The Why Axis

          INTRODUCTION

       Getting Beyond Assumptions

          What Makes People Do What They Do?

The sign on the road leading to the city of Shilong in the Khasi hills of northeast India had a puzzling message: “Equitable distribution of self-acquired property rights.” We asked Minott, our driver, what it meant.

Minott had met us at the Guwahati airport after the long flight from the United States. He was an informative, enjoyable guide as we traveled over impossible roads through these beautiful, quiet villages situated in ginger-scented green hills, surrounded by lush rice and pineapple fields. A short, skinny, grinning twenty-eight-year-old, full of wound-up eager-to-please energy, Minott spoke seven dialects and reasonably good English, and he won us over immediately.

“I do not work in the rice fields, like most men of my tribe,” he told us proudly. “I work as a translator. And a driver. And I operate a gas station in my sister’s house. And I trade goods at the market. You see! I work very hard!”

We nodded in agreement. He certainly seemed like a natural-born entrepreneur. In the United States, Minott would undoubtedly have operated a successful franchise, or even, given the blessing of a good education, a Silicon Valley–style software startup.

But Minott’s life was constricted. “I can’t get married,” he sighed. When we asked why, he explained that, as a Khasi man, he would have to live either with his sister or with his wife’s family, and he did not want to do that. He wanted to have a house of his own, but this was impossible in his society. He was not allowed to own property. Many of the things he wanted to do required his sister’s permission, because in the matrilineal Khasi society, women hold the economic power. Even the most able, enterprising men, such as Minott, are relegated to second-class citizenship. The sign on the road, Minott explained, was part of a nascent men’s movement, as the men in Khasi society began to articulate their resentment over being treated as “breeding bulls and babysitters.”¹

Here was a parallel universe—one we believed might help us solve one of the most vexing economic questions in Western society: Why are women less economically successful than men?

If you’re like most people, you have an opinion about the reasons why gender inequality—and other problems such as discrimination, the education gap between rich and poor students, and poverty—exist. But how do you really know why? Anecdotes? Gut feelings? Introspection?

As you’ll see, this book is about moving beyond anecdotes and urban legends. In these pages, you will be our co-explorer, discovering why everyday people behave as they do. To get at the real underbelly of human motivation, we run experiments in the wild, where we can observe people going about their business in their natural environments when they’re not aware that they’re being observed. Then we crunch the results to come up with conclusions that will change the way you view humanity, and yourself. Our unique approach culls new lessons from observations of everyday life, yielding an understanding of the incentives that motivate people—whether these take the form of money, social recognition, or something else.

So how do we learn about underlying motivations and the right incentives? How do we get at the real underbelly of human motivation? For the last twenty years, we’ve left the confines of our offices to try to figure out what motivates people to do what they do in their natural environments. Our reason for doing this is simple: if you put a bigot in a laboratory where he knows he’s being observed, he won’t act like a bigot—he’ll say what he thinks the scientist wants to hear, or he’ll act the way he knows society expects him to because he is motivated to behave as the researcher wishes. But if you watch his behavior in his own neighborhood bar as someone “different” walks in (or give him an opportunity to converse with someone who looks and talks like a boorish Borat), you’ll witness simple discrimination.

For that reason, our research has taken us on a journey from the foothills of Kilimanjaro to California wineries, from sultry northern India to the chilly streets of Chicago, from the playgrounds of schools in Israel to the boardrooms of some of the largest corporations in the world. Venturing out into the real world has provided us with a unique understanding of what’s really going on with people.

By observing the way people behave in everyday markets, we can better understand their motives. One of our key discoveries is that self-interest lies at the root of human motivation—not necessarily selfishness, but self-interest. These may seem like the same thing, but in fact they are very different. This is a key insight, because once we establish what people really value—money, altruism, relationships, praise, what have you—then we can more accurately figure out the triggers or mechanisms needed to induce them to get better grades at school, stay out of trouble with the law, perform better on the job, give more to charity, discriminate less against others, and so on.

How did we develop this approach? As a sports-card dealer in the 1980s, John would often experiment with different negotiation tactics and pricing policies to discover what worked best. And later on, as a sports-card-dealing undergraduate studying economics at the University of Wisconsin–Stevens Point, he often wondered whether he could learn something important about economics by using field experiments. Could the laws of economics be tested in the real world? Thousands of miles away, Uri was wondering how to incentivize employees who collect donations for a charity. In the process, he discovered that when motivating volunteers, the traditional pay-per-performance model can actually be worse than not paying them at all.

