CHAPTER 3 Quantitative Demand Analysis Copyright © 2014 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education. Chapter Outline Chapter Overview • The elasticity concept • Own price elasticity of demand – Elasticity and total revenue – Factors affecting the own price elasticity of demand – Marginal revenue and the own price elasticity of demand • Cross-price elasticity – Revenue changes with multiple products • Income elasticity • Other Elasticities – Linear demand functions – Nonlinear demand functions • Obtaining elasticities from demand functions – Elasticities for linear demand functions – Elasticities for nonlinear demand functions • Regression Analysis – Statistical significance of estimated coefficients – Overall fit of regression line – Regression for nonlinear functions and multiple regression 3-2 Introduction Chapter Overview • Chapter 2 focused on interpreting demand functions in qualitative terms: – An increase in the price of a good leads quantity demanded for that good to decline. – A decrease in income leads demand for a normal good to decline. • This chapter examines the magnitude of changes using the elasticity concept, and introduces basic analysis to measure different elasticities. 3-3 Own Price Elasticity of Demand Own Price Elasticity • Own price elasticity of demand – Measures the responsiveness of a percentage change in the quantity demanded of good X to a percentage change in its price. π πΈπ π π ,ππ %Δππ = %Δππ – Sign: negative by law of demand. – Magnitude of absolute value relative to unity: • πΈπ π • πΈπ π • πΈπ π π ,ππ π ,ππ π ,ππ > 1: Elastic. < 1: Inelastic. = 1: Unitary elastic. 3-4 Copyright © 2014 by the McGraw-Hill Companies, Inc. All rights reserved. 2-5 Own Price Elasticity of Demand Total Revenue Test • When demand is elastic: – A price increase (decrease) leads to a decrease (increase) in total revenue. • When demand is inelastic: – A price increase (decrease) leads to an increase (decrease) in total revenue. • When demand is unitary elastic: – Total revenue is maximized. 3-6 Copyright © 2014 by the McGraw-Hill Companies, Inc. All rights reserved. 2-7 Own Price Elasticity of Demand Extreme Elasticities Price Demand πΈππ π ,ππ = 0 Perfectly elastic Demand πΈπππ ,ππ = −∞ Perfectly Inelastic Quantity 3-8 Own Price Elasticity of Demand Factors Affecting the Own Price Elasticity • Three factors can impact the own price elasticity of demand: – Availability of consumption substitutes. – Time/Duration of purchase horizon. – Expenditure share of consumers’ budgets. 3-9 Own Price Elasticity of Demand Elasticity and Marginal Revenue • The marginal revenue can be derived from a market demand curve. – Marginal revenue measures the additional revenue due to a change in output. • This link relates marginal revenue to the own price elasticity of demand as follows: 1+πΈ ππ = π πΈ – When −∞ < πΈ < −1 then, ππ > 0. – When πΈ = −1 then, ππ = 0. – When −1 < πΈ < 0 then, ππ < 0. 3-10 Own Price Elasticity of Demand Demand and Marginal Revenue Price 6 Unitary π MR Demand 0 1 3 6 Quantity Marginal Revenue (MR) 3-11 Cross-Price Elasticity Cross-Price Elasticity • Cross-price elasticity – Measures responsiveness of a percent change in demand for good X due to a percent change in the price of good Y. π πΈπ π – If πΈπ π ,ππ – If πΈπ π π π ,ππ π ,ππ %Δππ = %Δππ > 0, then π and π are substitutes. < 0, then π and π are complements. 3-12 Cross-Price Elasticity Cross-Price Elasticity in Action • Suppose it is estimated that the cross-price elasticity of demand between clothing and food is -0.18. If the price of food is projected to increase by 10 percent, by how much will demand for clothing change? %βππΆπππ‘βπππ π π −0.18 = ⇒ %βππΆπππ‘βπππ = −1.8 10 – That is, demand for clothing is expected to decline by 1.8 percent when the price of food increases 10 percent. 