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Economics

ules

E N F THE

Dani Rodrik

W. W. NORTON & COMPANY

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1 2 3 4 5 6 7 8 9 0

To MY MOTHER, KARMELA RODRIK,

AND THE MEMORY OF MY FATHER, VITALI RODRIK.

THEY GAVE ME THE LOVE OF LEARNING AND THE POSSIBILITIES

FOR EMBRACING IT.

CONTENTS

Preface and Acknowledgments xi

INTRODUCTION The Use and Misuse of Economic Ideas

CHAPTER 1

CHAPTER 2

CHAPTER 3

CHAPTER 4

CHAPTER 5

CHAPTER 6

EPILOGUE

Notes 217

Index 233

What Models Do 9

The Science of Economic Modeling 45

Navigating among Models 83

Models and Theories 113

When Economists Go Wrong 147

Economics and Its Critics 177

The Twenty Commandments 213

PREFACE AND

ACKNOWLEDGMENTS

This book has its origins in a course I taught with Roberto

Mangabeira Unger on political economy for several years at

Harvard. In his inimitable fashion, Roberto pushed me to

think hard about the strengths and weaknesses of economics

and to articulate what I found useful in the economic method.

The discipline had become sterile and stale, Roberto argued,

because economics had given up on grand social theorizing

in the style of Adam Smith and Karl Marx. I pointed out, in

turn, that the strength of economics lay precisely in small-scale

theorizing, the kind of contextual thinking that clarifies cause

and effect and sheds light-even if partial-on social reality. A

modest science practiced with humility, I argued, is more likely

to be useful than a search for universal theories about how capi

talist systems function or what determines wealth and poverty

around the world. I don't think I ever convinced him, but I

hope he will find that his arguments did have some impact.

PR E FAC E A N D ACK N O WL E D GM E N T S

The idea ofairing these thoughts in the form of a book finally

jelled at the Institute for Advanced Study (IAS), to which I

moved in the summer of 2 0 1 3 for two enjoyable years. I had

spent the bulk of my academic career in multidisciplinary envi

ronments, and I considered myself well exposed to-if not well

versed in-different traditions within the social sciences. But the

institute was a mind-stretching experience of an entirely differ

ent order of magnitude. The institute's School of Social Science,

my new home, was grounded in humanistic and interpretive

approaches that stand in sharp contrast to the empiricist positiv

ism of economics. In my encounters with many of the visitors

to the school-drawn from anthropology, sociology, history,

philosophy, and political science, alongside economics-I was

struck by a strong undercurrent of suspicion toward econo

mists. To them, economists either stated the obvious or greatly

overreached by applying simple frameworks to complex social

phenomena. I sometimes felt that the few economists around

were treated as the idiots savants of social science: good with

math and statistics, but not much use otherwise.

The irony was that I had seen this kind of attitude before-in

reverse. Hang around a bunch of economists and see what they

say about sociology or anthropology! To economists, other social

scientists are soft, undisciplined, verbose, insufficiently empiri

cal, or (alternatively) inadequately versed in the pitfalls of empir

ical analysis. Economists know how to think and get results,

while others go around in circles. So perhaps I should have b een

ready for the suspicions going in the opposite direction.

xii

PR E FAC E A N D ACK N O WL E D GM E N T S

One of the surprising consequences of my immersion in the

disciplinary maelstrom of the institute was that it made me feel

better as an economist. I have long been critical of my fellow

economists for being narrow-minded, taking their models too

literally, and paying inadequate attention to social processes .

But I felt that many o f the criticisms coming from outside the

field missed the point. There was too much misinformation

about what economists really do. And I couldn't help but think

that some of the practices in the other social sciences could b e

improved with the kind of attention t o analytic argumentation

and evidence that is the bread and butter of economists.

Yet it was also clear that economists had none other than

themselves to blame for this state of affairs. The problem is not

just their sense of self-satisfaction and their often doctrinaire

attachment to a particular way of looking at the world. It is

also that economists do a bad j ob of presenting their science to

others. A substantial part of this book is devoted to showing

that economics encompasses a large and evolving variety of

frameworks, with different interpretations of how the world

works and diverse implications for public policy. Yet, what

noneconomists typically hear from economics sounds like a

single-minded paean to markets, rationality, and selfish behav

ior. Economists excel at contingent explanations of social life

accounts that are explicit about how markets (and government

intervention therein) produce different consequences for effi

ciency, equity, and economic growth, depending on specific

background conditions. Yet economists often come across as

xiii

PR E FAC E A N D ACK N O WL E D GM E N T S

pronouncing universal economic laws that hold everywhere,

regardless of context.

I felt there was a need for a book that would bridge this

divide-one aimed at both economists and noneconomists.

My message for economists is that they need a better story

about the kind of science they practice . I will provide an

alternative framing highlighting the useful work that goes on

within economics , while making transparent the pitfalls to

which the practitioners of the science are prone. My message

for noneconomists is that many of the standard criticisms of

economics lose their bite under this alternative account . There

is much to criticize in economics , but there is also much to

appreciate (and emulate) .

The Institute for Advanced Study was the p erfect environ

ment for writing this book in more than one way. With its

quiet woods, excellent meals, and incredible resources, the IAS

is a true scholars' haven. Faculty colleagues Danielle Allen,

Didier Fassin, Joan Scott, and Michael Walzer stimulated my

thinking about economics and provided inspiration with their

contrasting, but equally exacting, models of scholarship. My

faculty assistant, Nancy Cotterman, gave me useful feedback

on the manuscript on top of her amazingly efficient adminis

trative support. I am grateful to the institute's leadership, espe

cially its director, Robbert Dijkgraaf, for allowing me to be

part of this extraordinary intellectual community.

Andrew Wylie's guidance and advice ensured that the

manuscript would end up in the right hands-namely, W. W.

xiv

PR E FAC E A N D ACK N O WL E D GM E N T S

Norton. At Norton, Brendan Curry was a wonderful editor

and Stephanie Hiebert meticulously copyedited the manu

script; they both improved the book in countless ways. Special

thanks to Avinash Dixit, a scholar who exemplifies the virtues

of economists that I discuss in this book, who provided detailed

comment and suggestions. My friends and coauthors Sharun

Mukand and Arvind Subramanian generously gave their time

and helped shape the overall project with their ideas and con

tributions. Last but not least, my greatest debt, as always, is

to my wife, Pmar Dogan, who gave me her love and support

throughout, in addition to helping me clarify my argument

and discussion of economics concepts.

x v

Economics

Rules

INTRODU CTION

The Use and Misuse of

Economic Ideas

elegates from forty-four nations met in the New

Hampshire resort of Bretton Woo ds in July 1944 to

construct the postwar international economic order.

When they left three weeks later, they had designed the con

stitution of a global system that would last for more than three

decades. The system was the brainchild of two economists:

the towering English giant of the profession, John Maynard

Keynes; and the US Treasury official Harry Dexter White.*

* Whether White was actually a Soviet spy has been an ongoing controversy.

The case against White was made forcefully in B enn Steil 's The Battle of

Bretton Woods: John Maynard Keynes, Harry Dexter White, and the Making of

a New World Order (Princeton, NJ: Princeton University Press, 2 0 1 3). For

the argument on the other side, see James M. Boughton, "Dirtying White:

Why Does B enn Steil's History of Bretton Woods Distort the Ideas of

Harry Dexter White?" Nation, June 24, 2 0 1 3 . Whatever the facts of the

case, it is clear that the International Monetary Fund and the World Bank

E C O N O M I C S RUL E S

Keynes and White differed on many matters, especially where

issues of national interest were at stake, but they had in com

mon a mental frame shaped by the experience of the interwar

period. Their obj ective was to avoid the upheavals of the last

years of the Gold Standard and of the Great Depression. They

agreed . that achieving this goal required fixed, but occasionally

adjustable, exchange rates; liberalization of international trade

but not capital flows; enlarged scope for national monetary and

fiscal policies ; and enhanced cooperation through two new

international agencies, the International Monetary Fund and

the International B ank for Reconstruction and Development

(which came to be known as the World B ank) .

Keynes and White's regime proved remarkably successful.

It unleashed an era of unprecedented economic growth and

stability for advanced market economies, as well as for scores

of countries that would become newly independent. The sys

tem was eventually -undermined in the 1970s by the growth of

speculative capital flows, which Keynes had warned against.

But it remained the standard for global institutional engineer

ing. Through each successive upheaval of the world economy,

the rallying cry of the reformers was "a new Bretton Woo ds! "

In 1952 , a Columbia University economist named Wil

liam Vickrey proposed a new pricing system for the New

served quite well the economic interests of the United States (as well as

those of the rest of the Western world) in the decades following the end of

the Second World War.

T H E U S E A N D M I S U S E O F E C O N O M I C I D E A S

York City subway. He recommended that fares be increased at

peak times and in sections with high traffic, and be lowered at

other times and in other sections. This system of "congestion

pricing" was nothing other than the application of economic

supply-demand principles to public transport. Differential fares

would give commuters with more-flexible hours the incentive

to avoid peak travel times . They would allow passenger traffic

to spread out over time, reducing the pressure on the system

while enabling even larger total passenger flow. Vickrey would

later recommend a similar system for roads and auto traffic as

well. But many thought his ideas were crazy and unworkable.

Singapore was the first country to put congestion pricing to

a test. Beginning in 1975, Singaporean drivers were charged

tolls for entering the central business district. This system was

replaced in 1 9 9 8 by an electronic toll, which made it p ossible to

charge drivers varying rates depending on the average speed of

traffic in the network. By all accounts, the system has reduced

traffic congestion, increased public-transport use, reduced car

bon emissions, and generated considerable revenue for the Sin

gaporean authorities to boot. Its success has led other maj or

cities, like London, Milan, and Stockholm, to emulate it with

various modifications .

In 1 997, Santiago Levy, an economics professor at Boston

University serving as deputy minister of finance in his native

Mexico, sought to overhaul the government's antipoverty

approach. Existing programs provided assistance to the poor

mainly in the form of food subsidies. Levy argued that these

E C O N O M I C S RUL E S

programs were ineffective and inefficient. A central tenet of

economics holds that when it comes to the welfare of the poor,

direct cash grants are more effective than subsidies on specific

consumer goods. In addition, Levy thought he could use cash

grants as leverage to improve outcomes on health and edu

cation. Mothers would be given cash; in return, they would

have to ensure that their children were in school and receiving

health care. In economists' lingo, the program gave mothers an

incentive to invest in their children.

Progresa (later renamed Oportunidades, and later still, Pros

pera) was the first maj or conditional cash transfer (CCT) pro

gram established in a developing country. With the program

scheduled for a gradual introduction, Levy also drew up an

ingenious implementation scheme that would permit a clear

cut evaluation of whether it worked, or not . It was all based

on simple principles of economics, but it revolutionized the

way policy niakers tliought about antipoverty programs. As the

positive results came in, the program became a template for

other nations. More than a dozen Latin American countries,

including Brazil and Chile, would eventually adopt similar

programs. A pilot CCT program was even instituted in New

York City under Mayor Michael Bloomberg.

Three sets of economic ideas in three different areas: the

world economy, urban transport, and the fight against poverty.

In each case, economists remade part of our world by apply

ing simple economic frameworks to public problems. These

examples represent economics at its best. There are many oth-

T H E U S E A N D M I S U S E O F E C O N O M I C I D E A S

ers: Game theory has been used to set up auctions of airwaves

for telecommunications; market design models have helped the

medical profession assign residents to hospitals; industrial orga

nization models underpin competition and antitrust policies;

and recent developments in macroeconomic theory have led

to the widespread adoption of inflation targeting policies by

central banks around the world. 1 When economists get it right,

the world gets better.

Yet economists often fail, as many examples in this book

will illustrate. I wrote this book to try to explain why econom

ics sometimes gets it right and sometimes doesn't. "Models"

the abstract, typically mathematical frameworks that economists

use to make sense of the world-form the heart of the book.

Models are both economics' strength and its Achilles' heel;

they are also what make economics a science-not a science

like quantum physics or molecular biology, but a science

nonetheles s .

Rather than a single, specific model, economics encompasses

a collection of models. The discipline advances by expanding

its library of models and by improving the mapping between

these models and the real world. The diversity of models in

economics is the necessary counterpart to the flexibility of the

social world. Different social settings require different models.

Economists are unlikely ever to uncover universal, general

purpose models.

But , in part b ecause economists take the natural sciences as

their example, they have a tendency to misuse their models.

E C O N O M I C S RUL E S

They are prone to mistake a model for the model, relevant and

applicable under all conditions. Economists must overcome

this temptation. They have to select their models carefully as

circumstances change, or as they turn their gaze from one set

ting to another. They need to learn how to shift among differ

ent models more fluidly.

This book both celebrates and critiques economics . I defend

the core of the discipline-the role that economic models play

in creating knowledge-but criticize the manner in which

economists often practice their craft and (mis)use their mod

els . The arguments I present are not the "party view." I sus

pect many economists will disagree with my take on the

discipline, especially with my views on the kind of science

that economics is.

In my interactions with many noneconomists and practi

tioners of other social sciences, I have often been baffled by

outsider views on economics. Many of the complaints are well

known: economics is simplistic and insular; it makes universal

claims that ignore the role of culture, history, and other back

ground conditions; it reifies the market; it is full of implicit

value judgments; and besides, it fails to explain and predict

developments in the economy. Each of these criticisms derives

in large part from a failure to recognize that economics is, in

fact, a collection of diverse models that do not have a particular

ideological bent or lead to a unique conclusion. Of course, to

the extent that economists themselves fail to reflect this diver

sity within their profession, the fault lies with them.

T H E U S E A N D M I S U S E O F E C O N O M I C I D E A S

Another clarification at the outset. The term "economics"

has come to be used in two different ways. One definition

focuses on the substantive domain of study; in this interpreta

tion, economics is a social science devoted to understanding

how the economy works. The second definition fo cuses on

methods: economics is a way of doing social science, using par

ticular tools. In this interpretation the discipline is associated

with an apparatus of formal modeling and statistical analysis

rather than particular hypotheses or theories about the econ

omy. Therefore, economic methods can be applied to many

other areas besides the economy-everything from decisions

within the family to questions about political institutions.

I use the term "economics" largely in the second sense.

Everything I will say about the advantages and misapplication

of models applies equally well to research in political science,

sociology, or law that uses a similar approach. There has been a

tendency in public discussion to associate these methods exclu

sively with a Freakonomics kind of work. This approach, popu

larized by the economist Steven Levitt, has been used to shed

light on diverse social phenomena, ranging from the practices

of sumo wrestlers to cheating by public school teachers, using

careful empirical analysis and incentive-based reasoning. 2 Some

critics suggest that this line of work trivializes economics. It

eschews the big questions of the field-when do markets work

and fail, what makes economies grow, how can full employ

ment and price stability be reconciled, and so on-in favor of

mundane, everyday applications.

E C O N O M I C S RUL E S

In this book I focus squarely on these bigger questions and

how economic models help us answer them. We cannot look

to economics for universal explanations or prescriptions that

apply regardless of context. The possibilities of social life are

too diverse to be squeezed into unique frameworks . But each

economic model is like a partial map that illuminates a frag

ment of the terrain. Taken together, economists' models are

our best cognitive guide to the endless hills and valleys that

constitute social experience.

CHAPTER l

What Models Do

he Swedish-born economist Axel Leij onhufvud

published in 1973 a little article called "Life among

the Econ." It was a delightful mock ethnography in

which he described in great detail the prevailing practices, sta

tus relations, and taboos among economists . What defines the

"Econ tribe," explained Leijonhufvud, is their obsession with

what he called "modls"-a reference to the stylized mathe

matical models that are economists' tool of the trade. While

of no apparent practical use, the more ornate and ceremonial

the modl, the greater a person's status. The Econ's emphasis on

modls, Leij onhufvud wrote, explains why they hold members

of other tribes such as the " Sociogs" and "Polscis" in such low

regard: those other tribes do not make modls .*

* Axel Leij onhufvud, "Life among the E con," Western Economic Journal 1 1 ,

no. 3 (September 1973) : 327. Since this article was published, the use of

E C O N O M I C S RUL E S

Leij onhufvud's words still ring true more than four decades

later. Training in economics consists essentially of learning a

sequence of models. Perhaps the most important determinant

of the pecking order in the profession is the ability to develop

new models, or use existing models in conjunction with new

evidence, to shed light on some aspect of social reality. The

most heated intellectual debates revolve around the relevance

or applicability of this or that model. If you want to grievously

wound an economist, say simply, "You don't have a model."

Models are a source of pride. Hang around economists and

before long you will encounter the ubiquitous mug or T-shirt

that says, "Economists do it with models." You will also get the

sense that many among them would get rather more joy out

of toying with those mathematical contraptions than hanging

out with the runway prancers of the real world. (No sexism is

intended here: my wife, also an economist, was once presented

one of those mugs as a gift from her students at the end of a term.)

For critics , economists' reliance on models captures almost

everything that is wrong with the profession: the reduction

of the complexities of social life to a few simplistic relation

ships, the willingness to make patently untrue assumptions, the

obsession with mathematical rigor over realism, the frequent

jump from stylized abstraction to policy conclusions. They find

it mind-boggling that economists move so quickly from equa-

models has become more common in other social sciences, especially in

political science.

WHAT M O D E L S D O

tions on the page to advocacy of, say, free trade or a tax policy

of one kind or another. An alternative charge asserts that eco

nomics makes the mundane complex. Economic models dress

up common sense in mathematical formalism. And among the

harshest critics are economists who have chosen to part ways

with the orthodoxy. The maverick economist Kenneth Bould

ing is supposed to have said, "Mathematics brought rigor to

economics; unfortunately it also brought mortis." The Cam

bridge University economist Ha-Joon Chang says, " 95 percent

of economics is common sense-made to look difficult, with

the use of jargons and mathematics ."1

In truth, simple models of the type that economists con

struct are absolutely essential to understanding the workings

of society. Their simplicity, formalism, and neglect of many

facets of the real world are precisely what make them valuable.

These are a feature, not a bug. What makes a model useful is

that it captures an aspect of reality. What makes it indispens

able, when used well, is that it captures the most relevant aspect of

reality in a given context. Different contexts-different markets,

social settings, countries, time periods , and so on-require

different models. And this is where economists typically get

into trouble. They often discard their profession's most valuable

contribution-the multiplicity of models tailored to a variety

of settings-in favor of the search for the one and only uni

versal model. When models are selected judiciously, they are a

source of illumination. When used dogmatically, they lead to

hubris and errors in policy.

1 1

E C O N O M I C S RUL E S

A Variety of Models

Economists build models to capture salient aspects of social

interactions. Such interactions typically take place in markets

for goods and services. Economists tend to have quite a broad

understanding of what a market is. The buyers and sellers can

be individuals, firms , or other collective entities. The goods

and services in question can b e almost anything, including

things such as political office or status, for which no market

price exists. Markets can be local, regional, national, or inter

national; they can be organized physically, as in a bazaar, or

virtually, as in long-distance commerce. Economists are tra

ditionally preoccupied with how markets work: Do they use

resources efficiently? Can they b e improved, and if so, how?

How are the gains from exchange distributed? Economists also

use models, however, to shed light on the functioning of other

institutions-schools, trade unions, governments.

But what are economic models? The easiest way to under

stand them is as simplifications designed to show how specific

mechanisms work by isolating them from other, confounding

effects . A model focuses on particular causes and seeks to show

how they work their effects through the system. A modeler

builds an artificial world that reveals certain types of connec

tions among the parts of the whole-connections that might

be hard to discern if you were looking at the real world in its

welter of complexity. Models in economics are no different

from physical models used by physicians or architects. A plastic

1 2

WHA T M O D E L S D O

model of the respiratory system that you might encounter in

a physician's office focuses on the detail of the lungs , leaving

out the rest of the human body. An architect might build one

model to present the landscape around a house, and another

one to display the layout of the interior of the home. Econo

mists' models are similar, except that they are not physical con

structs but operate symbolically, using words and mathematics.

The workhorse model of economics is the supply-demand

model familiar to everyone who has ever taken an introduc

tory economics course. It's the one with the cross made up

of a downward-sloping demand curve and an upward-sloping

supply curve, and prices and quantities on the axes.* The arti

ficial world here is the one that economists call a "perfectly

competitive market," with a large number of consumers and

producers. All of them pursue their economic interests, and

none have the capacity to affect the market price. The model

leaves many things out: that people have other motives besides

material ones , that rationality is often overshadowed by emo

tion or erroneous cognitive shortcuts, that some producers can

* The supply-demand diagrams, along with the cross, apparently made

their first appearance in print in 1838, in a book by the French economist

Antoine-Augustin Cournot. Cournot is better known today for his

work on duopoly, and the cross is usually attributed to the p opular 1890

textbook by Alfred Marshall. See Thomas M . Humphrey, "Marshallian

Cross Diagrams and Their Uses before Alfred Marshall: The Origins of

Supply and Demand Geometry," Economic Review (Federal Reserve Bank

ofRichmond), March/April 1 9 9 2 , 3-23.

1 3

E C O N O M I C S RUL E S

b ehave monopolistically, and so on. But it does elucidate some

simple workings of a real-life market economy.

S ome of these are obvious. For example, a rise in production

costs increases market prices and reduces quantities demanded

and supplied. Or, when energy costs rise, utility bills increase

and households find extra ways of saving on heating and

electricity. But others are not. For example, whether a tax is

imposed on the producers or consumers of a commodity-say,

oil-has nothing to do with who ends up paying for it. The tax

might be administered on oil companies, but it might be con

sumers who really pay for it through higher prices at the pump.

Or the extra cost might be imposed on consumers in the form

of a sales tax, but the oil companies might be forced to absorb

it through lower prices. It all depends on the "price elastici

ties" of demand and supply. With the addition of a longish list

of extra assumptions-on which, more later-this model also

generates rather strong implications about how well markets

work. In particular, a competitive market economy is efficient

in the sense that it is impossible to improve one person's well

b eing without reducing somebody else's . (This is what econo

mists call "Pareto efficiency.")

Consider now a very different model, called the "prisoners'

dilemma." It has its origins in research by mathematicians, but

it is a cornerstone of much contemporary work in economics.

The way it is typically presented, two individuals face punish

ment if either of them makes a confession. Let's frame it as an

economics problem. Assume that two competing firms must

WHAT M O D E L S D O

decide whether to have a big advertising budget. Advertising

would allow one firm to steal some of the other's customers.

But when they both advertise, the effects on customer demand

cancel out . The firms end up having spent money needlessly.

We might expect that neither firm would choose to spend

much on advertising, but the model shows that this logic is

off base. When the firms make their choices independently

and they care only about their own profits, each one has an

incentive to advertise, regardless of what the other firm does:*

When the other firm does not advertise, you can steal custom

ers from it if you do advertise; when the other firm does adver

tise, you have to advertise to prevent loss of customers. So the

two firms end up in a bad equilibrium in which both have to

waste resources. This market, unlike the one described in the

previous paragraph, is not at all efficient.

The obvious difference b etween the two models is that one

describes a scenario with many, many market participants (the

market for, say, oranges) while the other describes competi

tion b etween two large firms (the interaction between airplane

manufacturers B o eing and Airbus, perhaps) . But it would b e

a mistake t o think that this difference is t h e exclusive reason

* Strictly speaking, another assumption is also needed: the firms have no

way of making credible promises to each other-that is, promises they will

not have the incentive to renege on later. For example, each firm may want

to promise to the other that it will not advertise. But these promises are not

credible, because each firm has an interest in advertising, regardless of what

the other firm does.

E C O N O M I C S RUL E S

that one market is efficient and the other not . Other assump

tions built in to each of the models play a part. Tweaking those

other assumptions, often implicit, generates still other kinds

of results.

Consider a third model that is agnostic on the number of

market participants, but that has outcomes of a very differ

ent kind. Let's call this the coordination model. A firm (or

firms; the number doesn't matter) is deciding whether to invest

in shipbuilding. If it can produce at sufficiently large scale,

it knows the venture will b e profitable. But one key input is

low-cost steel, and it must be produced nearby. The company's

decision boils down to this: if there is a steel factory close by,

invest in shipbuilding; otherwise, don't invest. Now consider

the thinking of potential steel investors in the region. Assume

that shipyards are the only potential customers of steel. Steel

producers figure they'll make money if there's a shipyard to

buy their steel, but not otherwise.

Now we have two possible outcomes-what economists call

"multiple equilibria." There is a "good" outcome, in which

both types of investments are made, and both the shipyard and

the steelmakers end up profitable and happy. Equilibrium is

reached. Then there is a "bad " outcome, in which neither type

of investment is made. This second outcome also is an equilib

rium because the decisions not to invest reinforce each other. If

there is no shipyard, steelmakers won't invest, and if there is no

steel, the shipyard won't be built. This result is largely unrelated

to the number of potential market participants. It depends cru-

WHAT M O D E L S D O

cially instead on three other features: (1) there are economies of

scale (in other words, profitable operation requires large scale);

(2) steel factories and shipyards need each other; and (3) there

are no alternative markets and sources of inputs (that can be

provided through foreign trade, for example) .

Three models, three different visions of how markets func

tion (or don't). None of them is right or wrong. Each high

lights an important mechanism that is (or could be) at work in

real-world economies. Already we begin to see how selecting

the "right" model, the one that best fits the setting, will be

important. One conventional view of economists is that they

are knee-j erk market fundamentalists: they think the answer

to every problem is to let the market be free. Many econo

mists may have that predisposition. But it is certainly not what

economics teaches. The correct answer to almost any ques

tion in economics is: It depends. Different models, each equally

respectable, provide different answers.

Models do more than warn us that results could go either

way. They are useful because they tell us precisely what the

likely outcomes depend on. Consider some important exam

ples . D o es the minimum wage lower or raise employment? The

answer depends on whether individual employers behave com

p etitively or not (that is, whether they can influence the going

wage in their location). 2 D oes capital flow into an emerging

market economy raise or lower economic growth? It depends

on whether the country's growth is constrained by lack of

investable funds or by p o or profitability due , say, to high taxes . 3

1 7

E C O N O M I C S RUL E S

Does a reduction in the government's fiscal deficit hamper or

stimulate economic activity? The answer depends on the state

of credibility, monetary policy, and the currency regime. 4

The answer to each question depends on some critical fea

ture of the real-world context. Models highlight those fea

tures and show how they influence the outcome. In each case

there is a standard model that produces a conventional answer:

minimum wages reduce employment, capital flow increases

growth, and fiscal cutbacks hamper economic activity. But

these conclusions are true only to the extent that their critical

assumptions-the features of the real world identified above

approximate reality. When they don't, we need to rely on

models with different assumptions.

I will discuss critical assumptions and give more examples

of economic models later. But first a couple of analogies about

what models are and what they do.

Models as Fables

O ne way to think of economic models is as fables. These short

stories often revolve around a few principal characters who live

in an unnamed but generic place (a village, a forest) and whose

b ehavior and interaction produce an outcome that serves as

a lesson of sorts . The characters can be anthropomorphized

animals or inanimate objects, as well as humans. A fable is sim

plicity itself: the context in which the story unfolds is sketched

in sparse terms , and the b ehavior of the characters is driven by

1 8

WHA T M O D E L S D O

stylized motives such as greed or j ealousy. A fable makes little

effort to be realistic or to draw a complete picture of the life of

its characters. It sacrifices realism and ambiguity for the clarity

of its story line. Importantly, each fable has a transparent moral:

honesty is best, he laughs best who laughs last, misery loves

company, don't kick a man when he's down , and so on.

Economic models are similar. They are simple and are set

in abstract environments . They make no claim to realism for

many of their assumptions. While they seem to be populated by

real p eople and firms , the behavior of the principal characters

is drawn in highly stylized form. Inanimate objects ("random

shocks," "exogenous parameters ," "nature") often feature in

the model and drive the action. The story line revolves around

clear cause-and-effect, if-then relationships . And the moral

or p olicy implication, as economists call it-is typically quite

transparent: free markets are efficient, opportunistic b ehavior

in strategic interactions can leave everyone worse off, incen

tives matter, and so on.

Fables are short and to the p oint. They take no chance

that their message will be lost. The story of the hare and the

tortoise imprints on your conscious mind the importance of

steady, if slow, progress. The story becomes an interpretive

shortcut, to be applied in a variety of similar settings. Pair

ing economic models with fables may seem to denigrate their

"scientific" status. But part of their appeal is that they work in

exactly the same way. A student exposed to the competitive

supply-demand framework is left with an enduring respect for

E C O N O M I CS RUL E S

the power of markets . Once you work through the prisoners'

dilemma, you can never think of problems of cooperation in

quite the same way. Even when the specific details of the mod

els are forgotten, they remain templates for understanding and

interpreting the world.

The analogy is not missed by the profession's best prac

titioners . In their self-reflective moments , they are ready to

acknowledge that the abstract mo dels they put to paper are

essentially fables . As the distinguished economic theorist

Ariel Rubinstein puts it, "The word 'model ' sounds more sci

entific than ' fable' or ' fairy tale' [yet] I do not see much dif

ference b etween them."5 In the words of philosopher Allan

Gibbard and economist Hal Varian, "[An economic] model

always tells a story."6 Nancy Cartwright, the philosopher of

science, uses the term " fable" in relation to economic and

physics models alike, though she thinks economic models

are more like_ parables .7 Unlike fables , in which the moral is

clear, Cartwright says that economic models require lots of

care and interpretation in drawing out the p olicy implica

tion . This complexity is related to the fact that each model

captures only a contextual truth, a conclusion that applies to

a specific setting.

