Paying more for airline passengers to give up seats

In a previous blog post about the mishandling by United Airlines of a passenger that had already boarded the plane, I suggested the following thought experiment: “Suppose United offered $10,000 to each person who gave up their seat. I suspect most passengers sitting on the plane would have volunteered.”

The next day, AP News reports that “Delta OKs offers of up to $9,950 to flyers who give up seats.”

This must be just a coincidence.

A United case for free markets and clearly defined rights

A lot has been written and said about United Airlines and their mishandling of a problem of overbooking. In case anyone missed the story, a United Airlines flight was overbooked. The airline also needed to fly crew members to the plane’s destination. The airline asked for volunteers to give up seats and even offered some money as an inducement, but that wasn’t enough. So the airline randomly selected passengers to remove involuntarily. Three agreed to leave the plane but one refused. The airline called airport police, who forcibly removed the passenger. Photos and videos of the passenger being dragged out of the plane caused worldwide criticism of the incident and airline. There are numerous memes floating on the internet now inspired by the event.

I am not going to criticize the airline or defend it. Others are doing that. However, I think the story provides an ideal case for illustrating two important economic principles: the superiority of free markets and the importance of clearly defined property rights.

First, economic systems determine how scarce resources are allocated. There are different ways of doing this. One involves free markets, where the exchange of money determines how resources are reallocated. Another involves various forms of command and control, where government or other entities dictate who does what and what goes where.

The airline had (some may say created) a problem of scarcity. There were more people who needed seats than there were seats available. A free market solution to the problem is simple: offer enough money to induce people to voluntarily give up their seat. Here is a thought experiment. Suppose United offered $10,000 to each person who gave up their seat. I suspect most passengers sitting on the plane would have volunteered. The airline said it offered compensation (the WSJ article linked above states that the airline offered up to $1,000). Clearly, the airline did not offer enough. In a free market environment, if the buyer values the resource more than the holder of the resource does, then an efficient exchange can occur if the buyer offers more than the seller’s value. If it was worth more than $1,000 a seat to United to get a crew member on the plane, then the airline should have offered more. If it was not worth more than $1,000, then the airline should not have pursued the matter further. That is the simplicity of the free market.

When there is command and control, such as when the government decides who flies and who doesn’t, then the government uses the power of the state to enforce its preferences, which we saw clearly here when the airline utilized police to drag an unwilling passenger off the plane. If the airline had utilized market principles, then there would have been no incident worth reporting. Stated differently, when markets function well (and when they are allowed to function well), then there is almost never a story to report. I find that interesting.

Second, when there is confusion about property rights, then there will be conflicts. People who buy plane tickets, either with a seat assignment or who are sitting in a seat, believe they have rights to the seat on the plane. In contrast, airlines not only can overbook but also can involuntarily deny boarding of passengers and even tell passengers they have to get off the plane, suggesting the airline believes it has rights to the seat on the plane. (Anyone interested can read United’s Contract of Carriage document here, especially rule 25, which describes what the airline’s obligations and rights are with respect to “denied boarding compensation”).

Regardless of whether passengers or airlines actually own rights, it is the beliefs they hold that matter most here. If passengers believe they have rights to the seat and if airlines believe they control those rights, then there will be a conflict when there is a problem of overbooking (that is, economic scarcity). Markets won’t work well here because there is no basis for determining who should pay and how much, since there is uncertainty about who initially owns the right to be transferred. If the airline believes it has the right, then it doesn’t need to offer any compensation. It can just drag unwilling passengers off the plane and place other passengers in the vacated seats.

The Nobel winning economist Ronald Coase described this problem and pointed to a solution: make clear who has rights to the seat. According to the Coase Theorem, bargaining is efficient when property rights are clearly defined and when bargaining is reasonably feasible. Airlines have demonstrated that bargaining for overbooked seats can work if they just offer enough compensation, suggesting they effectively acknowledge the beliefs of passengers that passengers hold rights to seats they have paid for, regardless of what their overbooking rules say.

