protects people entering marriage from the potential negative effects of a marriage breaking up as a result of their own actions. By offering this option, a spouse discouraged in a marriage could easily dissolve the contract without facing the financial or other penalties. This offers an easy way out.

The introduction and wide acceptance of no-fault divorce has affected the rates of marriage and divorce and the distribution of outcomes after a divorce. Robert Rowthorn has written about many of the observed changes. For example, women with children have experienced a decline in their standard of living following a divorce. Some estimate the decline to be as much as 36.6 percent. An econometric study finds that eliminating fault also led to an increase in spousal abuse, effectively reducing the penalty for such abuse. It also led to greater number of total working hours (both domestic and outside the home) for women, who now had greater need to insure against the possibility of abandonment and the reduced payout from such a dissolution of their marriage.

In every case, the partner who initiates the divorce is better off under no-fault divorce laws because the initiating spouse minimizes his or her initial investment in the marriage he or she is reluctant to continue, and more importantly because the initiating spouse faces no penalty after the end of the marriage for the reduced investment of time, effort, or money that led to the eventual breakup. Moreover, marriage rates have declined and divorce rates have increased. Over time, it is apparent that perceptions of marriage and the ability one has to trust one’s spouse have changed substantially. Thus, it is clear that whereas trust and reciprocity have some behavioral foundations, they can also be substantively affected by social norms, incentives, and institutions. In this case, although trust may be a naturally occurring behavior, having the ability to punish fault can create substantial benefits for both parties.

Trust and Distrust

It has often been observed that trust is difficult to build but very easy to destroy. Years and years of good-faith behavior can all be overshadowed by a single visible indiscretion. This is true in many contexts. Paul Slovic, in discussing the public trust of scientists and scientific research, outlined several principles that characterize the creation and destruction of trust. His principles focus on how media reporting on scientific findings can lead to trust or distrust of science in general, but they can be applied more widely. The principles Slovic outlines are based on empirical research, but the principles may rightly be called working hypotheses, because none has been proved in a general setting. There are four principles.

Trust-destroying events are more visible or more noticeable than trust-building events. In the case of scientific misconduct, media seldom report on incidents of well-executed and valid methods. Alternatively, if the media discover a scientist has fabricated data or altered results of an experiment, the event quickly becomes a front-page news story. The same is true more generally. Seldom does a friend bring up in casual conversation the integrity of a faithful spouse. However, a spouse who has been caught cheating becomes a topic of nearly all conversations for those in the know. This can work to make the trustdestroying event more prominent in decision making, much like availability bias.

Trust-destroying events carry more weight than trust-building events. In general, humans tend to believe that trust-destroying events are more representative of unobservable behavior than trust-building events. Thus people often respond to a visible breach of trust by assuming it is consistent with a broader and more-common set of behaviors.

People tend to believe sources of negative or trust-destroying news more than those that are trust-building. Sensational stories of politicians engaging in sexual harassment, betrayal of a spouse, or other ethical violations have a life of their own. These stories, once published, can plague a candidate throughout his or her career. Stories explaining the context of the behavior are often looked upon with skepticism. In other contexts, we might have a tendency to believe the rumormongers more than those sharing legitimate information.

Distrust is self-reinforcing. Once we have experienced a trust-destroying event, we often reduce contact with the person we no longer trust. For example, a spouse caught cheating might be expelled from the house. In this case, the opportunity to rebuild trust is diminished, much like confirmation bias. With fewer interactions, it is difficult to have the opportunity to create any trust-building experience.

Given this bias toward distrust, it is easy to see how public feuds or deep divisions between social or demographic groups can arise. Within the context of business, it is easy to lose customers after very minor customer-service issues. Customers who believe their trust has been betrayed might simply abandon their relationship with the company. Because trust is fragile, it is also extremely valuable both to the trustee and the truster.

Reciprocity

Notably, it is impossible to measure trust without also inducing some measure of reciprocity. Recall that to measure trust, one person must give another person a decision that will affect both persons’ outcomes. Much like the trust game, to observe trust by the sender we must offer the second player an opportunity to behave opportunistically or reciprocally. If the trustee does not have an incentive to behave opportunistically, then the first player need not rely on trust. For example, if the receiver is given a greater reward for returning more of the pot to the sender, then the sender need only rely on selfinterest and not trust. Reciprocity functions much like Rabin’s notion of fairness, the difference being that reciprocity is defined much more broadly as an in-kind response to the actions of others. Thus, if others are behaving in a way that appears kind, kindness is returned, whereas those behaving in a way that appears cruel are treated cruelly.

The subtle difference is that beliefs are not necessary to define kindness or cruelty, as in the definition of fairness. Ernst Fehr and Simon Gächter cite several examples that illustrate the point. A waitress who smiles at her customers receives more in tips than a waitress who does not smile. The smile does not necessarily make the customer better off, but it gives some subtle signal that the waitress is happy to be serving the customer. They also point to samples given out in supermarkets. Customers feel some social pressure to buy the product once they have tried a sample, even if they did not like it. These behaviors are based not on the notion that the supermarket or the manufacturer was being kind to them so much as the fact that they were given something and feel the need to reciprocate. Similarly, we have the urge to insult anyone who takes a dig at us. Discussions in the next section illustrate more clearly how reciprocity can differ from the notion of fairness.

