The Why Axis: Hidden Motives and the Undiscovered Economics of Everyday Life (3 page)

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.

We
³
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.