But here, too , fables offer a useful analogy. There are count

less fables , and each provides a guide for action under a some

what different set of circumstances. Taken together, they result

in morals that often appear contradictory. Some fables extol the

virtues of trust and cooperation, while others recommend self-

WHAT M O D E L S D O

reliance. S ome praise prior preparation; others warn about the

dangers of overplanning. Some say you should spend and enjoy

the money you have; others say you should save for a rainy day.

Having friends is good, but having too many friends is not so

good . Each fable has a definite moral, but in totality, fables

foster doubt and uncertainty.

So we need to use judgment when selecting the fable that

applies to a particular situation. Economic models require the

same discernment. We've already seen how different models

produce different conclusions. Self-interested behavior can result

in both efficiency (the perfectly competitive market model) and

waste (the prisoners' dilemma model) depending on what we

assume about background conditions. As with fables, good

judgment is indispensable in selecting from the available menu

of contending models. Luckily, evidence can provide some

useful guidance for sifting across models, though the process

remains more craft than science (see Chapter 3) .

Models as Experiments

If the idea of models as fables does not appeal, you can think

of them as lab experiments. This is perhaps a surprising anal

ogy. If fables make models seem like simplistic fairy tales , the

comparison to lab experiments risks dressing them up in exces

sively scientific garb. After all, in many cultures lab experi

ments constitute the height of scientific respectability. They

are the means by which scientists in white coats arrive at the

2 1

E C O N O M I C S RUL E S

"truth" about how the world works and whether a particular

hypothesis is true. Can economic models come even close?

Consider what a lab experiment really is. The lab is an

artificial environment built to insulate the materials involved

in the experiments from the environment of the real world.

The researcher designs experimental conditions that seek to

highlight a hypothesized causal chain, isolating the process

from other potentially important influences . When, say, grav

ity exerts confounding effects, the researcher carries out the

experiment in a vacuum. As the Finnish philosopher Uskali

Maki explains, the economics modeler in fact practices a simi

lar method of insulation, isolation, and identification. The

main difference is that the lab experiment purposely manipu

lates the physical environment to achieve the isolation needed

to observe the causal effect, whereas a model does this by

manipulating the assumptions that go into it.* Models build

mental environments to test hypotheses.

* Uskali Maki, "Models Are Experiments, Experiments Are Models,"

Journal of Economic Methodology 1 2 , no. 2 (2005): 303-1 5. Note that isolating

an effect in economic models is not as simple as it may seem. We always

have to make some assumptions about other background conditions. For

this reason, Nancy Cartwright argues that the effect is always the result

of the joint operation of many causes and we can never truly isolate cause

and effect in economics. See Cartwright, Hunting Causes and Using Them:

Approaches in Philosophy and Economics (Cambridge: Cambridge University

Press, 2007) . This is true in general, but the value of having multiple

models is that it enables us to alter the background conditions selectively,

to ascertain which, if any, make a substantive contribution to the effect.

WHAT M O D E L S D O

You may obj ect that in a lab experiment, as artificial as its

environment may be, the action still takes place in the real

world. We know if it works or does not work, in at least one

setting. An economic model, by contrast, is a thoroughly arti

ficial construct that unfolds in our minds only. Yet the dif

ference can be in degree rather than in kind. Experimental

results, too , may require significant extrapolation before they

can be applied to the real world. Something that worked in the

lab may not work outside it. For example, a drug might fail in

practice when it mixes with real-world conditions that were

left out of consideration-"controlled for"-under the experi

mental setting.

This is the distinction that philosophers of science refer to

as internal versus external validity. A well-designed experi

ment that successfully traces out cause and effect in a specific

setting is said to have a high degree of " internal validity." But

its "external validity" depends on whether its conclusion can

travel successfully outside the experimental context to other

settings .

So-called field experiments, carried out not in the lab but

under real-world conditions, also face this challenge. Such

experiments have become very popular in economics recently,

and they are sometimes thought to generate knowledge that is

Varying some background conditions may make a big difference; varying

others, very little. See also my discussion on the realism of assumptions later

in the chapter.

E C O N O M I C S RUL E S

model-free; that is, they're supposed to provide insight about

how the world works without the baggage of assumptions

and hypothesized causal chains that comes with models. But

this is not quite right. To give one example: In Colombia,

the randomized distribution of private-school vouchers has

significantly improved educational attainment. But this is no

guarantee that similar programs would have the same outcome

in the United States or in South Africa. The ultimate outcome

relies on a host of factors that vary from country to coun

try. Income levels and preferences of parents, the quality gap

b etween private and public schools, the incentives that drive

schoolteachers and administrators-all of these factors , and

many other potentially important considerations, come into

play. 8 Getting from " it worked there" to " it will work here"

requires many additional steps.9

The gulf b etween real experiments carried out in the lab

(or in the field) and the thought experiments we call "models"

is less than we might have thought. B oth kinds of exercises

need some extrapolation b efore they can be applied when and

where we need them. Sound extrapolation in turn requires a

combination of goo d judgment, evidence from other sources,

and structured reasoning. The power of all these types of

experiments is that they teach us something about the world

outside the context in which they're carried out, on account

of our ability to discern similarity and draw parallels across

diverse settings .

As with real experiments, the value of models resides in being

WHAT M O D E L S D O

able to isolate and identify specific causal mechanisms, one at a

time. That these mechanisms operate in the real world alongside

many others that may obfuscate their workings is a complica

tion faced by all who attempt scientific explanations . Economic

models may even have an advantage here. Contingency

dependence on specific postulated conditions-is built into

them. As we'll see in Chapter 3, this lack of certainty encour

ages us to figure out which among multiple contending models

provides a better description of the immediate reality.

Unrealistic Assumptions

Consumers are hyperrational, they are selfish, they always

prefer more consumption to less, and they have a long time

horizon, stretching into infinity. Economic models are typi

cally assembled out of many such unrealistic assumptions. To

be sure, many models are more realistic in one or more of these

dimensions. But even in these more layered guises , other unre

alistic assumptions can creep in somewhere else. Simplification

and abstraction necessarily require that many elements remain

counterfactual in the sense that they violate reality. What is the

b est way to think about this lack of realism?

Milton Friedman, one of the twentieth century's greatest

economists, provided an answer in 1953 that deeply influenced

the profession. 10 Friedman went beyond arguing that unrealis

tic assumptions were a necessary part of theorizing. He claimed

that the realism of assumptions was simply irrelevant. Whether

E C O N O M I C S RUL E S

a theory made the correct predictions was all that mattered. As

long as it did, the assumptions that went into the theory need

not bear any resemblance to real life . While this is a crude sum

mary of a more sophisticated argument, it does convey the gist

that most readers took from Friedman's essay. As such, it was

a wonderfully liberating argument, giving economists license

to develop all kinds of models built on assumptions wildly at

variance with actual experience.

However, it cannot be true that the realism of assumptions

1s entirely irrelevant. As Stanford economist Paul Pfleiderer

explains, we always need to apply a "realism filter" to critical

assumptions before a model can be treated as useful.11 (Here's

that term "critical" again. I will turn to it shortly.) The reason

is that we can never be sure of a model's predictive success .

Prediction, as Groucho Marx might have said, always involves

the future. v:Je can �oncoct an almost endless variety of models to explain a reality after the fact. But most of these models are

unhelpful; they will fail to make the correct prediction in the

future, when conditions change.

Suppose I have data on traffic accidents in a locality for the

last five years . I notice that there are more accidents at the end

of the workday, b etween 5 : 0 0 and 7:0 0 p.m. The most reason

able explanation is that more people are on the road at that

time, driving home from work. But suppose a researcher comes

up with an alternative story. It's John's fault, he says. John's

brain emits invisible waves that affect everyone's driving. Once

he is out of his office and on the street, his brain waves mess

WHAT M O D E L S D O

with traffic, causing more accidents. It may be a silly theory,

but it does "explain" the rise in traffic accidents at the end of

the workday.

We know in this case that the second model is not a useful

one. If John changes his schedule or he retires, it will have no

predictive value. The number of accidents will not go down

when John is no longer out and about. The explanation fails

because its critical assumption-that John emits traffic-disrupt

ing brain waves-is false. For a model to be useful in the sense

of tracking reality, its critical assumptions also have to track

reality sufficiently closely. 12

What exactly is a critical assumption? We can say an assump

tion is critical if its modification in an arguably more realistic

direction would produce a substantive difference in the conclu

sion produced by the model. Many, if not most, assumptions

are not critical in this sense. Consider the p erfectly competitive

market model. The answers to many questions of interest do

not depend crucially on the details of that model. In his essay

on methodology, Milton Friedman discussed taxes on ciga

rettes. We can safely predict that raising the tax rate will lead to

an increase in the retail price of cigarettes , he wrote, regardless

of whether there are many or few firms and whether different

cigarette brands are p erfect substitutes or not. Similarly, any

reasonable relaxation of the requirement of perfect rationality

would be unlikely to make much difference to that result. Even

if firms do not make calculations to the last decimal point, we

can be reasonably confident that they will notice an increase in

E C O N O M I C S RUL E S

the taxes they have to pay. These specific assumptions are not

critical in view of which question is posed and how the model is

used-for example, how does a tax effect the price of cigarettes?

Their lack of realism therefore is not of great importance.

Suppose we were interested in a different question: the effect

of imposing price controls on the cigarette industry. Now the

degree of competition in the industry, which depends in part

on the extent to which consumers are willing to substitute

between different brands, becomes of great importance. In the

p erfectly competitive market model, a price control leads to

firms reducing their supply. The lower price decreases their

profitability, and they respond by cutting back their sales. But

in a model of a market that is monopolized by a single firm,

a moderate price ceiling (that is, a ceiling that is not too far

below the unrestricted market price) actually induces the firm

to increase its output. To see how this mechanism operates, a bit

of simple algebra or - geometry comes in handy. Intuitively, a

monopolist increases profits by restricting sales and raising the

market price. Price controls, which rob the monopolist of its

price-setting powers, effectively blunt the incentive to under

produce. The monopolist responds by increasing sales.* Selling

more cigarettes is now the only means to making more profits.

What we assume about the degree of market competition

becomes critical when we want to predict the effects of price

* This is the same logic that causes an increase in employment after a

(moderate) minimum wage has been imposed.

WHA T M O D E L S D O

controls. The realism of this particular assumption matters, and

it matters greatly. The applicability of a model depends on how

closely critical assumptions approximate the real world. And

what makes an assumption critical depends in part on what the

model is used for. I will return to this issue later in the book,

when I examine in greater detail how we select which model

to apply in a given setting.

It is perfectly legitimate, and indeed necessary, to question a

model's efficacy when its critical assumptions are patently coun

terfactual, as withJohn's brain waves . In such instances, we can

rightly say that the modeler has oversimplified and is leading us

astray. The appropriate response, however, is to construct alter

native models with more fitting assumptions-not to abandon

models per se. The antidote to a bad model is a goo d model.

Ultimately, we cannot avoid unrealism in assumptions .

As Cartwright says, " Criticizing economic models for using

unrealistic assumptions is like criticizing Galileo's rolling ball

experiments for using a plane honed to be as frictionless as pos

sible."13 But just as we would not want to apply Galileo's law of

acceleration to a marble dropped into a j ar of honey, this is not

an excuse for using models whose critical assumptions grossly

violate reality.

On Math and Models

Economic models consist of clearly stated assumptions and

behavioral mechanisms. As such, they lend themselves to

E C O N O M I C S RUL E S

the language of mathematics . Flip the pages of any academic

j ournal in economics and you will encounter a nearly endless

stream of equations and Greek symbols. By the standards of

the physical sciences, the math that economists use is not very

advanced: the rudiments of multivariate calculus and optimi

zation are typically sufficient to follow most economic theo

rizing. Nevertheless, the mathematical formalism does require

some investment on the part of the reader. It raises a compre

hensibility barrier b etween economics and most other social

sciences. It also heightens noneconomists' suspicions about the

profession: the math makes it seem as if economists have with

drawn from the real world and live in abstractions of their own

construction.

When I was a young college student, I knew I wanted to

get a PhD because I loved writing and doing research. But I

was interested in a wide variety of social phenomena and could

not make up my mind b etween political science and econom

ics. I applied to both kinds of doctoral programs, but I post

p oned the ultimate decision by enrolling in a multidisciplinary

master's program. I remember well the experience that finally

resolved my indecision. I was in the library of the Woodrow

Wilson School at Princeton and picked up the latest issues of

the American Economic Review (AER) and the American Political

Science Review (APSR) , the flagship publications of the two dis

ciplines . Looking at them side by side, it dawned on me that I

would be able to read the A PSR with a PhD in economics, but

much of the AER would be inaccessible to me with a PhD in

3 0

W H A T M O D E L S D O

political science. With hindsight, I realize this conclusion was

perhaps not quite right. The political philosophy articles in the

APSR can be as abstruse as any in the AER, math aside. And

much of political science has since gone the way of economics

in adopting mathematical formalism. Nonetheless, there was a

germ of truth in my observation. To this day, economics is by

and large the only social science that remains almost entirely

impenetrable to those who have not undertaken the requisite

apprenticeship in graduate school.

The reason economists use mathematics is typically misun

derstood. It has little to do with sophistication, complexity,

or a claim to higher truth. Math essentially plays two roles

in economics , neither of which is cause for glory: clarity and

consistency. First, math ensures that the elements of a model

the assumptions, behavioral mechanisms, and main results

are stated clearly and are transparent. Once a model is stated

in mathematical form, what it says or does is obvious to all

who can read it. This clarity is of great value and is not ade

quately appreciated. We still have endless debates today about

what Karl Marx, John Maynard Keynes , or Joseph S chumpeter

really meant. Even though all three are giants of the economics

profession, they formulated their models largely (but not exclu

sively) in verbal form. By contrast, no ink has ever been spilled

over what Paul Samuelson, Joe Stiglitz, or Ken Arrow had in

mind when they developed the theories that won them their

Nobel. Mathematical models require that all the t's be crossed

and the i's b e dotted.

3 1

E C O N O M I C S RUL E S

The second virtue of mathematics is that it ensures the inter

nal consistency of a model-simply put, that the conclusions

follow from the assumptions. This is a mundane but indispens

able contribution. S ome arguments are simple enough that

they can be self-evident. Others require greater care, especially

in light of cognitive biases that draw us toward results we want

to see . Sometimes a result can be plainly wrong. More often,

the argument turns out to be poorly specified, with criti

cal assumptions left out. Here, math provides a useful check.

Alfred Marshall, the towering economist of the pre-Keynesian

era and author of the first real economics textbook, had a good

rule: use math as a shorthand language, translate into English,

and then burn the math! Or as I tell my students , economists

use math not because they're smart, but because they're not

smart enough.

When I was still young and green as an economist, I once

heard a lecture __ by the great development economist Sir W.

Arthur Lewis, winner of the 1979 Nobel Prize in Economic

S ciences. Lewis had an uncanny ability to distill complex eco

nomic relationships to their essence by using simple models.

But as with many economists from an older tradition, he tended

to present his argument in verbal rather than mathematical

form. On this occasion his topic was the determination of poor

countries' terms of trade-the relative price of their exports to

their imports. When Lewis finished, one of the younger, more

mathematically oriented economists in the audience stood up

and scribbled a few equations on the blackboard. He pointed

WHAT M O D E L S D O

out that at first he had been confused by what Professor Lewis

was saying. But, he continued as a bemused Lewis watched,

now he could see how it worked: we have these three equations

that determine these three unknowns.

S o , math plays a purely instrumental role in economic

models. In principle, models do not require math, and it is not

the math that makes the models useful or scientific.* As the

Arthur Lewis example illustrates , some stellar practitioners of

the craft rarely use any math at all. Tom S chelling, who has

developed some of the key concepts of contemporary game

theory, such as credibility, commitment, and deterrence, won

the Nobel Prize for his largely math-free work . 14 Schelling

has the rare knack of laying out what are fairly complicated

models of interaction among strategically minded individu

als while using only words , real-world examples, and perhaps

a figure at most. His writings have greatly influenced both

academics and policy makers. I must admit, though, that the

depth of his insights and the precise nature of the arguments

b ecame fully evident to me only after I saw them expressed

more fully with mathematics .

Nonmathematical models are more common in social sci

ences outside of economics. You can always tell that a social

* Outside of economics, the term "rational choice" has become a synonym

for an approach to social science that uses predominantly mathematical

models. This use of the term conflates several things. Doing social science

using models requires neither math nor, necessarily, the assumption that

individuals are rational.

E C O N O M I C S RUL E S

scientist is about to embark on a model when he or she begins ,

"Assume that we have . . . " or something similar, followed by an

abstraction. Here, for example, is the sociologist Diego Gam

betta examining the consequences of different types of beliefs

about the nature of knowledge: " Imagine two ideal-type soci

eties that differ in one respect only . . ."15 Papers in political

science are frequently peppered with references to independent

and dependent variables-a sure sign that the author is mim

icking models even when a clear-cut framework is lacking.

Verbal arguments that seem intuitive often collapse, or are

revealed to be incomplete, under closer mathematical scru

tiny. The reason is that "verbal models" can ignore nonob

vious but potentially significant interactions. For example,

many empirical studies have found that government interven

tion is negatively correlated with p erformance : industries that

receive subsidies experience lower productivity growth than

industries that aon't.- How do we interpret these findings? It is

common, even among economists, to conclude that govern

ments must be intervening for the wrong rather than right rea

sons , that they support weak industries in response to political

lobbying. This may sound reasonable-too obvious even to

require further analysis. Yet when we mathematically describe

the behavior of a government that intervenes for the right

reason-by subsidizing industries to enhance the economy's

efficiency-we see that this conclusion may not be warranted.

Industries that are performing poorly b ecause markets are

malfunctioning warrant greater government intervention-

WHAT M O D E L S D O

but not to the extent that their disadvantages are completely

offset. Therefore, the negative correlation between subsidies

and performance does not tell us whether governments are

intervening in desirable or undesirable ways, as both types

of intervention would generate the observed correlation. Not

clear? Well, you can check the math !*

At the other end of the spectrum, too many economists

fall in love with the math and forget its instrumental nature.

Excessive formalization-math for its own sake-is rampant

in the discipline. Some branches of economics , such as mathe

matical economics , have come to look more like applied math

ematics than like any kind of social science. Their reference

point has become other mathematical models instead of the

* Dani Rodrik, "Why We Learn Nothing from Regressing Economic

Growth on Policies," Seoul Journal of Economics 25, no. 2 (Summer

2 0 1 2) : 1 37-51 . Further afield from economics, John Maynard Smith, a

distinguished theorist of evolutionary biology, explains why it is important

to develop the mathematics of an argument in this video: http://www.

web ofstorie s . c o m /play/j oh n . maynard . smith / 5 2 ;j s e s sionid=36363 04FA

6745B8E 5D200253DAF409EO . Maynard describes his frustration with

a verbal theory of why some animals, like the antelope, j ump up and

down while running, exhibiting a behavior that is called "stetting." This

behavior seems inefficient because it slows the animal down. The theory

is that stetting is a way of signaling potential predators that the antelope is

not worth pursuing: the antelope is so fast that it c an get away even with

this inefficient run. Smith recollects how he tried to model this scenario

mathematically and could never produce the desired result-that strotting

could be efficient when used as a signal.

E C O N O M I C S RUL E S

real world. The abstract of one paper in the field opens with

this sentence: "We establish new characterizations of Walra

sian expectations equilibria based on the veto mechanism in

the framework of differential information economies with a

complete finite measure space of agents ."16 One of the pro

fession's leading, and most mathematically oriented, j ournals

(Econometrica) imp osed a moratorium at one p oint on "social

choice" theory-abstract models of voting mechanisms

b ecause papers in the field had become mathematically so eso

teric and divorced from actual politics . 17

B efore we judge such work too harshly, it is worth noting

that some of the most useful applications in economics have

come out of highly mathematical, and what to outsiders would

surely seem abstruse, models. The theory of auctions, draw

ing on abstract game theory, is virtually impenetrable even to

many economists.* Yet it produced the principles used by the

Federal Communications Commission to allocate the nation's

telecommunications spectrum to phone companies and broad

casters as efficiently as possible, while raising more than $60

billion for the federal government. 18 Models of matching and

market design, equally mathematical, are used today to assign

residents to hospitals and students to public schools. In each

* For a relatively informal introduction to the theory, see Paul Milgrom,

"Auctions and Bidding: A Primer," journal of Economic Perspectives 3 , no.

3 (Summer 1989), 3-2 2 . A more thorough treatment can be found in

Paul Klemperer, Auctions: Theory and Practice (Princeton, NJ: Princeton

University Press, 2004).

WHAT M O D E L S D O

case, models that seemed to be highly abstract and to have

few connections with the real world turned out to have useful

applications many years later.

The good news is that, contrary to common perception,

math for its own sake does not get you far in the economics pro

fession. What's valued is "smarts": the ability to shed new light

on an old topic, make an intractable problem soluble, or devise

an ingenious new empirical approach to a substantive question.

In fact, the emphasis on mathematical methods in economics

is long past its peak. Today, models that are empirically ori

ented or policy relevant are greatly preferred in top j ournals

over purely theoretical, mathematical exercises. The profes

sion's stars and most heavily cited economists are those who

have shed light on important public problems, such as poverty,

public finance, economic growth, and financial crises-not its

mathematical wizards.

Simplicity versus Complexity

Despite the math, economic models tend to be simple. For the

most part, they can be solved using pen and paper. It's one rea

son why they have to leave out many aspects of the real world.

But as we've seen, lack of realism is not a good criticism on

its own . To use an example from Milton Friedman again, a

model that included the eye color of the businesspeople com

peting against each other would be more realistic, but it would

not be a b etter one.19 Still, whether some influences matter or

E C O N O M I C S RUL E S

not depends on what is assumed at the outset. Perhaps blue

eyed businessmen are more dim-witted and systematically

underprice their products . The strategic simplifications of the

modeler, made for reasons of tractability, can have important

implications for substantive outcomes.

Wouldn't it b e better to opt for complexity over simplicity?

Two related developments in recent years have made this ques

tion more pertinent. First, the stupendous increase in comput

ing power and the attendant sharp fall in its cost have made

it easier to run large-scale computational models. These are

models with thousands of equations, containing nonlinearities

and complex interactions. Computers can solve them, even if

the human brain cannot. Climate models are a well-known

example. Large-scale computational models are not unknown

in economics, even though they are rarely as big. Most central

banks use multiequation models to forecast the economy and

predict the effects of monetary and fiscal policy.

The second development is the arrival of " big data," and the

evolution of statistical and computational techniques that distill

patterns and regularities from them. "Big data" refers to the

humongous amount of quantitative information that is gener

ated by our use of the Internet and social media-an almost

complete and continuous record of where we are and what we

do, moment by moment. Perhaps we have reached, or soon

will reach, the stage where we can rely on the patterns revealed

in this data to uncover the mysteries of our social relations.

"Big data gives us a chance to view society in all its complex-

3 8

WHAT M O D E L S D O

ity," writes one of the leading proponents of this view. 20 This

would send our traditional economic models the way of the

horse and buggy.

C ertainly, complexity has great surface appeal. Who could

possibly deny that society and the economy are complex systems?

"Nobody really agrees on what makes a complex system 'com

plex,"' writes Duncan Watts, a mathematician and sociologist,

" but it's generally accepted that complexity arises out of many

interdependent components interacting in nonlinear ways."

Interestingly, the immediate example that Watts deploys is the

economy: " The U. S . economy, for example, is the product of

the individual actions of millions of people, as well as hundreds

of thousands of firms, thousands of government agencies, and

countless other external and internal factors , ranging from the

weather in Texas to interest rates in China."21 As Watts notes ,

disturbances in one part o f the economy-say, i n mortgage

finance-can be amplified and produce maj or shocks for the

entire economy, as in the " butterfly effect" from chaos theory.

It is interesting that Watts would point to the economy, since

efforts to construct large-scale economic models have been sin

gularly unproductive to date. To put it even more strongly, I

cannot think of an important economic insight that has come

out of such models. In fact, they have often led us astray. Over

confidence in the prevailing macroeconomic orthodoxy of the

day resulted in the construction of several large-scale simula

tion models of the US economy in the 1960s and 1970s built on

Keynesian foundations. These models performed rather badly

E C O N O M I C S RUL E S

in the stagflationary environment of the late 1970s and 1 9 8 0 s .

They were subsequently j ettisoned in favor o f "new classical"

approaches with rational expectations and price flexibility.

Instead of relying on such models, it would have been far b et

ter to carry several small models in our heads simultaneously,

of both Keynesian and new classical varieties, and know when

to switch from one to the other.

Without these smaller, more transparent models, large-scale

computational models are, in fact, unintelligible. I mean this in

two senses. First, the assumptions and behavioral relations that

are built into the large models must come from somewhere.

D epending on whether you believe in the Keynesian model or

the new classical model, you will develop a different large-scale

model. If you think economic relationships are highly nonlin

ear or exhibit discontinuities, you will build a different model

than if you think they are linear and "smooth." These prior

understandingsdo not derive from complexity itself; they must

come from some first-level theorizing.

Second, and alternatively, suppose we can build large-scale

models relatively theory-free, using big-data techniques based

on observed empirical regularities such as consumer spending

patterns. Such models can deliver predictions, like weather

models do, but never knowledge on their own. For they are

like a black box: we can see what is coming out, but not the

operative mechanism inside. To eke out knowledge from these

models, we need to figure out and scrutinize the underlying

causal mechanisms that produce specific results . In effect, we

4 0

WHAT M O D E L S D O

need to construct a small-scale version of the larger model.

Only then can we say that we understand what's going on.

Moreover, when we evaluate the predictions of the complex

model-it predicted this recession, but will it predict the next

one?-our judgment will depend on the nature of these under

lying causal mechanisms. If they are plausible and reasonable,

by the same standards we apply to small-scale models, we may

have reason for confidence. Not otherwise.

Consider the large-scale computational models that are com

mon in the analysis of international trade agreements among

nations. These agreements change import and export policies in

hundreds of industries that are linked through markets for lab or,

capital, and other productive inputs. A change in one industry

affects all the others, and vice versa. If we want to understand

the economy-wide consequences of trade agreements, we need

a model that tracks all these interactions. In principle, that is

what the so-called computable general equilibrium (CGE) mod

els do. They are constructed partly on the basis of the preva

lent models of trade, and partly on ad hoe assumptions meant

to replicate observed economic regularities (such as the share of

national output that is traded internationally) . When pundits in

the media report, say, that the Transatlantic Trade and Invest

ment Partnership (TTIP) between the United States and Europe

will create so many billions of dollars of exports and income,

they are citing results from these models.

Without doubt, models of this sort can provide a sense

of the orders of magnitude involved in a decision. But ulti-

E C O N O M I C S RUL E S

mately, they are credible only to the extent that their results

can be motivated and justified by much smaller, pen-and-paper

models. Unless the underlying explanation is transparent and

intuitive-unless there exists a simpler model that generates a

similar result-complexity on its own buys us nothing other

than perhaps a bit more detail.

What about some of the specific insights arising out of mod

els that emphasize complexity, such as tipping points, comple

mentarities, multiple equilibria, or path dependence? It is true

that such "nonstandard" outcomes emphasized by complexity

theorists stand in sharp contrast to the more linear, smooth

behavior of economists' workhorse models. It is also certainly

true that real-world outcomes are sometimes b etter described

in those spikier ways . However, not only can these kinds of

outcomes be generated in smaller, simpler models, but they

actually originate in them. Tipping-point models, referring to

a sudden change in aggregate behavior after a sufficient num

b er of individuals make a switch, were first developed and

applied to different social settings by Tom Schelling. His para

digmatic example, developed in the 1970s, was the collapse of

mixed neighborhoods into complete segregation once a critical

threshold of white flight is reached. The potential for multiple

equilibria has long been known and studied by economists,

often in the context of highly stylized models. I gave an exam

ple (our shipbuilder and the coordination game) at the begin

ning of the chapter. Path dependence is a feature of a large class

of dynamic economic models . And so on.

4 2

WHAT M O D E L S D O

A critic might argue that economists treat such models as

exceptions to the "normal" cases covered by the workhorse

competitive market model. And the critic would have a point.

Economists tend to fixate too much on certain standard models

at the expense of others. In some settings, a simple model can

be, well, too simple. We may need more detail. The trick is

to isolate just the interactions that are hypothesized to matter,

but no more. As the preceding examples suggest, models can

do this and still remain simple. O ne model is not always better

than another. Remember: it is a model, not the model.

Simplicity, Realism , and Reality

In his exceptionally brief-one paragraph, to be exact-short

story called "On Exactitude in Science," the Argentine novel

ist Jorge Luis B orges describes a mythical empire in the dis

tant past in which cartographers took their craft very seriously

and strived for p erfection. In their quest to capture as much

detail as possible, they drew ever-bigger maps. The map of a

province expanded to the size of a city; a map of the empire

occupied a whole province. In time, even this level of detail

b ecame insufficient and the cartographers' guild drew a map of

the empire on a 1 :1 scale the size of the empire itself But future

generations, less enamored by the art of cartography and more

interested in help with navigation, would find no use for these

map s . They discarded them and left them to rot in the desert.22

As B orges's story illustrates, the argument that models need

E C O N O M I C S R UL E S

to be made more complex to make them more useful gets it

backward. Economic models are relevant and teach us about

the world because they are simple. Relevance does not require

complexity, and complexity may impede relevance. Simple

models-in the plural-are indispensable. Models are never

true; but there is truth in models.23 We can understand the

world only by simplifying it.

