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Outline. Own-price elasticity Forecasting quantity demanded and expenditure Other elasticities Adjustment time. Own-price elasticity. Definition: percentage change in quantity demanded resulting from 1% increase in price of the item. Alternatively,. Own-price elasticity: Calculation.

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  1. Outline • Own-price elasticity • Forecasting quantity demanded and expenditure • Other elasticities • Adjustment time

  2. Own-price elasticity • Definition: percentage change in quantity demanded resulting from 1% increase in price of the item. • Alternatively,

  3. Own-price elasticity: Calculation • % change in qty = 100*(1.44-1.5)/1.47 = -4.1% • % change in price = 100*(1.10-1)/1.05 = 9.5% • Price elasticity=-4.1%/9.5%=-0.432

  4. Own-price elasticity • Elasticity: 1% price increase leads to more than 1% drop in quantity demanded. • Inelastic: 1% price increase leads to less than 1% drop in quantity demanded.

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

  6. Own-price elasticity “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, American Airlines, 1989

  7. Own-price elasticity:Estimates

  8. Own-price elasticity: Factors • Availability of substitutes • Cost / benefit of economizing – buyer’s “involvement”

  9. Own-price elasticity: Factors • Buyer’s prior commitments • Learning: Apple or Dell • complementary purchases: printer and inkjet cartridges • Taste: baby formula • Through smart business strategy: in 1981, American Airlines pioneered frequent flyer program, which became very attractive to business travelers

  10. Outline • Own-price elasticity • Forecasting quantity demanded and expenditure • Other elasticities • Adjustment time

  11. 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?

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

  13. Forecasting:Price increase • If demand elastic, price increase leads to • proportionately greater reduction in purchases • lower total sales revenue (sales revenue=price*quantity demanded) • If demand inelastic, price increase leads to • proportionately smaller reduction in purchases • highertotal sales revenue

  14. Forecasting:Price increase • If demand inelastic, price increase leads to • proportionately smaller reduction in purchases • higherexpenditure = higher sales revenue • Lower sales  lower cost • higher profit

  15. Forecasting:Coke vs Pepsi, Nov. 1999 • Coke • raised price • increased advertising • Pepsi followed • Both increased profit (demand was inelastic)

  16. Outline • Own-price elasticity • Forecasting quantity demanded and expenditure • Other elasticities • Adjustment time

  17. Income elasticity • Definition: percentage change in quantity demanded resulting from 1% increase in income. • Alternatively,

  18. Income elasticity: Estimates

  19. Income elasticity: Estimates

  20. Cross elasticity: Estimates

  21. Cross elasticity: Estimates

  22. Gas Prices: cars versus SUVs • Among 9027 households in the U.S., 38% had one care, 13% two cars, 15% one car and one SUV, 3% two SUVs. • The estimated cross price elasticity of (car+SUV) bundle with respect to gas price is -0.793 • The estimated cross price elasticity of (two cars) bundle with respect to gas price is +0.695

  23. SUV case revisited • Between 2004.9 and 2005.9., gas price increased by 66%. • In response to it, the SUV price dropped by 1.4% (through rebate as incentives) • The own price elasticity of SUV demand is estimated at -2.5, and the cross-elasticity with respect to gas is -0.25. • Therefore, the predicted change in SUV demand would be 66%*-0.25+(-1.4%)*-2.5=-13% • This is close to the actual change in sales: 16.8%!

  24. Advertising elasticity • direct effect – raises demand • indirect effect – makes demand less sensitive to price

  25. Advertising elasticity: Estimates If advertising elasticities are so low, why do manufacturers of beer, wine, cigarettes advertise so heavily? ---brand owners advertise to draw customers from each other – brand-level demand is more sensitive to advertising

  26. Advertising effect: direct and indirect

  27. Outline • Own-price elasticity • Forecasting quantity demanded and expenditure • Other elasticities • Adjustment time

  28. Adjustment time • Definitions • Short run: buyer cannot adjust at least one item of consumption or usage • Long run: long enough time for buyer to adjust all items

  29. Adjustment time

  30. Adjustment time:Short/long run elasticities

  31. Adjustment time:adjustment time effect and replacement frequency effect • Is demand more or less elastic in long run? • Does income change lead to bigger or smaller effect on quantity in long run?

  32. Summary • Own-price elasticity • Forecasting quantity demanded and expenditure • Other elasticities • Adjustment time

  33. Elasticity: Advanced • Elasticity of y with respect to x

  34. How to apply: easy, easy easy! • Example: y: demand, x: price, demand equation is Y=-10x+20 Elasticity of y with respect to x when x=1 is equal to

  35. Brain Tweezing • Elasticity is different at different x’s. • Try x=0.5 and try x=1.5 and see it yourself!

  36. Brain Tweezing: How to forecast the impact of price change? • Assume: Y=a*x+b • We don’t know a and b • We can estimate a and b using historical sales data: simple regressions. • Then we can calculate the elasticity at any level of x. • Finally, we can forecast the impact of price change on y and the total sales revenue y*x!

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