Netflix, 2011: Consumers paid ~$10/month for a streaming + DVD bundle. Netflix announced a packaging change — retaining both would cost $15.98/month, a 60% price increase. What happened?

• Before the increase: 24.6 million U.S. subscribers
• After the increase: 810,000 cancelled — dropping to 23.79 million
• Stock price fell from ~$33.60 to ~$7.80 per share in one year

Netflix officials expected an inelastic response (~600,000 cancellations). They underestimated how many substitutes existed (Hulu, Amazon Prime, Redbox). By 2021, however, Netflix had 214 million subscribers in 50 countries and its stock was over $600/share.

Lesson: Elasticity determines whether a price hike boosts or kills your revenue. Misjudging elasticity can be very costly in the short run.

Worked Example — Point Elasticity:

Demand function: $Q = 120 - 2P$. Find the point elasticity at $P = 30$.

Step 1: Find Q at P = 30: $Q = 120 - 2(30) = 60$

Step 2: Find $\frac{dQ}{dP}$: Since $Q = 120 - 2P$, $\frac{dQ}{dP} = -2$

Step 3: Apply the formula: $E_d = (-2) \times \frac{30}{60} = -1.0$

Notice: At $P = 40$, $Q = 40$ → $E_d = (-2)(40/40) = -2.0$ (elastic). At $P = 20$, $Q = 80$ → $E_d = (-2)(20/80) = -0.5$ (inelastic). Elasticity varies along the curve even though slope is constant.

Worked Example — Points A and B on a demand curve:

Step 1: % change in quantity = $\frac{2800 - 3000}{(2800 + 3000)/2} = \frac{-200}{2900} = -6.9\%$

Step 2: % change in price = $\frac{70 - 60}{(70 + 60)/2} = \frac{10}{65} = 15.4\%$

Step 3: Elasticity = $\frac{6.9\%}{15.4\%} = 0.45$ (taking absolute value)

Result: Elasticity = 0.45 < 1 → Inelastic. A 1% change in price leads to only a 0.45% change in quantity demanded.

Worked Example — Full Demand Schedule with Elasticity at Every Point:

Consider the demand function $Q = 400 - 10P$:

Key Observations:

1. Revenue peaks near $P = 20$ where elasticity ≈ 1
2. At high prices (elastic zone), price cuts increase revenue
3. At low prices (inelastic zone), price cuts decrease revenue
4. Slope ($\Delta Q / \Delta P = -10$) is constant, but elasticity changes dramatically

Worked Example — Apartment Supply:

An apartment rents for $650/month and 10,000 units are supplied. When price rises to $700/month, landlords supply 13,000 units.

Result: Elasticity = 3.53 > 1 → Elastic supply. A 1% rise in price causes a 3.53% increase in quantity supplied.

The Band Example: A band plays in a 15,000-seat arena. Should they raise ticket prices?

• If demand is elastic → cut the price. The % increase in tickets sold exceeds the % decrease in price, so total revenue increases.
• If demand is inelastic → raise the price. The % decrease in tickets sold is less than the % increase in price, so revenue increases.
• If demand is unitary → any moderate price change leaves revenue unchanged.

Some famous bands have inelastic demand right up to a full arena — they could charge even higher prices but choose not to, hoping fans will spend more on merchandise instead.

Coffee Price Fluctuations: The elasticity of coffee demand is about 0.3 (highly inelastic). When a frost destroyed Brazil’s crop in 1994, supply shifted left → prices skyrocketed because consumers kept buying nearly the same quantity. When Vietnam entered the market in the late 1990s, supply shifted right → prices collapsed.

With inelastic demand, supply shifts cause large price swings but small quantity changes.

Cigarette Taxes:

• Demand elasticity for cigarettes ≈ 0.3 (very inelastic — consumers are addicted)
• Supply is relatively elastic (factories can adjust production)
• Result: Most of the tax burden falls on consumers as higher prices. Quantity barely changes.
• A 10% price increase → only ~3% reduction in quantity smoked
• Conclusion: Cigarette taxes raise revenue effectively but don’t reduce smoking much. To reduce smoking, you need programs that shift the demand curve left (anti-smoking campaigns).

Youth vs Adults: Youth smoking demand is more elastic than adult smoking — price increases reduce teen smoking more effectively.

Worked Example — Tax Incidence Calculation:

A $2.00 per-unit tax is imposed on gasoline. Before the tax: $P = $3.00$, $Q = 100$ million gallons/day.

Demand elasticity = 0.3 (inelastic). Supply elasticity = 1.5 (elastic).

Formula for consumer’s share of the tax burden:

Result:

• Consumers pay: $2.00 × 83.3% = $1.67 more per gallon → new consumer price = $4.67
• Producers receive: $2.00 × 16.7% = $0.33 less per gallon → producer price = $2.67
• The less elastic side (consumers) bears the overwhelming burden

The 1973 OPEC Oil Crisis:

• In 1973, oil was $12/barrel. OPEC cut exports → supply shifted left.
• Short run (inelastic demand): Price nearly doubled to $25/barrel, but quantity only fell from 17M to 16M barrels/day.
• Long run (more elastic demand): By 1983, after a decade of insulation, fuel-efficient cars, and conservation, U.S. petroleum consumption was 15.3M barrels/day — lower than 1973 even though the economy was 25% larger.

General Pattern: In the short run, price bounces more than quantity. In the long run, quantity adjusts more and price changes are muted.

Example: Average annual income rises from $25,000 to $38,000. Bread consumption falls from 30 loaves to 22 loaves per year.

Bread is an inferior good (negative income elasticity). As people earn more, they buy less bread (perhaps switching to more expensive alternatives).

Example: The cross-price elasticity of apples with respect to oranges is 0.4. If the price of oranges falls by 3%, what happens to apple demand?

Apple demand falls by 1.2%. This makes sense — apples and oranges are substitutes. When oranges get cheaper, people switch to oranges.

Worked Example — Wage Elasticity of Labor Supply:

A factory raises wages from $15/hr to $18/hr. Hours worked per week increase from 38 to 40.

Result: Inelastic (0.28). Workers barely change hours when wages rise — consistent with adult labor supply being relatively inelastic. Workers have fixed schedules, family commitments, etc.

Case Study — Why Gasoline Demand Is Inelastic Short-Run but Elastic Long-Run:

This explains why the 1973 OPEC crisis caused a massive short-run price spike — consumers had no immediate alternatives. But by the 1980s, the U.S. had shifted to fuel-efficient cars and conservation, and OPEC’s power waned.

Case Study — Housing Supply Elasticity Varies by City:

Implication: When demand for housing rises equally in all three cities:

• Houston: Quantity supplied increases significantly, prices rise modestly
• San Francisco: Prices spike, quantity barely increases → housing crisis
• Manhattan: Prices explode, almost no new supply possible

This explains why median home prices diverged dramatically after 2000: Houston stayed affordable while San Francisco and New York became among the most expensive cities in the world.