4 4

CHAPTER 2

The S cience of Econolllic

Modeling

odels make economics a science . With this asser

tion, I do not have in mind sciences like physics

or chemistry, which seek to uncover fundamen

tal laws of nature. Economics is a social s cience, and society

does not have fundamental laws-at least, not in quite the

same way that nature does. Unlike a rock or a planet, humans

have agency; they choose what they do. Their actions pro

duce a near infinite variety of p ossibilities . At b est, we can

talk in terms of tendencies, context-specific regularities, and

likely consequences . Nor do I have in mind something like

mathematics, which generates precise statements, albeit about

abstract entities, that can be determined to be either true or

false. Economics deals with the real world and is much messier

than that. Economists often go astray precisely because they

fancy themselves as physicists and mathematicians manque.

E C O N O M I C S RUL E S

At the other end of the spectrum, critics scoff at econo

mists' scientific pretensions-chiding them for practicing

make-believe science at b est. Keynes, uncharacteristically,

had a modest ambition for economics : " I f economists could

manage to get themselves thought of as humble, competent

people , on a level with dentists , that would b e splendid! " he

wrote in 1 9 3 0 . 1 Perhaps even dentistry is too lofty a goal,

in view of the variety of maladies and syndromes that afflict

human societies . A good deal of modesty is in order about not

only how much economists know, but also how much they

can learn.

With those caveats out of the way, we can review what

makes models scientific. First, as I explained in the previous

chapter, models clarify the nature of hypotheses, making clear

their logic and what they do and don't depend on. This is

typically a matter of refining intuition, crossing the t's and

dotting the i's-which is important in itself But quite often

their greater contribution is to open our eyes to counterintui

tive possibilities and unexpected consequences. Second, mod

els enable the accumulation of knowledge, by expanding the

set of plausible explanations for, and our understanding of, a

variety of social phenomena. In this way, economic science

advances as a library would expand: by adding to its collec

tion. Third, models imply an empirical method; they suggest

how specific hypotheses and explanations can be applied, in

principle at least, to actual settings . They enable arguments

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

to be judged right or wrong. And even when evidence is too

weak to discriminate among them, models provide a method

for sorting out disagreements. Finally, models allow knowl

edge to be generated on the basis of commonly shared pro

fessional standards rather than prevailing hierarchies based

on rank, personal connections, or ideology. The status of an

economist's work depends , by and large, on its quality, not on

his or her identity.

Clarifying Hypotheses

The grandiosely titled First Fundamental Theorem of Wel

fare Economics is probably the crown j ewel of economics.

(We will meet a close competitor shortly.) First-year doctoral

students typically spend their first semester building up to

a proof of this theorem, picking up a fair bit of mathemat

ics (real analysis and topology) along the way that most will

never use again. The theorem is nothing more than a math

ematical statement of a key implication of what the previous

chapter called the "perfectly competitive market model." It

says, in brief, that a competitive market economy is efficient.

More precisely, under the stated assumptions of the theorem,

the market economy delivers as much economic output as any

economic system possibly could. There is no way to improve

on this outcome, in the sense that no reshuffling of resources

could p ossibly leave someone b etter off without making some

E C O N O M I C S RUL E S

others worse off.* Note that this definition of efficiency

Pareto efficiency, named after the Italian polymath Vilfredo

Pareto-pays no attention to equity or other p ossible social

values : a market outcome in which one p erson receives 99 per

cent of total income would be "efficient" as long as his losses

from any reshuffle exceeded the gains that would accrue to the

rest of society.

Distributional complications aside, this is a powerful result

one that is not obvious. If today we associate markets readily

with efficiency, it is largely because of more than two centu

ries of-let's not b eat around the bush-indoctrination about

the benefits of markets and capitalism. It is not at all evident,

on its face, that millions of consumers, workers , firms, sav

ers , investors, banks, and speculators , each of them pursuing

strictly their own personal advantage, would collectively arrive

at anything other than economic chaos . Yet the model says the

outcome is-- actually efficient.

The First Fundamental Theorem of Welfare Economics is

colloquially known among economists as the Invisible Hand

Theorem. It was Adam Smith, perhaps the father of econom

ics, who first stated it in broad terms. Though he did not use

* The S econd Fundamental Theorem of Welfare Economics, in turn, is

a statement about how alternative efficient outcomes can b e reached via

a suitable redistribution of resources, drawing, in essence, a distinction

between questions of efficiency and distribution. More recent work has

shown how this distinction crumbles when some of the premises of the two

theorems-such as completeness of markets or information-fail to hold.

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

the term " invisible hand " in quite this context, Smith argued

that decentralized decision making by individual consumers

and producers in a market would nonetheless provide collec

tive benefit. "It is not from the benevolence of the butcher, the

brewer, or the baker, that we expect our dinner," he famously

wrote, " but from their regard to their own interest."2

Smith's point that price incentives turn markets into a stu

pendously effective coordination machine running on auto

pilot was brought home powerfully by Milton Friedman in

his popular TV series Free to Choose in 1980, on the eve of a

wave of market reforms under the Reagan and Thatcher gov

ernments. Holding a pencil in his hand, Friedman marveled

at the feat accomplished by free markets: it took thousands of

people all over the world to make this pencil, he pointed out

to mine the graphite, cut the wood, assemble the components,

and market the final product. Yet it was the price system, not

any central authority, that managed to coordinate their actions

so that the pencil would end up in the hands of the consumer. 3

C ompared to Adam Smith's and Milton Friedman's expli

cations , the First Fundamental Theorem itself entails a logic

that is highly abstract and almost impenetrably dense. It was

first formulated fully in the early 1950s by Kenneth Arrow and

Gerard Debreu, using mathematics that was then unfamiliar to

most economists .4 The first sentence of D ebreu's 1951 article

gives a sense of the nature of the exercise: " The activity of the

economic system we study can be viewed as the transformation

by n production units and the consumption by m consump-

E C O N O M I C S RUL E S

tion units of l commodities (the quantities of which may or

may not be perfectly divisible) ."* Even though the Arrow and

Debreu articles are foundational, having earned each econo

mist a Nobel Prize, they are rarely read. (I confess I looked at

them for the first time as I was writing this.) Economists study

them instead from textbooks and other secondhand treatments.

The First Fundamental Theorem is a big deal because it

actually proves the Invisible Hand hypothesis . That is, it shows

that under certain assumptions, the efficiency of a market

economy is not just conj ecture or possibility; it follows logi

cally from the premises. The payoff from all the mathematics is

that we actually have a precise statement. The model shows us

exactly how the result is produced. It reveals, in particular, the

specific assumptions that we have to make to be sure efficiency

is achieved.

There is, in fact, a long list of such assumptions. Consum

ers and producers need to be rational and singularly focused

on maximizing their economic advantage. We have to have

markets in everything, including a full set of futures markets

spanning all possible contingencies. Information has to be

complete-meaning, for example, that consumers are knowl

edgeable about all attributes of a good even before purchasing

and experiencing it. We need to rule out monopolistic behav-

* The j oke is that when Debreu received the Nobel Prize in 1983, he

was accosted by journalists who wanted to know his views about where

the economy was headed. He is said to have thought awhile and then

continued, " Imagine an economy with n goods and m consumers . . . "

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T H E S C I E N C E O F E C O N O M I C M O D E L I N G

ior o n the part o f producers, increasing returns t o scale, and

"externalities" (such as pollution or learning spillovers from

R&D) . Economists from Adam Smith on knew, of course, that

such complications might interfere with the invisible hand. But

Arrow and Debreu put it all together and made it all explicit

and precise.

The First Fundamental Theorem is about a purely hypo

thetical world; it does not claim to describe any actual markets .

Taking it to the real world requires judgment, evidence, and

further theorizing. How one interprets its relevance for eco

nomic policy is a Rorschach test of sorts . For economic liberals

and political conservatives , the theorem establishes the superi

ority of a market-based society. For the left, the long list of pre

requisites demonstrates the virtual unattainability of efficiency

through markets. The theorem on its own settles little in real

world policy debates. But no one could deny that, thanks to it

and the literature it has spawned, we understand much better

than we ever did the circumstances under which Adam Smith's

Invisible Hand does and does not do its j ob .*

Let's turn now to another important example of how eco

nomic modeling helps clarify arguments that may be somewhat

counterintuitive. In 1 9 3 8 , a young Paul Samuelson was chal-

* The assumptions needed to satisfy the Invisible Hand Theorem are

sufficient, not necessary. In other words, markets can be efficient even when

some of the assumptions fail. This bit of leeway enables some economists

to argue that free markets are desirable even when the full Arrow-Debreu

criteria are not met.

5 1

E C O N O M I C S R UL E S

lenged by Stanislaw Ulam, the Polish-American mathemati

cian, to state one proposition in the social sciences that is both

true and nontrivial. Samuelson's answer was David Ricardo's

Principle of Comparative Advantage. "Using four numbers, as

if by magic, it shows that there is indeed a free lunch-a free

lunch that comes with international trade."5 Ricardo's dem

onstration, back in 1 8 17, that specialization according to com

parative advantage produces economic gains for all countries

was as simple as it is powerful. 6 The nontrivial nature of the

principle is obvious by how often it is misunderstood, even

among sophisticated commentators. The antitrade sentiment

attributed to Abraham Lincoln-"when we buy manufactured

goods from abroad, we get the goods and the foreigner gets the

money; when we buy the manufactured goods at home, we get

the goods and we keep the money"-may be apocryphal, but

not many can see easily through its illogic.

It was well understood long before Ricardo that cheap

imports from other nations enabled a nation to economize

on domestic resources such as labor and capital, which could

then be put to alternative uses .7 But how trade could possibly

benefit both sides remained unclear. In particular, if a country

was more efficient across the board, producing all goods while

using fewer resources than other countries did, could it pos

sibly gain from trade as well? Ricardo answered this question

affirmatively. He laid out a numerical example, in what was

one of the very first (and most successful) uses of models in

economics. It was what economists call a 2 X 2 model of trade:

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

two countries (England and Portugal) and two commodities

(cloth and wine) .

Suppose, Ricardo wrote, it takes the labor of 80 workers

to produce a given amount of wine in Portugal, and the labor

of 90 workers to produce a given amount of cloth. In Eng

land, it takes 1 2 0 and 1 0 0 workers , respectively, to produce

the same quantities of the two goods. Note that Portugal is

more efficient than England in both cloth and wine. N everthe

less, Ricardo showed that Portugal would benefit by export

ing wine to England and importing cloth in exchange. This

way, Portugal could "obtain more cloth from England, than

she could produce by diverting a portion of her capital from the

cultivation of vines to the manufacture of cloth."8 What gener

ates the gains from trade is compara tive advantage, not absolute

advantage. A country benefits by exporting what it produces

relatively less badly and importing what it produces relatively

less well.

If this is not clear, remember what Samuelson said: the prin

ciple is not at all obvious . You do need to think and make a few

calculations before it can sink in.

Ricardo's simple model clarified what the gains from trade

did not depend on. A country did not have to be b etter than

its trade partner at producing something to successfully export

it. Neither did it have to be worse to benefit by importing it.

Subsequent tinkering with the model by theorists over gen

erations would clarify other things that the principle did not

depend on. It did not matter how many commodities there

E C O N O M I C S RUL E S

were, or how many countries participated in trade; whether

there were nontraded goods and services in addition to traded

ones; whether trade was balanced in any given period; whether

capital (or other resources) could move easily from one indus

try to another. It turns out none of these simplifications is criti

cal, insofar as the Principle of Comparative Advantage and the

gains from trade are concerned.

Further work would also clarify the principle's limitations .

F o r example, some o f the conditions under which the First

Fundamental Theorem fails can also produce losses from trade.

It is possible to come up with examples in which at least some

countries lose out with trade in the presence of externalities or

scale economies. Developing economies during the 1950s and

1960s became obsessed with this prospect and in response built

up barriers against imports behind which they hoped their

industries would flourish. And even when the gains from trade

are there, theTcerta·inly do not imply that everyone in the nation

will gain from trade. In fact, most extant models conclude that

at least some groups end up worse off-employees of import

competing industries, or unskilled workers in a country that

has a comparatively abundant number of skilled workers, for

example. Someone who advocates free trade because it will

benefit everyone probably does not understand how compara

tive advantage really works.

The Principle of C omparative Advantage and the First

Fundamental Theorem of Welfare Economics are two of the

clearest and most significant instances in which models have

5 4

T H E S C I E N C E OF E C O N O M I C M O D E L I N G

laid bare the nature of economic hypotheses-what they say

exactly, why they work, and the conditions under which we

can expect them to apply. But they are representative of a gen

eral style of inquiry. Is financial speculation good or bad for

stability? Should we help poor families with cash grants or edu

cational subsidies? Should monetary policy be discretionary or

follow strict rules? The economists' approach in each case is to

posit a model and check the conditions under which one or the

other result prevails.

Direct evidence is rarely a substitute for disciplined think

ing of this kind. Let's take an extreme case and suppose we're

given evidence that decisively settles one of these questions.

Such evidence will be necessarily specific to a particular geo

graphic setting and time period: financial speculation did sta

bilize corn futures on the Chicago B oard of Trade between

1 9 9 5 and 2014, or direct cash grants were indeed more effec

tive than subsidies for primary-school children in Tanzania

between 2 0 1 0 and 2 0 1 2 . As useful as evidence of this sort

is, we need to embed it in economic models before we can

interpret it appropriately. For example, were cash grants more

effective than subsidies because of better incentives for fami

lies or b ecause they reduced the workload of the bureaucrats

administering the program? Extrapolating the evidence to

other settings (or the future) also requires the use of models.

Is financial speculation in, say, currency markets also stabiliz

ing? Will speculation in corn futures still stabilize the market

two years hence? Answering such questions requires models-

E C O N O M I C S RUL E S

models that often remain vague and implicit. The more explicit

the models are, the more transparent become the assumptions

we're making to interpret and extrapolate evidence.

When Standard Intuition Fails Us

One of economists' many j okes about themselves is that "an

economist is someone who sees something work in practice,

and asks if it also works in theory." This might seem absurd,

until we realize how easily intuition can lead us astray and

how sometimes life delivers counterintuitive outcomes. Eco

nomic models can train our intuition to take in the possibility

of such unexpected consequences. These surprises come under

vanous gmses.

The first category is "general-equilibrium interactions." To

be distinguished from "partial-equilibrium" or single-market

analysis, the - term is- a fancy way of saying we keep track of

feedback effects across different markets . What happens in,

say, labor markets affects goods markets, which in turn affects

capital markets , and so on. Following this chain often seriously

qualifies-and sometimes reverses-the conclusions of simple

supply-demand models confined to one market at a time.

Consider immigration, a topic of great policy interest m

the United States and other advanced economies. How does

an increase in immigration-in, say, Florida-affect the labor

market in the state? Our immediate intuition would be based

on supply and demand: an increase in the supply of workers

5 6

T H E S C I E N C E OF E C O N O M I C M O D E L I N G

should reduce its price, wages. This impact o f immigration

would be pretty much the end of the story if there were no

second- or third-round effects .

But what iflocal workers responded to the increased compe

tition by moving out of state, to jobs in other parts of the coun

try? What if the availability of a larger employee pool resulted

in greater physical investment in the state, as firms moved in to

build new factories and businesses? What if more workers at the

low end of the skill distribution slowed down the introduction

of new technologies? What if the migrant workers stimulated

demand for the types of goods that are produced by migrant

labor specifically? Each of these possibilities would tend to off

set the initial impact of immigration. Something along these

lines seems to have happened in 1980, when Miami received

a large influx of Cuban immigrants-amounting to 7 percent

of Miami's labor force-during the Mariel boatlift. UC B erke

ley economist David Card found that the influx had virtually

no effect on wages or unemployment in Miami, even among

the least skilled workers, who were the most directly affected.

While the precise reason for this outcome is still debated, it

is likely that some combination of general-equilibrium effects

was at work. 9

Here's another example of how thinking in general

equilibrium terms is important. Suppose you are a highly

skilled professional-an engineer, accountant, or experienced

machinist-working in the US garment industry. Is expanded

foreign trade with low-income countries like Vietnam or

E C O N O M I C S RUL E S

Bangladesh good or bad for you? If you think only about what

happens in the garment industry (that is , in partial-equilibrium

terms) , you'll conclude that you would be worse off. These

countries likely will pose a severe competitive threat to US

garment firms . But now consider the export side. As the wider

US economy increases its exports to those new markets, which

expand thanks to receipts from the United States, new employ

ment opportunities arise in the growing export-oriented

sectors. Since these expanding sectors are likely to be skill

intensive, they will want to hire lots of engineers, accountants,

and experienced machinists. As these multimarket interac

tions work their way through the economy, you may find that

your real compensation ends up higher than before, as demand

increases for your skill set whether you move to another firm

or not.*

Unexpected results also accrue from the economics of "sec

ond best." The- General Theory of Second B est is among the

most useful in the tool kit of applied economists, and perhaps

the least intuitive to the untrained mind . It was first <level-

* This is the remarkable Stolper-Samuelson theorem, an extension of the

basic Principle of Comparative Advantage. It says that opening up to trade

benefits the factor of production that is relatively abundant (regardless of

the sector where it is employed) and hurts the scarce factor. The crucial

assumption it rests on is that different factors of production-workers of

different skill types and c apital-are mobile across industries. Wolfgang

Stolper and Paul A. Samuelson, "Protection and Real Wages," Review of

Economic Studies 9, no. 1 (1941) : 58-73.

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T H E S C I E N C E O F E C O N O M I C M O D E L I N G

aped b y James Meade in the context o f trade policy, and subse

quently generalized by Richard Lipsey and Kelvin Lancaster. 10

Its core insight observes that freeing up some markets , or open

ing a market th�t did not exist before, is not always beneficial

when other, related markets remain restricted.

Early on, the theory was applied to trade agreements among

a group of countries, such as the European Common Mar

ket. In these arrangements, participating countries free up

trade among themselves, reducing or eliminating trade barriers

vis-a-vis each other. The basic intuition from the Principle of

Comparative Advantage suggests that all countries should reap

the gains from trade. But that is not necessarily so. Thanks to

the preferential nature of the barriers, France and Germany

now trade more with each other, which is good. This phenom

enon is known as the "trade creation effect." But for the same

reason, Germany and France may now import even less from

low-cost sources in Asia or the United States, which is bad. In

the j argon, that's called the "trade diversion effect."

To see how trade diversion reduces economic well-being,

imagine that b eef is supplied by the United States to G ermany

at a price of $ 10 0 . Assume that Germany imposes a tariff of

20 percent, raising the consumer price of US beef in the Ger

man market to $ 1 20. France, meanwhile, can supply beef of

equivalent quality only at a price of $1 19. Prior to the preferen

tial agreement between France and Germany, French suppliers,

facing the same tariff rate as US producers, were outcompeted.

Now consider what happens when Germany eliminates its tar-

E C O N O M I C S RUL E S

iffs on imports from France but keeps in place those on the

United States . French-supplied beef suddenly becomes cheaper

in Germany ($ 1 19 versus $ 1 20) , and imports from the United

States . collapse. German consumers are better off by $ 1 , but the

German government forfeits $20 of tariff revenue previously

collected on US beef (which could have b een handed back to

consumers or used to reduce other taxes in Germany) . On bal

ance, Germany gets a raw deal.

" Second best" logic applies to a wide variety of issues. One

of the best known is Dutch disease syndrome, named after the

consequences of the late-1950s discovery of natural gas in the

Netherlands . Many observers subsequently noted that the com

petitiveness of Dutch manufacturing suffered in the 1960s, as

the Dutch guilder strengthened in response to the gas bonanza

and Dutch factories lost market share. The General Theory of

Second Best clarifies the circumstances under which a resource

boom can be (economically) bad news. The boom naturally

crowds out some economic activities-such as manufacturing

because of the currency appreciation.* This in itself is not a prob

lem: structural change is part and parcel of economic progress.

But if the crowded activities were being underprovided in the

first place-either because of government-imposed restrictions

* While currency appreciation is the more immediate mechanism, the

same effect can be caused by an increase in domestic wages. Crowding out

requires simply that domestic wages increase in foreign currency terms,

which can happen because of a rise in wages, an increase in the value of the

domestic currency, or some combination of the two.

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

o r because they were the source o f technological spillovers to

other parts of the economy-then it is different. The economic

losses from the contraction of important activities can even

outweigh the direct gains from the resource boom. This is not

of purely theoretical concern. Governments in resource-rich

countries in sub-Saharan Africa face this challenge on a daily

basis , as wage pressures emanating from lucrative mining activ

ities erode their competitiveness in manufacturing.

Second-best interactions need not always reverse the stan

dard conclusions; sometimes they strengthen the case for mar

ket liberalization. In the Dutch disease example, the adverse

effect on manufacturing would be good news if the declining

industries were " dirty" ones that caused environmental dam

ages they did not pay for. But often the effect is to turn our

standard intuitions upside down, with a move that appears

to be in the right direction instead taking us further away

from the target. Two wrongs can make a right. Since markets

are never textbook p erfect, such second-best problems per

vade real life. As the Princeton economist Avinash Dixit says,

" The world is second-best at best."11 This means we have to

be wary of economists' benchmark models , which presume

well-functioning markets . Often they need to be tweaked by

introducing some of the more salient market imp erfections.

Selecting the right model to apply is key.

Strategic b ehavior and interactions offer a third source of

counterintuitive outcomes. We've already seen an example of

this in the context of the prisoners' dilemma. Opportunistic

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behavior leads in this case to an outcome that each player would

rather avoid. More broadly, as Thomas Schelling observed long

ago, recognizing the presence of strategic interactions-what I

do will affect what you do, and vice versa-can produce actions

that would make little sense otherwise . 12 My threat to bomb

you if you do not meet my demand is not credible as long as

you retain the capacity to retaliate; so the threat is ineffective.

But what if I act "crazy," sowing doubt in your mind that I am

rational in the first place?

Strategic moves, designed to turn the interaction to one

player's advantage, can take varied forms . To convince you

that I will not negotiate my price down further before the

deadline for reaching an agreement, I might simply cut off all

communication-a strategy of " burning bridges." To prevent

you from competing with me, I might build such excess capac

ity that, were you to enter my line ofbusiness, I would have the

incentive to ·· engage - in aggressive price cutting that eventually

would drive both of us into bankruptcy. To increase my trust

worthiness as a borrower, I might contract with a third party

(the mafia?) to impose a large cost on me (break my leg?) if I

fail to pay back the money you lend to me. 1 3 In all these cases,

actions that would not make sense outside the strategic context

suddenly sound plausible in light of the intended goal of alter

ing a competitor's or partner's cost-benefit calculus.

Finally, some counterintuitive outcomes arise out of the

problem of " time-inconsistent preferences," which represent

a conflict, loosely speaking, between what is desirable in the

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

short r u n and what i s desirable in the long run. Politicians may

recognize that printing money only produces inflation in the

long run, but they often cannot resist the temptation to inflate

a little bit right now to stimulate some extra economic activity

before they're up for election. Consumers know they should

save for old age, but often they cannot stop maxing out their

credit cards. These examples are a kind of strategic interaction,

except that the interaction takes place between today's self and

the future sel£ The inability of today's self to commit to the

desirable pattern of behavior harms the future self.

The generic solution to these problems is a strategy of pre

commitment. In the inflation example, the policy maker might

choose to delegate monetary policy to an independent cen

tral bank that is tasked with price stability alone or is run by

an ultraconservative banker. In the saving example, someone

might ask an employer to make automatic deductions to a

retirement plan. The paradox in these cases is that reducing

one's freedom of action can make one b etter off, defying the

usual economic dictum that more choice is always better than

less . But the paradox is only an illusion. What is a paradox

for one class of models is often readily comprehensible within

another class of models.

Scientific Progress, One Model at a Time

Ask an economist what makes economics a science, and the

reply is likely to be, " It's a science because we work with the sci-

6 3

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entific method: we build hypotheses and then test them. When

a theory fails the test, we discard it and either replace it or come

up with an improved version. Ultimately, economics advances

by developing theories that better explain the world."

This is a nice story, but it bears little relationship to what

economists do in practice and how the field really makes prog

ress.* For one thing, much of economists' work departs sig

nificantly from the hypothetico-deductive mold according to

which hypotheses are first formulated and then confronted

with real-world evidence. A more common strategy is to for

mulate models in response to a particular regularity or outcome

that existing models don't appear to explain-for example, the

apparently perverse behavior of banks to ration how much they

lend to firms instead of charging them higher interest rates.

The researcher develops a new model that he or she claims bet

ter accounts for the " deviant" observations.

In the case of eredit-rationing, default risk is a plausible expla

nation: raising interest rates above a certain threshold would

lead the borrower to gamble on increasingly risky projects,

* Ever since Thomas Kuhn's The Structure of Scientific Revolutions (Chicago:

University of Chicago Press, 1 962) , it has become commonplace to

question whether even the natural sciences fit this idealized mold. Kuhn

pointed out that scientists work within "paradigms" that they're unwilling

to give up even in the presence of evidence that violates them. My point

about economics will be different. It is that economics as a science advances

"horizontally" (by multiplying models) rather than "vertically" (by newer

ones replacing older ones).

T H E S C I E N C E OF E C O N O M I C M O D E L I N G

since the losses are capped at the lower end. Thanks to limited

liability, the borrower might not be forced to turn over to his

creditors an amount greater than his marketable assets . 14 The

resulting model might be presented as a deduction from first

principles. That, after all, is the accepted view of economists'

scientific method. But in fact, the thinking that produced the

model involved a large element of induction. And since the

model is specifically devised to account for a particular empiri

cal reality, it can't be directly tested by being confronted with

that same reality. In other words, credit rationing cannot itself

constitute a test of the theory, since it's what motivated the

theory in the first place .

Moreover, even when a truly deductive, hypothesis-testing

approach is followed, much of what economists produce is not

really testable in any strict sense of the word. The field is rife

with models that yield contradictory conclusions, as we've

seen. Yet very few of the models that economists work with

have ever been rejected so decisively that the profession dis

carded them as dearly false. Considerable academic activity

purports to provide empirical support for this or that model.

But these exercises are typically brittle, their conclusions often

weakened (or overturned) by subsequent empirical analysis.

C onsequently, the profession's progression of favored models

tends to follow fad and fashion, or changing tastes about what

is an appropriate modeling strategy, instead of evidence per se.

The sociology of the profession is a subj ect for a later chapter.

The more fundamental point is that the fluidity of social reality

E C O N O M I C S RUL E S

makes economic models inherently difficult, even impossible,

to test. First, the social world rarely delivers clean evidence

that would allow a researcher to draw clear-cut inferences

about the validity of alternative hypotheses . Most questions

of interest-what makes economies grow? does fiscal p olicy

stimulate the economy? do cash transfers reduce p overty?

cannot be studied in the laboratory. The causes we look for

are typically confounded by a jumble of interactions in the

data we have. D espite econometricians' best efforts , convinc

ing causal evidence is notoriously elusive.

An even greater obstacle is that we cannot expect any of

our economic models to be universally valid . O ne can debate

whether there are many universal laws , even in physics.* But,

as I have emphasized repeatedly, economics is something else.

* Here i s the physicist Steven Weinberg: "None of the laws of physics

known today (with the p ossible exception of the general principles of

quantum mechanics) are exactly and universally valid. Nevertheless,

many of them h ave settled down to a final form, valid in certain known

circumstances. The equations of electricity and magnetism that are today

known as Maxwell's equations are not the equations originally written

down by Maxwell; they are equations that physicists settled on after

decades of subsequent work by other physicists . . . . They are understood

today to be an approximation that is valid in a limited context . . . but in

this form and in this limited context they have survived for a century and

may be expected to survive indefinitely. This is the sort of law of physics

that I think corresponds to something as real as anything else we know."

Weinberg, " S okal's Hoax," New York Review of Books 43, no. 13 (August 8 ,

1996) : 1 1-1 5 .

6 6

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

In economic s , context is all. What is true of one setting need

not b e true of another. S ome markets are competitive; oth

ers , not. S ome require second-best analysis ; others may not .

S ome political systems face time-inconsistent problems in

monetary policy; others don't. And so on. It is not surprising

to find-as with, say, privatization of state assets or import

liberalization-that the responses of different societies to

quite similar p olicy interventions often vary greatly. Savvy

economists end up applying different models to make sense

of divergent outcome s . This reliance on multiple models does

not reflect the inadequacy of our models; it reflects the con

tingency of social life .

Knowledge accumulates in economics n o t vertically, with

b etter models replacing worse ones, but horizontally, with

newer models explaining aspects of social outcomes that were

unadd:ressed earlier. Fresh models don't really replace older

ones. They bring in a new dimension that may be more rel- 1

evant in some settings.

Consider how economists' understanding of the most basic

question in economics has evolved: How do markets really

work? In the beginning, the focus was markets that were fully

competitive, with a large number of producers and consum

ers , none of whom could influence market prices . It was in the

context of such competitive markets that the fundamental effi

ciency properties of a market economy were established. But

there was also an early strand of work that analyzed outcomes

when markets were imperfectly competitive, either monopo -

E C O N O M I C S RUL E S

lized by a single producer or dominated by a couple of large

firms . It was well recognized that behavior in these markets

differed profoundly from the competitive benchmark.

Unlike the competitive model, which comes essentially in

unique form, the number and variety of imperfectly competi

tive models are limited only by the researcher's imagination.

In addition to monopolies and duopolies, we have "monopo

listic competition" (a large number of firms , each with market

p ower in a different brand) , B ertrand versus Cournot compe

tition (different assumptions about how prices are set) , static

versus dynamic models (which affect the degree of collusion

that can be sustained by firms), simultaneous versus sequen

tial moves (which determine whether there might be first

mover advantages), and so on. D epending on what we assume

along these and many other dimensions, we have learned from

decades of modeling that imperfect competition can produce

a bewildering array of p ossibilities . More important, thanks to

the transparency of the assumptions, we have also learned what

each one of these outcomes is predicated on.

