In 1990, the US Congress passed a special 10% excise tax on the value (above $100,000) of all new boats and yachts. Supporters believed that the tax would generate needed additional revenue while impacting only the wealthiest of Americans. While the Demand and Supply model suggests that the corresponding leftward shift of the Supply Curve should lead to a reduction in quantity demanded, proponents believed that this decrease would be insignificant.
The reality was quite different. Already suffering depressed sales due to an ongoing economic recession, the introduction of the tax in 1991 crippled the industry. According to the National Marine Manufacturers Association, sales decreased from $17 billion in 1989 to $10 billion in 1992. They further estimated that the tax led to the loss of an additional 25,000 jobs, that on top of the roughly 100,000 lost due to the recession. (Bowman, 1993). The tax was repealed just two years later in 1993.
Domestic buyers of boats could easily defer purchase or purchase used instead. Ocean-going yacht buyers had the additional option of buying yachts overseas. And so, it turned out demand for expensive boats and yachts was very sensitive to changes in price. In general, the Demand and Supply model is very useful for exploring the potential impact of market disruptions like the tax. But the model doesn’t go quite far enough. To really understand the potential impact of the tax, or perhaps an increase in the price of your company’s dog food, you need to have to have a strong sense of just how much quantity demanded might change.
Elasticity is the formal method of determining the sensitivity of quantity demanded (typically) to a given change in price or some other determinant of demand. While intuitively it might seem that the slope of the Demand Curve would convey this, that’s not actually true. What if I were to tell you that the slope of a product’s demand curve is -10. For each one dollar increase in price, sales should decrease by ten units. Is that significant? It depends. If I’m talking about weekly sales for a pizza chain, that seems insignificant. The demand is apparently relatively insensitive to price changes. On the other hand, if I’m instead talking about a single car dealership and weekly demand for vehicles, we’d say that the demand is incredibly price sensitive. In short, how significant the change is, depends on the original price and the original sales level.
(Price) Elasticity (of Demand) = Percentage Change in Sales / Percentage Change in Price
Elasticity gets around this problem by comparing percentage changes. If I tell you the one-dollar change in the price of pizza is roughly 10% of the total price and the 10 unit decrease in sales is 1% of weekly sales, then the resulting elasticity would be 0.1 (= 1%/10%). That’s relatively small. Whereas for the dealership, the one-dollar change is .005% of the price while the change in sales might be 10%. The elasticity in this case would be 2,000. By comparing percentage changes, elasticity provides a pretty good measure of price sensitivity.
Now, consider a t-shirt company that sells 1,000 units a week at $20 each. Sales revenue is $20,000 per week. What would be the impact of a 5% increase in price. First, let’s assume that the Price Elasticity is equal to 0.5. A 5% price increase will cause a 2.5% decrease in sales. What will happen to revenue? Price will increase to $21 ($1 is 5% of $20) and sales will decrease to 975 units. Sales revenue will be $21 X 975 = $20,475. It went up.
Now assume Price Elasticity is equal to 5. A 5% price increase this time will cause a 25% decrease in sales. Price will again be $21. But this time sales will decrease to 750 units. Revenue will be $21 x 750 = $15,750. It decreased this time!
In general, when the Price Elasticity is less than one, a price decrease will increase revenue, and vice versa. But when Price Elasticity is greater than one, a price decrease will decrease revenue, and vice versa. The former is referred to as Inelastic Demand and the latter Elastic Demand.
Elasticity < 1 Inelastic Demand
Elasticity > 1 Elastic Demand
Elasticity = 1 Unitary Elasticity – And revenue is maximized
There are four determinants of Price Elasticity:
- Price (proportion of budget)
- Availability of Substitutes
- Necessity or Luxury
- Time Frame
Newspapers make up an insignificant proportion of the typical buyer’s budget. Even an increase of as much as 50% corresponds to such a small amount of money that it’s largely unimportant to the buyer. Airline flights, on the other hand, are somewhat expensive. The difference in fares across airlines is often in the hundreds of dollars. And so, it pays the consumer to shop around. All else equal, newspapers would therefore tend to be less elastic than airlines.
Another important consideration is the ability to substitute away from one product to another. With the aid of travel websites, consumers can check fares across multiple airlines. The same isn’t true for most newspapers. Most cities have one, or at most two, major newspapers. And even when there are two, they tend to be sufficiently different in content and approach to make them poor substitutes. So, for the buyer, the only real option is whether to do without the local paper altogether. For this reason, newspapers would again tend to be less elastic than airlines.
In general, luxuries tend to be more price-sensitive (i.e. elastic) than necessities. The buyer of a luxury product (defined simply as any good that doesn’t qualify as a necessity) can always simply decide to delay purchasing the product altogether. This isn’t practical for a necessity. Stopping at a gas station, the customer finding that the price of her favorite snack has increased can simply do without. But she will still need to purchase gas even if its price increased as well. For most of us, both airline tickets and newspapers are both luxuries. Of course, this isn’t true for everyone. But to the extent they are luxuries, this would tend to make them both slightly more elastic.
Finally, the time frame matters in several ways. First, consider the Price Elasticity of gasoline. While on any given morning you have to go ahead and fill up regardless of any price increase, over time you have options. If you expect the price to remain high and it’s time to purchase a new vehicle or move, you can choose a more fuel-efficient vehicle or a home closer to your work or school. We observed this in the late 70s and early 80s. Consumers adapted to high fuel prices by purchasing smaller more fuel-efficient vehicles. Conversely when fuel prices fell later in the same decade, consumers dutifully switched back to larger, more powerful vehicles.
Time frame also matters with respect to the duration of the price change. While even a twenty percent reduction in the price of clothing might be met with a collective yawn. A twenty percent reduction that was expected to last only a short amount of time before returning to normal might elicit some reaction. JC Penney, the retailing giant, learned this lesson the hard way. It disastrously eliminated most ‘sales’ replacing them with a permanent price reduction. The result was a significant decline in sales revenue relative to the old strategy of periodic temporary price reductions.
Time frame might explain why airlines rely on promotions rather than simple price reductions. By making the price change temporary, they increase the response to a price reduction. (And they have an easy path to subsequently raise prices again.) And time frame might also be relevant to a local newspaper. While they might not observe a significant drop in circulation immediately following a price increase, over time sales may continue to decline as subscribers are able to find more alternative sources of information.