In the past, economists have been skeptical about running controlled field experiments. For an experiment to be valid, everything else but the item under investigation has to be held constant. This is how researchers test their theories: if they want to determine whether Diet Coke causes cancer in rats, they will hold “other things equal” and only vary the amount of Diet Coke consumed. Same air, same light, same type of rat. For years, economists believed that there was no possible way to perform such tests in the “real world” because they could not easily control other important factors.

But in reality, the economic world is not a chemistry test tube—there are billions of people and thousands of firms. At odds with received economic wisdom, we will show that if you have “dirtiness”—that is, if you are looking at the way things work in an uncontrolled, quirky, real world—then randomized field experiments yield real answers. In fact, field experiments have become one of the most important empirical innovations in decades. Our methodology permits us not only to measure something that is happening but also to ascertain why it happens. We offer examples of the way our methodology can solve many of the world’s most vexing economic problems, including the following:

       •  Why, in most modern economies, do women still earn less than men for equal work, and occupy fewer of the top management positions?

       •  Why are some people charged more than others for products and services?

       •  Why do people discriminate against one another, and how can we get them to stop—and avoid it ourselves?

       •  Despite the fact that the United States spends far more on public education than most other developed countries, the high school dropout rate is higher than 50 percent in some places. Do expensive, faddish educational programs make any difference at all? How can we close the education gap between rich and poor students in a cost-effective manner?

       •  How can businesses innovate more creatively, improve productivity, and create more value, opportunities, and jobs in an increasingly global, competitive world?

       •  How can nonprofit organizations encourage more people to give back to society, and how can you make your favorite charity more effective?

You may think that these questions have little or nothing in common. But from where we sit, all of these questions can be considered from an economic perspective—and all of them are amenable to simple economic solutions. Field experiments can unlock these solutions. It’s all a matter of understanding the right incentives and of figuring out what really makes people do what they do.

Correlation vs. Causality

People love to say, “This causes that,” whether we know it to be a fact or not. But in the absence of experimental data gathered in the real world, we are all pretty much talking through our hats when we infer causality this way.

Not long ago, with fellow University of Chicago economists Steve Levitt and Chad Syverson, we chatted with executives at a big and well-known retailer about how they could boost sales. A high-ranking marketing executive showed us the following picture in an effort to demonstrate that his company’s retail advertisements were effective in generating sales (for confidentiality purposes the numbers are changed, but the relationship is similar):

“This is the smoking gun,” he said proudly. “It shows a clear positive relationship between ads and sales. When we placed 1,000 ads, sales were roughly $35 million. But see how sales dipped to roughly $20 million when we placed only 100 ads?”

To see why the relationship between ad placements and sales might not be as clear-cut as the executive believed, take a look at a similar figure that we have produced:

This second chart shows two very different phenomena: the number of drowning incidents from 1999 to 2005, and the number of retail ice cream cone sales (in millions) from one of the biggest ice cream companies in the United States over the same time period. Of course, it’s shocking to see such a relationship between these two variables.

Parents persuaded by charts like this might believe that the correlation is causal, and never let their kids eat ice cream near open water. But, of course, there is a hidden third variable lurking in the background. In the summertime, people eat more ice cream and swim more. More swimming leads to more drownings. Even though people do eat more ice cream cones in the summer, eating ice cream doesn’t cause people to drown. Swimming does.

So what was the hidden variable lurking in the background of the chart the marketing executive showed us? We learned later that the retailer placed a lot of ads during the November and December holiday shopping season when, not surprisingly, the company sold a lot of products. This gave the illusion that ads and sales were related causally. But when we dug deeper into the data and took account of the fact of when the ads were placed, we found no causality in the data—just correlation. Consumers bought more products because of the holidays, not necessarily because of the retail ads.

Our world is beleaguered by mistakes like this. In cases where we think a causal relationship could exist, it’s easy to mistake simple correlations with causality. In so doing, we stand to waste a lot of money and effort for nothing. The problem is that the world is filled with complicated relationships, and it’s difficult to find true causal relationships.

Then there’s the current trend “big data.” By gathering mounds and mounds of data and observing the patterns, people using big data can draw interesting conclusions. Big data is important, but it also suffers from big problems. The underlying approach relies heavily on correlations, not causality. As David Brooks has noted, “A zillion things can correlate with each other, depending on how you structure the data and what you compare. To discern meaningful correlations from meaningless ones, you often have to rely on some causal hypothesis about what is leading to what. You wind up back in the land of human theorizing.”²

The other problem with big data is that it is so big that it’s hard to find your way in it. Companies have so much data that they don’t know what to look at. They collect everything, and then become overwhelmed because they have so many possible permutations of variables of interest that they really don’t even know where to start. Because our work focuses on using field experiments to infer causal relationships, and because we think hard about those causal relationships of interest before generating the data, we go well beyond what “big data” can ever deliver.