In the 1970s , economists began to model another aspect of

markets: asymmetric information. This is an important feature

of real-world markets . Workers have a better sense of their abil

ity than do employers. Creditors know whether they are likely

to default or not, while lenders do not. Buyers of used cars

do not know whether they're buying a lemon, but sellers do.

Work by Michael Spence, Joseph Stiglitz, and George Aker

lof showed that these types of markets could exhibit a variety

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

o f distinctive features, including signaling (costly investment

in behavior that has no immediate apparent benefit), rationing

(refusal to provide a good or service, even at a higher price) ,

and market collapse. This work earned these three economists

a j oint Nobel Prize in 2 0 0 1 and spawned a huge literature that

hums along to this day. As a result, we understand much better

the workings of credit and insurance markets, where informa

tion asymmetries are rife.*

Today, economists are increasingly turning their attention

to markets in which consumers do not behave fully rationally.

* In his Nobel address, here's how George Akerlof described the shift in

economic modeling of which he was part: "At the beginning of the 1960s ,

standard microeconomic theory was overwhelmingly based upon the

perfectly competitive general equilibrium model. By the 1990s the study of

this model was j ust one branch of economic theory. Then, standard papers in

economic theory were in a very different style from now, where economic

models are tailored to specific markets and specific situations. In this new

style, economic theory is not j ust the exploration of deviations from the

single model of perfect competition. Instead, in this new style, the economic

model is customized to describe the salient features of reality that describe

the special problem under consideration. Perfect competition is only one

model among many, although itself an interesting special case. Since the

'Market for "Lemons"' [the research that won Akerlof his Nobel Prize] was

an early paper in this new style of economics, its origins and history are a

saga in that change." Akerlof, "Writing the 'The Market for "Lemons"':

A Personal and Interpretive Essay" (20 0 1 Nobel Prize lecture), http://

www. nobelpriz e . org/nobel_prizes/economic-sciences/laureates/20 0 1 /

akerlof-article .html?utm_source=facebook&utm_medium=social&utm_

campaign=facebook_page.

E C O N O M I C S RUL E S

This reorientation has produced a new field called behavioral

economics, which attempts to integrate the insights of psy

chology with the formal modeling approaches of economics .

These new frameworks hold great promise when consumers

behave in ways that cannot be explained by extant models

when, for example, they walk half a mile to get to another

store where a soccer ball sells for $2 less but would not do

the same to save $ 1 0 0 on an expensive stereo . Many standard

conclusions no longer apply when b ehavior is driven by norms

or heuristics-rules of thumb-rather than cost-benefit con

siderations . The irrelevance of sunk costs (payments already

made that cannot be recouped) and the equivalence between

financial costs and opportunity costs (the value of choices not

exercised) do not hold under less than full rationality, to cite

but two examples .

Although grossly simplified, this telescopic account should

give a sense oftfie expanding diversity of the profession's explan

atory models. We have moved beyond competitive models to

imperfect competition, asymmetric information, and b ehav

ioral economics. Idealized, flawless markets have given way to

markets that can fail in all sorts of ways . Rational behavior is

being overlaid with findings from psychology. Typically, the

expansion has its roots in empirical observations that seem

to contradict existing models. Why, for example, were many

firms paying their workers wages that were substantially higher

than the going market wage for apparently similar workers?15

Why would more parents show up late to pick up their kids

T H E S C I E N C E OF E C O N O M I C M O D E L I N G

when the day care center began to charge them. a fine for doing

so?* Each question precipitated new models.

The newer generations of models do not render the older

generations wrong or less relevant; they simply expand the

range of the discipline's insights. The garden-variety perfectly

competitive market model remains indispensable for answering

many real-world questions. We do not have to be concerned

with asymmetric information in a range of contexts-in

repeated purchases of simple consumer goods, for example

b ecause people tend to learn over time relevant characteristics

such as quality and durability. And we would go badly wrong if

we assumed consumer behavior is always driven by heuristics,

with rationality rarely playing a role. Older models remain use

ful; we add to them.

Progress? Yes , definitely so. Economists' understanding of

markets has never been as sophisticated as it is today. But it's

a different kind of progress than in the natural sciences. Its

horizontal expansion does not presume there are fixed laws of

* This is the famous Israeli day care center experiment reported in Uri

Gneezy and Aldo Rustichini, "A Fine Is a Price," Journal of Legal Studies

29, no. 1 Qanuary 2000) : 1-17. The authors interpret the result as a

consequence of modification of the information environment in which

the parents make their decisions, in a way that is more or less compatible

with the usual rationality postulates. An interpretation based on a shift in

norms once the fine has been introduced is provided by Samuel Bowles,

"Machiavelli's Mistake: Why Good Laws Are No Substitute for Good

Citizens" (unpublished book manuscript, 20 14).

E C O N O M I C S RUL E S

nature waiting to be discovered. It seeks instead to uncover and

understand society's possibilities .

Itzhak Gilboa and his coauthors provide a useful analogy in

the _ ir distinction between rule-based and case-based learning. 16

"In everyday as well as professional life," they write, "people

use both rule-based reasoning and case-based reasoning for

making predictions, classifications, diagnostics, and for mak

ing ethical and legal judgments." Rule-based reasoning has

the advantage that it provides a compact way of organizing

a large volume of information, even though it may sacrifice

some accuracy in particular applications. Case-based reason

ing, on the other hand, works via analogies, drawing on other

cases that present similarities . When the relevant data cannot

b e forced into succinct rules without sacrificing too much rel

evance, the case-based approach b ecomes particularly useful.

As Gilboa and his coauthors note, " S ome of the practices that

evolved in economics can be b etter understood if scientific

knowledge can also be viewed as a collection of cases." In this

p erspective, economic science advances by expanding its col

lection of useful cases .

Models and Empirical Methods

The multiplicity of models is economics' strength. But for a

discipline with scientific pretensions, the multiplicity can also

be viewed as problematic. What kind of a science has a dif-

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

ferent model for everything? Can a collection of cases, to use

Gilboa and his coauthors' analogy, really amount to a science?

Yes , as long as we keep in mind that models contain infor

mation about the circumstances in which they're relevant and

applicable. They tell us when we can use them, and when we

might not. To continue the analogy, economic models are cases

that come with explicit user's guides-teaching notes on how

to apply them. That's because they are transparent about their

critical assumptions and b ehavioral mechanisms.

This means that, in any specific setting, we can discrimi

nate , at least in principle, between models that are helpful and

models that aren't. Should we apply the competitive model

or the monopoly model to, say, the PC industry? The answer

depends on whether significant barriers-such as large sunk

costs or anticomp etitive practices-prevent potential com

p etitors from entering the market. Should we worry about

second-best complications like Dutch disease or trade diver

sion? The answer depends largely on whether specific market

imperfections-technological spillovers from manufacturing

and trade barriers against third countries , respectively-are

present and important . Actually, a lot more goes into this pro

cess of navigating among models, as I ' ll discuss more exten

sively in the next chapter. But precisely b ecause models lay

bare how specific assumptions are needed to produce certain

results , they can be sorted by context. The multiplicity of

models does not imply that anything goes. It simply means we

E C O N O M I C S RU L E S

have a menu to choose from and need an empirical method for

making that choice.

I do not want to claim that empirical verification necessar

ily or always works well. But even when the empirical data are

inconclusive, models enable rational and constructive debate

because they clarify sources of disagreement. In economics,

policy discussion usually means pitting one model against

another. Viewpoints and policy prescriptions that aren't backed

by a model typically don't have standing. And once the models

are produced, it becomes clear to all what each side assumes

about the real world. This may not resolve the disagreement.

Indeed, typically it doesn't, given the different ways that each

side is likely to read reality. But at least we can expect that the

two sides will eventually agree on what they disagree about.

These kinds of debates take place endlessly in economics .

For example, the controversy over the effects of redistributive

taxation largely boils down to the shape of the labor supply

curve of entrepreneurs. Those who think that entrepreneur

ship does not respond much to income incentives are much

less worried about raising taxes than are those who believe

that entrepreneurship is highly sensitive to incentives. Prob

ably the topics that provoke the fiercest debates in the profes

sion are the roles of monetary and fiscal policy in a recession.

These debates are essentially about whether recovery is ham

p ered by the economy's demand curve or supply curve. If

you believe aggregate demand is repressed, you will generally

be in favor of monetary and fiscal stimulus. If you think the

T H E S C I E N C E OF E C O N O M I C M O D E L I N G

problem is supply shock-because of excessive taxation, say,

or policy uncertainty-your remedies will be quite different.

Occasionally, empirical evidence will accumulate to the point

where the profession's preference for one set of models over

another will become overwhelming. This is what happened,

for example, in development economics, where the hypothesis

of the ignorant peasant was discarded in the 1960s in favor of

models of the calculating peasant, once it became clear that

poor farmers' responsiveness to prices was much greater than

many had thought.*

O ne debate I've been involved in focuses on the role ofindus

trial policy in low- and middle-income countries.17 These are

government policies such as cheap credit or subsidies designed

to foster structural change, from traditional low-productivity

activities such as subsistence agriculture to modern, produc

tive industries such as manufacturing. Critics have tradition

ally scoffed at them by calling them a strategy of "picking

winners"-a fool 's errand, in other words. E conomic research

has clarified over the years that the rationale for such policies

is quite strong in the environment that characterizes develop

ing economies. For a variety of reasons, related to both market

and government failures, modern firms and industries would

be smaller than they should be if left to market forces alone.

* Theodore W. Schultz, a Nobel Prize winner, led the way. Schultz,

Transforming Traditional Agriculture (New Haven, CT: Yale University Press,

1964) .

E C O N O M I C S RUL E S

Research has also shown that governments have many ways of

stimulating positive structural change without picking winners

by investing in a portfolio of new industries as venture capital

firms do, for example. Above all, various models have clarified

that the real debate is not about industrial policy and econom

ics, but about the nature of government. If government can be a

force for good and intervene effectively, at least occasionally, then

some kind of industrial policy should be favored. If instead gov

ernment is hopelessly corrupt, industrial policy will likely make

things worse. Note how, in this case, research has pushed the

disagreement onto a domain-public administration-in which

economists have no particular expertise.

Models, Authority, and Hierarchy

Two well-known economists, Carmen Reinhart and Kenneth

Rogoff, published a paper in 2 0 1 0 that would become fodder

in a political battle with high stakes.18 The paper appeared to

show that public-debt levels above 90 percent of GDP signifi

cantly impede economic growth. C onservative US politicians

and European Union officials latched on to this work to justify

their ongoing call for fiscal austerity. Even though Reinhart

and Rogoff's interpretation of their results was considerably

more cautious, the paper b ecame exhibit A in the fiscal con

servatives' case for reducing public spending despite the eco

nomic downturn.

T H E S C I E N C E OF E C O N O M I C M O D E L I N G

A graduate student in economics at the University of Mas

sachusetts at Amherst, Thomas Herndon, then did what aca

demics are routinely supposed to do: replicate others' work and

subj ect it to criticism. Along with a relatively minor spread

sheet error, he identified some methodological choices in the

original Reinhart-Rogoff work that threw the robustness of

their results into question. Most important, even though debt

levels and growth remained negatively correlated, the evidence

for a 90 percent threshold appeared weak. And, as many others

also had argued, the correlation itself could be the result oflow

growth leading to high indebtedness, rather than the other way

around. When Herndon published his critique, coauthored

with UMass professors Michael Ash and Robert Pollin, it set

off a firestorm. 1 9

B ecause the 90 percent threshold had become politically

charged, its subsequent demolition also gained broader politi

cal meaning. Reinhart and Rogoff vigorously contested accu

sations by many commentators that they were willing, if not

willful, participants in a game of political deception. They

defended their empirical methods and insisted that they were

not the deficit hawks their critics p ortrayed them to be. Despite

their protests, they were accused· of providing scholarly cover

for a set of policies for which there was , in fact, limited sup

porting evidence.

The controversy over the Reinhart-Rogoff analysis over

shadowed what, in fact, was a salutary process of s crutiny

E C O N O M I C S RUL E S

and refinement of economic research. Reinhart and Rogoff

quickly acknowledged the spreadsheet mistake they had made.

The dueling analyses clarified the nature of the data, their limi

tations, and how alternative methods of processing changed

the results. Ultimately, Reinhart and Rogoff were perhaps not

that far apart from their critics on either what the evidence

showed or what the policy implications were; they certainly

did not believe in a rigid threshold of 90 percent, and they

agreed that the correlation b etween high debt and low growth

could have different interpretations. The episode's silver lining

reveals that economics can progress by the rules of science.

No matter how far apart their political views may have been,

the two sides shared a common language about what consti

tutes evidence and-for the most part-a common approach to

resolving differences.

The fracas was frequently portrayed in the media as two

world-famous Harvard professors brought low by a graduate

student from a lesser-known, unorthodox department. This is

largely hyperbole. But the clash did illustrate an import aspect

of economics-something that the profession shares with other

sciences: Ultimately, what determines the standing of a piece of

research is not the affiliation, status, or network of the author;

it is how well it stacks up to the research criteria of the profes

sion itself The authority of the work derives from its internal

properties-how well it is put together, how convincing the

evidence is-not from the identity, connections, or ideology of

the researcher. And because these standards are shared within

7 8

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

the profession, anyone c a n point t o shoddy work and say it

is shoddy.*

This may not seem particularly impressive, unless you con

sider how unusual it is compared to many other social sciences

or much of the humanities .t It would be truly rare in those

other fields for a graduate student to get much mileage chal

lenging a senior scholar's work, as happens with some frequency

* On the difference between social sciences whose standards of

argumentation and evidence pass this test and those whose standards do not,

see Jon Elster, Explaining Social Behavior: More Nuts and Bolts for the Social

Sciences (Cambridge: Cambridge University Press, 2007), especially pp.

445-67. A very different interpretation of economics is provided in Marion

Fourcade, Etienne Ollion, and Yann Algan, The Superiority of Economists,

MaxPo Discussion Paper 14/3 (Paris: Max Planck Sciences Po Center on

Coping with Instability in Market Societies, 2014). These authors interpret

the consensus on the academic hierarchy within the discipline as a tight

form of control exercised by the top departments in the discipline. The

sharing of norms about what constitutes good work, as in many natural

sciences, is an equally plausible explanation for this consensus.

t In a famous hoax, physicist Alan Sokal submitted an article to a leading

journal of cultural studies purporting to describe how quantum gravity

could produce a "liberatory postmodern science." The article, which

parodied the convoluted style of argument in the fashionable academic world

of cultural studies, was promptly published by the editors. Sokal announced

that his intention was to test the intellectual standards of the discipline by

checking whether the journal would publish a piece "liberally salted with

nonsense." Sokal, "A Physicist Experiments with Cultural Studies,'' April

1 5 , 1996, http://www.physics.nyu. edu/sokal/lingua_franca_ v4.pdf.

7 9

E C O N O M I C S RUL E S

in economics. But because models enable the highlighting of

error, in economics anyone can do it.

There is a flip side to this apparent democracy of ideas

that is less salutary. B ecause economists share a language and

method, they are prone to disregard, or deprecate, nonecono

mists' points of view. Critics are not taken seriously-what is

your model? where is the evidence?-unless they're willing to

follow the rules of engagement. Only card-carrying members

of the profession are viewed as legitimate participants in eco

nomic debates-hence the paradox that economics is highly

sensitive to criticism from inside, but extremely insensitive to

criticism from outside.

Wrong versus Not Even Wrong

The Swiss-Austrian physicist Wolfgang Pauli, a pioneer of

quantum physics , was known for his high standards and cut

ting wit. As a young and unknown student, he once endorsed

a comment made by Einstein in a colloquium by saying "You

know, what Mr. Einstein said is not so stupid." Pauli was par

ticularly critical of arguments that had scientific pretensions

but were poorly stated and had no way of b eing tested. Upon

b eing shown such a work by a younger physicist, his response

was , " It's not even wrong."20

What Pauli probably meant is that it was impossible to chal

lenge the work because no clear, coherent argument had b een

put forth. The assumptions, causal links, and implications were

T H E S C I E N C E O F E C O N O M I C M O D E L I N G

so vague as to render the supposed contribution irrefutable

under any circumstances. "It's not even wrong" is just about as

damning a comment for scholarly effort as one might imagine.

Having sat through quite a few talks that left me with precisely

this sentiment, I can attest that it is not an irregular occurrence.

My obvious bias aside-and apologies to my noneconomist

colleagues-obscurity of this kind happens a lot less frequently

in economics than in other disciplines.

The scientific status I have claimed for economics is not a

particularly exalted one . It lies far from the p ositivist ideal, first

articulated by the French philosopher Auguste Comte in the

early part of the 19th century, whereby a combination of logic

and evidence produces ever-higher degrees of certainty about

the nature of social life .* B oth the generality and the testabil

ity of economic propositions are limited. Economic science is

merely disciplined intuition-intuition rendered transparent

by logic and hardened by plausible evidence. "The whole of

science," Einstein once said, " is nothing but a refinement of

everyday thinking."21 At their best, economists' models pro

vide some of that refinement-and not much more.

* My take on economics is, in fact, much closer to the pragmatist tradition

in epistemology than to the positivist one.

CHAP T ER 3

Navigatin g anion g Models

makes economics a science is models. It

b ecomes a useful science when those models

are deployed to enhance our understanding of

how the world works and how it can be improved. Identifying

which models to use means parsing and selecting-focusing

on models that seem relevant and helpful to a specific setting,

while discarding the rest. How this sifting is done in practice

or more important, how it should be done-is the subj ect of

this chapter. But first a warning: these methods are as much

craft as they are science. Good judgment and experience are

indispensable, and training can get you only so far. Perhaps as

a consequence, graduate programs in economics pay very little

attention to craft.

Freshly minted PhDs come out of graduate school with a

large inventory of models but virtually no formal training-no

course work, no assignments, no problem sets-in how one

E C O N O M I C S RUL E S

chooses among them. The models they end up working with

are typically the newest, the ones that have caught the profes

sion's interest in the most recent generation of research. Gradu

ates who eventually b ecome good applied economists pick up

the requisite skills along the way, as they are confronted with

policy questions and challenges during their professional lives.

But unfortunately, few able practitioners bother to systematize

what they've learned, in the form of books or articles, for the

benefit of less experienced members of the discipline.

Model selection also gets short shrift in economics in light of

the profession's official take on what kind of science it is . As I 've

discussed already, the party line holds that economics advances

by improving existing models and testing hypotheses. Models

are continually refined until the true universal model comes

into view. Hypotheses that fail the test are discarded; those that

pass are retained. This way of thinking leaves little room for

the idea that economists have to carry multiple models in their

heads simultaneously, and that they must build maps between

specific settings and applicable models .

If all that economists do is expand the library of models-if,

in other words, they are pure theorists-they can't do much

harm. But most economists are engaged also in more practi

cal things . In particular, they are interested in two related

questions: how does the world really work, and how can we

improve on the state of things? To j udge by the attention their

work gets in public discussion, the world expects practical

relevance of them to o. Answering the second of these ques-

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N AV I GA T I N G AM O N G M O D E L S

tions usually requires having a n answer t o the first. The posi

tive and the normative analyses-investigations, resp ec tively,

of what is and what should be-are deeply intertwined . In

economists' terms , both questions translate to this: What is

the underlying model?

I have stressed that a model is never an accurate descrip

tion of any reality. As David Colander and Roland Kupers put

it, " Scientific models provide, at best, half-truths."1 So when

economists ask, "What is the underlying model? " they are

not asking for the best possible representation of the market,

region, or country they happen to be analyzing. Even if they

could develop such a representation, it would be far too com

plicated and thus useless . They are asking for the model that

highlights the dominant causal mechanism or channels at work.

This model will provide the best explanation of what's happen

ing and stands the best chance of predicting the consequences

of our actions.

Imagine that your car has a problem and you want to figure

out what's wrong and how to fix it . You could pick apart the

entire car, piece by piece, in the hope of eventually encoun

tering the broken part. This is not merely time-consuming,

but may not even lead you to the solution. A car is a system,

after all. The problem may reside in the way different compo

nents relate to each other-or fail to relate-instead of in spe

cific components. Alternatively, you could try to diagnose first

which of the car's many subsystems-brakes , transmission, and

so on-led to the malfunction. Your diagnosis can draw from a

E C O N O M I C S RUL E S

wide variety of signals: what happened just before the car broke

down, how the car responds as you turn the ignition on, and

of course, the more thorough software-based diagnostics that

today's repair shops routinely use. The exercise will eventually

lead you to the culprit: perhaps the cooling or ignition system.

Now you can focus only on the subsystem that needs fixing.

All parts of the car are required for it to run: transmission,

cooling, ignition. So we can say they are all "causal " to the

movement of the car. But the dominant mechanism in explain

ing the failure is only one of these. The rest are incidental to

the question at hand. A more complicated and realistic model

of the car-say, a full-size working replica, like Jorge Luis

Borges's famous map the size of the world-wouldn't be of

much help. What helps is knowing what to fo cus on. By the

same token, the "correct" economic model is the one that iso

lates the critical relationships, allowing us to understand what

is really caus.al among all the things going on. And the way we

arrive at the right model is not very different from the kind of

diagnostics we perform on a car.

Diagnostics for Growth Strategy

My own aha! moment about diagnostics came as I was assist

ing governments of developing nations with their economic

programs. The countries varied greatly-from South Africa to

El Salvador, from Uruguay to Ethiopia. But in each case my

colleagues and I faced the same central question: what kinds

N AV IGAT I N G AMO N G M O D E L S

o f policies should the government adopt t o increase the econ

omy's growth rate and raise the incomes of all social strata, the

disadvantaged groups in particular.

There was typically no shortage of proposals for reform.

• S ome analysts would focus on skills, training, and improv

ing the country's base of human capital.

• Some would focus on macroeconomic policy, recommend

ing ways to strengthen monetary and fiscal policies.

• S ome thought the country needed greater openness to trade

and foreign investment.

• S ome said taxes on private enterprise were too high and

there were too many other costs of doing business.

• S ome recommended industrial policies to restructure the

economy and foster new, high-productivity industries .

• Some advised tackling corruption and strengthening prop

erty rights.

• S ome came down in favor of infrastructure investments.

Until recently, multilateral institutions such as the World

Bank usually would have thrown all these recommendations

into a document and, voila! we would have a growth strategy.

By the 1990s, policy makers were forced to acknowledge that

this process did not work very well. A laundry-list approach

to developing policy presented governments with an impos

sibly ambitious agenda that they had no chance of implement

ing. Governments invariably failed to deliver on most of the

E C O N O M I C S RUL E S

intended reforms. And those they did follow through on were

not necessarily the most important ones, so the economies'

response remained tepid. Meanwhile, outside advisers would

skirt blame by pointing to "slippages in reform" or "reform

fatigue" on the part of their clients. 2

My colleagues and I advocated a more strategic approach,

prioritizing a narrower range of reforms. The reforms had to

be targeted at the largest obstacles, avoiding the risk that gov

ernments would waste large amounts of political capital with

little economic growth in return. But which reforms, among

the long list above, fit the bill?

The answer dep ended on the favored model of growth.

Those of us who lo oked at growth from the perspective of

the "neoclassical mo del " emphasized the supply of physi

cal and human c apital and the barriers it faced. Those who

preferred " endogenous" growth models , in which growth

is driven by investment in new technologies, homed in on

the environment for market comp etition and innovation.

Those who had worked intensively with models that put

institutional quality at center stage concentrated on property

rights and contract enforcement. Those who were steeped

in " dual economy" models would look at the conditions fo r

structural transformation and t h e transition fr o m traditional

economic activities such as subsistence agriculture to mod

ern firms and industries . E ach one of these models provided

a different entry p oi nt to the problem and emphasized a dif

ferent set of p riorities .

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N A V I GA T I N G AM O N G M O D E L S

Once it became clear that our differences on policy were the

result of favoring different models, the discussion became a lot

clearer. Now we could understand where each one of us was

coming from. More important, we could begin to narrow our

differences by confronting the separate models informally with

the evidence at hand. What should we be seeing if this or that

model was true-that is, captured the most important mecha

nism behind growth in that particular setting? What kind of evi

dence would help us determine the more relevant of two models

with different implications? Since we did not have the luxury

of waiting for all the needed data to accumulate, or to carry out

randomized or laboratory experiments on actual economies, we

had to do this in real time, with the evidence at hand.

Eventually, we developed a decision tree that helped us navi

gate across potential models. 3 The tree looks something like

the chart shown on the next page, which omits many of the

details . We would start at the top of the tree by asking whether

the constraints on investment were mainly on the supply side or

on the demand side. In other words, was investment depressed

because of inadequate supply of funds or poor returns? If the

constraints were on the supply side, we would ask whether they

were due mainly to a lack of saving or to a poorly functioning

financial system. If they were on the demand side, we would

ask whether private returns were low because of market or

government failures. If the culprit seemed to be government

failures, was this a matter of high taxes, corruption, or policy

instability? And so on.

E C O N O M I C S RUL E S

Output/Income

I Physical capital I I Human capital I Employment I Productivity / ' / ' / ' / '

Supply- Supply- Demand- Supply- Demand- Supply- Demand- side side side side side side side problems problems problems problems problems problems problems

Low private returns and therefore inadequate demand for investment due to:

Government failures

Market failures

Problems in other markets

High taxes ; poor protection of property rights or contracts ; corruption; macroeconomic instability and inflation; . . .

Product market failures (coordination failures, learning externalities, and spillovers): . . .

Inadequate levels of other inputs in the production function: human capital, employment, technology; poor geography; . . .

F R O M G R O W T H M O D E L S TO G R O W T H D I AG N O ST I C S .

S o u rce: D a n i R o d r i k, " D i a g n o s t i c s before P r e s c r i p t i on," Journal o f Economic Perspectives 24, n o . 3

(S u m m e r 2010): 33-44. N ote: O n ly s o m e of t h e d e t a i l s are s h o w n .

At each node of the decision tree, we tried to develop infor

mal empirical tests to help us select among models that would

send us down different paths . For example, when the main

problem of an economy is inadequate supply of capital, as in the

neoclassical growth model, borrowing costs will be inversely

related to investment. Reductions in the cost of capital will

be associated with a strong investment response. Further, any

increase in transfers from abroad, such as workers' remittances

or foreign aid, will ignite a domestic investment boom. Sec-

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N AV I GA T I N G AM O N G M O D E L S

tors that are the most capital-intensive o r most dependent on

borrowing will be those that have the slowest growth. Did the

implications of the model match up with observed b ehavior of

the economy in question? If yes , the answer to "What is the

underlying model? " might indeed be a version of the neoclas

sical growth model.

O n the other hand, in an economy constrained by invest

ment demand, private investment would respond primarily to

profitability shocks in goods markets. When entrepreneurs are

deterred by corruption, for example, their primary concern

will be whether they can retain the returns on their invest

ments . Availability of funds will not make much difference to

their behavior. A surge in remittances or foreign capital inflow

would produce a boom in consumption rather than investment.

(This is the case shown in the chart.) These, too, are implica

tions that could be checked against observed reality. 4

Even though the available evidence rarely settled such ques

tions once and for all, it was often possible to pare down a long

catalog of failures to a considerably shorter list. In the case of

South Africa, we were able to dismiss fairly quickly some of the

conventional culprits that preoccupied policy makers: short

age of skills, poor governance, macroeconomic instability, bad

infrastructure, or lack of openness to trade. The recent b ehavior

of the economy did not support a conclusion that any of these

were maj or constraints. The model-based approach forced us

to think in economy-wide (that is, general-equilibrium) rather

than partial-equilibrium terms. For example, business people

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E C O N O M I C S RUL E S

would complain about the difficulty of finding skilled work

ers , which had led many observers to believe skill shortages

were a n1aj or obstacle. But this conclusion was belied by the

fact that the most rapidly expanding segments of the economy

had been, in fact, the skill-intensive parts , such as financ e .

Whatever was holding back the economy as a whole could not

have been lack of skills . The framework instead revealed a few

critical problem areas-the high cost of unskilled labor and

the lack of competitiveness of most manufacturing industries

in particular. 5

The virtue of diagnostic analysis is that it does not presume

that a single model applies to all countries. When we worked

on El Salvador, in Central America, we concluded that a model

with market failures in modern industries provided a better

account of the economy's woes. Low investment and growth

could not be explained by inadequacy of funds, p oor institu

tions and policies, low skills, high cost of labor, or other pos

sible factors . For example, the Salvadoran economy received

plenty of remittances from abroad and had good access to

international capital markets , thanks to its credit rating. So

the problems were not on the supply side of investment. L ow

investment seemed instead to be the product of difficulties that

firms faced in getting started in the more modern, productive

parts of the economy. Some of these difficulties arose from per

vasive coordination failures, of the type I discussed in Chapter

1 . For instance, pineapple canneries could not operate profit

ably without frequent air cargo service to the US market. But

N AV IGAT I N G AMO N G M O D E L S

the cargo service was not profitable without a large number of

existing exporters, such as pineapple canneries. Other prob

lems included inadequate information on costs and markets in

new lines of business, given the absence of pioneer firms whose

experience could have otherwise provided valuable signals to

aspiring entrants. Our policy recommendations correspond

ingly focused on these particular problem areas. 6

Nor does the diagnostic approach presume that the under

lying model remains the same over time for a given country.

