1 / 40

Elasticity

Elasticity. Managerial Economics Jack Wu. New York City Transit Authority. May 2003: projected deficit of $1 billion over following two years Raised single-ride fares from $1.50 to $2 Raised discount fares One-day unlimited pass from $4 to $7 30-day unlimited pass from $63 to $70

tirza
Download Presentation

Elasticity

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Elasticity Managerial Economics Jack Wu

  2. New York City Transit Authority • May 2003: projected deficit of $1 billion over following two years • Raised single-ride fares from $1.50 to $2 • Raised discount fares • One-day unlimited pass from $4 to $7 • 30-day unlimited pass from $63 to $70 • Increased pay-per-ride MetroCard discount from 10% bonus for purchase of $15 or more to 20% for purchase of $10 or more.

  3. NY MTA • MTA expected to raise an additional $286 million in revenue. • Management projected that average fares would increase from $1.04 to $1.30, and that total subway ridership would decrease by 2.9%.

  4. MANAGERIAL ECONOMICS QUESTION • Would the MTA forecasts be realized? • In order to gauge the effects of the price increases, the MTA needed to predict how the new fares would impact total subway use, as well as how it would affect subway riders’ use of discount fares. • <Note> We can use the concept of elasticity to address these questions.

  5. Own-Price Elasticity: E=Q%/P% Definition: percentage change in quantity demanded resulting from 1% increase in price of the item. Alternatively,

  6. Own-price elasticity: Calculation

  7. Calculating Elasticity • Arc Approach: Elasticity={[Q2-Q1]/avgQ}/{[P2-P1]/avgP • % change in qty = (1.44-1.5)/1.47 = -4.1% • % change in price = (1.10-1)/1.05 = 9.5% • Elasticity=-4.1%/9.5% =-0.432

  8. Calculating Elasticity • Point approach: Elasticity={[Q2-Q1]/Q1}/{[P2-P1]/P1} % change in qty = (1.44-1.5)/1.5= -4% % change in price = (1.10-1)/1= 10% Elasticity=-4%/10%=-0.4

  9. Own-Price Elasticity • |E|=0, perfectly inelastic • 0<|E|<1, inelastic • |E|=1, unit elastic • |E|>1, elastic • |E|=infinity, perfectly elastic

  10. Own-price elasticity: Slope • Steeper demand curve means demand less elastic • But slope not same as elasticity

  11. DEMAND CURVES perfectly inelastic demand Price perfectly elastic demand 0 Quantity

  12. Linear Demand Curve • Vertical intercept: perfectly elastic • Upper segment: elastic • Middle: Unit elastic • Lower segment: inelastic • Horizontal intercept: perfectly inelastic

  13. Own-Price Elasticities

  14. Own-Price Elasticity: Determinants • availability of direct or indirect substitutes • cost / benefit of economizing (searching for better price) • buyer’s prior commitments • separation of buyer and payee • Broadly defined market versus narrowly defined market

  15. AMERICAN AIRLINES “Extensive research and many years of experience have taught us that business travel demand is quite inelastic… On the other hand, pleasure travel has substantial elasticity.” Robert L. Crandall, CEO, 1989

  16. AAdvantage 1981: American Airlines pioneered frequent flyer program • buyer commitment • business executives fly at the expense of others

  17. FORECASTING:WHEN TO RAISE PRICE • CEO: “Profits are low. We must raise prices.” • Sales Manager: “But my sales would fall!” • Real issue: How sensitive are buyers to price changes?

  18. Forecasting • Forecasting quantity demanded • Change in quantity demanded = price elasticity of demand x change in price

  19. Forecasting:Price increase • If demand elastic, price increase leads to • proportionately greater reduction in purchases • lower expenditure • If demand inelastic, price increase leads to • proportionately smaller reduction in purchases • higherexpenditure

  20. Income Elasticity, I=Q%/Y% Definition: percentage change in quantity demanded resulting from 1% increase in income. Alternatively,

  21. Income Elasticity • I >0, Normal good • I <0, Inferior good • Among normal goods: 0<I<1, necessity I>1, luxury

  22. INCOME ELASTICITY

  23. Cross-Price Elasticity: C=Q%/Po% • Definition: percentage change in quantity demanded for one item resulting from 1% increase in the price of another item. • (%change in quantity demanded for one item) / (% change in price of another item)

  24. Cross-Price Elasticity • C>0, Substitutes • C<0, complements • C=0, independent

  25. CROSS-PRICE ELASTICITIES

  26. Advertising Elasticity: a=Q%/A% Definition: percentage change in quantity demanded resulting from 1% increase in advertising expenditure.

  27. Advertising elasticity: Estimates If advertising elasticities are so low, why do manufacturers of beer, wine, cigarettes advertise so heavily?

  28. Advertising • direct effect: raises demand • indirect effect: makes demand less sensitive to price Own price elasticity for antihypertensive drugs Without advertising: -2.05 With advertising: -1.6

  29. Forecasting Demand • Q%=E*P%+I*Y%+C*Po%+a*A%

  30. Forecasting Demand Effect on cigarette demand of • 10% higher income • 5% less advertising

  31. Adjustment Time • short run: time horizon within which a buyer cannot adjust at least one item of consumption/usage • long run: time horizon long enough to adjust all items of consumption/usage

  32. Adjustment Time • For non-durable items, the longer the time that buyers have to adjust, the bigger will be the response to a price change. • For durable items, a countervailing effect (that is, the replacement frequency effect) leads demand to be relatively more elastic in the short run.

  33. NON-DURABLE: SHORT/LONG-RUN DEMAND 5 Price ($ per unit) • 4.5 long-run demand short-run demand 0 1.5 1.6 1.75 Quantity (Million units a month)

  34. SHORT/LONG-RUN ELASTICITIES

  35. Statistical Estimation: Data • time series –record of changes over time in one market • cross section -- record of data at one time over several markets • Panel data: cross section over time

  36. Multiple Regression Statistical technique to estimate the separate effect of each independent variable on the dependent variable • dependent variable = variable whose changes are to be explained • independent variable = factor affecting the dependent variable

  37. DISCUSSION QUESTION 1 • Drugs that are not covered by patent can be freely manufactured by anyone. By contrast, the production and sale of patented drugs is tightly controlled. The advertising elasticity of the demand for antihypertensive drugs was around 0.26 for all drugs, and 0.24 for those covered by patents. For all antihypertensive drugs, the own price elasticity was about -2.0 without advertising, and about -1.6 in the long run with advertising.

  38. DISCUSSION QUESTION 1: CONTINUED • Consider a 5% increase in advertising expenditure. By how much would the demand for a patented drug rise? What about the demand for a drug not covered by patent? • Why is the demand for patented drugs less responsive to advertising than the demand for drugs not covered by patent? • Suppose that a drug manufacturer were to increase advertising. Explain why it should also raise the price of its drugs.

  39. DISCUSSION QUESTION 2 • An Australian telecommunications carrier wants to estimate the own-price elasticity of the demand for international calls to the United States. It has collected annual records of international calls and prices. In each of the following groups, choose the one factor that you would also consider in the regression equation. Explain your reasoning.

  40. DISCUSSION QUESTION 2: CONTINUED • (A)Consumer characteristics: (i) average per capita income, (ii) average age. • (B)Complements: (i) number of telephone lines, (ii) number of mobile telephone subscribers. • (C)Prices of related items: (i) price of electricity, (ii) postage rate from Australia to the United States.

More Related