You Paid HOW MUCH for a Ticket to the Game?

I hear there is a big game coming up soon, and ticket prices are pretty high (and I’m not talking about the Washington Nationals’ Opening Day). So I reached out to the BLS experts on the Consumer Price Index (CPI) to learn a little more about how we handle the change in the price of sporting event tickets. We hear the face value of a ticket to a certain high-profile game is X, but then we hear the cost on the secondary market is Y (often several times X). But what if the game features a major-market team or a high-profile player, versus a game with less well-known teams or players? What if heavy rains are predicted for an outdoor game, or the halftime entertainer has recently encountered some social-media scandal? How can the CPI account for such differences when determining the rate of change in the price of a ticket?

What I learned

It turns out that BLS has experts in the price of sporting event tickets, and the experts know lots of answers—and know more questions we could explore. BLS even has detailed instructions for determining the price of tickets to sporting events—17 pages of instructions!

Sporting events are a subset of the CPI item category “Admissions,” which also includes movies and concerts. Here’s a chart showing the annual rate of change in the price of admission to sporting events over the past 20 years.

Editor’s note: Data for this chart are available in the table below.

Constant quality

A basic principle behind the CPI is what’s known as the matched model. That is, we want to determine the price of comparable (matched) items from one time period to the next. The fancy CPI term for this is constant quality. This means we have to carefully identify the characteristics of the item we choose to study, with the goal of keeping those characteristics constant each time we determine the price.

The source of tickets included in the CPI sample can include both individual sports franchises (such as the Mudville nine) and ticket resellers. In all cases we want to determine the price of a ticket based on a variety of price-determining factors that we hope to hold constant over time. For example:

• Admission type, such as adult versus child, but also individual tickets versus season tickets or a multigame ticket plan. When we follow the price of season tickets, we do so during a limited time of the year. For example, we might follow the price of baseball season tickets in the fall, when they are typically marketed, and then again the next fall.
• Seat type, such as box seats versus those in the nosebleed section. Ideally, we want to follow the price for the same seat (or same section) from one period to the next.
• Other factors, such as weekday versus weekend games or day versus night games.

We include professional, college, and high school sporting events in our sample. We see much less variation in the price of high school games than in the upper ranks. And we include both preseason (exhibition) and regular season games.

To get back to the original question, what about playoff games? We do not follow the price of tickets for most professional sports playoff games because the venue is not guaranteed to host a playoff game every year. To be included in the CPI, the requirement is for the venue to be constant—for example, certain college bowl games held in the same venue every year.

Are there other price-determining characteristics that can be tracked? One that CPI uses when appropriate is the type of opponent. Some ticket prices vary by type of opponent, such as a premium game against a conference opponent or traditional rival versus a nonpremium game. Such a distinction may be difficult to identify, however.

Quality adjustment

While we take care to select items that can be tracked over time, sometimes the price-determining characteristics change. Suppose the partial season ticket package that we first identified included 20 games, but the following year a comparable package included only 18 games. We consider this to be a quality change, something we don’t want to include when comparing prices.

We have a couple options for handling quality change. We can drop the item from collection and replace it with a new item. We determine the price of the new item and then track the change in that price going forward. This may be done for tickets to sporting events; if we can’t determine the price of a comparable ticket to one we examined previously, the item may be dropped from the index and replaced.

Alternatively, we can make a quality adjustment to account for changes in quality. In the case of the season ticket package where the number of games changes but all else is the same, we may be able to use simple math to make the old and new prices comparable.

For other items that change frequently, such as apparel and electronics, quality adjustment can be more complex. If you are a price index methodology geek, read the following to learn more about quality adjustment. Or, since we’ve carefully indented it, you can easily skip it.

The CPI uses hedonic quality adjustment, the practice of decomposing an item into its constituent characteristics, obtaining estimates of the value of the utility derived from each characteristic, and using those value estimates to adjust prices when the quality of a good changes. The CPI obtains the value estimates used to adjust prices through the statistical technique known as regression analysis. Hedonic regression models are estimated to determine the value of the utility derived from each of the characteristics that jointly constitute an item.

OK, back to things we all understand, like how the price of tickets to sporting events might vary. Could we consider making other quality adjustments for ticket prices? There are a variety of features that might be part of that equation, such as:

• The quality of the opponent. (Is their record 12-3 or 3-12?)
• The quality of the home team. A team having a poor season might have declining attendance as the season progresses, perhaps lowering ticket prices. A contender, conversely, may see rising prices as the season progresses.
• The weather on game day.

BLS actually has some index theorists working right now to investigate whether it is possible to develop a hedonic model to address some of these issues. But that’s for another today. For now, let’s just enjoy the game.

Before I go, let’s look at one more question you may be wondering about: How do price trends for admission to sporting events over the past 20 years compare to prices for all items? If you guessed that it’s more expensive to attend a sporting event, you’re right. Since 1999, prices for admission to sporting events have grown more than twice as fast as overall consumer prices. See the chart below.

Editor’s note: Data for this chart are available in the table below.