As circumstances change, a different model may become more

relevant. In fact, if the initial diagnosis is largely correct and the

government effectively addresses the problems, the underlying

model, by necessity, will be transformed. For example , as mar

ket failures in modern manufacturing industries are overcome,

infrastructure constraints (for example, ports, energy) may

become much more severe. Or skill shortages may b ecome the

more dominant obstacle. Model selection is a dynamic process,

not a onetime affair.

General Principles of Model Selection

Let's step back now from the specifics of growth diagnostics.

Experience helps to highlight some general rules and practices .

The key skill is b eing able to move back and forth between the

candidate models and the real world. Let's call this "verifica

tion." The process of model selection relies on some combina

tion of four separate verification strategies :

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E C O N O M I C S RUL E S

1 . Verifying critical assumptions of a model to see how well

they reflect the setting in question

2. Verifying that the mechanisms p osited in the model are,

in fact, operating

3. Verifying that the direct implications of the model are

borne out

4. Verifying whether the incidental implications , those that

the model generates as a by-product, are broadly consis

tent with observed outcomes

Verifying Critical Assumptions

As I've already discussed, what matters to the empirical rel

evance of a model is the realism of its critical assumptions. These

assumptions would produce a substantively different result if

they were altered to be more realistic. Many assumptions may

be harmless in this sense. Others can be critical for some types

of questions the model answers but not for others.

Consider a case in which a government concerned with the

high price of oil is contemplating a price cap. Answering this

question requires a view-a model-of how the market for

oil works. Let's simplify things greatly and restrict our atten

tion to two contending models: the competitive model and

the monopoly model. Proponents of the competitive model see

high prices as the result of too little supply relative to demand.

N AV I GA T I N G AM O N G M O D E L S

In this model a price cap-a ceiling above which oil companies

cannot charge more-would not be particularly effective. It

would create a gap between the amount of oil that consumers

demanded and the amount that producers were willing to sup

ply. There would be rationing, queues, or some other way of

eliminating the gap. The market price of oil would, in fact, be

likely to rise as total supply fell. Some people might get the oil

at a cheaper price by being at the front of the queue or by being

allotted rations, but others would surely pay the higher price.

Not a very goo d policy overall.

Proponents of the monopoly model see high prices as the

result of the oil industry acting as a cartel. In this model the

industry would create an artificial shortage by withholding sup

plies from the market in order to engineer a price rise, thereby

increasing the industry's profits. A price cap would produce

very different results in this model. Once the cap was instituted,

firms would no longer be able to determine market prices by

changing how much they sold. They would now act as price

taking firms; in other words, they would behave in the same

way that firms in the competitive model would.* If the price cap

was not set too low, the total supply would rise and the market

price would fall. The cartel would collapse, and the price cap

would be effective because it acted as a trust-busting p olicy.

* I'm neglecting here some questions about the mechanism by which

the cartel operates, and assuming simply that the cartel acts like a unified

monopoly.

E C O N O M I C S RUL E S

What are the critical and noncritical assumptions in these

models' descriptions of the world? First, both models are about

the supply side of the industry-how the oil firms behave.

Therefore we can leave aside their assumptions about consum

ers and how they make their choices. Whether they are fully

rational, p ossess full information, vary in their incomes and

preferences, or have long time horizons is not of much inter

est. The only critical assumption on the demand side is that

there is a downward-sloping market demand curve, meaning

that an increase in the price of oil causes a reduction in the

quantity of oil consumed, everything else remaining the same .

This proposition is plausible under a very large range of cir

cumstances and can be empirically verified. These other issues

may b ecome critical in some contexts-for example, when

we're discussing the distributional effects of oil taxes-but they

do not help us choose between the two contending models

in this case. The -second assumption is that strategic dimen

sions besides price-setting b ehavior do not play a role either. So

we may also ignore implicit or explicit assumptions about, say,

firms' hiring or advertising strategies .

The truly critical assumption here is that firms have market

power in one case and not in the other. In the monopolistic

model they think they can raise the market price by restricting

supply, whereas in the competitive model they hold no such

hope. In some ways, this is an assumption about firms' psychol

ogy. We cannot get into their managers' heads to figure out

what they really believe. Asking them the question point-blank

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N AV IGAT I N G AM O N G M O D E L S

i s not likely t o yield a reliable answer, given their stake i n the

issue. But we can examine prevailing conditions to see whether

a particular set of beliefs is more plausible.

The number and size distribution of firms in the industry

will play an important role . If the number is large and there

are no dominant firms, it is unlikely that firms will be able to

or will act noncompetitively. How easily new firms can enter

the industry is another important consideration. Even if few

firms currently occupy the space, the threat of new competi

tors will deter them from exercising market power. Moreover,

the oil industry is global rather than national. Comp etition

from foreign producers can act as a source of market disci

pline at the margin, even when import volumes are small.

Finally, the more easily consumers can substitute between oil

and alternative sources of energy, the less likely it is that oil

firms will be able to exert market power. Each one of these

factors can be observed and measured in principle. I ndeed,

national antitrust authorities routinely p erform this kind of a

diagnostic exercise when they suspect that firms have (and are

abusing) market power.

Models often make assumptions that are critical but unstated.

Failing to scrutinize those assumptions can lead to severe pro b

lems in practice. Economists and policy makers learned this the

hard way during the 1980s-90s frenzy over market liberaliza

tion. Freeing up prices and removing market restrictions, many

thought, would be enough for markets to work and allocate

resources efficiently. But all models of market economies pre-

E C O N O M I C S RUL E S

sume the existence of various social, legal, and political insti

tutions. Property rights and contracts must be enforced, fair

competition must be ensured, theft and extortion must be pre

vented, and justice must be administered. Where those insti

tutional underpinnings are nonexistent or weak, as in much

of the developing world, freeing up marke_ts not only fails to

deliver the expected results, but also can backfire. Privatization

of state enterprises in the former Soviet Union, for example,

often empowered insiders and political cronies instead of pro

ducing efficient markets . The critical assumptions behind mar

ket efficiency were obscured by the fact that advanced market

economies already have strong market-supporting institutions.

Western economists took them for granted.

Once their blind spot was revealed by the disappointing

performance of developing and p ostsocialist economies , prac

titioners reacted in the usual way: by developing a new crop

of models that underscored the importance of institutions .

This was a rediscovery of an old insight: Adam Smith himself

had stressed the role of the state in ensuring conditions of free

competition, and economic historians like Douglass North had

long pointed to improved property rights as a reason for the

rise of Britain as an economic power. 7 The formalization and

extension of these ideas helped economists to understand better

how economic outcomes depend on the presence, variety, and

shape of those institutions. Thanks to these models, the critical

role that institutions play in driving economic performance has

come back to the fore.

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N AV I GA T I N G AM O N G M O D E L S

Verifying Mechanisms

Models generate conclusions by pairing assumptions with

mechanisms of causation. In the oil industry example, the rela

tionship between firms' supply and the market price is a criti

cal mechanism: when the industry restricts supply, the market

price goes up; when supply is increased, the market price goes

down. Note that the models do not assume this is how the

world works; they derive it as an implication. The relationship

between industry supply and market prices is not an assump

tion, but a result that follows from the assumptions, in particular,

that demand curves slope downward and that market prices are

determined by equating the quantities demanded and supplied.

In our oil example, this is a fairly innocuous mechanism

that passes the verification test comfortably. The relationship

between quantities supplied and prices makes sense intuitively,

and there are plenty of real-world examples in which shocks to

supply have had observable effects on prices in the hypothesized

direction; consider the oil shock of 1 973-74, for example. We

do not need to have seen a demand curve or know what the

technical definition of a market equilibrium is-both abstract

concepts that do not have physical counterparts-to believe

that the mechanism the model relies on is reasonable. But in

other cases, the mechanism may result from more complicated

behavior and may require greater justification. When the jus

tification is weak, we should be concerned about whether the

model in question really applies.

E C O N O M I C S RUL E S

Consider the Dutch disease model again. It explains how the

discovery of a natural resource can harm an economy's perfor

mance through a particular channel. As a result of the resource

boom, the country's exchange rate appreciates and manufac

turing's profitability declines . Since manufacturing is thought

to be a source of technological dynamism ("positive spill

overs ," in economists' parlance) for the economy as a whole,

the hit that manufacturing takes translates into broader losses.

The link between the real exchange rate and the health of the

manufacturing sector is critical here. If we want to apply it to

understand what happened in a resource-rich country, we need

to convince ourselves that the manufacturing sector's position

did deteriorate. If no real-world evidence supports the model's

operative mechanism, the model probably isn't a good guide to

what is really going on. We may need to turn to an alternative

model that explains why resource booms can be bad news. For

example, we may-examine a model in which resource revenues

induce conflict among competing elites, sparking internal strife

and instability. The causal mechanism now is quite different,

but it remains subj ect to verification.

Verifying Direct I mplications

Many models are constructed to account for regularly observed

phenomena. By design, their direct implications are consistent

with reality. But others are built up from first principles , using

the profession's preferred building blocks . They may be math-

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N AV IGAT I N G AM O N G M O D E L S

ematically elegant and match up well with the prevailing mod

eling conventions of the day. However, this does not make

them necessarily more useful, esp ecially when their conclu

sions have a tenuous relationship with reality.

Macroeconomists have been particularly prone to this prob

lem. In recent decades they have put considerable effort into

developing macro models that require sophisticated mathemat

ical tools, populated by fully rational, infinitely lived individu

als solving complicated dynamic optimization problems under

uncertainty. These are models that are "microfounded," in the

profession's parlance: The macro-level implications are derived

from the b ehavior of individuals, rather than simply postu

lated. This is a good thing, in principle. For example, aggre

gate saving b ehavior derives from the optimization problem in

which a representative consumer maximizes his consumption

while adhering to a lifetime (intertemporal) budget constraint.*

Keynesian models, by contrast, take a shortcut, assuming a

fixed relationship between saving and national income .

However, these models shed limited light on the classical

questions of macroeconomics: Why are there economic booms

and recessions? What generates unemployment? What roles can

fiscal and monetary policy play in stabilizing the economy? In

trying to render their models tractable, economists neglected

* An early example of these "real business cycle" (RBC) models is Finn

E. Kydland and Edward C. Prescott, "Time to Build and Aggregate

Fluctuations," Econometrica 50, no . 6 (1982) : 1345-70.

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E C O N O M I C S RUL E S

many important aspects of the real world. In particular, they

assumed away imperfections and frictions in markets for labor,

capital, and goods . The ups and downs of the economy were

ascribed to exogenous and vague "shocks" to technology and

consumer preferences. The unemployed weren't looking for

j obs they couldn't find; they represented a worker's optimal

trade-off between leisure and labor. Perhaps unsurprisingly,

these models were poor forecasters of maj or macroeconomic

variables such as inflation and growth. 8

As long as the economy hummed along at a steady clip and

unemployment was low, these shortcomings were not partic

ularly evident. But their failures become more apparent and

costly in the aftermath of the financial crisis of 2008-9. These

newfangled models simply could not explain the magnitude

and duration of the recession that followed. They needed, at

the very least, to incorporate more realism about financial

market imperfections. Traditional Keynesian models, despite

their lack of microfoundations, could explain how economies

can get stuck with high unemployment and seemed more rel

evant than ever. Yet the advocates of the new models were

reluctant to give up on them-not b ecause these models did

a b etter j ob of tracking reality, but because they were what

models were supposed to look like. Their modeling strategy

trumped the realism of conclusions.

Economists' attachment to particular modeling conven

tions-rational, forward-looking individuals, well-functioning

markets , and so on-often leads them to overlook obvious

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conflicts with the world around them. Yale University game

theorist Barry Nalebuff is more world-savvy than most, yet

even he has gotten into trouble. Nale buff and another game

theorist found themselves in a cab late one night in Israel. The

driver did not turn the meter on but promised them he would

charge a lower price at the end of the ride than what the meter

would have indicated. Nalebuff and his colleague had no rea

son to trust the driver. But they were game theorists and rea

soned as follows: Once they had reached their destination, the

driver would have very little bargaining power. He would have

to accept pretty much what his passengers were willing to pay.

So they decided that the driver's offer was a good deal, and

they went along. Once arriving at their destination, the driver

requested 2 , 5 0 0 shekels . Nalebuff refused and offered 2 , 20 0

shekels instead. While Nalebuff was attempting t o negotiate,

the outraged driver locked the car, imprisoning his passengers

inside, and drove at breakneck speed back to where he had

picked them up. He kicked them to the curb, yelling, " See how

far your 2 , 20 0 shekels will get you now."9

Standard game theory, it turned out, was a poor guide for

what actually transpired. A little bit of induction may have

helped Nalebuff and his colleague recognize at the outset that

real-world people do not act like the rational automatons that

populate theorists' models!

Today, it is unlikely they would have made the same mis

calculation. Experimental work has become much more com

mon, and game theorists have a greater appreciation of where

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their standard predictions go wrong. Consider the "ultimatum

game," in which the calculations are reminiscent of the taxicab

experience. Two players have to agree on how to share $100.

One side makes a take-it-or-leave-it offer, which the other side

either accepts or rej ects . If the responder accepts, then each

side receives what they agreed on. If he rej ects , they both get

nothing. If both players are "rational," the first player will keep

almost the entire $ 1 0 0 for himself, offering the other player a

tiny share (perhaps j ust $ 1) . The respondent will agree, because

even a token amount is b etter than nothing. In reality, of course,

people play this game very differently. Most offers are in the

range of $30-$50, and anything less is typically rej ected by the

responding player. Standard game theory has little predictive

power for this game. That's one reason why economists have

moved to different types of models. Recent work in behavioral

economics incorporates considerations of fairness and therefore

is more applicable to real-life settings that resemble the ultima

tum game.

Lab experiments use human subj ects , typically undergradu

ates, and have long been common in psychology. Thanks to

these investigations, economists are learning more about what

drives human behavior besides material self-interest, such as

altruism, reciprocity, and trust. Models of competition and

markets are being discarded or refined if their results are rou

tinely violated in these experiments. But many economists

remain skeptical about the value of lab experiments because

of the artificial setting in which they occur. In addition, they

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argue, the monetary stakes fo r the human subj ects used i n the

experiments are typically small, and college students may not

be representative of the population at large.

One type of experiment that economists have turned to in

recent years-the field experiment-is, in principle, immune

to such criticisms. Typically in these experiments , economists

working in concert with local organizations separate people or

communities randomly into "treatment" and "control" groups

and observe whether real-life outcomes differ in the manner pre

dicted by the particular model motivating the treatment. One of

the very first such experiments was attempted during the rollout

in 1997 of the Mexican antipoverty program that I mentioned

in the Introduction. The program-originally called Progresa,

then Oportunidades, and now Prospera-was the front-runner of

today's popular conditional cash grant programs, which pro

vide poor families with income support as long as they keep

their children in school and show up for regular health check

ups . As the economist Santiago Levy, who was instrumental in

designing and implementing the program, describes it, the goal

was to leverage some simple economic principles to achieve

b etter results. 10 Direct cash grants would provide more effec

tive poverty relief than food subsidies already in place . And the

conditional element of the grants would ensure, it was hoped,

improved education and health.

Even though the program was national in scope, it would

be phased in gradually. So, Levy got the idea that he could

undertake a clean test of the effectiveness of the program. By

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E C O N O M I C S RUL E S

selecting at random the communities participating in the pro

gram in the early phases, he would create separate treatment

and control group s . The difference in outcomes b etween the

two groups could then be attributed to the effects of Progresa.

Subsequent evaluations found that Progresa reduced the num

ber of p eople below the poverty line by 10 p ercent; increased

boys' and girls' secondary-school enrollment rates by 8 and

14 percent, respectively; and lowered the incidence of ill

ness in young children by ab out 12 p ercent . 1 1 These positive

results validated the thinking that had gone into the design

of the program and led governments in other countries, from

Brazil to the Philippines , to institute similar conditional cash

transfer programs.

Since the Progresa experiment, randomized field experiments

have swept the field. A wide variety of social policies have been

evaluated using essentially the same technique. These range

from the free distribution of insecticide-treated bed nets in

Kenya to the distribution of report cards to parents in Pakistan

on how their children's schools are doing relative to others in

the same district. Each one of these experiments is essentially

a test of an underlying economic model: in Kenya, a model for

the effect of small price disincentives in discouraging bed net

use; and in Pakistan, a model for the role that parents empow

ered by b etter information can play in improving school perfor

mance. They have shown the powerful impact of imaginative

solutions when an important constraint is identified correctly.

For example, Ted Miguel and Michael Kremer found that

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N AV I GA T I N G AM O N G M O D E L S

a relatively cheap deworming treatment fo r schoolchildren i n

Kenya produced substantial benefits in terms o f school atten

dance and, eventually, wages.12 Esther Duflo, Rema Hanna,

and Stephen Ryan found that placing cameras in the classroom,

so that the presence of teachers could be recorded, reduced

teacher absenteeism by 21 percent in rural India . 13 There were

also important negative results. Field experiments to date have

shown that microfinance-the provision of small loans, typi

cally to women or groups of women-is not particularly effec

tive in reducing poverty. 14 These results stand in sharp contrast

to the hype that microfinance has attracted in development

policy circles. They throw cold water on models that suggest

lack of access to finance is among the most important con

straints that poor households face.

MIT, Yale, and UC B erkeley have maj or centers devoted to

running field experiments that evaluate policy and test models.

The obvious shortcoming of field experiments is that they are

only tenuously related to many of the central questions of eco

nomics. It is difficult to see how economy-wide experiments

could be performed that would test macroeconomic questions

on the role of fiscal or exchange-rate policy, for example. And,

as usual, one needs to interpret experimental results with care,

since those results may not apply to other settings-the usual

problem of external validity.

Economists sometimes test whether their models' implica

tions are borne out in so-called natural experiments . These

experiments rely on randomness that is generated not by the

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E C O N O M I C S RUL E S

researcher, but serendipitously by circumstances that have

nothing to do with the research per se. One of the first such

exercises in economics was MIT economist Joshua Angrist's

work examining the effect of military service on men's subse

quent earning ability in the labor market. To avoid the prob

lem that men who choose to j oin the army may be inherently

different from those who do not, Angrist used the Vietnam

War-era draft lottery, which had created random recruitment.

He found that men who had served in the early 1970s ended

up earning about 15 percent less a decade later than men who

had never served.15

Columbia University economists Donald Davis and David

Weinstein used the US bombing of Japanese cities during the

Second World War to test two models of city growth. O ne

model was based on scale economies (decline in production

costs as urban _ densit� increased) , and th� other was based on

locational advantages (such as access to a natural seaport). Even

though the bombing was obviously not random, it created a

natural way to test whether cities that had been badly destroyed

would remain depressed or bounce back to their original posi

tion. The model based on scale economies suggested that cities

would not recover after b eing sharply reduced in size, whereas

the locational-advantage model predicted otherwise. Davis and

Weinstein found that most Japanese cities returned to their pre

war relative size within a decade and a half, providing support

for the latter model.16

Economists employ a wide a range of strategies to verify

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N AV I GA T I N G AM O N G M O D E L S

whether the immediate implications o f different models are

confirmed in the real world, from the informal and anecdotal

to the sophisticated and quantitative. Experimental meth

ods generally provide more credible tests, as long as they can

be carried out in settings close enough to the application in

question. Many policy questions, however, either do not lend

themselves to experiments or require answers in real time, thus

not allowing the luxury of time-consuming field experiments.

In such cases, there is no alternative to keen observation com

bined with common sense.

Verifying I ncidental Implications

A significant advantage of having models to work with is that

they provide a wide range of implications that go beyond the

initial observation or motivating problem. These additional

implications provide extra leverage for navigating among

them. They enable the economist to move from the induc

tive back to the deductive mode of analysis , helping greatly in

model selection.

During the mid-1990s I was investigating an empirical reg

ularity that had received little attention in economics: coun

tries that were more exposed to international trade had larger

public sectors. This fact had b een first observed by the Yale

political scientist David Cameron for a subset of the member

countries of the Organisation for Economic Co-operation and

D evelopment (OECD) . 17 My own research showed that the

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finding extended also to virtually all the countries of the world

(those with the requisite statistics, that is) . The question was

why. Cameron had hypothesized that public spending was a

buffer-a source of social insurance and a stabilizer for econo

mies that might otherwise be subj ected to extensive foreign

shocks . The correlation evidence was certainly consistent with

this explanation.

So much for induction. But the hypothesis could be taken

one step further-to ask what additional implications it had

for the real world. This is where the deduction stage comes in.

If Cameron's supposition was true, then the size of the pub

lic sector, upon analysis, would appear particularly sensitive to

fluctuations in the economy, rather than exposure to trade per

se. This implication generated an extra, more refined hypoth

esis that could be tested against the data. When I carried out

the empirical test, looking at the effects of volatility generated

by the external terms - of trade (prices of exports and imports

on world markets) , the results fell in line. I concluded that the

compensation-for-risk model had a lot going for it. 1 8

My colleagues and I made considerable u s e of this kind of

approach in our growth diagnostics work as well. We system

atically looked for the tangential implications of a hypoth

esis to see whether they checked out. First, if an economy's

prospects are undermined by bottlenecks in a particular area,

the relative prices of the associated resources should be com

paratively high. Shortage of physical capital (that is, plant and

equipment) should show up in high real interest rates; short-

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N AV I GA T I N G AM O N G M O D E L S

age o f skills should result i n a high skill premium i n the labor

market; infrastructure constraints should produce power short

ages and road congestion; and so on. Second, changes in the

availability of resources in short supply should produce a par

ticularly large response in economic activity. Investment in

capital-constrained economies should respond vigorously to an

inflow of remittances and other foreign funds; a similar inflow

in return-constrained economies will stimulate consumption

over investment.

Third, serious constraints should lead firms and households

to make investments that would enable them to bypass that

constraint. If electricity is in short supply, we should see lots of

demand for private generators. If regulations on large firms are

excessive, we should see firms taking steps to remain small. If

monetary instability is a big deal, we should see a shift to for

eign currencies in everyday and financial transactions (" dollar

ization"). Finally, firms that do relatively b etter should be those

that rely comparatively less on the resources in short supply.

As my former Harvard colleague Ricardo Hausmann likes to

point out, the reason we see lots of camels and very few hip

pos in the desert is obvious: one animal lives in water, and the

other doesn't need much water at all.* Similarly, the reason we

see only skill-intensive firms doing well in an economy such as

South Africa's is that unskilled labor is particularly expensive.

* Hausmann, Klinger, and Wagner, Doing Growth D iagnostics in Practice. I

rely here greatly on this summary of " diagnostic signals."

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E C O N O M I C S RUL E S

External Validity, Redux

Ultimately, model selection is not unlike external validation

in lab or field experiments. We have an idea that works in

one setting (the model); the question is whether it also works

in another (the real world) . The external validity of models

depends on the setting in which they're applied. Once we give

up on claims of universality for our models and accept contin

gency, we recover their empirical relevance.

External validity is not a question that can be answered sci

entifically, although, as we have seen, imaginative empirical

methods do help. A lot hangs on what is essentially analogical

reasoning. As Robert Sugden puts it, " The gap between the

model world and the real world has to be crossed by induc

tive inference . . . [and this] depends on subj ective judgments

of 'similarity,' 'salience,' and 'credibility."'19 While we can

imagine expressing concepts such as "similarity" in formal or

quantitative terms, this formalization won't be helpful in most

contexts. There is an unavoidable craft element involved in

rendering models useful.

1 1 2

CHAPTER 4

Models and Theories

ou may have noticed that thus far I have generally

stayed away from the word "theory." Even though

"model" and "theory" are sometimes used inter

changeably, not least by economists, it is best to keep them

apart. The word "theory" has a ring of ambition to it. In the

general definition, it refers to a collection of ideas or hypoth

eses put forth to explain certain facts or phenomena. In some

usages, there is a presumption that it has been tested and veri

fied; in others, it remains merely an assertion. The theory of

general relativity and string theory are two examples from

physics. Einstein's theory is considered to be fully borne out by

subsequent experimental work. String theory, developed more

recently and aimed at the unification of all forces and particles

in physics, has so far received scant empirical support. Darwin's

theory of evolution based on natural selection is impossible to

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E C O N O M I C S RUL E S

verify directly and experimentally, in view of how long it takes

for species to evolve, though there is plenty of suggestive evi

dence in its favor.

As with these examples from the natural sciences, a theory

is presumed to be of general and universal validity. The same

theory of evolution applies in both Northern and Southern

Hemispheres-and might even apply to alien life . Economic

models are different. They are contextual and come in almost

infinite variety. They provide at best partial explanations,

and they claim to be no more than abstractions designed to

clarify particular mechanisms of interaction and causal chan

nels. By leaving all potential other causes out of the analysis,

these thought experiments are meant to isolate and identify

the effects of a narrow set of causes. They leave us short of a

full explanation of real-world phenomena when many causes

might be simultaneously operating.

To see the dfrference b etween models and theories, as well

as where they can overlap, we should first distinguish among

three kinds of questions.

First, there are "what" questions of this sort: What is the

effect of A on X? For example: What is the effect of an increase

in the level of the minimum wage on employment? What is

the effect of capital inflow on a country's rate of economic

growth? What is the consequence of an increase in government

spending on inflation? As we've seen, economic models pro

vide answers to these questions by describing plausible causal

channels and clarifying how these channels depend on a par-

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M O D E L S A N D T H E O R I E S

ticular setting. Notice that answering these questions does not

amount to making a forecast, even if we can be reasonably sure

that we have the appropriate model. In the real world, many

things change alongside the effect we're analyzing. We may

be correct in our prediction that a rise in the minimum wage

depresses employment, but in the real world the effect may

be confounded by a general uptick in demand that increases

employers' payrolls regardless . This kind of analysis is the

proper domain of economic models.

Second, there are "why" questions that seek an explanation of

an observed set of facts or developments . Why did the industrial

revolution take place? Why did inequality rise in the United

States after the 1970s? Why did we have the global financial

crisis of 2008? In each case we can conceive of theories-and

not only economic ones-that purport to provide an answer.

But they are specific rather than universal theories. They aim to

shed light on particular historical episodes and do not describe

general laws and tendencies.

Still, the formulation of such theories poses difficulties for the

analyst. An economic model scrutinizes the consequences of a

particular cause. It answers what statistician Andrew Gelman

calls a question of "forward causation." But explaining some

thing after the fact requires scrutinizing all possible causes. It is,

again in Gelman's terminology, a matter of "reverse causal infer

ence." It requires looking for particular models, or some combi

nation of models, that account for the facts under investigation.

The process involves model selection and parsing of the type

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E C O N O M I C S RUL E S

we saw in the previous chapter. Specific models are an essential

input to the construction of such theories, as we'll see later.1

Finally, there are the big, timeless questions of economics

and social science. What determines the distribution of income

in a society? Is capitalism a stable or unstable economic system?

What are the sources of social cooperation and trust, and why

do they vary across societies? These questions are the domain

of grand theories. A successful answer would explain the past

and also provide a guide to the future . To that extent, these

theories would form the social analogue of the physical laws

of nature. Contemporary economics is often criticized for not

taking on these big questions. Where is to day's Karl Marx or

Adam Smith? Would they even get tenure at a half-decent

university? These are fair criticisms. But a reasonable counter

argument would be that universal theories are impossible to

formulate in the social sciences, and that the b est we can do is

come up witn a series- of contingent explanations.

Economics does have its general theories-particular models

that make ambitious claims about their explanatory p ower over

the workings of market-based societies . These can be a source

of great clarification, as we' ll see. But I will argue that general

economic theories are no more than a sca:ff olding for empiri

cal contingencies. They are a way of organizing our thoughts,

rather than stand-alone explanatory frameworks. On their

own, they have little real leverage over the world. They need

to be combined with considerable contextual analysis before

they become useful.

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M O D E L S A N D T H E O R I E S

I will then turn to theories of the intermediate kind, meant

to explain particular developments in the economy. I focus on a

concrete question: Why has inequality increased in the United

States so much since the 1 970s? We will assess the relative con

tributions of different models and show how such a process

generates insight even when it does not produce a conclusive

and widely agreed theory.

The Theory of Value and Its Distribution

Perhaps the most fundamental question in economics 1s,

What creates value? For an economist, this means: What

explains the prices of different goods and services in a market

economy? The " theory of value" in economics is essentially a

theory about price formation. If this question no longer seems

foundational-or particularly interesting-for the contempo

rary reader, it is b ecause it has been demystified by theoretical

developments that cut through a thicket of confusion sur

rounding it.

Classical economists such as Adam Smith, David Ricardo,

and Karl Marx subscribed to the view that the costs of produc

tion determined value. If something costs more to produce, its

price must be higher. Costs of production were, in turn, traced

to wage payments made to workers , either directly in the activ

ity in question or indirectly when labor was employed to pro

duce the machines that were being used. This was dubbed the

" labor theory of value," to be distinguished from earlier theo-

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E C O N O M I C S RUL E S

ries, like that of the French physiocrats, who viewed land as the

ultimate source of value.

But it is one thing to say labor creates value and another to

explain the level of wages. Classical economists tended to have

a pretty dreary view on that. They presumed wages would

hover around the subsistence level, the level required to feed,

clothe, and shelter a family. If wages rose too much above this

level, the result would be an increase in population-because

more children could survive-and in the labor force. As a

consequence, wages would drop back down to their "natural"

level. The main beneficiaries of economic advances and tech

nological progress would therefore be owners of land, which

was in finite supply. It was this kind of thinking, associated

in particular with Thomas Malthus, that led the nineteenth

century essayist Thomas Carlyle to famously call economics

the " dismal science."