The lesson here is therefore simple. If airlines are going to overbook their flights, then they should be prepared to pay passengers enough to induce volunteers to vacate their seats on the plane.

Corruption, 2016

Transparency International is a non-governmental organization, headquartered in Berlin, with a mission to document and root out public corruption worldwide. The organization defines corruption as “the abuse of entrusted power for private gain. It can be classified as grand, petty and political, depending on the amounts of money lost and the sector where it occurs.”

For more than two decades Transparency International has produced an annual Corruption Perceptions Index. The most recent edition of the index (here) ranks 176 countries from the least corrupt to the most corrupt. The index ranges from a scale of 0 to 100, “where a 0 equals the highest level of perceived corruption and 100 equals the lowest level of perceived corruption.” The Index  “aggregates data from a number of different sources that provide perceptions of business people and country experts of the level of corruption in the public sector.”


The least corrupt countries are Denmark, New Zealand, Finland and Sweden. They always stay at the top of the list. The most corrupt countries are Syria, North Korea, South Sudan and Somalia. Denmark’s score is 90 while Somalia’s is 10. The United States is number 18 on the list, with a score of 74, below Canada, Germany and the UK. That’s alarming. Not that the US is below other countries but that the US is more than halfway to the midpoint of the CPI scale (Slovakia and Croatia have scores of 51 and 49 respectively).

Corruption matters because it erodes public trust in government and business, and trust is very important for promoting economic growth and well-being. For example, note the following figure I produced showing the correlation between corruption and per capita gross domestic product. Of course, correlation does not mean causation. And we can debate whether corruption produces low growth or whether low growth invites corruption, but the correlation is stark. Highly corrupt countries are very poor. Moreover, for every 10 point improvement in a country’s perceived corruption, GDP per capita increases by more than $7,000 (that’s what the equation in the figure shows).


Transparency International also draws a connection between corruption and social inequality. As noted on their website (here): “it’s timely to look at the links between populism, socio-economic malaise and the anti-corruption agenda. Indeed, [US President] Trump and many other populist leaders regularly make a connection between a ‘corrupt elite’  interested only in enriching themselves and their (rich) supporters and the marginalisation of ‘working people’. Is there evidence to back this up? Yes. Corruption and social inequality are indeed closely related and provide a source for popular discontent. Yet, the track record of populist leaders in tackling this problem is dismal; they use the corruption-inequality message to drum up support but have no intention of tackling the problem seriously.”

In other words, we preach virtues but don’t practice them ourselves.

Which reminds me. After discussing these ideas in my applied ethics class I suggested that students can obtain an automatic A in the class if they leave me a $100 bill with their name written on it in pencil. Some students laughed while others wanted to negotiate the price. Apparently they didn’t learn anything.

Doing bad when I think I’m good

A perplexing question in social science research is why people behave in ways inconsistent with their beliefs and their perceptions about themselves. For example, if we know it is wrong to lie, cheat or steal, then why do people lie, cheat or steal? Economists might say people conduct a rational analysis to assess the benefits of lying, cheating or stealing relative to the costs of getting caught or having a guilty conscience and will behave inappropriately when the benefits of doing so outweigh the costs. Psychologists might look to the internalized norms and values of people and say they will lie, cheat or steal when their internal value systems become corrupted. But what if people maintain a strong internal value system but still lie, cheat or steal? Is it possible for me to behave dishonestly and still consider myself an honest person? The question is not trivial. Consider these variations:

I see myself as a person dedicated to healthy eating and exercise but who routinely (over)indulges in sugary and unhealthy foods.

I see myself as a person who values education and a growing intellect but who routinely watches too much television or plays too many games on a smartphone or tablet.

I see myself as a person who is fair and impartial but who regularly denigrates the statements of persons whose political views differ from mine.

I see myself as a person who treats others with dignity and respect but who often hurls insults at political opponents because its just “politics”.

I see myself as a religious person but who rarely attends church or reads scriptures and prays.

