The Metrics of High Gas Prices

In the United States, gas prices hit all-time highs this year, even in inflation-adjusted dollars. This new reality has motivated some rethinking about metrics related to cars, gas, and money.

Total Cost of Ownership for Cars

Total Cost of Ownership (TCO) is a metric that includes not only the purchase price of a car but also the costs to run and maintain the car over time. While a business would likely use TCO to evaluate buying a fleet of cars, relatively few consumers use it when buying their own cars.

However, new-car buyers are increasingly doing a rough form of TCO as they abandon gas-guzzling SUVs and trucks in favor of fuel-efficient cars. Moreover, according to this New York Times article, many consumers are using their future savings at the pump to load up on options like leather seats and fancy car stereos.

In this new math for the auto industry, gas mileage often trumps sticker price for consumers.

“Affordability is not so much the issue as fuel economy,” said George Pipas, Ford’s chief sales analyst. “Just because you want more fuel efficiency doesn’t mean you don’t want a moonroof or leather interior.”

Gallons Per Mile

Earlier this summer, a pair of Duke University professors published research that suggests people often misinterpret the “miles per gallon” metric when comparing different cars. For example, which of the following saves the most gas?

(a) Replacing a 20-MPG car with a 40-MPG car

(b) Replacing a 10-MPG car with a 20-MPG car

(c) The previous two choices will have an equivalent effect

Many people don’t realize the answer is (b). However, if you flip the metric to be gallons per mile—or better, gallons per 10,000 miles—things clarify. (Gallons per 10,000 miles just means the number of gallons of gas necessary to drive 10,000 miles.)

Per this spreadsheet...

...a 10-MPG gas guzzler requires 0.10 gallons to go a mile; that is 1,000 gallons for 10,000 miles. In comparison, the 20-MPG normal car takes 500 gallons to go 10,000 miles. And the 40-MPG efficient car takes 250 gallons to go 10,000 miles. So switching from the gas guzzler to the normal car saves double the gas as switching from the normal car to the fuel-efficient car. At $4 per gallon, that’s a $2,000 versus $1,000 savings.

This result is worth considering in light of government policies that simply promote ownership of fuel-efficient cars. Such policies might instead want to base the subsidy on the fuel-inefficiency of the owner’s previous car, thereby creating greater incentives to get the worst gas guzzlers off the road.

We Feel It Because We See It

Behavioral economist Dan Ariely, author of Predictably Irrational, had a recent piece about why there’s so much angst about gas prices. He argues that we care more about gas prices than the prices of other necessities because when we buy gas, the cost adds up right before our eyes.

Looking back at my family’s expenses over the past few years, I see big increases in our health care costs and in how much we pay for food. The rise in what we spend on gas is not nearly as extreme as our increases in categories like electricity and telephone. So why does the amount we spend on gasoline feel so enormous? I think it is because of the way we buy gas.

For the several minutes that I stand at the pump, all I do is stare at the growing total on the meter — there is nothing else to do. And I have time to remember how much it cost a year ago, two years ago and even six years ago.

Yet I have no such memory about the prices of items in any other category. I have no idea how much milk was six years ago, how much bread was three years ago or how much yogurt was a week ago. But I suspect that if I stood next to the yogurt case in the supermarket for five minutes every week with nothing to do but stare at the price, I would also know how much it has gone up — and I might become outraged when yogurt passed the $2 mark.

I like the spirit of the example, but I don’t know anyone who buys $50 worth of yogurt per week or whose livelihood relies on eating yogurt. In contrast, large numbers of people have those situations with gas.

I would have rather seen Ariely use health care as the example. At various points in people’s lives, it’s an absolute necessity, yet few people understand exactly how much they pay (through some combination of direct, employer, and insurer payments) or how that amount has changed over time.

How Not To Do Customer Service

Once upon a time, a cable TV installer arrived at my house. He didn’t know which services I ordered, but he knew he was there to install something. As first steps go, this one was not a confidence-builder.

I told him which services I ordered. As he was doing the install, I noticed he was providing the wrong set top box for our service. When I asked him about this, he was surprised I knew the difference and said that he “just ran out” of the correct boxes, but this one would work.

I pointed out that it wouldn’t work as well. I asked him to get the correct box and come back. He said he couldn’t do that; I needed to make another appointment.

I asked him why that was my problem to solve, considering it was he who did not have the correct equipment. He didn’t have an answer, but he suggested the fastest solution was for me to take the wrong box and swap it at the local cable store, nearby on Bloomfield Ave. He said this in a knowing tone, as if I’d eventually end up there anyway.