Marx, whose influence would extend well into the twen

tieth century, also adhered to the labor theory of value. He,

too, b elieved that wages were held down. But in his theory

the culprits were capitalists who exploited workers and man

aged to discipline them through the "reserve army of the

unemployed." In Marx's case, capitalists expropriated the

surplus value from workers' efforts. But this was a Pyrrhic

victory, as competition among capitalists would eventually

drive the profit rate down and invite a generalized crisis of

the capitalist system.

The labor theory of value, placing the onus of price determi-

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M O D E L S A N D T H E O R I E S

nation solely on the production side, had little to say about con

sumers. But didn't the demand side of the picture play a role?

Shouldn't prices also respond to the preferences of consumers

and any changes in those preferences? The classical approach

focused on the long run. It had little to say on short-run fluc

tuations or on the determination of relative prices.

The full synthesis of the supply and demand sides of price

determination came with the "marginalist'' revolution of the

late nineteenth century. Marginalist economists such as Wil

liam Stanley Jevons, Leon Walras , Eugen von Bohm-Bawerk,

Alfred Marshall, Knut Wicksell, and John Bates Clark shifted

the ground of analysis one step back: from observed quanti

ties such as wages and rents toward unobserved hypotheti

cal mathematical constructs such as "consumer's utility" and

"production functions ." They also generalized the classical

approach by allowing substitution among different production

inputs such as labor and capital; they could now analyze how

firms switch from, say, labor to machines as wages and machine

prices changed. Their use of explicit mathematical relation

ships enabled them to describe the determination of prices,

costs , and quantities in different markets as the simultaneous

outcome of (and interplay between) consumer preferences and

the state of production technology.

The marginalists established a chief insight of the modern

theory of value-namely, that prices are determined at the

margin. What determines the market price of oil, for example,

is not the production cost or consumer valuation of oil o n aver-

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E C O N O M I C S RUL E S

age. It is the cost and valuation of the last unit of oil sold. In mar

ket equilibrium, the production cost and consumer valuation

of that last unit (the marginal unit) are exactly equal-to each

other and to the market price . If they were not, the market

would not be in equilibrium and there would be adjustments

to bring these back into equilibrium. When the market price

exceeds consumers' valuation of the last unit, consumers cut

back on their purchases; when it falls short, consumers buy

more. Similarly, when the market price is greater than the cost

of producing the last unit, firms expand production; when it is

less , firms reduce production.

The marginalists discovered that the supply and demand

curves represent none other than the marginal costs and mar

ginal valuations of the producers and consumers, respectively.

The market price is where these two schedules intersect. The

answer to the question of whether value is determined by pro

duction costs or, alternatively, by consumer benefits is that it is

determined by both-at the margin.

The marginalists' approach to determining prices applied

equally well to costs of production. Labor's earnings (wages)

are determined by the marginal productivity oflabor, and capi

talists' earnings (rents) are determined by the marginal product

of capital-what the last unit of lab or and capital, respectively,

add to the output of the firm. Now, suppose that production

takes place under constant returns , meaning that doubling the

amount of capital and labor used doubles the amount of output.

Under this assumption, the math guarantees that paying labor,

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M O D E L S A N D T H E O R I E S

capital, and other inputs their marginal productivity results in

a full allocation of the income generated by production among

all the inputs that contribute to production. In other words, we

now have a theory of distribution-who gets what-in addi

tion to a theory of value.

This theory tells us how national income is distributed

b etween labor and capital. If we distinguish further among

different types of labor, we can also get the distribution of

income across workers of various skill types, such as high

school dropouts, high school graduates, and college graduates .

This is what's called the functional distribution of income. By

combining it with information on the type and amount of

capital people own, we can, in turn, derive the distribution of

income across individuals or households-the personal distri

bution of income.

How useful are such theories? O n the face of it, the neoclas

sical synthesis appears to provide solid answers to two of the

fundamental questions in economics: What creates value, and

what determines how it is distributed? These theories have

clarified a lot. In particular, we now understand how produc

tion, consumption, and prices are all j ointly determined as a

system. And we have a plausible account of the functional dis

tribution of income . But the theories are based on concepts

marginal utility, marginal cost, marginal product-that cannot

be observed. They require additional assumptions and con

siderably more structure before they can be made operational

in the sense of measurement and explanation. Furthermore,

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E C O N O M I C S RUL E S

they are far from universal. Subsequent research has made clear

that, even within their own logic, these theories depend on

special circumstances.

We've already seen how the supply-demand framework

on which value theory rests is subj ect to important caveats.

The conditions for perfect competition may not exist, and the

market may be monopolized by a small number of produc

ers . Consumers may behave in ways that are far from rational.

Production may be subj ect to scale economies, and marginal

costs may decrease with quantities produced, contradicting the

rising marginal costs required for the standard upward-sloping

supply curve. And in any case, where do concepts such as the

"production function" and "utility" come from? Firms clearly

differ in their ability to access, adopt, and employ available

technologies . Consumer preferences are hardly fixed; they are

shaped in part by what happens in the economic and social

world. Opening up -these particular black boxes creates new

theoretical challenges that are not yet fully resolved.

The neoclassical theory of distribution has its own special

holes . For one thing, the notion of a coherent, measurable

concept of " capital" as a unified factor of production has been

the source of considerable controversy within the profession.

But let's set that thorny issue aside. Focusing on wages alone,

does the marginal-productivity theory track the behavior of

labor compensation?

The answer is that it depends on the precise question and the

setting we're examining. Looking across countries, between 80

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M O D E L S A N D T H E O R I E S

and 90 percent of the differences in wage levels can be accounted

for by the variation in national labor productivity levels. We do

not observe marginal productivity directly; all we can measure

is average labor productivity (gross domestic product divided by

employment levels) . But as long as the relationship between the

average and the marginal does not vary much across nations,

the tight cross-country association between wages and average

labor productivity can be interpreted as supporting the theory.

This is not a trivial matter. It allows us to conclude, for exam

ple, that wages in Bangladesh or Ethiopia are a small fraction of

wages in the United States largely because of the poor state of

productivity in these countries-and not because of the exploi

tation of labor or coercive institutions. Institutions might mat

ter, but they seem to be directly responsible for at most a small

share of the variation across countries in distributive outcomes

between labor and capital. 2

But let's look at what has happened in the United States since

2000. Average real compensation grew by about 1 percent per

year between 2 0 0 0 and 201 1 , from about $32 per hour to $35

per hour (in 2 0 1 1 dollars) . Meanwhile, labor productivity grew

by 1 .9 percent p er year during the same period, at almost twice

the growth rate of compensation. Some of this gap is due to

the fact that the prices of the goods US workers consume rose

more rapidly than the prices of goods they produce. So the

consuming power of workers increased less rapidly than their

productivity-something that can be accommodated within

the standard theory without a great stretch. This relative-price

1 23

E C O N O M I C S RUL E S

effect, however, accounts for only about a quarter of the gap,

leaving the remaining three-quarters a mystery.*

To remain strictly within the boundaries of neoclassical dis

tribution theory, we would have to say that labor's marginal

contribution to output fell sharply in this p eriod. One pos

sible culprit is the increasing use of machines and other forms

of capital, as well as the displacement of labor by new tech

nologies . Indeed, many economists make this argument when

interpreting the weak growth in wages over the last decade. But

the same result may also have b een due to changes outside the

ambit of neoclassical theory-in bargaining, workplace norms ,

and policies such as minimum wages. Distinguishing among

these alternative explanations is difficult because the neoclas

sical theory hinges on the mathematical representation of the

underlying technology (the "production function") and the

changes therein, which are not directly observable. Ultimately,

a theory that cannot be pinned down is not very helpful.

A wide variety of alternative theories of distribution exist.

S ome emphasize explicit bargaining between employers and

employees, where the prevalence of trade unions and collec

tive-bargaining rules can shape the sharing of revenues of

the enterprise between the two parties. Compensation levels

of high income earners such as CEOs seem also to be deter-

* Lawrence Mishel, The Wedges between Productivity and Median Compensation

Growth, Issue Brief330 (Washington, DC: Economic Policy Institute, 2 0 1 2) .

Mishel focuses on median wages, which have increased considerably more

slowly than average wages, because of rising inequality in compensation;

1 24

M O D E L S A N D T H E O R I E S

mined largely by bargaining. 3 Other models highlight the role

of norms in the spread that is considered acceptable between,

say, the CEO 's compensation and the amounts earned by rank

and-file employees. Most economists would acknowledge that

workers in the United States and Europe greatly benefited

from the more egalitarian social understanding of the 1950s

and 1960s. Yet other models suggest that profit-maximizing

reasons motivate certain firms to pay more than the going mar

ket wage, without departing from the marginal-productivity

framework as such. For example, above-market "efficiency"

wages , as they are called, may make sense for employers in

order to motivate workers or minimize labor turnover (to

reduce costs of hiring and training). These wrinkles move us

away from general-purpose models and take us back, again, to

specific models that may be relevant in different settings .

The big theories in the end deliver less than what they

promise. They are shallow approaches that identify the proxi

mate causes but need to be backed up with considerable detail,

necessarily specific to context. As I 've highlighted, they are

best thought of as a scaffolding.

The Theory of Business Cycles

and Unemployment

Ever since Paul Samuelson's doctoral dissertation, published

in 1947 as Foundations of Economic Analysis, economics has

been split between microeconomics and macroeconomics. The

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E C O N O M I C S RUL E S

domain of microeconomics is price theory, the ideas covered in

the previous section. Macroeconomics deals with the behavior

of economic aggregates-inflation, total output, and employ

ment, in particular. Macroeconomics takes as its central ques

tions the up-and-down .fluctuations in economic activity that

economists call the " business cycle." Here, too , there has been

no shortage of grand theorizing. We have learned considerably

with each successive wave. But the attempts to develop a grand

unified theory of what determines the business cycle have to

be judged a failure.

To classical economists , there was not much difference

between the way individual markets worked and the way the

economy as a whole behaved. Unemployment, in particular,

could be understood as a result of wages (the market price of

labor) being set at the wrong level. If wages were too high,

employers would hire too few workers, just as too high a price

for apples would. result in too little apple consumption. This

scenario has come to be called "classical unemployment."

Along similar lines, the overall level of prices in the economy

was determined by the quantity of money and liquidity in the

system. Sustained price inflation was the result of too much

money being in circulation.

The classical economists' approach to the business cycle

was typified by their view that the macroeconomy, to use

the term anachronistically, was self-stabilizing. Unemploy

ment would eventually be eliminated as the shortage of j obs

brought wages down. A burst of inflation similarly would be

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M O D E L S A N D T H E O R I E S

cured on its own: the resultant loss in international competi

tiveness would produce a trade deficit, financed by the out

flow of gold abroad, which in turn would lead to a c orrective

reduction in the domestic money supply. These supposedly

automatic adj ustment mechanisms ensured that the business

cycle, inflation, and unemployment would all take care of

themselves . The Gold Standard epitomized this economic

orthodoxy and stoo d well into the twentieth century. Under

Gold Standard rules, countries fixed their currencies' value

against gold. For example, in the United States the price of

gold stood unchanged at $20 . 67 per ounce b etween 1 83 4 and

1933.* Governments renounced any interference in the free

flow of money across their borders , effectively placing their

monetary p olicy on economic autopilot. There was no con

cept of fiscal p olicy or stabilization policy as we know them

today. Governments could (and should) do nothing, except to

stay out of the way of these adjustments.

John Maynard Keynes thought otherwise . A conservative

revolutionary, he formulated doctrines that aimed to save capi

talism from what he felt were its inherent instabilities . Keynes

argued that it was possible for an economy with unemployment

to remain in an equilibrium for a considerable stretch of time.

The classical adjustment mechanisms would take too long to

* With the exception of the interlude during the greenback era from 1861

to 1878. Michael D. B ordo, "The Classical Gold Standard: S ome Lessons

for Today," Federal Reserve Bank of St. Louis Review, May 198 1 , 2-17.

1 27

E C O N O M I C S RUL E S

work themselves out-years, perhaps even decades , and in the

long run , as he famously put it, "we are all dead." Moreover,

Keynes argued, there was plenty that the government could do.

When private demand fell short of what was required to gener

ate sufficient employment, Keynes contended, it should step in

and increase fiscal spending. Even if the expansion of govern

ment programs led to people digging ditches and then filling

them back in, the net result would be fuller employment and

rising national income. The Great D epression gave great cur

rency to these ideas , as governments found themselves forced

to respond to catastrophic spells of unemployment, which in

the United States p eaked at a quarter of the labor force.

Keynes was an exceptionally good and witty writer, but

he did not formulate explicit models, and his reasoning was

sometimes cloudy. To this day, economic historians debate

what the great theorist really meant by this or that. The ink on

his magnum ·op-us , The General Theory of Employment, Interest,

and Money (published in 1 93 6) , was barely dry b efore mod

els trying to encapsulate the Keynesian framework began to

appear. Among these, the most famous, and the one that had the

greatest impact for decades, was John Hicks's "Mr. Keynes and

the 'Classics .' "4 Hicks's model was the vehicle through which

Keynes's views transformed standard macroeconomics-despite

the protests of many, including Keynes, that it was at best a par

tial representation of the General Theory. Keynes was , in fact,

explicit that he was not interested in crafting a model of his

ideas . He thought it more important to communicate some

1 2 8

M O D E L S A N D T H E O R I E S

"comparatively simple fundamental ideas" than to crystallize

them in particular forms . 5

Crucial to the Keynesian apparatus was the possibility of

an imbalance between saving and investment in the economy.

These two have to equal each other after the fact, as a matter

of accounting identity: whatever is saved must find its way into

investment, and all investment has to be financed by saving

(ignoring what can be b orrowed from or lent to other coun

tries) . But Keynes highlighted the possibility that the mecha

nism through which the identity is restored could introduce

unemployment into the economy. Suppose, for concreteness,

the amount that households desire to save initially exceeds

investment. Keynes thought investment is determined by psy

chological factors ("animal spirits") that are largely external to

macroeconomic variables such as interest rates. If the invest

ment level is somehow fixed by other considerations, it is sav

ing that must adjust. How does saving come down, then, to

the lower level required by the equality between investment

and saving?

Classical economists offering a response would emphasize

the role of price adjustments, including the interest rate. A

decline in the level of prices, or a fall in the interest rate, would

b oost households' incentives to consume and eventually lower

savings. Keynes thought such price changes would be too slow,

especially in the downward direction. He highlighted instead

adjustments in the level of aggregate output and employment.

Since household saving depends on the household's income, a

1 29

E C O N O M I C S RUL E S

reduction in output (and therefore incomes and employment)

also lowers saving and brings it closer to equality with invest

ment. Moreover, in situations of economic depression, where

unemployment has shot up, people may want to hoard money

so much that the interest rate becomes essentially insensitive

to changes in economic circumstances. This is the Keynesian

" liquidity trap." In this scenario the adjustment can arrive only

through a sufficiently large drop in output and employment.

The high level of saving among individual households proves,

collectively, self- defeating. Recession follows.

In this model of autonomous changes in aggregate demand,

business cycle fluctuations are the result. Insufficient demand is

the fundamental cause of unemployment. An increase in pri

vate investment or consumption spending, were it to happen,

would fix the problem. In the absence of either, the govern

ment has to act: fiscal spending must be raised to make up for

lack of private demand. This demand-side view of macroeco

nomics prevailed pretty much through the 1970s . It was elabo

rated in models of increasing variety and spawned large-scale

computerized versions that could generate quantitative fore

casts of maj or macroeconomic aggregates such as employment

levels and capacity utilization rates.

Then two things happened: the oil shock and Robert Lucas .

The oil crisis of 1 973, precipitated by the embargo applied by the

Organization of the Petroleum Exporting Countries (OPEC),

fomented a new set of economic circumstances that had not

been on economists' radar screen: recession and inflation at the

1 3 0

M O D E L S A N D T H E O R I E S

same time, or "stagflation." Demand-side models wouldn't be

much help in the face of what was patently a supply-side shock.

Of course, the Keynesian model could be tweaked to accom

modate the effect of a rise in input prices . Many attempts were

made to do just that. But then Lucas, the University of Chicago

economist and future Nobel Prize winner, came along with a

set of ideas that revolutionized the field of macroeconomics and

eventually did much greater damage to the Keynesian model.

At the close of the 1970s, Lucas reintroduced classical think

ing into macroeconomics, in a new guise . Along with others

(in particular Tom Sargent, then at the University of Min

nesota), Lucas argued that Keynesian models took a far too

mechanical view of how individuals behave in the economy

and how they respond to government policies . 6 In the words

ofJohn Cochrane, another Chicago economist, Lucas and Sar

gent put people back into macroeconomics .7 Instead of rely

ing on aggregate relationships between, say, consumption and

income, they b egan to model how individuals decide to con

sume, save, and supply labor in much the same way that micro

economics had traditionally done, but they extended those

models to macrobehavior. These became the "microfounda

tions" of a larger theory.

This change in modeling strategy had a couple of important

implications. O ne is that it brought budget constraints explic

itly into the picture, both for individuals and for the govern

ment. Private consumption depends on future income as well

as current income, and government deficits today imply higher

1 3 1

E C O N O M I C S RUL E S

taxes (or lower government spending) tomorrow. The strategy

also forced a reconsideration of how expectations are formed.

If people are rational in making their consumption decisions,

Lucas and Sargent argued, they should also b e rational in how

they make their forecasts about the future. These forecasts

should be consistent with the underlying model of the economy

hence the hypothesis of "rational expectations," which took the

profession by storm. Rational expectations quickly became the

benchmark in the modeling of expectations, which economists

use to analyze the reaction of the private sector to changes in gov

ernment policy, among other questions.

Lucas , Sargent, and their followers argued that such micro

founded models could account for the main features of business

cycles and generate temporary unemployment without relying

on Keynesian assumptions such as sluggish adjustment in prices.

Rational expectations implied that people did not make pre

dictable errors,-but it did not rule out temporary mistakes when

people had incomplete information about prices. " Shocks"

to consumer tastes, employment preferences, or technologi

cal conditions-that is, to demand and supply curves-could

generate aggregate fluctuations in output and employment.

Equally important, the new theory implied that the govern

ment's influence in stabilizing the economy was much weaker.

In fact, any kind of stabilization p olicy would produce perverse

outcomes. When people knew the government had a policy of

stimulating the economy through monetary and fiscal expan

sion, they would b ehave in ways that would defeat the pur-

1 3 2

M O D E L S A N D T H E O R I E S

pose of such policies . For example, activist monetary policy

would lead firms to raise their prices, producing inflation with

no gains in terms of output and employment. Fiscal stimulus

would only lead to crowding out-cutbacks in spending on the

part of the private sector.

What made the "new classical approach," as it came to be

called, a winner-at least in academia-was not its empirical

validation. The real-world fit of the model was heavily con

tested, as was the realism of some of the key ingredients. But

shortly after the arrival of the new theory, in the mid-1980s

the US economy entered a period of economic growth, full

employment, and price stability. The business cycle looked to

be conquered in this era of "great moderation." As a result, the

descriptive and predictive realism of the new classical approach

seemed, from a practical perspective, not to matter a whole lot .

The great appeal o f the theory lay in the model itself. The

microfoundations, the math, the new techniques, the close

links to game theory, econometrics, and other highly regarded

fields within economics-all these made the new macroeco

nomics appear light-years ahead of Keynesian models . "This

is what macroeconomic models are supp osed to look like" was

the implicit or explicit rebuke to anyone who would ques

tion the strategy beneath the model. Meanwhile, the Keynes

ian modeling apparatus deriving from Hicks became virtually

extinct. But Keynesianism did not disappear altogether. Those

who thought active government policy retained a role in sta

bilizing the economy were ultimately forced to develop vari-

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E C O N O M I C S RUL E S

ants of microfounded models, called new Keynesian models, to

retain credibility within the discipline.

The disconnect b etween the new classical theory and

the real economy came home to ro ost in the aftermath of

the global financial crisis of 2 0 0 8 . Why economists failed

to see the crisis coming is the subj ect of the next chapter.

The crisis was instigated largely by failures in the financial

system; the Keynesian and new classical macro models alike

were mute on such matters . But once the US economy sank

into recession and unemployment took off, the question of

appropriate remedies was-or should have b een-squarely

the province of macroeconomics . Yet the prevailing macro

models , descendants of the Lucas-Sargent approach, offered

little help. Writing in early 2 0 03 , Lucas had said, " [The] cen

tral problem of depression prevention has b een solved, for

all practical purposes."8 In the intervening years not much

thought had gone into fighting a great recession, b ecause

there wouldn't b e one .

On one thing, the new and old models agreed. When eco

nomic uncertainty produces a sudden flight to safety in that

households and firms hoard as much cash as they can, the Fed

eral Reserve should produce additional liquidity by printing

money-lots of it. Increasing the amount of money in circu

lation prevents deflation and a more severe recession. Milton

Friedman had pointed out many years earlier that failure to

act in this way was the Fed's biggest mistake during the Great

D epression of the 1930s. When the Fed's B en B ernanke, an

1 3 4

M O D E L S A N D T H E O R I E S

expert on the Depression, inj ected hundreds of billions of dol

lars of liquidity into the economy in 200 8-9, Lucas applauded

the action.9 President Obama's initial fiscal stimulus package of

2009 also received widespread support (including from Lucas),

even if viewed as a desperate, last-resort measure.*

B eyond these measures, and once the financial panic subsided,

the new classical models suggested restraint and caution and not

much else. The Fed's policies of quantitative easing-its mon

etary expansion-had to be withdrawn quickly; otherwise, it

soon would lead to inflation. Economists trained on these mod

els kept warning about the dangers of inflation and urged the

Fed to tighten its policy, even though unemployment remained

high, the economy performed below par, and-notably

-inflation refused to appear. They argued against continued

fiscal stimulus to lift aggregate demand and employment, since

such measures would only crowd out private consumption and

investment. The economy would get back on track largely

* Holman W. Jenkins Jr. , " Chicago Economics on Trial" (interview

with Robert E. Lucas) , Wall Street journal, S eptember 24, 2 0 1 1 , http : //

o nline .wsj . c o m /news/article s / SB 1 0 0 0 1 4240 5 3 1 1 1 9 0 4 1 9 4 6 0 4 5 7 6 5 8 3 3 8

2 5 5 0 8 49232 . I n a survey of thirty-seven leading economists in 2 0 1 4 ,

a l l except o n e a g r e e d t h a t t h e stimulus had reduced unemployment,

and the maj ority thought the benefits of the p ackage exceeded its costs.

Justin Wolfers, "What D eb ate? Economists Agree the Stimulus Lifted

the E conomy," The Upshot, New York Times, July 29, 2 0 1 4 , http : //

www.nytimes.com/2014/07 /30/upshot/what-debate-economists-agree-the

stimulus-lifted-the-economy.html?rref=upshot.

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E C O N O M I C S RUL E S

on its own. When this failed to happen, Lucas and others fin

gered obstacles put in place by the Democratic administration.

The sluggish recovery was due to uncertainty created by the

prospect of higher taxes and other government interventions,

they claimed.10 Businesses failed to invest and consumers failed

to spend because they faced an artificial climate of uncertainty

created by an activist government.

To many others, the recession vindicated Keynes's ong1-

nal ideas . The economist and New York Times columnist Paul

Krugman was vociferous in arguing that the fiscal stimulus

was inadequate and had been withdrawn too soon, condemn

ing the economy to unnecessarily high and prolonged levels

of unemployment.11 Brad DeLong and Larry Summers, from

UC B erkeley and Harvard, respectively, argued that concerns

about the deficit were misplaced; fiscal stimulus would actually

pay for itself as it helped the economy recover.12 These are all

well-known- and distinguished economists. Krugman had won

a Nobel Prize for his pioneering work of introducing imperfect

competition into the theory of international trade. Summers

had served as secretary of the treasury in the Obama adminis

tration. But they were outsiders to the new classical models that

had come to dominate the discipline.

The main bone of contention between the Keynesians

and the new classicals was whether the problems were on the

demand or the supply side of the economy. In principle, econo

mists had ways to discriminate between the competing ideas

and choose the more relevant ones. The principles of model

1 3 6

M O D E L S A N D T H E O R I E S

selection discussed in the previous chapter are tailor-made for

such a proj ect. Keynesians, reasonably enough, pointed out that

if the problem was a shortfall in supply, there would be evidence

of inflationary pressures and there was none. Unemployment

seemed to affect all sectors of the economy and was not related

to the specific circumstances of each industry, again pointing to

a generalized collapse in demand as the culprit. 13 The other side,

meanwhile, presented evidence from news articles, changes in

the tax code , and forecaster disagreements that policy uncer

tainty had risen and seemed to explain at least a portion of the

increase in unemployment and decline in economic growth,

both over time and across US states. 14 It is not clear whether the

evidence swayed anyone's prior opinions in the debate. When

conviction in the relevance of a theory is strong, as in this case,

empirical analysis hardly settles matters-especially when the

analysis has to be carried out in real time.

What can we conclude about these grand theories of the

business cycle? Certainly they have not b een pointless. Clas

sical, Keynesian, and new classical theories each make useful

contributions . The Keynesian approach had little relevance to

the experience of the 1970s, but many of its insights remain

valid and useful today. The new classical approach has made

us more cognizant of the need to understand how individuals

will respond to government policies . Where these have failed

is as grand theories that apply at all times, regardless of circum

stances. As models that are specific to particular settings , they

remain immensely valuable.

1 3 7

E C O N O M I C S RUL E S

Theories as Explanation of Specific Events

Let's turn now to the intermediate kind of economic theory

that I mentioned at the beginning of the chapter. Less ambi

tious in scope, it seeks to uncover the causes of a particular

set of developments. It makes no claim to provide a generic

explanation for all developments of a similar type. It is typically

historically and geographically specific.

The specific example I will consider here is the theories

behind the rise in inequality in the United States and some

other advanced economies since the late 1 970s. Even if widely

accepted, these theories are not meant to apply to other settings.

The explanations I will consider do not attempt to account also

for, say, the rise of inequality in this country during the gilded

age before World War I or the decline in inequality in many

Latin American countries since the 1 9 9 0 s . They are sui generis.

The steep rise in -US inequality that began in the mid-1 970s

is well documented. The Gini coefficient, a widely used mea

sure of inequality that varies from 0 (no inequality) to 1 (maxi

mum inequality, with all income going to a single household),

rose from 0.40 in 1 973 to 0.48 in 2 0 1 2-a 20 percent increase.15

The country's richest 1 0 percent raised their share of national

income from 32 to 48 p ercent over the same period.16 What

caused this dramatic change?

One factor behind the rise in inequality was an increase in

the "skill premium," the gap between what high- and low-

1 3 8

M O D E L S A N D T H E O R I E S

skilled workers earn. When economists first homed in on this

gap beginning in the late 1980s, there was a plausible expla

nation at hand: globalization. The US economy had become

much more exposed to international trade in recent years.

Other advanced economies in Europe and Japan had largely

caught up with the United States in productivity and now

offered stiff competition. And there were many newly rising

exporters in East Asia-South Korea, Taiwan, China-where

wages were a fraction of the US level.

Since Ricardo's days there had been many elaborations of

the Principle of Comparative Advantage. The reigning version

of the theory, called the " factor endowments" theory and first

articulated by Eli Heckscher and B ertil Ohlin in the early twen

tieth century, predicted precisely the kinds of changes in relative

wages that were taking place in the United States. According

to the theory, the country would be exporting goods that were

intensive in skilled labor and importing goo ds that were inten

sive in unskilled labor. Greater openness to international trade

was good news for American skilled workers, who could now

access larger markets, but bad news for low-skilled workers,

who had to put up with greater competition. As UCLA econo

mist Edward Leamer put it in the early 1990s, "Our low-skill

workers face a sea of low-paid, low-skilled workers around the

world."17 As a consequence, the gap between the wages of the

two types of workers would increase. In fact, the theory had an

even stronger implication. Unskilled workers would lose out

1 39

E C O N O M I C S RUL E S

not just in relative but also in absolute terms. Increased open

ness would reduce their living standards.*

Discussion might have rested there, but economists noticed

other developments that seemed incompatible with the factor

endowments theory. For one thing, the skill premium was also

rising in the United States' low-wage trade partners in Asia and

Latin America. This was a problem for the theory because it

had predicted a movement in the skill premium in the opposite

direction in those countries. Unskilled workers should have

benefited through higher wages in countries exporting low

skill-intensive goods . And in the United States, individual

industries were defying the theory's predictions. Firms were

substituting skilled labor for unskilled labor-there was skill

upgrading-when they should have been doing the reverse if

trade had caused unskilled labor to become cheaper. 18 This was

a good example of how economists could use the incidental

implications of a model to verify, or in this case disprove, a

specific explanation.

These conflicting findings did not necessarily rule out glo

balization as a driver of rising inequality. But they did imply

that if globalization was the real cause, it must have operated

through channels other than those highlighted by the factor

endowments theory. An alternative globalization-based model

* This is the consequence of the Stolper-Samuelson theorem, an extension

of the factor endowments theory. Wolfgang Stolper and Paul A. Samuelson,

"Protection and Real Wages," Review of Economic Studies 9, no. 1 (1941):

58-73.

1 40

M O D E L S A N D T H E O R I E S

soon coalesced around foreign investment and o:ffshoring.

Industrial operations depend on the production of many dif

ferent comp onents. Suppose, reasonably, that the most skill

intensive parts of an industry are manufactured in the United

States, while the least skill-intensive parts are manufactured in

a developing country such as Mexico. As globalization renders

o:ffshoring easier by reducing tariff, transport, and communica

tion costs , US firms move some of their production to Mexico.