I see myself as a competent and careful blogger but who infrequently adds new posts to his blog or reads and comments on the blog postings of others.

A study published in 2008, entitled The Dishonesty of Honest People: A Theory of Self-Concept Maintenance, provides a compelling insight here. According to the authors of the study, people have and want to maintain a particular image of themselves, such as being a person of honesty. A problem arises when people face a decision that can produce a short-term gain but require them to act in a way that is contrary to their self-image or self-concept. When people are torn by competing motivations–“gaining from cheating versus maintaining a positive self-concept as honest”–they will solve this dilemma “by finding a balance or equilibrium between the two motivating forces, such that they derive some financial benefit from behaving dishonestly but still maintain their positive self-concept in terms of being honest.” But how? The trick is to define the behavior in a way that still allows them to maintain the desired self-concept. The authors describe this as malleability. The more malleable the situation, the more likely people will behave inappropriately while still maintaining a positive self-concept. Consider this variation of an example provided by the authors: I might be able to justify taking a $1 notebook from my friend, even if I cannot justify stealing $1 from his wallet to buy the notebook myself. The malleability here comes from my defining this action as “borrowing” rather than stealing, or thinking that because I let my friend use something of mine previously, then my taking the notebook is okay because “this is what friends do.” Of course, there is limit to this rationalization. I might be able to rationalize taking the $1 notebook but probably not taking my friend’s $20,000 car. Thus, malleability and limits set the boundaries within which rationalization occurs.

The scholars conducted experiments to see how people behave when given opportunities to cheat and to redefine how they see themselves. The experiments confirmed their expectations. As summarized by the authors, “people who think highly of themselves in terms of honesty make use of various mechanisms that allow them to engage in a limited amount of dishonesty while retaining positive views of themselves. In other words, there is a band of acceptable dishonesty that is limited by internal reward considerations.” In other words, I can lie as long as I can convince myself it is really not lying. If I can do this easily, then good for me. I get my lie and self-worth too. If I cannot do this easily, then I’ll resign myself to being honest.

So, if we want to reduce dishonesty in society, we need to limit the malleability of contexts in which people might lie, cheat or steal. In other words, we need to make it harder for people to rationalize their unethical behavior that allows them to maintain a positive self-concept even though they are doing wrong. In their study, the authors were able to do this by asking the subjects of their experiments to write down as many of the Ten Commandments as they could remember. Perhaps this means we should be promoting greater religious observance in society.

Lying is still lying, regardless of what we want to call it. Cheating is still cheating. And stealing is still stealing. All our wrong. We need to call it what it is.

Phew! That was a lot of work creating this post. Time for this healthy exerciser to take a chocolate break.



It’s best to be far on the right side of the line, not close to it

I am reading Maureen O’Hara‘s book, Something for Nothing: Arbitrage and ethics on Wall Street. Professor O’Hara is a financial economist at Cornell University. In her book she explains how modern finance works and what led to many of the contemporary ethical scandals of Wall Street. I’ll probably have more to say about the book after I finish it, but I enjoyed this tidbit:

Some people want to stay as close to the legal line as possible, while remaining on the “right” side of that line. However, Professor O’Hara says, “laws reflect moral standards, and over time the laws change to reflect what is acceptable to society. … But that also highlights why a strategy of being exactly on the line of legality is a poor business practice; when the lines shift, you go from being a weasel to being a felon, even when you have done nothing differently.”

Adopting an ethical standard is a higher one than merely following the letter of the law. So being on the right side of the ethical line, even close to it, can keep you from falling into the “weasel” category. But adopting a strategy of staying close to the ethical line can cause problems. There are differing ethical perspectives, and these don’t always agree or even provide clear-cut answers. Therefore, if you really want to follow a strategy of ethical conduct, it is best to stay as far away from the ethical line as possible–if there really is such a thing as an ethical line anyway.