Fortunately, field experiments can provide the kind of hard data that citizens, educators, philanthropists, policy makers, and CEOs need in order to not only avoid making big mistakes but also to develop a better understanding of the people they are supposed to serve: What really motivates people and why?

What kinds of incentives cause people to do the “right” things? When do incentives in the form of punishments and sanctions steer people away from undesirable behaviors? And when do incentives just plain not work?

As economists, we clearly believe that there’s more to motivation than meets the eye, and that when one does find a causal relationship between variables, the implication can be profound. In fact, incentives are not simple blunt instruments. Hidden motives are actually very complex, and they don’t always operate the way we think they should. Until one fully understands what incentives motivate people, it is impossible to predict how new policies, or changes, will actually work.

In this book, we show the many ways that incentives can work to change ourselves, our businesses, our schools, and the world for the better; but before we try to apply them, we need to understand how these incentives change our hidden motives.

We³ are also fueled by our personal interests and passions. For example, consider how we got interested in the question: Why do people discriminate against each other? It wasn’t just because discrimination hurts society in general, or because it is a murky issue that has vexed researchers for years. We chose to study it because we, and our loved ones, have been on the receiving end.

Uri will never forget the nightmarish stories his father, Jacob, a Holocaust survivor from Budapest, told him about what happened to his tight-knit neighborhood. When the Nazis took over Hungary and the Holocaust swept into Budapest in 1944, Jacob was no longer allowed to work. His mother, Magda, managed to move the family into one of three safe houses run by the Swedish diplomat Raoul Wallenberg outside the Jewish ghetto. But the houses turned out to be not so safe after all.

One night, members of the pro-Nazi Arrowcross party flushed their Jewish neighbors from their homes, marched them to the Danube river, and shot every man, woman, and child. The next night, the same thing happened to the people in the second building. On the next night, Uri’s father and his family were expecting to go to a similar destination. But instead the Nazi sympathizers forced them at gun-point into the ghetto, where Magda fended off the family’s starvation by fighting over the decidedly un-Kosher meat of dead horses. They escaped death by sheer luck. Many years later, not far from the sites of those roundups, Uri lectured at Budapest University—the same institution from which his grandfather was summarily ejected on the basis of his religion. Uri could not help shuddering as he stood at the lectern.

When we think of discrimination, these are the types of ugly, virulent prejudice that we think about. But John faced a much different kind of discrimination when he entered the job market as a newly minted Ph.D. in 1995. Although he applied to more than 150 academic jobs and had completed several field experiments, he was given only one interview. He later learned that other nearly identical applicants received thirty interviews from just forty or so applications. The main difference between John and these other applicants was that John received his Ph.D. from the University of Wyoming, whereas they had received theirs from “brand-name” schools like Harvard and Princeton. Employers were using that bit of information to screen their applicants—effectively discriminating between the “haves” and the “have-nots.”

You, too, have likely experienced this type of discrimination—maybe without even knowing it. And like most people, you may think that human beings treat each other unfairly because we’re simply wired that way. It’s easy to understand why most of us assume the worst of each other. All around us, every day, accusations of racism fly. President Obama’s supporters accuse his detractors of racism and vice versa; bloggers, news organizations, politicians, and other public officials routinely jump to conclusions about people’s motivations before the facts are out.

What does all this have to do with economics? The answer is this: rather than accept that humans are hardwired to be racists or bigots, we wanted to learn more about the underlying motivations for why people actually discriminate. Clearly discrimination has serious, long-term effects on people’s lives, and we wanted to understand how discrimination works in real markets, where people function every day. What causes it? Is it driven by deep-seated prejudice alone, or is there another explanation?

Using various field experiments in real markets, we have learned that the kind of discrimination that John faced is today much more common than the kind that Uri’s family faced. Unabashed hatred and pure animus are not as pervasive as most of us believe. As a result, if you really want to end discrimination, don’t just focus on the ugly, racist side of things—that’s the wrong culprit. Instead, consider the economic incentive for the discrimination, and then look through the microscope. As it turns out, most cases of modern-day discrimination are caused by people or companies trying to increase their profits.

But that does not mean that outright hatred is dead. As it turns out, people often discriminate in a bigoted way when they perceive others as having a choice in the matter. As Archie Bunker, the racist protagonist of the old television sitcom All in the Family, asked Sammy Davis Jr. in one famous episode: “Your bein’ colored, now, I know you had no choice in that. But whatever made you turn Jew?”⁴

These insights turn out to be important not only for society, but also for you. Furthermore, policy makers cannot begin to battle something that they don’t understand. If you are someone who designs laws, understanding how not to be discriminated against is invaluably important.