It can be expected that the components that are o:ffshored will

be, for US firms, among the least skill-intensive. But the same

components, when produced in Mexico, will be among the

most skill-intensive there. As a result, somewhat paradoxically,

industries in both the United States and Mexico experience skill

upgrading. Relative demand for skilled workers rises in both

countries, as does the risk premium. Rob Feenstra and Gor

don Hanson, who first advanced this hypothesis, showed that

evidence from Mexican maquiladoras-manufacturing plants

operating in the country's free-trade zones-was consistent

with the model.19

The main alternative to the globalization thesis was tech

nological change. This was an age of rapid advances in infor

mation and communication technologies and the spread

of computers. Normally, broad technological progress that

increases labor productivity is expected to improve everyone's

living standards. But some may benefit more than others . The

new technologies required skilled workers to operate them,

so the demand for those with college education or higher rose

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E C O N O M I C S RUL E S

much more rapidly than the demand for less skilled workers .

This was "skill-biased technological change" (SBTC) , as econ

omists called it. 20

The SBTC hypothesis explained the rise in the skill pre

mium. In addition, unlike the factor endowments model, it

was consistent with skill upgrading within firms and indus

tries . Employers were hiring more skilled workers as a result

of automation and greater use of computers. Since these tech

nological changes were sweeping the rest of the world as well,

the theory also accounted for rising wage inequality in devel

oping nations. By the end of the 1990s, a near-consensus had

emerged among trade and labor economists that SBTC was

the primary culprit behind the increase in the skill premium.

Trade may have played a role, but it accounted for no more

than 10-20 percent of the trend.

D oubts crept in b efore too long. The skill premium had

stabilized durfo.g the 1 9 9 0 s , even though the introduction of

new technologies had not slowed down. (It would start to rise

again, with a vengeance, in the 2 0 0 0 s .) Many of the develop

ments in wages could not be explained by SBTC alone. For

example, wage inequality grew significantly within skill cat

egories as well, such as among college graduates . The upgrad

ing of j obs and the rise in the share of high-skill occupations

had been taking place since at least the 1 9 5 0 s , without nec

essarily producing inequality. Even if technological changes

were somehow b ehind all these trends, wasn't it possible that

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M O D E L S A N D T H E O R I E S

increased globalization was the stimulus b ehind the new

technologies introduced after the 1 970s? Finally, an impor

tant part of the rise in equality had to do with the growth of

incomes at the very top of the income distribution-the top

1 p ercent. A substantial part of that upward trend, in turn,

derived from capital income (returns on stocks and bonds)

rather than wage s .

These concerns made i t unlikely that SBTC on its own

could account for what was happening with inequality. A

third, catchall category of explanations focused on the wide

range of policy and attitudinal changes that had taken place

from the late 1 970s on. Macroeconomic policy became more

concerned about price stability and less focused on full employ

ment. Trade unions shrank, workers lost bargaining power,

and the minimum wage was allowed to lag behind prices .

Workplace norms that precluded large wage dispersion-the

gap between the highest and lowest paid employees-became

weaker. Deregulation and the vast expansion of the finance

sector enabled the amassing of fortunes that would have been

unthinkable decades ago. 2 1

In the end, it was clear that no single theory could fully

explain the story of US inequality since the 1970s. Nor was

there a good way of parsing the relative contributions of differ

ent theories. Certain theories (models) gave us a b etter under

standing of the channels through which trade, technology, and

other factors may have operated. The failure of other theories

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allowed us to rule out mechanisms that appeared equally plau

sible at the outset. There was no closure, but there was plenty

of learning along the way.

Theories Are Really Just Models

As we've seen, theories in economics are either so general that

they have little real leverage in the real world or so specific that

they can account at best for a particular slice of reality. I have

illustrated this conundrum with specific theories, but the point

is valid for other areas in economics as well. History has not

been kind to theorists who claimed to have discovered the uni

versal laws of capitalism. Unlike nature, capitalism is a human,

and therefore malleable, construction.

Yet judging by the frequency with which the term " the

ory" is used, economics is full of theorie s . There is game

theory, contract theory, s earch theory, growth theory, mon

etary theory, and so on. But do not be fo oled by the termi

nology. In reality, each one of these is simply a particular

collection of model s , to be applied judiciously and with due

care to setting. Each s erves as a tool kit rather than an all

purpose explanation of the phenomena it studies . As long as

more is not expe cted of them, these theories can b e quite

useful and relevant.

Nearly half a century ago, Albert Hirschman, one of eco

nomics' most creative minds, complained about social scien

tists' "compulsion to theorize " and described how the search

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M O D E L S A N D T H E O R I E S

for grand paradigms could be a " hindrance to understand

ing."22 The urge to formulate all-encompassing theories, he

feared, would blind scholars to the role of contingency and

the variety of possibilities that the real world threw their way.

Much of what happens in the world of economics these days

does reflect a more modest goal: the search for understanding

one cause at a time. When ambition eclipses this aim, trouble

often looms.

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CHAPTE R 5

When Econolllists Go Wrong

t is probably the shortest graduation speech on record.

When macroeconomist Tom Sargent stepped up to the

podium at UC Berkeley's graduation ceremony in May

2007, he said he found such speeches too long. He got right

to the heart of the matter. Economics , he said, is "organized

common sense." He went on to list twelve items that he said

"our beautiful subj ect teaches ." The first was , "Many things

that are desirable are not feasible." The second, " Individuals

and communities face trade-offs." By the fourth item, Sargent

was on to the role of the government: "Everyone responds

to incentives . . . . That is why social safety nets don't always

end up working as intended." Next item: " There are tradeoffs

between equality and efficiency," by which he meant that gov

ernments could improve the distribution of income only at

some economic cost.1

Sargent probably thought his list was uncontroversial.

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Indeed, his speech would earn plaudits from economists at

both ends of the political spectrum. But there were dissenters,

such as the economist and blogger Noah Smith. By the end

of the list, Smith complained, ten of Sargent's twelve lessons

were "cautions against trying to use government to promote

equality or help people." Paul Krugman was critical as well.

He chided Sargent for trying to pass off as universal truths ideas

that applied only to a well-functioning market economy at full

employment. Take Sargent's observation about the trade-off

between equality and efficiency. Smith wrote that there was,

in fact, no such trade-off under one of economics' benchmark

assumptions (that transfers among individuals can take place

without causing inefficiency) . Krugman pointed to recent

empirical research that suggested high inequality might ham

p er economic growth. 2

Sargent's critics were right. B eyond trite generalities such

as " incentives matter" or "beware unintended consequences,"

there are few immutable truths in economics . All the valuable

lessons that the "beautiful profession" teaches are contextual.

They are if-then statements in which the " if" matters as much

as the "then."

But Sargent did accurately summarize what economists tend to

think. Smith and Krugman notwithstanding, most economists

do believe, to continue with the same example, that there is a

trade-off b etween equity and efficiency. Mind you, these same

economists are fully aware that certain models (and some evi-

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dence) point in the opposite direction. But their existence does

not seem to stand in the way of a categorical near-consensus.

There are, in fact, many important matters on which nearly

all professional economists agree. Greg Mankiw, the Harvard

professor and author of a leading economics textbook, pro

vided a list in his blog a few years back. 3 Here are some of the

top ones (the numbers in parentheses indicate the percentage of

economists who agree with the proposition) .

1 . A ceiling on rents reduces the quantity and quality of

housing available. (93%)

2. Tariffs and import quotas usually reduce general eco

nomic welfare. (93%)

3. Flexible and floating exchange rates offer an effective

international monetary arrangement. (90%)

4. Fiscal policy (for example, tax cuts and/or government

expenditure increases) has a significant stimulative impact

on a less than fully employed economy. (90%)

5. The United States should not restrict employers from out

sourcing work to foreign countries. (90%)

6. The United States should eliminate agricultural subsidies.

(85%)

7. A large federal budget deficit has an adverse effect on the

economy. (83%)

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8. A minimum wage increases unemployment among young

and unskilled workers. (79%)

Unless you skipped the previous chapters, the degree of con

sensus on these propositions should surprise you. For at lea.st

four of the eight, we have already seen models that contradict

them. Rent controls (ceilings on what landlords can charge) do

not necessarily restrict the supply of housing if landlords behave

monopolistically, trade restrictions do not necessarily reduce effi

ciency, fiscal stimulus does not necessarily work, and minimum

wages do not necessarily raise unemployment. In all of these

cases, there are models with imperfect competition, imperfect

markets, or imperfect information where the reverse outcome

prevails. The same is true of Mankiw's other propositions as well.

What economics teaches us are the explicit conditions

critical assumptions-under which one conclusion or its oppo

site is correct. - Yet virtually all the economists surveyed (90

percent or more) are apparently willing to vouch for the gen

eral validity of a particular set of critical assumptions. Perhaps

they stick their necks out because they believe those assump

tions are more common in the real world. Or they think one

set of models works b etter "on average" than any other. Even

so, as scientists , should they not adorn their endorsements

with the appropriate caveats? Shouldn't they worry that such

categorical statements have the p otential to mislead?

We have arrived at one of the central paradoxes of econom

ics: uniformity amid diversity. Economists work with a pleth-

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WH E N E C O N O M I S T S G O WRO N G

ora of models, pointing in all kinds of contradictory directions.

Yet when it comes to the issues of the day, their views often

converge in ways that cannot be justified by the strength of the

available evidence.

Let me be clear: Economists are constantly debating vig

orously on a variety of issues. What should the top income

tax rate be? Should the minimum wage be raised? Are pat

ents important for stimulating innovation? On these and many

other issues , economists often see both sides . Frustrated by the

conflicting and hedged advice he was receiving from his advis

ers, President Harry S . Truman is said to have asked for a "one

handed economist." "If all the economists were laid end to end,

they' d still not reach a conclusion," George B ernard Shaw once

supposedly quipped. An economists' consensus is perhaps more

a rarity than a regularity. But when it happens, we need to

pause and take stock.

Sometimes the consensus is innocuous: Yes , incentives do

matter. Sometimes it may be appropriately circumscribed, geo

graphically or historically:* Yes , the Soviet economic system

* Roger Gordon and Gordon B. Dahl report "broad consensus" among a

panel of economists from leading academic departments on fairly specific

questions, such as whether "the Fed's new policies in 2 0 1 1 will increase

GDP growth by at least 1% in 2 0 1 2 . " They also find, appropriately, that

there is greater agreement when the academic literature relevant to the

question is large. Gordon and Dahl, "Views among Economists: Professional

Consensus or Point-Counterpoint?" American Economic Review: Papers &

Proceedings 103, no. 3 (2013): 629-35 .

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E C O N O M I C S RUL E S

was hugely inefficient. At other times, consensus reflects an

evaluation after the fact based on accumulated evidence: Yes ,

the Obama fiscal stimulus of 2009 reduced unemployment.

But when a consensus forms around the universal applicability

of a conclusion from a specific model, the critical assumptions

of which are likely to be violated in many settings-as with

p erfect competition, say, or full consumer information-we

have a problem.

When economists confuse a model for the model, two kinds

of mischief may follow. First there are the errors of omission,

in which a blind spot shows up in the inability to see troubles

looming ahead. Most economists, for instance, failed to grasp

the dangerous confluence of circumstances that produced the

global financial crisis of 2 0 07-8 . Then there are the errors

of commission, in which fixation on a particular view of the

world makes economists complicit in policies whose failure

might have been predicted ahead of time. Economists' advo

cacy of the so-called Washington Consensus and of financial

globalization are in this category. Let's consider both types of

errors in more depth.

Errors of Omission : The Financial Crisis

Soon after the financial crisis broke, University of Chicago

legal theorist and economist Richard Posner castigated his

economist colleagues . The profession's leading economists, he

wrote, thought another depression was out of the question, asset

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WH E N E C O N O M I S T S G O WRO N G

bubbles never happened, global banks were safe and sound,

and the US national debt was nothing to worry about. 4 Yet all

these beliefs turned out to be false. The housing bubble burst in

2 0 0 8 , bringing down the US financial industry alongside it and

triggering a maj or government bailout to stabilize the sector.

The crisis simultaneously spilled over to Europe and the rest of

the world, producing the worst economic downturn since the

Great Depression. Unemployment peaked at 10 percent in the

United States in October 2009, before coming down to 5 . 6

percent b y the end of 2014. A s I write these words in late 2014,

nearly one young worker out of four remains unemployed in

the countries that are part of the Eurozone.

Many economists were worried about the state of the US

economy prior to the crisis. But the main obj ects of concern

were the country's low saving rate and the outsized current

account deficit-the large excess of imports over exports.

When scenarios of a so-called hard landing were entertained,

the fo cus was a possible sharp depreciation of the US dollar,

which would have rekindled inflation and undermined con

fidence in the US economy. The crisis hit instead in an area

where very few people expected it. The soft underbelly of the

US economy turned out to be housing and the bloated finan

cial sector that had supercharged it.

A p oorly regulated shadow banking sector had created an

alphabet soup of new financial instruments. These new deriva

tives were supposed to have distributed risk to those who were

willing to b ear it. Instead, they facilitated risk taking and over-

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E C O N O M I C S RUL E S

use of leverage. They also connected disparate segments of the

economy in ways that no one fully grasped at the time, ensur

ing that failure at one end would precipitate collapse at the

other. With a few, but notable, exceptions, such as the future

Nobel Prize winner Robert Shiller and the future governor of

India's Central Bank and Chicago economist Raghu Raj an,

economists overlooked the extent of problems in housing and

finance. Shiller had long argued that asset prices were exces

sively volatile and had focused on a bubble in housing prices. 5

Raj an had fretted about the downside of what was then praised

as "financial innovation" and warned as early as 2005 that

bankers were taking excessive risks , earning a rebuke from

Larry Summers, then president of Harvard, as a "Luddite."6

That economists were mostly blind-sided by the crisis is

undeniable. Many interpreted this as evidence of a fu nda

mental breakdown in economics . The discipline needed to

b e rethought and reconfigured. But what makes this episo de

particularly curious is that there were, in fact, plenty of mod

els to help explain what had b een going on u nder the econ

omy's hood.

Bubbles-steady increases in asset prices divorced from their

underlying value-are not a new phenomenon. Their presence

was known going back at least to the tulip craze of the sev

enteenth century and the South S ea bubble of the early eigh

teenth century. They were the obj ect of study in models of

varying complexity, including models based on p erfectly ratio

nal, forward-looking investors (so-called rational bubbles). The

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W H E N E C O N O M I S T S G O WR O N G

financial crisis of 2008 had all the features of a bank run, and

that, too , was a staple of economics. Models of self-fulfilling

panic-a coordination failure in which individually rational

withdrawals of credit lines produce collective irrationality

in the form of a systemic drying up of liquidity-were well

known to every student of economics, as were the conditions

that facilitate such panics. The need for deposit insurance (cou

pled with regulation) to prevent bank runs was featured in all

finance textbooks.

A key pattern in the run up to the crisis was excessive risk tak

ing by managers of financial institutions. Their compensation

depended on it, but their behavior was not consistent with the

interests of the banks' shareholders. This divergence between

the interests of managers and shareholders is a centerpiece of

principal-agent models. These models focus on situations in

which a "principal" (a regulator, electorate, or shareholders)

tries to control the behavior of an "agent" (a regulated firm,

elected government, or CEO) when the latter has more infor

mation about the economic environment than the former. The

resulting difficulties and inefficiencies should not have come as

a surprise to economists. Another incentive distortion centered

around credit-rating agencies that evaluated mortgage securi

ties. These agencies were paid by the same financial institutions

whose issuances they rated. That they had an incentive to tailor

their ratings to the satisfaction of their paymasters ought to

have been obvious even to a first-year student in economics.

The economy-wide consequences of asset price collapses

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E C O N O M I C S RUL E S

were also familiar to economists after a wave of financial crises

experienced by developing countries from the early 1980s on.

No one who had studied these episodes should have remained

nonchalant about the buildup of private debt in housing and

construction in the United States and Europe . The man

ner in which deleveraging would reverberate throughout the

economy, being magnified along the way as banks , firms, and

households all tried simultaneously to reduce their debt and

build up their financial assets, was also reminiscent of those

earlier financial crises.

Clearly, economists did not lack models to understand what

was happening. In fact, once the crisis b egan to play itself out,

the models that we just reviewed would prove indispensable for

understanding how, for example, China's decision to accumu

late large amounts of foreign reserves would ultimately cause

a mortgage lender in California to take excessive risks. All the

steps in between-the reduction in interest rates as demand for

dollar assets went up, the incentive of poorly supervised finan

cial institutions to seek riskier instruments to maintain profits,

the building up of financial fragility as portfolios expanded

through short-term borrowing, the inability of shareholders to

properly rein in bank CEOs, the bubble in housing prices

could be readily explained by existing frameworks. But econo

mists had placed excessive faith in some models at the expense

of others, and that turned out to be a big problem.

Many of the favored models revolved around the "efficient

markets hypothesis" (EMH).7 The hypothesis had b een formu-

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WH E N E C O N O M I S T S G O WR O N G

lated by Eugene Fama, a Chicago finance professor who would

subsequently receive the Nobel Prize, somewhat awkwardly,

in the same year as Robert Shiller. It says, in brief, that mar

ket prices reflect all information available to traders. For an

individual investor, the EMH means that, without access to

inside information, beating the market repeatedly is impos

sible. For central bankers and financial regulators, the EMH

cautions against trying to move the market in one direction or

another. Since all the relevant information is already contained

in market prices, any intervention is more likely to distort the

market than to correct it.

The EMH does not imply that observers could have fore

seen the financial crisis . In fact, since it says changes in asset

prices are unpredictable, it implies quite the opposite-that the

crisis could not have b een predicted. Nevertheless, it is hard to

square the model with the reality: a sustained rise in asset prices

followed by a sharp collapse. To explain it without j ettison

ing EMH requires us to believe that the financial collapse was

caused by a huge rush of " bad news" about the future prospects

of the economy, which markets then priced in instantaneously.

(This is more or less what Fama himself would argue in 2 0 1 3 .)*

* Fama concedes that he doesn't have a reason for why future economic

prospects would have worsened so drastically, but he adds that he isn't a

macroeconomist, and macroeconomics has never been goo d at discerning

when recessions are coming on. John Cassidy, "Interview with Eugene

Fama," New Yorker, January 1 3 , 2010, http : //www.newyorker.com/news/

j ohn-cassidy /interview-with-eugene-fama.

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E C O N O M I C S RUL E S

This conclusion reverses the generally accepted line of causa

tion, which goes from the financial crash to the great recession.

Excessive reliance on EMH, to the neglect of models of bub

bles and other financial-market pathologies, b etrayed a broader

set of predilections. There was great faith in what financial

markets could achieve. Markets became, in effect, the engine

of social progress. They would not only mediate efficiently

b etween savers and investors; they would also distribute risk to

those most able to bear it and provide access to credit for previ

ously excluded households, such as those with limited means

or no credit history. Through financial innovation, portfolio

holders could eke out the maximum return while taking on

the least amount of risk.

Moreover, markets came to be viewed not only as inher

ently efficient and stable, but also as self-disciplining. If big

banks and speculators engaged in shenanigans, markets would

discover and pl1nisli them. Investors who made bad decisions

and took inappropriate risks would be driven out; those who

behaved responsibly would profit from their prudence. Federal

Reserve Chairman Alan Greenspan's mea culpa before a 2008

congressional panel would speak volumes about the prevailing

state of mind: "Those of us who have looked to the self-interest

of lending institutions to protect shareholders' equity, myself

included," he confessed, "are in a state of shocked disbelie£"8

Government, meanwhile, could not be trusted. Bureau

crats and regulators were either captive to special interests

or incomp etent-and sometimes b oth at once. The less they

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WH E N E C O N O M I S T S G O WR O N G

did, the better. And in any case, financial markets were now

so sophisticated that any effort at regulating them was futile.

Financial institutions would always find a way around the

regulations. Government was condemned to follow one step

behind. Such thinking by economists had legitimized and

enabled a great wave of financial deregulation that set the stage

for the crisis. And it didn't hurt that these views were shared

by some of the top economists in government, such as Larry

Summers and Alan Greenspan.

In sum, economists (and those who listened to them) became

overconfident in their preferred models of the moment: mar

kets are efficient, financial innovation improves the risk-return

trade-off, self-regulation works b est, and government inter

vention is ineffective and harmful. They forgot about the other

models. There was too much Fama, too little Shiller. The eco

nomics of the profession may have been fine, but evidently

there was trouble with its psychology and sociology.

Errors of Commission:

The Washington Consensus

In 1 989, John Williamson convened a conference in Washing

ton, D C , for maj or economic policy makers from Latin Amer

ica. Williamson, an economist at the Institute for I nternational

Economics, a Washington think tank (now called the Peterson

I nstitute) , was a longtime observer of the region's economies .

He had noticed a remarkable convergence of views among

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E C O N O M I C S RUL E S

policy makers on recommended reforms for Latin America.

Virtually identical slates of ideas emanated from international

financial institutions such as the World B ank and the Inter

national Monetary Fund, think tanks, and various economic

agencies of the US government. Economists with PhDs from

US universities had meanwhile taken important positions in

Latin American governments, and they were rapidly imple

menting those same policies . In the paper he wrote for the

conference, Williamson termed this reform agenda the "Wash

ington Consensus ."9

The term took off--and took on a life of its own. It came to

denote an ambitious agenda that, critics charged, aimed to turn

developing nations into textbook cases of free-market econo

mies. This may have been hyperbole, but it accurately described

the general drift. The agenda reflected an urge to unshackle

these economies from the restraints of government regulation.

The policy economists in Latin America and their advisers in

Washington were convinced that government intervention had

crushed growth and brought about the debt crisis of the 1980s.

The remedy could be summarized in three words: "stabilize,

privatize, and liberalize." Williamson would frequently protest

that his own list had described modest reforms that fell far short

of "market fundamentalism," the blanket term for the view

that markets are the solution to all public policy problems. But

the term "Washington Consensus" fit the zeitgeist of the era

only too well.

Advocates of the Washington Consensus-whether in its

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original or expanded versions-presented it as good economics.

For them, the policies reflected what sound economics teaches:

Free markets and competition enable the efficient allocation

of scarce resources. Government regulations, trade restric

tions, and state ownership create waste and hamper economic

growth. But this was an economics that did not go beyond

Econ 1 0 1 , as the advocates ought to have recognized .

O ne problem was that the Washington Consensus skated

over the deeper institutional underpinnings of a market econ

omy, without which none of the market-oriented reforms

could reliably deliver their intended benefits. To take the

simplest example, in the absence of the rule of law, contract

enforcement, and proper antitrust regulations , privatization is

as likely to create monopolies for government cronies as it is to

foster competition and efficiency. As the importance of institu

tions sank in, because of the poor response of many economies

to Washington C onsensus policies , reform efforts expanded

in their direction. But it is one thing to slash import tariffs

or remove ceilings on interest rates-two common enough

approaches-and quite another to install, on short order, insti

tutions that advanced economies acquired over decades, if not

centuries. A useful reform agenda had to work with existing

institutions, not engage in wishful thinking.

Further still, the Washington Consensus presented a univer

sal recipe. It presumed that all developing countries were pretty

much alike-suffering from similar syndromes and in need of

an undifferentiated list of reforms. Local context received little

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E C O N O M I C S RUL E S

consideration, as did the need to prioritize according to urgency

or feasibility of reforms. As country after country failed to

respond to the reforms, the advocates' instinct was to expand

the "to do" list rather than to fine-tune the reforms already in

place. So the initial Washington Consensus was supplemented

by a burgeoning list of additional measures encompassing labor

markets, financial standards, governance improvements, cen

tral banking rules, and so on.10

The economists behind the Washington Consensus for

got they were operating in an inherently second-best world.

As discussed in Chapter 2, in environments where markets

are subj ect to multiple imperfections , the usual intuition on

the effects of policies can be quite misleading. Privatization,

deregulation, and trade liberalization can all backfire. Market

restrictions of a certain sort can be desirable. Policy reforms

in these environments require models that explicitly take such

second-best complications into account.

Consider how opening up to trade-one of the key items

of the Washington Consensus-was supposed to work. As

barriers to imports were slashed, firms that were unable to

compete internationally would shrink or close down, releas

ing their resources (workers, capital, managers) to be employed

in other parts of the economy. More efficient, internationally

competitive sectors, meanwhile, would expand, absorbing

those resources and setting the stage for more rapid economic

growth. In Latin American and African countries that adopted

this strategy, the first part of this prediction largely material-

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ized, but not the second. Manufacturing firms, previously pro

tected by import barriers, took a big hit. But the expansion of

new, export-oriented activities based on modern technologies

lagged. Workers flooded less productive, informal service sec

tors such as petty trading instead. Overall productivity suffered.

Why did this happen? Many of the affected markets did not

work as expected. Labor markets were not flexible enough to

reallocate labor quickly to new, more efficient sectors . Capital

markets failed to support the creation of export-oriented firms.

The currency remained overvalued, rendering the bulk of

manufacturing globally uncompetitive. C o ordination failures,

knowledge spillovers, and the high cost of establishing a beach

head kept potential entrants out of new areas of comparative

advantage. And governments, strapped for cash, were unable to

invest in the infrastructure or other forms of support required

by nascent industries.

Washington Consensus outcomes m Latin America and

Africa stand in sharp contrast with the experience of Asian

countries. The latter pursued strategies of global engagement

that were explicitly second best. Instead of liberalizing imports

early on, South Korea, Taiwan, and later China all began their

export push by directly subsidizing homegrown manufacturing.

Inefficient manufacturing enterprises were protected during the

early stages, to prevent large job losses that would, in all likeli

hood, lead to the expansion of even less productive informal

occupations such as retail trade. These countries also employed

macroeconomic and financial controls that kept their currencies

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E C O N O M I C S RUL E S

competitive in world markets . All of them undertook industrial

policies to nurture new manufacturing sectors and reduce their

economies' dependence on natural resources. And each country

fine-tuned the specifics of its strategy beyond these generalities.

Many observers of Asia's experience and the success of its

"unorthodox" policies conclude that these cases have proved

standard economics wrong. This interpretation is incorrect.

It is true that many of Asia's economic p olicies do not make

sense in light of economic models with well-functioning mar

kets . But these are evidently the wrong models to use. There

is very little in China's or South Korea's strategy that cannot

b e explained by models that take on board some of the major

second-best challenges these economies faced. 1 1 When econo

mists confront the way markets really work-or fail to work

in low-income settings with few firms , high barriers to entry,

poor information, and malfunctioning institutions, these alter

native models prove indispensable.

Where economists pushed the logic of the Washington

Consensus the furthest, with probably the greatest damage,

was in financial globalization. Williamson's original list did not

include freeing up cross-border capital flow; he was a skeptic

about the benefits of financial globalization. Yet by the mid-

1990s, removing obstacles to the free flow of capital around the

world had become the last frontier of market-based economics.

The Organisation for Economic Co-operation and Develop

ment (OECD), the rich-country club, made the freeing up of

capital movements across countries a precondition for mem-

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WH E N E C O N O M I S T S G O WR O N G

bership. And senior economists at the International Monetary

Fund (IMF) tried to enshrine the principle of free capital flow

in the organization's charter.

B ehind this push lay the thinking of distinguished econo

mists such as onetime MIT professor Stanley Fischer. Fischer

had j oined the IMF in 1994 as the deputy to its managing

director and chief economist. He was well aware that liberal

izing financial flow across national borders could create insta

bility. The historical record of free finance certainly presented

plenty to worry about. The financial excesses under a previous

era of financial globalization during the interwar period-the

recurring financial panics and crashes, the painful economic

adjustments that flowed from sudden movements in market

sentiment, and the tight constraints placed on managing the

ups and downs of the macroeconomy-had been foremost on

Keynes's mind when he argued for capital controls at the end

of the Second World War.

Fischer did not overlook these risks, but he thought they

were worth taking. Free capital movement would enable

greater efficiency in the global allocation of savings. Capital

would flow from where it was plentiful to where it was scarce,

thus increasing economic growth. Residents of poor nations

would have access both to a larger pool of investible resources

and to foreign capital markets to diversify their portfolios. The

risks of instability, meanwhile, could be reduced by improving

macroeconomic management and enhancing financial regula

tion. 12 Fischer acknowledged the scant systematic evidence for

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developing countries benefiting from greater freedom of capi

tal mobility, but he thought it was only a matter of time before

such evidence would accrue.

Fischer's implicit model once again significantly discounted

second-best complications. He presumed that domestic macro

economic and regulatory weaknesses could be overcome with

sufficient will on the part of governments . In reality, these

changes proved much harder to accomplish, in part because

economists turned out to know little about what needed to

be done. Free capital mobility, coupled with domestic macro

economic and financial distortions, turned out to have severe

adverse outcomes. Access to foreign capital markets allowed

domestic banks to binge on short-term foreign debt, and it

enabled imprudent governments to borrow more than they

ever could on domestic markets . The consequence was a string

of painful financial crises in Thailand, South Korea, Indonesia,

Mexico, Russia;-Argentina, Brazil, Turkey, and elsewhere. The

IMF would eventually concede that full liberalization of capital

flow was not an appropriate objective f or all countries. 13

There was another problem. Advocates of financial glo

balization bought into a growth model in which the main

driver was the supply of saving and investable funds . In this

model, greater access to foreign finance would boost domestic

investment and produce higher rates of economic growth. Yet

neither investment nor growth rose in the developing coun

tries that opened themselves up to foreign finance. The lack

of a positive trend in investment or growth suggested that

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the constraints to growth in many of these countries lay else

where. Firms failed to invest not because they were shut out

of finance, but because (for a variety of reasons) they did not

foresee high returns. Increased financial flow stimulated con

sumption rather than investment. Moreover, by appreciating

the domestic currency, capital inflow made things worse, by

further cutting into the profitability of tradable industries. In

this alternative model, apparently describing reality b etter for

many developing and emerging market economies, free capital

flow was a poisoned gift .