Prisoner’s Dilemma in the classroom

The Prisoner’s Dilemma is a model that illustrates a conflict between the interests of individuals and the interests of those individuals as members of a collective or group. In most versions of the game, two or more persons can cooperate and receive a collective reward that is greater than the sum of individual rewards they could earn if they choose not to cooperate. The incentives of the game are such that the persons have an individual incentive not to cooperate, thus making them collectively worse off had they chosen to overlook their individual interests and instead think as a group. The game is famous in economics and other social sciences. Wikipedia has a lengthy discussion of the game, its refinements and implications here.

Even though the Prisoner’s Dilemma has been around for decades it is still a fun game to play with students. In my microeconomics class today I offered the following opportunity for the class to earn extra credit:

“You can earn extra credit by selecting the amount of extra credit points you want. However, if more than 4 of you select option B, then the entire class will receive 0 extra credit points.”

Option A was to earn 1 point extra credit.
Option B was to earn 4 points extra credit.

I use a web-based student response system so that students could register their choice on their cell phones and I would see the results immediately. Not surprisingly, of the 180 in class today, 10 chose option B, leading to no extra credit for the class. When I gave the class a chance to do it over again and even talk to each other, the number who chose option B increased to 17.

The incentives to choose option B are pretty strong here — getting 3 more extra credit points than one could get by cooperating with everyone else in the class and getting just 1 point. Even when I changed the payout structure so that option A gave 3 points and option B 4 points, there were 6 students who still chose option B, thus negating the extra credit opportunity for everyone.

What I find interesting here is not that there were some students who chose option B but that so many in the class chose option A. At least 90 percent of students were willing to forgo their individual interest of choosing option B in order to cooperate for the collective good.

In economics we teach that when people pursue their self-interest things will work out the best for everyone. But sometimes they don’t. Sometimes the pursuit of one’s interests can be damaging to others and the collective whole. Why does self-interest work in some cases but not in others? And when the incentives for collective action are not ideal, what can we do to encourage or promote more cooperative thinking and behavior?

Russell Crowe, in the movie A Beautiful Mind, played the mathematician John Nash who developed this idea. He explains the problem and solution nicely in this clip from the movie.

I asked my class these questions and got a lot of interesting responses. Because the student response system I use saves student responses, I can list some of them here:

“Anonymity is the problem”

“People only act in their self interest and don’t want to work as a whole for the better of everyone”

“so basically we need to be communists in order for this game to work”

“People are greedy”

“people think they deserve it more than others”

“Throw tomatos (sic) at the people who chose B”

“you do what you have to do”

“Take away the second option”

“build a wall make the people who picked B pay for it”

“this game don’t work cause we got more than 4 selfish people in class”

“Not as many laws and restrictions”

“Because people think that everyone else will pick A and that they will end up getting more when in reality they hurt everyone else”

“Need more communication and honesty”

“Sometimes selflessness is the answer”

“If people weren’t greedy then we would at least be able to get one point extra credit”

“All it takes is one bad egg to ruin it for everyone”

“punish those who answered B”

“Communicate with others to achieve extra credit”

“Put people who choose B in jail”

“freshmen think that 1 point if extra credit is actually going to influence their grade”

“do your work maybe you wouldn’t need to pick B”

Resolving the Prisoner’s Dilemma requires careful structuring of the way people interact and enforcement of the formal rules and informal norms we develop to promote cooperation. It also requires that people exercise self-restraint in the pursuit of their self-interest, since no rules or monitoring mechanisms are perfect. We wouldn’t (or shouldn’t) want to live in a society where such rules are perfectly enforceable. How to do this so as to protrct one’s freedom to choose makes for a fun discussion in class.

In the end I gave everyone in the class who chose option A in the last round of the game (in which 3 points were possible) the 3 points extra credit. I don’t know if the class learned much, but I hope they left feeling better about their teacher.



Bayesian analysis, probabilities of accidents and the Monty Hall Problem

In my research methods class today we talked about the difference between Classical and Bayesian analysis. In Classical analysis you use available statistics to make inferences about something, while in Bayesian analysis you use other information to interpret available statistics.