In the trust game, a receiver might feel compelled to provide some return to the sender simply because the receiver has been given the opportunity for a larger return by the sender. Because trust cannot be measured without also eliciting the presence of reciprocity, it is difficult to define trust without appealing to reciprocity. If reciprocity is an innate behavior, it could be that trust is simply self-interest given the presence of reciprocity. In this case, trust is really just an expression of risk preferences given the probability of reciprocal actions. Neurological and biological research into trust behavior suggests that this is not the case. For example, some drugs affect trust behavior in the trust game but not risk behavior in risk games. The fact that this risk is based in social interactions with others appears to lead us to use different decision-making mechanisms than we would to judge, say, risks from weather damage. Scientists have even found systematic differences in trust behavior between people who have physiological differences in how certain chemicals are processed in the brain. Thus there is strong evidence that trust is its own behavior with its own decision mechanism.

As mentioned in Chapter 15, many use the terms fairness and reciprocity interchangeably. However, the definitions of each differ substantially among authors. In this book I have drawn a distinction between the two common concepts that are often referred to as either fairness or reciprocity and selected the names I felt were most appropriate. Students should take care to understand the terminology used by a particular author when proceeding further with their studies in this area.

EXAMPLE 16.6 Reciprocity as Distinct from Fairness

Reciprocity, as I have defined it, need not be equivalent to fairness. Fairness dictates that one rewards intentions to be kind and punishes intentions to be cruel. Alternatively, reciprocity rewards actions that are kind and punishes actions that are cruel. Consider that you are in a hurry and fall in traffic behind a car going 15 miles per hour under the speed limit. To make matters worse, you are driving in a no-passing zone. When passing is finally allowed, you zoom past the slow car and might have the urge to put the proverbial exclamation point on your action by yelling, staring, or gesturing at the driver. This is true even if it is clear the driver was completely oblivious to your time pressure. But if the driver were truly oblivious to your plight, fairness would not predict any particular punishment should be desired. However, a negative reciprocal act does not require malice on the part of the one being reciprocated. Certainly malice likely induces further reciprocal action. However, we often feel a desire to punish someone even for behavior that unintentionally damages us.

One good example of this comes from an upstate New York high school, where the school, in an effort to encourage better nutrition, decided to limit those purchasing a school lunch to only one ketchup packet. The senior class was so incensed that they put together a protest on graduation day. As each senior crossed the stage to shake the hand of the principal, the student placed a ketchup packet in his hand, leaving him with a pocket full of ketchup by the end of the ceremony. Clearly the principal was not seeking the destruction or harm of the class. Nonetheless, they felt compelled to reciprocate the actions of the school’s cafeteria staff by sending him a clear negative message. In this case, the school administrators most likely felt that they were helping the students by limiting their ketchup consumption. Nonetheless, the students believed punishment was in order.

The notion of punishing negligent or unintentional behavior is canonized in our legal system. For example, one who kills a person intentionally is charged with murder and potentially faces life in prison or even death. Alternatively, someone who kills another through negligence faces charges of manslaughter and could face a long prison sentence. Note that the unintentional acts are punished, but less severely. Moreover, penalties are often made explicitly contingent on not only how cruel the crime is but also on extenuating circumstances. Thus, one committing murder when the victim was engaged in aggravating the perpetrator might face a much easier sentence than one committing murder unprovoked. Although research into reciprocity and fairness is still developing rapidly, it appears that people may be motivated by both in the course of events.

EXAMPLE 16.7 Reciprocity as a Business Model

In the last half of the 1990s, a new business model emerged for the software industry: open source. Open source software is available free to all, which might seem to limit the ability of a firm to capitalize on the distribution of their software. Many open-source projects rely on programmers to contribute code or applications that will also be made available freely. These applications require substantial time to program and are given ostensibly on a volunteer basis. One might thus question how this could be a sustainable model of business, or even a good idea for programmers to give away their services. A more-recent example is the existence of crowdsourcing efforts. In this realm, a firm or individual invites volunteers to provide some particular service generally for free. For example, Wikipedia invites people to contribute articles for their online encyclopedia without remuneration. The articles are then edited, modified, and revised by members of the crowd. Again, what would motivate a skilled writer or one with specialized knowledge to contribute for free? Nonetheless, Wikipedia has become the most comprehensive source for general information available, and it is often the first place one visits to learn about a topic. Clearly, people with the necessary knowledge have been sufficiently motivated.

People contributing to unpaid efforts such as crowdsourcing or open-source coding do have the possibility of direct personal rewards. For example, an open-source programmer may be creating an application or improving the functionality in some way that is directly applicable to his or her own work. In other words, programmers might use the program themselves and thus benefit from it. Still, it would be possible to use the program and not distribute it to others for free. Additionally, people may be able to use such visible projects to signal their own skill, essentially advertising for future jobs. This certainly explains some of the most breathtaking contributions to open-source projects. Nonetheless, a large group of contributors cite the feeling of contributing to a community that likes to give back as their primary reason for contributing to open-source projects. According to Boston Consulting Group, around 29 percent of contributors consider the need to reciprocate as a primary reason for contributing open-source code. This is about as many as contribute to improve their status or for their own private benefit. Interestingly, software developers and programmers are some of the biggest users of open-source software.

Firms involved in open-source software are able to make money through the distribution of support, licenses, training, and other benefits. Additionally, you often find attached to the software license a plea for donations. Donations make up a key part of