PRIN.OF ECON.ACCESS CODE
PRIN.OF ECON.ACCESS CODE
2nd Edition
ISBN: 9780393691757
Author: Mateer
Publisher: NORTON
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Chapter 11, Problem 1QFR
To determine

Challenges overcome for effective price discrimination

Expert Solution & Answer
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Explanation of Solution

Before a price maker firm executes price discrimination policy effectively it must overcome 2 basic challenges: -

  1. Different price elasticities of demand: For executing price discrimination policy effectively the price maker firm must be able to enjoy some or high degree of monopoly power and the same time different consumers must face different price elasticities of demand. E.g. people having low level of income will be more price elastic and sensible to price change while the business class travelers possess more inelastic demand.
  2. Separate markets: - The price maker firm must overcome the challenge of identifying and separating the market segments and prevent resale of good. E.g. to stop an adult people from using a kid's movie ticket. Preventing business travelers from purchasing discounted ticket.
Economics Concept Introduction

Introduction:

Price discrimination is the process of imposing different prices from different groups of people for different quantity or quality for the same good or service. The best example of price discrimination exercise is imposing differentiated prices for business class, first class and economy class travels in a same flight. Price discrimination can be exercised only when the firm or seller becomes price maker i.e. one which has partial or complete control over market price and the industry as a whole.

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Problem 3 You are given the following demand for European luxury automobiles: Q=1,000 P-0.5.2/1.6 where P-Price of European luxury cars PA = Price of American luxury cars P, Price of Japanese luxury cars I= Annual income of car buyers Assume that each of the coefficients is statistically significant (i.e., that they passed the t-test). On the basis of the information given, answer the following questions 1. Comment on the degree of substitutability between European and American luxury cars and between European and Japanese luxury cars. Explain some possible reasons for the results in the equation. 2. Comment on the coefficient for the income variable. Is this result what you would expect? Explain. 3. Comment on the coefficient of the European car price variable. Is that what you would expect? Explain.
Problem 2: A manufacturer of computer workstations gathered average monthly sales figures from its 56 branch offices and dealerships across the country and estimated the following demand for its product: Q=+15,000-2.80P+150A+0.3P+0.35Pm+0.2Pc (5,234) (1.29) (175) (0.12) (0.17) (0.13) R²=0.68 SER 786 F=21.25 The variables and their assumed values are P = Price of basic model = 7,000 Q==Quantity A = Advertising expenditures (in thousands) = 52 P = Average price of a personal computer = 4,000 P. Average price of a minicomputer = 15,000 Pe Average price of a leading competitor's workstation = 8,000 1. Compute the elasticities for each variable. On this basis, discuss the relative impact that each variable has on the demand. What implications do these results have for the firm's marketing and pricing policies? 2. Conduct a t-test for the statistical significance of each variable. In each case, state whether a one-tail or two-tail test is required. What difference, if any, does it make to…
You are the manager of a large automobile dealership who wants to learn more about the effective- ness of various discounts offered to customers over the past 14 months. Following are the average negotiated prices for each month and the quantities sold of a basic model (adjusted for various options) over this period of time. 1. Graph this information on a scatter plot. Estimate the demand equation. What do the regression results indicate about the desirability of discounting the price? Explain. Month Price Quantity Jan. 12,500 15 Feb. 12,200 17 Mar. 11,900 16 Apr. 12,000 18 May 11,800 20 June 12,500 18 July 11,700 22 Aug. 12,100 15 Sept. 11,400 22 Oct. 11,400 25 Nov. 11,200 24 Dec. 11,000 30 Jan. 10,800 25 Feb. 10,000 28 2. What other factors besides price might be included in this equation? Do you foresee any difficulty in obtaining these additional data or incorporating them in the regression analysis?
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