3-13 Cross-Price Elasticity Cross-Price Elasticity • Cross-price elasticity is important for firms selling multiple products. – Price changes for one product impact demand for other products. • Assessing the overall change in revenue from a price change for one good when a firm sells two goods is: βπ = π π 1 + πΈπ π π ,ππ + π π πΈπ π π ,ππ × %βππ 3-14 Cross-Price Elasticity Cross-Price Elasticity in Action • Suppose a restaurant earns $4,000 per week in revenues from hamburger sales (X) and $2,000 per week from soda sales (Y). If the own price elasticity for burgers is πΈππ ,ππ = −1.5 and the cross-price elasticity of demand between sodas and hamburgers is πΈππ,ππ = −4.0, what would happen to the firm’s total revenues if it reduced the price of hamburgers by 1 percent? βπ = $4,000 1 − 1.5 + $2,000 −4.0 −1% = $100 – That is, lowering the price of hamburgers 1 percent increases total revenue by $100. 3-15 Income Elasticity Income Elasticity • Income elasticity – Measures responsiveness of a percent change in demand for good X due to a percent change in income. π πΈπ π – If πΈπ – If πΈπ π ,π %Δππ = %Δπ π > 0, then π is a normal good. π < 0, then π is an inferior good. π ,π π ,π 3-16 Income Elasticity Income Elasticity in Action • Suppose that the income elasticity of demand for transportation is estimated to be 1.80. If income is projected to decrease by 15 percent, • what is the impact on the demand for transportation? π %Δππ 1.8 = −15 – Demand for transportation will decline by 27 percent. • is transportation a normal or inferior good? – Since demand decreases as income declines, transportation is a normal good. 3-17 Other Elasticities Other Elasticities • Own advertising elasticity of demand for good X is the ratio of the percentage change in the consumption of X to the percentage change in advertising spent on X. • Cross-advertising elasticity between goods X and Y would measure the percentage change in the consumption of X that results from a 1 percent change in advertising toward Y. 3-18 Obtaining Elasticities From Demand Functions Elasticities for Linear Demand Functions • From a linear demand function, we can easily compute various elasticities. • Given a linear demand function: π ππ = πΌ0 + πΌπ ππ + πΌπ ππ + πΌπ π + πΌπ» ππ» – Own price elasticity: πΌπ ππ ππ – Cross price elasticity: πΌπ – Income elasticity: πΌπ π . ππ ππ π ππ π π . . 3-19 Obtaining Elasticities From Demand Functions Elasticities for Linear Demand Functions In Action • The daily demand for Invigorated PED shoes is estimated to be ππ π = 100 − 3ππ + 4ππ − 0.01π + 2π΄π Suppose good X sells at $25 a pair, good Y sells at $35, the company utilizes 50 units of advertising, and average consumer income is $20,000. Calculate the own price, cross-price and income elasticities of demand. – ππ π = 100 − 3 $25 + 4 $35 − 0.01 $20,000 + 2 50 = 65 units. 25 = −1.15. 65 35 Cross-price elasticity: 4 = 2.15. 65 20,000 Income elasticity: −0.01 = −3.08. 65 – Own price elasticity: −3 – – 3-20 Obtaining Elasticities From Demand Functions Elasticities for Nonlinear Demand Functions • One non-linear demand function is the loglinear demand function: ln ππ π = π½0 + π½π ln ππ + π½π ln ππ + π½π ln π + π½π» ln π» – Own price elasticity: π½π . – Cross price elasticity: π½π . – Income elasticity: π½π . 3-21 Obtaining Elasticities From Demand Functions Elasticities for Nonlinear Demand Functions In Action • An analyst for a major apparel company estimates that the demand for its raincoats is given by ππ ππ π = 10 − 1.2 ln ππ + 3 ln π − 2 ln π΄π where π denotes the daily amount of rainfall and π΄π the level of advertising on good Y. What would be the impact on demand of a 10 percent increase in the daily amount of rainfall? πΈπ π π ,π = π½π = 3. So, πΈπ π π ,π = %βππ π %βπ ⇒3= %βππ π . 10 A 10 percent increase in rainfall will lead to a 30 percent increase in the demand for raincoats. 3-22 Regression Analysis Regression for Nonlinear Functions and Multiple Regression • Regression techniques can also be applied to the following settings: – Nonlinear functional relationships: • Nonlinear regression example: ln π = π½0 + π½π ln π + π – Functional relationships with multiple variables: • Multiple regression example: ππ π = πΌ0 + πΌπ ππ + πΌπ π + πΌπ» ππ» + π or ln ππ π = π½0 + π½π ln ππ + π½π ln π + π½π» ln ππ» + π 3-23 Conclusion • Elasticities are tools you can use to quantify the impact of changes in prices, income, and advertising on sales and revenues. • Given market or survey data, regression analysis can be used to estimate: – Demand functions. – Elasticities. – A host of other things, including cost functions. • Managers can quantify the impact of changes in prices, income, advertising, etc. 3-24