Consider the following silly but clarifying example: Suppose I show you a clear bowl with 5 red balls and 5 blue balls, and suppose I ask you to close your eyes and pull out a ball. What is the probability that you will successfully pull out a red ball? A classical statistician will say, correctly, 50 percent, since 5 of the 10 balls are red. However, a Bayesian may say something different if he knows something about who put the game together. For instance, if the Bayesian knows that I am a jokester and have a history of gluing red balls to bowls, then the Bayesian will say the probability that you can “successfully” pull out a red ball will be much less than 50 percent.

Here is another perhaps more relevant example: Suppose 60 percent of all vehicle accidents involve drivers using cell phones. Can we conclude that there is a greater than 50 percent chance that someone using a cell phone while driving will be in an accident? A Classical thinker may conclude “yes,” since more than half of all accidents involve cell phones. Politicians think this way, too, because they promote laws that restrict our ability to use cell phones while driving using these kinds of numbers. However, a Bayesian will want to consider other information, such as the percent of all drivers in accidents and the percent of cell phone use by drivers not in accidents.

For example, if 5 percent of drivers are in an accident on any given day and if the percent of non-accident drivers who use cell phones while driving is 30, then what is the probability that someone will be in an accident given that they are using a cell phone? It turns out to be a lot less than 60 percent–about 9.5 percent. (The formula is (0.05)(0.6)/[(0.05)(0.6)+(0.95)(0.3)] for anyone who wants to check my math.) Of course, to make the point that one should not use cell phones while driving, we should calculate the probability that someone will be in an accident given that they are not using a cell phone. This is less than 3 percent. (The formula is (0.05)(0.4)/[(0.05)(0.4)+(0.95)(0.7)].) So, using a cell phone while driving almost doubles the chance of being in an accident, while not using a cell phone decreases the likelihood of being in an accident by about 40 percent. Clearly one is better off not using a cell phone while driving. Wikipedia has a useful discussion of the math behind the analysis here.

These numbers are hypothetical. I do not have actual data on the percent of cars in accidents and the percent of drivers using cell phones, etc. The point is that we can obtain a better analysis by considering all relevant information carefully. That is, it is not always correct to draw conclusions from data we have presented to us. Moreover, biases can impair our ability to understand what is going on around us, unless we are careful in how we draw conclusions. We see the wisdom in this from observing how people behave during presidential elections. A person’s bias in favor of a particular candidate seems to make him or her impervious to evidence that the candidate is a lying and immoral buffoon.

This type of analysis is also helpful when considering medical tests. If 2 percent of the population has a disease and the doctor gives you a diagnosis that you have the disease, then what is the probability you really have it given that the doctor said you did? The answer depends on how accurate the medical test is. For example, if the medical test is accurate 95 percent of the time, then the chance you have the disease is only about 30 percent. In contrast, if the medical test is accurate only 80 percent of the time, then the chance you have the disease is really less than 8 percent. In either case, I would get a second opinion.

85-doorsWe had fun with this example in class: Suppose you are on the game show “Let’s Make a Deal.” Monty Hall, the show’s host, shows you three doors, A, B and C. Behind one is a new car, behind the other two are goats. You are asked to pick a door. You pick door A. Monty opens door B to reveal a goat and then offers to allow you to switch to door C or stay with your choice of door A. Should you switch or stay? Someone asked Marilyn vos Savant, a woman listed in the Guinness Book of World Records as having the highest IQ, this question. She gave her answer in 1990 in a Parade magazine column. It generated thousands of letters, many from PhDs saying she was wrong. Her column and responses are here. It’s funny to read the reactions of so-called academics. Answer the “stay or switch” question first before reading her response. To play the game to convince yourself that she was right, see this online app here. Play it many times by staying and see how often you win. Then play it many times by switching each time to see how often you win. You’ll find that the probability of winning the car doubles from one-third to two-thirds by switching. There’s also an official “Let’s Make a Deal” website.

Given the choice between watching “Let’s Make a Deal” and presidential candidates debate, I’ll place my odds on the game show.