Later, I went to the cable company’s Web site but couldn’t find a store locator to get the store’s exact address. I ended up finding the store locator by Googling the cable company’s name and “store locator.” Sure enough, it was on the company’s Web site, but there was no obvious way to get to it.

I put in my zip code. The only store that came up was a Best Buy somewhere in West Hartford—literally “somewhere” because there was no address or phone number provided. Perhaps the store locator was hard to find because it was not meant to be used.

So I moved on to the cable company’s “live chat” feature. Having started a session, the screen said, “Status: You are waiting for an analyst to assist you.”

While waiting for the chat feature to do something, I called the cable company’s support number. It told me they were experiencing higher than normal call volumes. “If your call is not of an urgent nature, please call back later.” I rechecked the chat window...no change.

While waiting, I searched Google for the cable company’s name plus the name of towns in the immediate vicinity. It provided a listing, not on Bloomfield Ave. I called the number. No one answered, and the voicemail box was full.

I had left the support number on speakerphone, and it eventually got me a person who gave me the address of the cable-company store where I could exchange my box. It was neither on Bloomfield Ave., nor at Best Buy, nor at the office where the voicemail was full.

Having gotten an answer on the phone, I bailed out of the chat feature, which was 25 minutes into waiting for an analyst. In doing so, I got a customer-satisfaction survey for my Web visit. Eager to express an opinion or two, I was disappointed to find that most of the questions were irrelevant to my visit. For example, the first question was, “Please rate the ability to limit sharing of your personal information on this site.” There were multiple screens, largely filled with such irrelevant questions. I skipped the whole thing.

Later, I went to the store. I waited a while. When my number was called, I found that the store itself “just ran out” of the correct boxes. I expressed frustration that my time was being wasted. I asked whether I had done something wrong in the process. No, said the person, but perhaps my expectations could have been set better.

Let us examine and extend that insight.

Maybe the cable guy could have said, “Hey, I’m sorry, but I just realized I don’t know what you ordered or if I have the right equipment. Let me get your order now, and if I’m not set to do this right, I’ll schedule myself to come back first thing tomorrow with the right gear.”

Or, lacking that, the cable guy could have said, “I’m sorry it’s a hassle, but your best bet is to swap this box at the local cable store. I think it’s on Bloomfield Ave., but let me call them to make sure they have the box you need and to get the exact address.”

Or, lacking that, the cable company’s Web site might have had a findable and functioning store locator.

Or, lacking that, the cable company’s chat feature and support line might have had one of those messages that estimates how long until a person would be available.

Or, lacking that, the person I eventually reached might have suggested that I call the store to make sure they had the box I needed because sometimes the boxes are out of stock. (Actually, this would not work because the store apparently does not have a public phone number. Rather, the only number given was the cable company’s general support number.)

The irony is, if one of the first few scenarios above would have happened, I probably would have said the overall experience was good, because I would have appreciated someone’s taking the initiative to fix a problem. But with failure at every turn, it’s harder to be understanding. And irony upon irony, the company’s one attempt to solicit my feedback (the customer-satisfaction survey on the Web site) was so poorly executed that it wasn’t worth using.

Having read this far, you might be wondering if I ever got the right box.

While at the cable store, I asked whether they had a waiting list or some other way to notify me when the correct box was available. Looking as if he was taking pity on me, the guy asked for my name and number. He wrote it on the back of a piece of scrap paper. He also offered that I could set up another appointment and maybe the correct box would be on that truck. “Maybe?” I asked. “Why would the truck come if the box wasn’t on the truck?”

That was like asking why things fall down, not up. It just works that way.

A day later, I happened to be driving near the cable store. Having zero expectation of success, I went in anyway, skipped the line, and asked someone if the correct type of boxes were available. The person said yes. I took a number. I got the box. Everyone lived happily ever after—the key word being “after.”

Enlightening about Lightning

In Connecticut today, we had three separate waves of thunderstorms, the last of which is still going. Earlier I was near enough to a lightning strike that the thunder had no rumble; it was a bomb-like detonation, right after the flash.

Having recently moved from San Francisco, where thunderstorms are rare, the summer thunderstorms in New England are still novel for me. According to statistics from the National Lightning Detection Network, Connecticut has between five and six times the lightning flashes per square mile as California.

Yet that’s only enough to rank Connecticut 36th among U.S. states for cloud-to-ground flash densities. The southeast dominates the top five, with Florida leading by a substantial margin. (Florida has seven times Connecticut’s lightening flashes per square mile. It also leads the nation in lightning deaths.)

