The Why Axis: Hidden Motives and the Undiscovered Economics of Everyday Life
Read The Why Axis: Hidden Motives and the Undiscovered Economics of Everyday Life Online
Authors: Uri Gneezy,John List
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.
Published in the United States by PublicAffairs™, a Member of the Perseus Books Group
All rights reserved.
No part of this book may be reproduced in any manner whatsoever without written permission except in the case of brief quotations embodied in critical articles and reviews. For information, address PublicAffairs, 250 West 57th Street, 15th Floor, New York, NY 10107.
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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
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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
What Makes People Do What They Do?
How Can You Get People to Do What You Want?
When Incentives (Don’t) Work and Why
What Can Craigslist, Mazes, and a Ball and Bucket Teach Us About Why Women Earn Less Than Men?
On the Plains Below Kilimanjaro
What Can a Matrilineal Society Teach Us About Women and Competition?
How Can Sad Silver Medalists and Happy Bronze Medalists Help Us Close the Achievement Gap?
Public Education: The $627 Billion Problem
How Can Poor Kids Catch Rich Kids in Just Months?
What Seven Words Can End Modern Discrimination?
I Don’t Really Hate You, I Just Like Money
Be Careful What You Choose, It May Be Used Against You!
The Hidden Motives Behind Discrimination
How Can We Save Ourselves from Ourselves?
Using Field Experiments to Inform Life and Death Situations
What Really Makes People Give to Charity?
Don’t Appeal to People’s Hearts; Appeal to Their Vanity
What Can Cleft Palates and Opt-Out Boxes Teach Us About People’s Reasons for Giving to Charity?
The Remarkable Phenomenon of Reciprocity
Why Is Today’s Business Manager an Endangered Species?
Creating a Culture of Experimentation at Your Business
How to Change the World . . . or at Least Get a Better Deal
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 to 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.
