It is standard among economists that when the price of a good increases, the quantity demanded for that good decreases (assuming other factors remain equal). The basic logic is that increasing the price of a particular good has two effects. The “substitution effect” states that when the price of a particular good increases, potential buyers switch part of their purchases to a substitute good. The ‘income effect’ means that when the price of a specific good rises, the overall purchasing power of income decreases, which tends to reduce the consumption of all ‘normal goods’ purchased by individuals. In fact, the economic definition of a “normal good” is a good of which more is consumed as income increases. This contrasts with “inferior goods,” where less is consumed as income increases. A standard example is that a steak may be a “normal good” while a hamburger may be an “inferior good.” As income increases, the average household consumes more steaks and less hamburgers.
However, there is a well-known theoretical exception to this rule, known as “Giffen goods.” Imagine a very “inferior” product. When the price of a good rises, the substitution effect provides an incentive to switch to another substitute. However, when the price of an inferior product increases and purchasing power decreases, people with lower incomes actually buy more of that product. If there are not many substitutes for the good and the inferior good effect is strong, a higher price may cause people to buy more of the good.
As a real-life example, consider the situation of a low-income household in which a single food item plays a large role in the diet of almost subsistence. An example I heard in class was the role of potatoes in the diet: Poor people in 19th century Ireland. Let’s say that external factors, such as a poor harvest, cause the price of potatoes to rise, but even after this price increase, potatoes still remain the cheapest source of calories in a basic diet. In these situations, poor people do not have cheaper food alternatives. Moreover, rising prices of staple foods, which account for a large portion of overall household spending, mean that the purchasing power of household income is weakening, and potatoes are an inferior good. Therefore, poor people in this situation react to higher potato prices by purchasing larger quantities of potatoes.
The situation of Giffen goods being ‘inferior goods’, which are essential foodstuffs that cannot be easily replaced but account for a significant proportion of low-income households’ purchases, is clearly rare. Francis Ysidro Edgeworth described Giffen products in 1914: ‘Only a very clever person will discover the exceptional cases. Only a very foolish person would make that the basis of a rule of general practice.’” Indeed, I know of no clear empirical evidence that Giffen’s good arguments applied to low-income Irish potatoes-eating families in the 19th century. However, there is contemporary evidence that rice was a Giffen good for low-income households in certain regions of China.
Garth Heutel suggests a completely different case when he says, “Theme park rides are Giffen goods.” (Southern Economic JournalPublished online September 17, 2024). His argument requires a shift in perspective. Requires great footwork. He focuses on a specific context in which people pay an admission fee to enter an amusement park but do not pay extra for the rides. In this context, the “price” of the ride is the time you wait in line, considering you’ve already paid the entrance fee. Additionally, you enter the park knowing that there will be lines, especially for the most popular rides. So Heutel argues that “higher prices” in this context refers to a situation where you enter the park and find that the line for a particular ride is longer than expected.
Here’s a simple example from Heutel to give you some intuition:
Consider a theme park that only has high-demand rides with long wait times, like roller coasters, and low-demand rides with short wait times, like merry-go-rounds. Guests planned their trips based on the estimated wait times for the rides (15 minutes for the carousel and 120 minutes for the roller coaster) and the total time spent in the park, which was 7 hours. Considering budget constraints, guests choose three roller coaster rides (6 hours) and four carousel rides (1 hour). …
When the guest arrived at the park, she discovered that the carousel wait time had unexpectedly increased from 15 to 30 minutes. How does she change her behavior? One option is to keep the roller coaster to three rides, leaving enough time (1 hour) to ride the carousel twice instead of four. This will reduce the total number of rides from 7 to 5. An alternative option is to ride the roller coaster one less time (2 instead of 3). She has two more hours left to ride the carousel, allowing her to ride it six times instead of the original four. This increases the total number of rides from 7 to 8. This option corresponds to Giffen’s behavior in her request for the carousel. Price (waiting time) increased and quantity demanded increased. If guests have a minimum total number of rides they want to achieve similar to their subsistence needs, they are more likely to choose the Giffen option.
Heutel provides data and theory to argue that this simplified example is a plausible representation of reality. I can’t do justice to the complexity of the analysis here, but here’s an overview:
I use a unique proprietary data set containing observations from hundreds of guests at several major theme parks in California and Florida. Each guest has at least one “tour plan,” which is a planned itinerary of rides the guest wants to do in the park. For each ride in the plan, we observe the pre-expected wait time, the actual wait time after the guest arrives for the ride, and the decision as to whether the guest will board or not. The main empirical test is how the actual waiting time, i.e. the deviation between the actual waiting time and the expected waiting time, affects the probability of boarding. … The law of demand says that the longer you wait, the less likely you are to get a ride. Giffen behavior suggests the opposite. …
I found statistically significant evidence for Giffen behavior among theme park guests. On average, a 10-minute increase in the difference between a ride’s actual wait time and the pre-expected wait time increases the odds of a ride by about 3 to 5 percentage points. This relationship holds under a variety of specifications and a variety of controls, including controls for weather, overall park wait times, users, rides, and date and time fixed effects. While this is true on average across all rides, I find that the effect primarily occurs on the most undesirable rides, i.e. non-headliner rides like rollers.
Coaster. These rides are likely to be inferior products and therefore more likely to exhibit Giffen behavior. I show that, consistent with theory, the Giffen effect is larger in theme parks with fewer alternative rides.
For me, it takes some mental effort to think about the “livelihood” problems of theme park visitors in terms of the limited hours a day compared to the “livelihood” problems of poor Chinese people who overeat. Dependent on rice. But of course the very different context is what makes this example worth passing on.