Having addressed where you’re likely to see lightning, we might as well also cover the following:

People ask, “Who is most likely to be struck by lightning?” Something stirs in the mind about metal objects, and you might guess golfers, out there on the open fairways with four-irons raised to the sky, or fisherman clutching their metal rods. But you might not think of farmers, perched on their tractors and insulated by rubber tires, and, in fact, farmers it is. Where we need protection is overhead, not on the ground. Closed vehicles act as Faraday cages — named after Michael Faraday, the nineteenth-century British physicist and chemist, who specialized in electromagnetism — and are a good choice for cover, because the metal that encases them channels the charge into the ground. As it descends to earth, lightning current is drawn to isolated objects, anything taller than others in its field. This might be a lone tree, a skyscraper, a mound of granite in a riverbed, or you in your small craft on open water. Farmers are vulnerable because of where they are when they’re out in their fields — the tallest object in an open space, plowing or haying as the summer day heats up.

The quote is from a fine essay by Jill Frayne in the Canadian magazine The Walrus. In addition to enlightening us about the science of lightning, she narrates a few close encounters: “The strike shot through the radio antenna, exploded in the living room into a blue fireball that roared down the hall, lifting up the linoleum runner by the tacks, ripping the nails out of the floor, splintering the house walls as fine as kindling before it ran off over the bedrock outside and died.”

Here’s the link again. It’s a good read.

And with that, I’ll post this before the power goes out.

[The image is from Wikipedia’s Lightning article.]

Dan Ariely’s Predictably Irrational

Dan Ariely is a Duke University professor specializing in behavioral economics. In Predictably Irrational, he explains his field like so:

According to the assumptions of standard economics, all human decisions are rational and informed, motivated by an accurate concept of the worth of all goods and services and the amount of happiness (utility) of all decisions are likely to produce....Behavioral economists, on the other hand, believe that people are susceptible to irrelevant influences from their immediate environment (which we call context effects), irrelevant emotions, shortsightedness, and other forms of irrationality.

Ariely provides many real-world examples of economic irrationality. For example, here’s an anecdote about a restaurant consultant who learned that...

...high-priced entrees on the menu boost revenue for the restaurant—even if no one buys them. Why? Because even though people generally won’t buy the most expensive dish on the menu, they will order the second most expensive dish. Thus, by creating an expensive dish, a restaurateur can lure customers into ordering the second most expensive choice (which can be cleverly engineered to deliver a higher profit margin).

While a book of such anecdotes would make for good reading, Ariely’s academic work is about going beyond the anecdote to the experiment. Thus, much of the book covers controlled experiments (often by Ariely) designed to test people’s rationality in decision-making. And to Ariely’s credit, he still makes it a good read.

Among the experiments Ariely describes:

• Seeing if people who knew they were starting an auction from an arbitrary price (the last two digits of their social security number) would nevertheless bid relative to that price. Without knowing others’ bids, each participant made a single “best offer” bid, which could be either up or down from his or her social-security-number starting point. “In the end, we could see that students with social security numbers ending in the upper 20 percent placed bids that were 216 to 346 percent higher than those of the students with social security numbers ending in the lowest 20 percent.”
• Exploring the distorting effect of free pricing. Given a choice between a single ultrafancy chocolate for 15 cents (well below normal price) and a single Hershey’s Kiss for 1 cent, 73% chose the ultrafancy chocolate. But when the price of each was reduced 1 cent—to 14 cents and “FREE!”, respectively—69% chose the Kiss. Note that it was one chocolate per person, so everyone faced an either/or choice, and the relative price difference was unchanged at 14 cents. “According to standard economic theory (simple cost-benefit analysis), then, the price reduction should not lead to any change in the behavior of our customers....And yet here we were, with people pressing up to the table to grab our Hershey’s Kisses, not because they made a reasoned cost-benefit analysis before elbowing their way in, but simply because the Kisses were FREE!”
• Testing whether people value items more highly after buying them. Because of high demand and limited supply, Duke ran a lottery to determine who could buy tickets to Duke basketball games. After a lottery, Ariely and another researcher called more than 100 students who either won or lost in the lottery. “In general, the students who did not own a ticket were willing to pay around $170 for one....Those who owned a ticket, on the other hand, demanded about $2,400 for it.” In other words, there was initially a single group of students, “all hungry for a basketball ticket before the lottery drawing; and then, bang—in an instance after the drawing, they were divided into two groups—ticket owners and non-ticket owners. It was an emotional chasm that was formed, between those who now imagined the glory of the game, and those who imagined what else they could buy with the price of the ticket.”

