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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Managerial Economics & Business Strategy Chapter 3 Quantitative Demand Analysis

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Overview I. Elasticities of Demand n Own Price Elasticity n Elasticity and Total Revenue n Cross-Price Elasticity n Income Elasticity II. Demand Functions n Linear n Log-Linear III. Regression Analysis

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Elasticities of Demand How responsive is variable G to a change in variable S + S and G are directly related - S and G are inversely related

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Own Price Elasticity of Demand Negative according to the law of demand Elastic: (sensitive) Inelastic: (insensitive) Unitary:

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Perfectly Elastic & Inelastic Demand Perfectly Elastic D Price Quantity Perfectly Inelastic D Price Quantity

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Own-Price Elasticity and Total Revenue Elastic n Increase in price leads to a decrease in total revenue. Inelastic n Increase in price leads to an increase in total revenue. Unitary n Total revenue is maximized at the point where demand is unitary elastic.

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Factors Affecting Price Elasticity n Available Substitutes The more substitutes available for the good, the more elastic the demand. n Time Demand tends to be more inelastic in the short term than in the long term. Time allows consumers to seek out available substitutes. n Expenditure Share Goods that comprise a small share of consumers budgets tend to be more inelastic than goods for which consumers spend a large portion of their incomes.

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Cross Price Elasticity of Demand + Substitutes - Complements

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Income Elasticity + Normal Good - Inferior Good

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Uses of Elasticities Pricing Managing cash flows Impact of changes in competitors prices Impact of economic booms and recessions Impact of advertising campaigns

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Example 1: Pricing and Cash Flows According to an FTC Report by Michael Ward, AT&Ts price elasticity of demand for long distance services is -8.64. AT&T needs to boost revenues in order to meet its marketing goals. To accomplish this goal, should AT&T raise or lower its price?

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Answer:Reduce the price! Since demand is elastic, a reduction in price will increase quantity demanded by a greater percentage than the price decline, resulting in more revenues for AT&T.

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Quantifying the Change If AT&T lowered price by 3 percent, what would happen to the volume of long distance telephone calls routed through AT&T?

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Answer Calls would increase by 25.92 percent!

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Impact of a change in a competitors price According to an FTC Report by Michael Ward, AT&Ts cross price elasticity of demand for long distance services is 9.06. If MCI and other competitors reduced their prices by 4 percent, what would happen to the demand for AT&T services?

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Answer AT&Ts demand would fall by 36.24 percent!

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Demand Functions Mathematical representations of demand curves Example: X and Y are substitutes (coefficient of P Y is positive) X is an inferior good (coefficient of M is negative)

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Specific Demand Functions Linear Demand Price Elasticity Cross Price Elasticity Income Elasticity

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Example of Linear Demand Q d = 10 - 2P Own-Price Elasticity: (-2)P/Q If P=1, Q=8 (since 10 - 2 = 8) Own price elasticity at P=1, Q=8: (-2)(1)/8= - 0.25

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Log-Linear Demand

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Example of Log-Linear Demand log Q d = 10 - 2 log P Own Price Elasticity: -2

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 P Q P Q D D Linear Log Linear

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Regression Analysis Used to estimate demand functions Important terminology n Least Squares Regression: Y = a + bX + e n Confidence Intervals n t-statistic n R-square or Coefficient of Determination n F-statistic

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Interpreting the Output Estimated demand function: n log Q x = 7.58 - 0.84 logP x n Own price elasticity: -0.84 (inelastic) How good is our estimate? n t-statistics of 5.29 and -2.80 indicate that the estimated coefficients are statistically different from zero n R-square of.17 indicates we explained only 17 percent of the variation n F-statistic significant at the 1 percent level.

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Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Summary n Elasticities are tools you can use to quantify the impact of changes in prices, income, and advertising on sales and revenues. n Given market or survey data, regression analysis can be used to estimate: Demand functions Elasticities A host of other things, including cost functions n Managers can quantify the impact of changes in prices, income, advertising, etc.

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