn out to be a = 1000 and b = - 1.3. Now consider two scenarios: (1) the price increases from $10 to $12.50; (2) the price increases from $20 to $25. a. Do you predict the percentage decrease in demand to be the same in scenario 1 as in scenario 2? Why or why not? b. What is the predicted percentage decrease in demand in scenario 1? What about scenario 2? Be as exact as possible.
Demand for Magnum Ice Cream is given by an equation Q = - 5,000 – 40P + 20Px + 5I + 0.2A Where, Q = Quantity of Magnum demanded, P = Price of Magnum Ice Cream, Px = Price of Walls Ice Cream, I = Per Capita Income and A = advertisement expenditure. State and elaborate the key steps for analyzing regression results of demand. Assume P = Rs 500, Px = Rs 600, I = Rs 5,000 and A = 10,000 (Rs in thousands). Calculate elasticities for each of the variables: Price Elasticity of Demand Cross Price Elasticity of Demand Income Elasticity of Demand Advertisement Elasticity 3. How does each of the elasticities help in managerial decision making? Given these estimates should Magnum consider reducing its price to increase market share? Explain.
ABC, Inc., sells tea products to various customers. In recent years, profits have been declining. The CFO of the company investigated the reasons for the profit decline and performed regression analysis for sales and costs. She determined that sales depend on product price, delivery speed, customer services, and marketing expenses. She also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales. List two advantages and two limitations of regression analysis.
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Demand Estimation for The San Francisco Bread Company Consider the hypothetical example of The San Francisco Bread Company, a San Francisco-based chain of bakery/cafes. San Francisco Bread Company has initiated an empirical estimation of customer traffic at 30 regional locations to help the firm formulate pricing and promotional plans for the coming year. Annual operating data for the 30 outlets appear in the attached Table 1. The following regression equation was fit to these data: Qi = b0 + b1Pi + b2Pxi + b3Adi + b4Ii + uit. Where: Q is the number of meals served, P is the average price per meal (customer ticket amount, in dollars), Px is the average price charged by competitors (in dollars), Ad is the local advertising budget for each outlet (in dollars), I is the average income per household in each outlet’s service area, ui…
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A multiple regression model, K = a + bX + cY + dZ, is estimated regression software, which produces the following output: a. Are the estimates of a, b, c, and d statistically significant at the 1 percent significance level? b. How much of the total variation is explained by this regression equation? c. Is the overall regression equation statistically significant at the 1 percent level of significance? d. If X equals 50, Y equals 200, and Z equals 45, what value do you predict K will take?
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A firm is faced with the following demand function (estimated in a regression equation based onpast data).QX = 200 – 4PX , where current price (PX ) = $30The firm is thinking of reducing price to $25 because someone suggested that wouldbring in more revenue. a. What is the own-price elasticity of demand? (show absolute value)b. Is the demand function elastic, inelastic or unitary elastic at a price of $30?c. Will the price reduction bring in more revenue?