Another issue that really bothered us was the gender gap in labor markets. Women still earn less than equally skilled men do, and are still too scarce in boardrooms and the C-level offices of companies.

Between us, we have four smart daughters (and four beautiful sons). Like you, we want all of our kids to get a fair shake as they grow up, go to college, and compete for jobs. But from their earliest years, we noticed that fair shakes weren’t always happening for our daughters. Why did one of our girl’s teachers seem to be telling her that she wasn’t as good at math as the boys, even though it was clear that she had mathematical talent? Why did the sports coaches at her school berate the boys in her class to “stop playing kickball like a girl”? And why were Uri’s two daughters—one competitive, one not so much so—so different?

We both wondered whether our daughters would be able to compete for great schools and great jobs, or whether they would be discouraged and sidelined along the way. After combining our observations from their early days in school with the facts about the great differences between men’s and women’s ability to command high salaries, climb the corporate ladder, and hold prominent public positions, we wondered if differences in competitiveness could help to explain the gender gap. So we asked a simple question: Are women different than men in terms of competitiveness? After finding important differences, we asked the age-old question: Is this difference in competitiveness because of nature or nurture?

To find answers, we boarded planes, helicopters, trains, and automobiles and went to the far corners of the earth to investigate gender competitiveness among the most and least patriarchal societies on the planet (that’s how we met Minott). The results of our research come down strongly on the side of nurture. In the right environment—one in which women are not deterred from competitive situations and are accepted by their society as powerful individuals—women grow up to be just as competitive as men, and sometimes even more so. This has important implications for our daughters and yours, and for policy makers who want to reduce the gender gap in labor markets. If you set the incentives correctly, the gender gap can be reduced drastically.

Another question we’ve explored is: How can we get people to donate more money to charity? Beyond our desire to be good citizens, we each had selfish reasons for our curiosity.

For his part, John has been interested in the economics of charity since he was a wet-behind-the-ears professor at the University of Central Florida, where he discovered that an integral part of our economy—the charitable sector—was largely driven by anecdotes and outdated rules of thumb devoid of scientific validation. Along the way, he came to know Brian Mullaney, the founder and CEO of Smile Train and WonderWork.org—whose ubiquitous magazine ads and direct-mail envelopes appeal for donations that can correct cleft lips and palates (and, through WonderWork.org, other maladies) with a simple surgery.

A large-scale field experiment touching roughly 800,000 direct-mail recipients revealed something about giving that no one would have guessed: allowing people to check a box saying “never contact me again” actually lead to higher levels of gifts, not lower. Many fundraising experts thought the idea was crazy; why on earth would any charity invite people to stop contributing? But as it turned out, people loved it. We raised much more money using the opt-out rather than the standard treatment, and only 39 percent of recipients opted out. Smile Train and WonderWork.org ended up saving money on postage, because they only needed to re-mail to those who were interested in giving in the future. It was a true win-win.

For his part, Uri became intrigued by the idea of getting people to give more to charity while experimenting with a new pricing mechanism at various companies—“pay what you want.” Under pay-what-you-want pricing, a company tells its customers that they can have the goods or services they need for any price they set (including $0). We were able to convince Disney to test this new and unusual pricing mechanism in one of its large theme parks. We found that when a charitable donation is combined with pay-what-you-want pricing, people pay a lot—much more, in fact, than they do according to the traditional pricing models.

And, as we discovered, human beings have more complicated and, yes, more complex reasons to give than simple altruism. When we looked at all kinds of techniques—door-to-door campaigns, direct-mail solicitations, matching grants, and so on—we found out what works best in setting the right incentives and convincing people to open their hearts and wallets. As you will see, a running theme throughout the book is this: once we discover what people value, then we can design useful policies that influence their behavior and induce change.

Here’s another dilemma that has grabbed us: How can you use incentives to keep kids in school and curtail youth gun violence?

This question is anything but abstract. Public schools in some areas of Chicago have horrendous attrition rates, in some cases as high as 50 percent, and one out of every thousand public school student gets shot. When the mayor of Chicago Heights asked John for some help, John responded as any good citizen would—and he brought the tool kit of an economist to the job. The large-scale experiments we describe in this book—the first of their kind anywhere in the country—are demonstrating that certain kinds of incentives, offered in the right way, can go a long way toward improving student performance. They can save lives, too.