Having found that people can indeed be predictably irrational, Ariely makes the move from descriptive to prescriptive:

The good news is that these [irrationalities] also provide opportunities for improvement. If we all make systematic mistakes in our decisions, then why not develop new strategies, tools, and methods to help us make better decisions and improve our overall well-being?

Among the new strategies he mentions is Save More Tomorrow, a program designed by behavioral-economics proponents Richard Thaler (University of Chicago) and Shlomo Benartzi (UCLA):

When new employees join a company, in addition to the regular decisions they are asked to make about what percentage of their paycheck to invest in their company’s retirement plan, they are also asked what percentage of their future salary raises they would be willing to invest in their retirement plan. It is difficult to sacrifice consumption today for saving in the distant future, but it is psychologically easier to sacrifice consumption in the future, and even easier to give up a percentage of a salary increase that one does not yet have.

Save More Tomorrow is a poster child for behavioral economics because it famously succeeded in a real-world test at an actual company, nearly quadrupling savings rates. Aiming for a similar real-world win, Ariely tried to sell the credit-card industry on the concept of a “self-control credit card,” where the consumer could self-restrict spending by category. There were no takers, but he is still holding out hope.

I’ve gone on at length about Predictably Irrational because I thought it was well worth my, and probably your, time. It’s a great combination of data-driven insight, real-world application, and well-told stories—by one of the principles in the field, no less.

Here’s the link to the book at Amazon, which has an excerpt and some author videos. See also Ariely’s Predictably Irrational site.

Social Norms versus Market Norms in Daycare

“Any questions?” asked the daycare-center director. She was a pleasant mix of smart and caring. She no doubt wished her center could accept all the applicants. But this being one of the few daycare centers near downtown San Francisco, the wait list dwarfed the enrollment.

“Wait list” was a misnomer. The center chose children based on unspecified factors, only one of which was place in line. So, all parents on this tour for applicants were listening attentively, mustering questions that demonstrated thoughtful consideration for their childrens’ welfare, and otherwise exhibiting best behavior.

Until the following exchange:

Parent: What is the policy if I’m late to pick up my child?

Director: We understand that once in a while you get stuck in traffic or can’t get here for extraordinary reasons. Just give us a call at the time, and we’ll make sure someone stays with your child until you get here.

Parent: Is there a fine or penalty?

Director: We’re not going to fine you for a rare event that’s totally out of your control.

Parent: But what if it happens repeatedly? How many times do I have to be late before you start fining me, and what’s the fine?

Director: Uh, we haven’t had to deal with that before.

Parent: Well how do I get that question answered?

Director: Let me get back to you on that.

As this exchange progressed, the questioning parent’s demeanor went from neutral to baffled, like a boss mystified by a subordinate’s inability to answer a simple question. Meanwhile, everybody else in the room was looking at each other like, “There’s one person we don’t have to worry about getting in before us.”

At the time, I didn’t ask myself why everyone except Baffled Parent knew something had gone awry. However, the incident came back to me when I read Dan Ariely’s Predictably Irrational. The book is about how people’s decisions—not just individually but in aggregate—can be skewed by factors beyond traditional economics’ view of rationality.

Ariely would explain that Baffled Parent tried to apply traditional economics’ “market norms” in a situation where “social norms” prevail. In fact, Ariely has an example of what happened when a day care center tried doing things Baffled Parent’s way:

A few years ago, [Uri Gneezy of UC San Diego and Aldo Rustichini of the University of Minnesota] studied a day care center in Israel to determine whether imposing a fine on parents who arrived late to pick up their children was a useful deterrent. Uri and Aldo concluded that the fine didn’t work well, and in fact it had long-term negative effects. Why? Before the fine was introduced, the teachers and parents had a social contract, with social norms about being late. Thus, if parents were late—as they occasionally were—they felt guilty about it—and their guilt compelled them to be more prompt in picking up their kids in the future. (In Israel, guilt seems to be an effective way to get compliance.) But once the fine was imposed, the day care center had inadvertently replaced the social norms with market norms. Now that the parents were paying for their tardiness, they interpreted the situation in terms of market norms. In other words, since they were being fined, they could decide for themselves whether to be late or not, and they frequently chose to be late. Needless to say, this is not what the day care center intended.

I’ll have more to say on Ariely’s book—of which social versus market norms is a small section—in a subsequent post.