by Gneezy, Uri
THE
WHY
AXIS
THE
WHY
AXIS
HIDDEN MOTIVES AND THE UNDISCOVERED
ECONOMICS OF EVERYDAY LIFE
URI GNEEZY
AND JOHN A. LIST
With a Foreword by STEVEN D. LEVITT
coauthor, Freakonomics and SuperFreakonomics
PublicAffairs
New York
Copyright © 2013 by Uri Gneezy and John A. List.
Foreword Copyright © 2013 by Steven D. Levitt.
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Library of Congress Cataloging-in-Publication Data
Gneezy, Uri.
The why axis : hidden motives and the undiscovered economics of everyday life / Uri Gneezy and John A. List ; with a foreword by Steven D. Levitt.
pages cm
Includes bibliographical references and index.
ISBN 978-1-61039-312-6 (e-book) 1. Economics—Psychological aspects. 2. Motivation (Psychology)—Economic aspects. I. List, John A., 1968-II. Title.
HB74.P8G56 2013
330.01'9—dc23
2013024592
First Edition
10987654321
For our most important field
experiments—our amazing children:
Annika, Eli, Noah, Greta,
and Mason
Noam, Netta, and Ron
CONTENTS
Foreword by Steven D. Levitt, coauthor of Freakonomics and SuperFreakonomics
INTRODUCTION
Getting Beyond Assumptions.
What Makes People Do What They Do?
CHAPTER 1
How Can You Get People to Do What You Want?
When Incentives (Don’t) Work and Why
CHAPTER 2
What Can Craigslist, Mazes, and a Ball and Bucket Teach Us About Why Women Earn Less Than Men?
On the Plains Below Kilimanjaro
CHAPTER 3
What Can a Matrilineal Society Teach Us About Women and Competition?
A Visit to the Khasi
CHAPTER 4
How Can Sad Silver Medalists and Happy Bronze Medalists Help Us Close the Achievement Gap?
Public Education: The $627 Billion Problem
CHAPTER 5
How Can Poor Kids Catch Rich Kids in Just Months?
A Voyage to Preschool
CHAPTER 6
What Seven Words Can End Modern Discrimination?
I Don’t Really Hate You, I Just Like Money
CHAPTER 7
Be Careful What You Choose, It May Be Used Against You!
The Hidden Motives Behind Discrimination
CHAPTER 8
How Can We Save Ourselves from Ourselves?
Using Field Experiments to Inform Life and Death Situations
CHAPTER 9
What Really Makes People Give to Charity?
Don’t Appeal to People’s Hearts; Appeal to Their Vanity
CHAPTER 10
What Can Cleft Palates and Opt-Out Boxes Teach Us About People’s Reasons for Giving to Charity?
The Remarkable Phenomenon of Reciprocity
CHAPTER 11
Why Is Today’s Business Manager an Endangered Species?
Creating a Culture of Experimentation at Your Business
EPILOGUE
How to Change the World . . . or at Least Get a Better Deal
Life Is a Laboratory
Acknowledgments
Notes
Index
FOREWORD
Sometimes the things that should be completely obvious turn out to be the hardest ones to see.
That was certainly the case for me as a young economist in the late 1990s. It was an exciting time in the economics world. I had the good fortune to be spending my time at Harvard and MIT, two revered institutions that were at the epicenter of the new wave in economics.
Historically, economics had been a discipline dominated by theory. The big advances had mostly come from impossibly smart people writing down complicated mathematical models that generated abstract theorems about how the world worked. With the explosion in computing power and big data sets, however, the economics profession was transformed in the 1980s and 1990s. Empirical research—the analysis of real-world data—increasingly became the focus of many economists. It became respectable for a young economist like me, having figured out I was not nearly smart enough to come up with fancy theoretical insights, to spend my time toiling in the data looking for interesting facts.
The big challenge then (and now) was how to figure out whether a relationship between two variables was truly causal, or whether it was merely correlation. Why did it matter? If a relationship was causal, then there was a role for public policy. If a relationship was causal, then you learned something important about how the world worked.
Causality, however, is very hard to prove. The best way to get at causality is through randomized experiments. That is why, for instance, the Food and Drug Administration requires randomized experiments before approving new drugs. The problem was that the sort of laboratory experiments used to test drugs weren’t all that applicable to the kinds of questions economists like me wanted to answer. Consequently, we spent our energy trying to find “accidental experiments”—quirky things that happen more or less by chance in the real world that vaguely mimic randomized experiments. For instance, when a hurricane happens to devastate one city and leave another untouched, one might think that it was more or less random which city got hit. Or consider the legalization of abortion with the Supreme Court’s Roe v. Wade decision in 1973. The likelihood a fetus got aborted changed dramatically with that decision in some states, but not in others. A comparison of life outcomes for babies born around that time in different states tells us something about the impact of the policy and maybe also about deeper questions, like how being born unwanted affects a person’s life.
So that is how I, along with a lot of other economists, spent my days: looking for accidental experiments.
Everything changed for me, though, when I one day met an economist a few years younger than me. He had a very different pedigree than my own. He hadn’t attended Harvard or MIT, but rather, had received his undergraduate degree at the University of Wisconsin–Stevens Point and then his Ph.D. from the University of Wyoming. His first job teaching was at the University of Central Florida—not the most prestigious place.
His name was John List. Unlike me and the other big-name economists, he was pioneering something that in retrospect was completely sensible and obvious: running randomized economics experiments in the real world. But for some reason, almost no one else was doing it. Somehow, because of the traditions of the profession and what the economists before us had done, it just never occurred t
o us that we could run randomized experiments on real people in real economic settings without these people even knowing they were part of an experiment. It was a truck driver’s son showing us the way.
Think about prejudice, for example. If a person acts in a biased way toward another, everyone has always assumed such a person is racist, sexist, homophobic, or what have you. But nobody has ever teased apart the underlying motives in behaviors that appear, on the surface, to be based on dislike, distaste, or flat-out hatred of other people in the way that John List and Uri Gneezy have. Their experiments—which they describe in Chapters 6 and 7—have shown that the hidden motive behind discrimination is not always hatred, but it is sometimes simply to make more money.
To me, the sign of true genius is the ability to see things that are completely obvious but to which everyone else is blind. And by that measure, John List and Uri Gneezy are definitely geniuses. They are true trailblazers in one of the greatest innovations in economics of the past fifty years. This book is their story of how the experimental approach, in the hands of incredibly thoughtful and creative researchers, can shed light on just about any problem under the sun. The only limit is the imagination of the person designing the experiment.
Not only are randomized field experiments (as John and Uri’s approach has come to be known) a powerful tool, it turns out they can be a whole lot of fun, too, as you will soon discover. I hope you enjoy reading this book as much as I have.
—Steven Levitt
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 som
ething 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):