The good news is that most economists learned their lesson

from this experience. On both the Washington Consensus and

financial globalization, there is now broad agreement that there

had been excessive zeal for a universal approach that oversold

the benefits of unfettered markets . Today it is almost a mantra

for development economists , finance experts, and international

agencies that no single set of policies is appropriate for all coun

tries and that domestic reforms must be tailored to specific cir

cumstances. C ommon blueprints are out; model selection is in.

The Psychology and Sociology of Economics

Is there something specific to economics that makes its prac

titioners more likely to commit such errors of omission or

commission? Would political scientists and anthropologists, for

example, claim a better record for their disciplines in public

debates? I am not sure. One difference is that economists are

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E C O N O M I C S R UL E S

more visible. Because many economists operate in the public

sphere and are called upon to advise on policy, their mistakes,

when they occur, are more noticeable. Nevertheless, it is worth

pondering what makes economists go astray.

To begin with, let's recognize that the public is rarely

exposed to the full range of views within economics. The

vast maj ority of economists see themselves as scientists and

researchers whose job is to write academic papers , not pontifi

cate on current events or advocate sp ecific policies . These are

the kinds of economists who are rarely contacted by j ournalists

or congressional aides, and would likely run away if they were.

When they're willing to engage on public issues , they adorn

their statements with so many ifs and buts that they have diffi

culty finding an audience. Most are quintessential ivory-tower

economists who would readily grant that they have limited

expertise to comment on public matters-at least without fur

ther study.

The economists whose voices are heard have either strong

convictions, or a willingness to overlook the fine print on p ol

icy recommendations. Or both. It is these advocates, with a

clear position on the issues, who have a natural advantage in

the media, think tanks, and government corridors. Often they

are successful "policy entrepreneurs" who make a difference

for the better. Auctions of wireless spectrum rights and airline

deregulation were both ideas that committed economists con

vinced politicians to adopt.14 In other cases, as we've seen, the

ideas b eing trumpeted may be more doubtful, and the advo�

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WH E N E C O N O M I S T S G O WR O N G

cates' pronouncements may be looked upon with skepticism,

or even scorn, by the rest of the profession. But few economist

critics will be troubled to challenge them publicly.

At the height of the Washington Consensus craze, I wrote

a paper with a graduate student criticizing the unconditional

advocacy of freer trade as a growth engine for developing

countries. 1 5 We pointed out that the relationship between trade

policy and growth was model- and country-specific. We also

showed that there was no strong or uniform evidence one way

or another. After circulating and presenting the paper, I got

two kinds of reactions. Committed advocates of the Washing

ton Consensus thought I was muddying the waters and under

mining the good cause of free trade. But many others expressed

their appreciation, complaining that the push for trade liberal

ization had gone much beyond what economic research was

able to support. The second type of reaction was unexpected,

since it came from people who had not taken a public stance.

They had chosen not to have their voices heard, despite their

skepticism. As a result, the public message was not representa

tive of the profession as a whole, where views were, in fact,

considerably more hedged.

It is certainly true that economists err on the side of mar

kets . To put it bluntly, economists feel proprietary. They think

they understand how markets work, and they fear that most

of the public doesn't-and they are largely right on both sup

positions. They know that markets can fail in myriad ways .

But they think the public's concerns are often ill informed,

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E C O N O M I C S RUL E S

exaggerated, and unjustified, so they are overly protective of

markets . Supply and demand, market efficiency, comparative

advantage, incentives-these are the crown j ewels of the pro

fession that need defending from the ignorant masses. Or so

the thinking goes.

Promoting markets m public debates has today become

almost a professional obligation. Economists' contributions in

public can therefore look radically different from their discus

sions in the seminar room. Among colleagues, the shortcom

ings of markets and the ways in which policy intervention can

make things better are fair game. Academic reputations are

built on new and imaginative demonstrations of market failure.

But in public, the tendency is to close ranks and support free

markets and free trade.

This dynamic produces what I call the "barbarians are only

on one side" syndrome. Those who want restrictions on mar

kets are organized lobbyists, rent-seeking cronies , and their ilk,

while those who want freer markets, even when they're wrong,

have their hearts in the right place and are therefore much less

dangerous. Taking up the cause of the former gives ammuni

tion to the barbarians, while siding with the latter is, at worst,

an honest mistake with no huge consequences.

Forced to take a stand, most economists are likely to cast

their vote in favor of the more market-oriented alternative.

We can see this leaning in the list of things that command sig

nificant consensus among economists at the beginning of this

chapter. 16 Of the fourteen items on the full list, only one has

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WH E N E C O N O M I S T S G O WR O N G

a decidedly pro-government bent, in favor of fiscal stimulus

during a recession.* A few reflect preferences b etween dif

ferent types of policy: budgets should be balanced over the

business cycle rather than year by year, cash payments are pref

erable to payments in kind such as free food, and the welfare

system should be replaced with a "negative income tax" (a

system of progressive taxation in which poor families receive

transfers from the government) . The vast majority of the rec

ommendations urge more reliance on markets and less gov

ernment intervention.

B eyond the general bias toward markets , economists are not

always good about drawing the links between their models and

the world. B ecause economists go through a similar training

and share a common method of analysis, they act very much like

a guild. The models themselves may be the product of analysis,

reflection, and observation, but practitioners' views about the

real world develop much more heuristically, as a by-product

of informal conversations and socialization among themselves .

This kind of echo chamber easily produces overconfidence

in the received wisdom or the model of the day. Meanwhile,

the guild mentality renders the profession insular and immune

* Ninety percent of economists reportedly agree with the following

proposition: " Fiscal policy (for example, tax cut and/or government

expenditure increase) has a significant stimulative impact on a less than

fully employed economy." Greg Mankiw, "News Flash: E conomists

Agree," February 14, 2009, Greg Mankiw's Biog, http://gregmankiw

.blogspot.com/2009/02/news-flash-economists-agree.html.

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E C O N O M I C S RUL E S

to outside criticism. The models may have problems, but only

card-carrying members of the profession are allowed to say

so. The obj ections of outsiders are discounted b ecause they do

not understand the models. The profession values smarts over

judgment, being interesting over being right-so its fads and

fashions do not always self- correct.

These problems are compounded by the fact that accepted

practice does not require economists to think through the con

ditions under which their models are useful. Asked point-blank,

they can state chapter and verse all the assumptions needed to

generate a particular result; that is, after all, the point of mod

eling. But ask them whether the model is more relevant to

Bolivia or to Thailand, or whether it resembles more the mar

ket for cable TV or the market for oranges, and they will have a

hard time producing an articulate answer. The standards of the

profession require that the modeler make only some general

claims about how what he or she is doing is relevant to the real

world. It is left to the reader or the user of the model to infer

the specific circumstances in which the model can help us b et

ter understand reality.* This fudge factor increases the chances

of malpractice . Models lifted out of their original context can

be used in settings for which they are inappropriate.

* As University of East Anglia economist Robert Sugden points out, "In

economics . . . there seems to .be a convention that modellers need not be

explicit about what their models tell us about the real world." Sugden,

"Credible Worlds, Capacities and Mechanisms" (unpublished paper, School

of Economics, University of East Anglia, August 2008), 1 8 .

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WH E N E C O N O M I S T S G O W R O N G

At the empirical end of economics, such as labor and devel

opment economics, where almost all economists work directly

with data and real�world evidence, paradoxically the problems

may be even more severe. This is because the underlying model

is often left unspecified from the outset. The empirical nature

of the analysis may make us think that we've learned more than

we have. Many empirical researchers believe that their work

does not require models at all . After all, they are simply asking

whether something works or whether A causes B. But behind

all causal assertions lie a model of some sort. If greater educa

tion results in higher earnings, for example, is that b ecause of

the returns to education or because education provides incen

tives to work harder, thereby also increasing earnings?17 Being

explicit about those models clarifies the nature of the finding

and also highlights their contingent character. Once the model

is laid out, we can see what the finding depends on and how

easily the finding can be extrapolated to other settings .

As we've seen, some of the most interesting applied work

these days takes the form of randomized field experiments in

which the researcher tests whether specific policy interventions

produce the intended effects (or not). These are meant to speak

directly to how the real world works-in one particular set

ting. But they again remain largely silent about the specific

conditions under which the findings apply-the features of

the economy and society to which the intervention may have

been particularly suited-and those under which we shouldn't

expect them to apply. They can easily produce the impres-

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E C O N O M I C S RUL E S

sion that the results are general when they are, in fact, deeply

context-specific.

The bottom line is that there is much to complain about

in the practices and professional biases of economists . But are

these shortcomings fundamental problems that render the

entire discipline an inherently flawed approach to social real

ity? I do not think so.

Power and Responsibility

Why do economists wield power beyond the classroom in the

first place? It is not evident that they should, given that most

of the discipline's practitioners are content with producing

research articles for each other and crave no such power.

The twin origins of their supposed power are slightly in ten

sion with each other. First, their discipline has scientific pre

tensions; it brings useful knowledge to b ear on public policy

questions. Second, their models provide narratives that lodge

easily in the popular consciousness. These fable-like narratives

often have morals that can be formulated in catchy terms (for

example, "taxation kills incentives") and also sync up with clear

political ideologies . The science and the storytelling parts are

usually complementary, as I explained in Chapter 1 . Working

in tandem, they enable economists' beliefs to gain tremendous

traction in the public debate.

Mischief occurs when economists begin to treat a model

as the model. Then the narrative takes on a life of its own

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WH E N E C O N O M I S T S G O WR O N G

and becomes dislodged from the setting that produced it. It

turns into an all-purpose explanation that obscures alternative,

and potentially more useful, story lines. Luckily, the antidote

exists-within economics . The corrective is for economists to

return to the seminar room and remind themselves of the other

models in their collection.

In an earlier book, I wrote that there are two kinds of econ

omists, drawing on a distinction made famous by the British

philosopher Isaiah B erlin. Even though I had in mind special

ists on the international economy at the time, the idea applies

more broadly. 18 "Hedgehogs" are captivated by a single big

idea-markets work best, governments are corrupt, interven

tion backfires-which they apply unremittingly. " F oxes ," by

contrast, lack a grand vision and hold many different views

about the world-some of them contradictory. The hedge

hog's take on a problem can always be predicted: the solu

tion lies in freer markets, regardless of the exact nature of

and context for the economic problem. Foxes will answer, " It

depends"; sometimes they recommend more markets, some

times more government.

Economics needs fewer hedgehogs and more foxes engaged

in public debates . Economists who are able to navigate from one

explanatory framework to another as circumstances require are

more likely to point us in the right direction.

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CHAPTER 6

Econoniics and Its Critics

n economist, a physician, and an architect are travel

ing on a train together, and they fall into a discus

sion as to which one of their professions is the most

honorable. The physician points out that God created Eve out

of Adam's rib, so He must have b een a surgeon. The architect

jumps in and says, "Before Adam and Eve existed, the universe

had to be created out of chaos, and that surely was a feat of

architecture." At which point, the economist says, "And where

do you think chaos came from?"*

Economics without its critics would be like Hamlet without

the prince. The discipline's scientific pretensions, its exalted

status within the social s ciences, and its practitioners' influence

* I heard this joke on a BBC radio program when I was a college student,

and it was told, characteristically, by an economist, E. F. Schumacher.

Economists are their own harshest critics.

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E C O N O M I C S RUL E S

in public debates are a magnet for detractors. Critics accuse

economists of having a reductionist approach to social phenom

ena, making unfounded universal claims, ignoring the social,

cultural, and political context, reifying markets and material

incentives, and having a conservative bias. I have complained

myself at length in this book about two weaknesses: the lack

of attention to model selection and the excessive focus at times

on some models at the expense of others. In plenty of instances

economists have led the world astray.

But I will argue in this chapter that much of the broader

criticism misses its mark. E conomics is a collection of mod

els that admits a wide diversity of p o ssibilities , rather than a

set of prepackaged conclusion s . As three economists , them

s elves criti c s , put it, standard accounts "tend to miss the

diversity that exists within the profession, and the many

new ideas that are b eing tried out," and they often overlook

the reality that "one can b e p art of the mainstream and yet

not necessarily hold ' ortho dox' ideas ."1 The critics do have

a p oi nt when they say e conomists act in ways that suggest

o therwise , by preaching universal solutions or market fun

damentalism. B ut critics also need to understand that econ

omists who do this are , in fact, not b eing true to their own

disc ipline . Such economists deserve their fellow e conomists'

rebuke as much as outsiders' reproach. O nce this p oint is

recognized, many of the standard criticisms are nullified or

lose their bit e .

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E C O N O M I C S A N D I T S CRI T I C S

Reconsidering the Usual Criticisms

We have seen some of the leading criticisms under various

guises in earlier chapters , . Take the complaint that economic

models are too simple. This obj ection misunderstands the

nature of analysis. Simplicity is, in fact, a requirement of sci

ence. Every explanation, hypothesis, causal account is neces

sarily an idealization; it leaves many things out so that it can

focus on the essence. The term "analysis" itself has its roots in

Greek, where it signifies the breaking of complex things into

simpler elements. It is the antonym of "synthesis," which refers

to combining things. Neither analysis nor synthesis is possible

without these simpler components.

Simple need not mean simplistic, of course. As Einstein is

supposed to have said, "Everything should b e made as sim

ple as possible, but no simpler." When causal mechanisms

interact strongly with each other and cannot be studied in

isolation, models do need to include those interactions . If a

coffee blight, say, both raises costs of production and disrupts a

price-fixing agreement among principal coffee exporters, we

cannot analyze the effects of each-the supply shock and the

reduced cartelization-separately. Such models will be more

complicated than others . But they will still fall far short of

claiming to represent social reality in any great detail . If this

is what the advocates of complexity have in mind, there can b e

n o obj ection to it. When, o n the other hand, the underlying

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E C O N O M I C S RUL E S

relationships remain nebulous or undefined, and purported

explanations do not build on such simple elements, complexity

can only lead to incoherence.

So, too, consider the related criticism that economic mod

els make unrealistic assumptions. Economics stands guilty as

charged. Many assumptions that go into economic models

p erfect competition, p erfect information, p erfect foresight

are patently untrue. But as I explained in Chapter 1 , models

with unrealistic assumptions can be as useful as lab experi

ments performed under conditions that depart starkly from

the real world. B oth allow us to identify a cause-effect rela

tionship by isolating it from other confounding factors. Criti

cal assumptions-those that relate directly to the substantive

result or the question asked-are where care is required. We

would not want to build an airplane on principles that derive

from a vacuum.

C onsider the effects of a sales tax on cars . The degree to

which consumers think of small and large cars as the same

(as substitutes for each other) is not of great interest when we

contemplate the effects of a (percentage) tax on all c ars across

the b oard. We might as well assume that these types of cars

are p erfect substitutes. But if the tax is on luxury cars alone,

the p erfect-substitutes assumption is no longer innocuous .

The effects on government revenue and car sales will depend

critically on the size of what economists call the cross-price

elasticity of demand (the sensitivity of demand for one cat

egory of goods to the price of another category) . The larger

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E C O N O M I C S A N D I T S CRI T I C S

this elasticity (in absolute value) , the greater the shift i n con

sumer purchases from large to small cars , and the lower the

tax revenues collected by the government. Economists have

to ensure that their prescriptions hold even when assumptions

become more realistic .

Since they take the individual as their unit of analysis , econ

omists are frequently criticized for neglecting the role of social

and cultural determinants ofbehavior. Sociologists and anthro

pologists often seek explanation for outcomes at the level of

the community or society instead of individuals. (Economists'

preference for basing aggregate outcomes on individual deci

sions is called "methodological individualism" and is similar to

the proclivity toward microfoundations in macroeconomics.)

Cultural practices and social norms are what valorize certain

categories of consumption and b ehavior and stigmatize oth

ers, these critics argue, and they often play the determining

role even when economic decisions such as consumption and

employment are involved. Economists' obsession with choices

made by individual households or investors, according to this

line of thought, obscures the fact that preferences and behav

ioral patterns are "socially constructed," or imposed by the

structure of society. 2

It is certainly true that economists' most basic benchmark

models neglect the social and cultural roots of people's prefer

ences and constraints. But there is no reason the models can

not be extended to incorporate these influences and to work

out their implications. In fact, an active research program in

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E C O N O M I C S R UL E S

economics does exactly this, analyzing how identities , norms,

and cultural practices are shaped by the interaction of indi

viduals with each other.3 Unless one b elieves that humans have

no agency at all, that their behavior is fully determined by

external forces outside their control, any reasonable explana

tion of social phenomena must square these phenomena with

the actions that individuals choose to take. Economists' models,

based as they are on explicit consideration of the constraints

(material, social, contextual) under which these decisions are

made, are well equipped for this kind of analysis. From the

p erspective of good social analysis, the contrast b etween indi

vidual- and societal-level analyses sets up a largely false and

unhelpful dichotomy.

Do economists have a bias toward market-based solutions?

Again, probably guilty as charged. As I 've already shown, how

ever, here the problem has to do more with the way economists

present themselves iri public than with the substance of the

discipline. Research careers these days are made not by dem

onstrating how markets work, but by generating interesting

counterexamples to Adam Smith's Invisible Hand dictum. It

may surprise the reader, for example, that the most vociferous

advocate of free trade in the profession, Jagdish Bhagwati, owes

his academic reputation to a series of models that showed how

free trade could leave a nation worse off.* The solution to the

* Jagdish Bhagwati has been a tireless advocate of free trade since the

1 9 8 0 s . In his early academic work, he showed that an open economy may

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E C O N O M I C S A N D I T S CRI T I C S

bias is not t o remake economics, but to b etter reflect the diver

sity of models that already exists in the public debate.

Then there is the criticism that economists' theories can

not be properly tested. Empirical analysis is never conclusive,

and invalid theories are rarely rej ected. The discipline hobbles

from one set of preferred models to another, driven less by evi

dence than by fads and ideology. Insofar as economists present

themselves as the physicists of the social world, this criticism

is deserved. As I explained earlier, however, comparisons to

natural sciences are misleading. Economics is a social science,

which means that the search for universal theories and results is

futile. A model (or theory) is at best contextually valid. Expect

ing general empirical validation or rejection makes little sense.

Economics advances by expanding the c ollection of poten

tially applicable models, with newer ones capturing aspects

of social reality that were overlooked or neglected by ear

lier ones. When an economist encounters a new pattern, his

reaction is to think of a model that might explain it. Eco

nomics advances also by b etter methods of model s election-

lose something from growth, because of attendant changes in the world

prices of its imports and exports. He also analyzed at length the presence of

market distortions and the needed policy responses, showing that laissez

faire was suboptimal under a wide range of conditions. Jagdish Bhagwati,

" Immiserizing Growth: A Geometrical Note," Review ef Economic Studies

2 5 , no. 3 Qune 1958) : 201-5; Bhagwati and V. K. Ramaswami, "Domestic

Distortions, Tariffs and the Theory of Optimum Subsidy," Journal of Political

Economy 7 1 , no. 1 (February 1963) : 44-50.

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E C O N O M I C S RUL E S

improving the match b etween model and real-world setting.

As I explained in Chapter 3, this is more a craft than a s cience,

and one that does not get the attention it deserves in econom

ics . But the advantage of working with models is that the ele

ments required for model selection-the critical assumptions ,

the c ausal channels, the direct and indirect implications-are

all transparent and laid bare. These elements enable econo

mists to check the correspondence between the model and

the setting, informally and suggestively, even if not formally

and conclusively.

Finally, economics is faulted for its failure to predict. God

created economic forecasters to make astrologers look good,

quipped John Kenneth Galbraith (himself an economist).

Exhibit A in recent times has b een the global financial crisis,

which unfolded at a time when the vast maj ority of economists

had been lulled into thinking macroeconomic and financial

stability had arrived for good. I explained in the previous chap

ter that this misperception was another by-product of the usual

blind spot: mistaking a model for the model. Paradoxically, had

economists taken their own models more seriously, they would

have b een less confident about the consequences of financial

innovation and financial globalization and more prepared for

the financial whiplash that resulted.

However, no social science should claim to make predic

tions and be j udged on that basis . The direction of social life

cannot be predicted. There are too many drivers at work. To

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E C O N O M I C S A N D I T S CRI T I C S

put it in the language o f models, there are numerous models

of the future, including those that have yet to be formulated!

At best, we can expect economics and other social s ciences

to make conditional predictions: to tell us the likely outcomes

of individual changes , taken one at a time, while other fac

tors remain constant. That is what good models do . They can

provide a guide to the consequences of certain large-scale

changes or to the effects when some causes swamp others.

We can be reasonably sure that massive price controls will

lead to shortages , that a harvest failure will raise coffee prices,

and that a huge injection of money by a central b ank will

produce inflation in normal times. But in these instances,

"everything else remains the same" is a reasonable assump

tion, and predictions look more like conditional predictions.

The trouble is that often we can neither guess which among

many plausible changes will actually take place, nor be con

fident about their relative weights in the ultimate outcome.

In such instances , economics demands caution and modesty

rather than self- confidence.

In the rest of the chapter, I will take up two other major

criticisms that until now I 've not said much about. First, I ' ll

discuss the charge that economics is rife with value judgments

and that much of what passes as scientific analysis in fact merely

expresses a normative preference for a market-based society.

Second, I ' ll evaluate the contention that economics discour

ages pluralism and is hostile to new approaches and ideas .

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E C O N O M I C S RUL E S

The Question of Values

Most models in economics assume that individuals behave self

ishly. They try to maximize their own (and perhaps also their

children's) consumption possibilities , and they don't care what

happens to others. In many settings this is sufficiently realistic.

The polar-opposite assumption of completely selfless behavior

would not make sense. And allowing some degree of altruism

and generosity would not substantially alter many of the results.

A fair amount of research relaxes this stark assumption and

allows for some degree of altruism and other-regarding behav

ior as well. In some settings-charity or voting in general elec

tions, for example-additional motivations besides self-interest

are indispensable for understanding what's going on. Nonethe

less , it is fair to say that self-interested behavior forms a bench

mark assumption in economics . But the models are meant to

describe what actually happens, not what should happen. There

are no value judgments in this kind of analysis.

The crowning achievement of economics, the Invisible

Hand Theorem, perhaps does make economists somewhat

more nonchalant and p ermissive toward displays of self

interest. After all, its key ii;isight is that self-interest can be

yoked to public purpose. A collection of selfish people need

not produce economic and social chao s . From society's stand

point, the antidote to the pursuit of material advantage by

some is the pursuit of material advantage by many others .

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E C O N O M I C S A N D I T S CR I T I C S

Free and unhindered competition neutralizes pathologies that

might otherwise have arisen.

There is an apt parallel here with the constitutional design

of the United States. James Madison, Alexander Hamilton, and

the others who were behind the US federal system took it as

a given that a political system would operate around the self

interest of organized pressure groups. They designed the sys

tem accordingly, with checks and balances. The multiplicity of

centers of power and the restraints placed on their authority,

along with the sheer scale of the union, would prevent any one

faction from gaining the upper hand. It would be unfair to

criticize the Federalists for having enshrined self-interest in US

politics; they thought they were simply dealing with its con

sequences. Similarly, economists whose models are p opulated

by selfish consumers are not taking a moral stand; they're only

describing what happens when such consumers interact with

equally self-interested firms in the marketplace.

But does this benchmark role of self-interest in economic

models produce a normative bias in its favor? We can ask

whether it "normalizes" such b ehavior (makes it the norm)

and crowds out other, more socially oriented behavior. A

finding that appears to amplify this concern is that college

students who maj or in economics tend to act in more self

interested ways than do those who maj or in other fields . Their

behavior is more consistent with benchmark economic models

such as the prisoners' dilemma. S ome have interpreted this

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E C O N O M I C S RUL E S

result as evidence that studying economics makes individuals

more selfish.

In fact, the results point in the direction of an alternative

hypothesis: certain types of students are more likely than others

to go into economics. Research on Israeli students has found

that differences in values between economics students and

noneconomics students were already in place before the former

group enrolled in their economics course of study. Research

from Switzerland shows that while certain types of prospective

economics maj ors (those focusing on business) start their col

lege career with a lower propensity to donate funds for needy

students, this propensity does not decline with the study of

economics . 4 So it may be true that economics attracts differ

ent kinds of students-more selfish ones! But evidence for the

charge that it somehow renders people more selfish is weaker.

B ecause self-interest features prominently in economic mod

els, economists--exhibit a bias toward incentive-based solutions

to public problems. Consider climate change and the ques

tion of how to address carbon emissions. Public opinion varies

greatly, but economists are virtually unanimous: they recom

mend either taxing carbon or implementing a close equivalent,

a quota on carbon emissions with trading of emission allow

ances among producers .* In b oth cases the aim is to make it

* These two policies are totally equivalent in a complete-information

world, but they produce different outcomes under uncertainty.

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more expensive and hence less profitable fo r firms t o use car

bon. To economists , the policy is the correct one b ecause it

acts on the relevant margin. Firms fail to take into account the

environmental effects of their decisions, so the right response

is to force them to " internalize" the external costs by paying

for carbon.

This remedy does not sit well with many noneconomists. It

appears to turn a moral responsibility-"thou shalt not despoil

the environment"-into a cost-benefit calculus. Going further,

some would say that a carbon tax or emission trading legiti

mizes pollution. The message to firms seems to be that emit

ting carbon and contributing to climate change is OK as long

as you pay a fee . The Harvard political philosopher Michael

Sandel has been a vocal critic in recent years of what he thinks

is economics' harmful effects on public culture. Here is Sandel

on material incentives:

Putting a price on the good things in life can corrupt

them. That's because markets don't only allocate goods;

they express and promote certain attitudes toward the

goods being exchanged. Paying kids to read books might

get them to read more, but might also teach them to

regard reading as a chore rather than a source of intrinsic

satisfaction. Hiring foreign mercenaries to fight our wars

might spare the lives of our citizens, but might also cor

rupt the meaning of citizenship. 5

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In other words, reliance on markets and incentives fosters val

ues that are corrosive and undermine social obj ectives .

An economist might respond that they look at obj ectives

like emission control not as moral matters, but as questions of

effectiveness. Moral exhortation is fine, but incentives work.

If they get more pushback, economists are likely to appeal to

empiricism. Fine, they will say, we can show you hundreds of

studies indicating that firms reduce their use of, say, oil when

its price goes up; show us the evidence that moral exhortation

achieves a reduction in carbon emissions .

Economists' instinct is to take the world, including human

selfishness, as given and to engineer solutions around that per

ceived constraint. They would argue, correctly, that this has

nothing to do with their values and ethics, but with their

empirical orientation. If this makes them sometimes too quick

to p ooh-pooh non-incentive-based solutions, it also makes

them willing fo acknowledge when evidence comes in that

suggests their opponents have a point.

I mentioned in passing in Chapter 2 an unexpected real

life experiment that caused quite a stir among economists.

To reduce tardiness, an Israeli day care had instituted a p en

alty for parents who showed up late to pick up their children.

This policy was in line with what economists would have rec

ommended: if you want to reduce a b ehavior, make it more

costly for the individuals who exhibit the behavior. To virtu

ally everyone's surprise, tardiness actually increased after the

penalty was put in place. Apparently, now that there was a

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E C O N O M I C S A N D I T S CRI T I C S

fee, parents felt it was O K to show up late . A moral injunc

tion that previously had kept parents' behavior in check was

relaxed once the monetary penalty came into play. Or to put it

in economists' terms, the moral cost of tardiness was reduced,

and perhaps eliminated. As the economist Sam Bowles points

out, this is an example of how material incentives may some

times crowd out moral, or other-regarding behavior. 6

The lesson for economists is that sometimes they need a

richer paradigm of human behavior (or of costs and b enefits)

than they use in the simplest models. Economists are usu

ally willing to think in those terms and to make the required

modifications, as long as there is evidence suggesting that the

benchmark model fails . It clearly did in this case. But they

would continue to regard this extension not in moral terms,

but in terms of relevance and efficacy. For example, does the

lesson of the Israeli day care speak also to carbon control? Is it

realistic to think that power plants operate in a moral universe

regarding the climate-change imperative that will be substan

tially affected by the imposition of a carbon tax? Are public

education campaigns, consciousness raising, or moral exhorta

tion likely to have a greater impact on carbon emissions? To

economists, these are empirical and not moral questions .

What about Sandel's broader charge that markets breed

"market values ," that they make us exchange things on markets

that shouldn't be? "We live in a time," Sandel writes, "when

almost everything can be bought and sold." Everything, in

his words, " is up for sale." Here are some of the examples

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E C O N O M I C S RUL E S

that Sandel cites in addition to carbon emission fees: a prison

cell upgrade for $90 a night in Santa Ana; access to the car

pool lane for a car with a single rider for $8 in Minneapolis

and other cities; an Indian surrogate mother for $ 8 , 0 0 0 ; the

right to shoot an endangered black rhino for $250,000; a doc

tor's cell phone number for $ 1 , 50 0 .7 These and other examples

illustrate for Sandel the increasing role that market values play

in our social life.

But what are these market values? D eep down there is

really only one: efficiency. All that an economist can claim

about a market-and one that works well, without the fre

quent imp erfections-is that it yields an efficient allocation

of resources in a precise sense: there is no feasible way to

make some people richer without making others poorer. Any

economist who makes a broader argument about the fairness,

j ustice, or moral worth of markets that is based on economics

proper is simply engaged in malpractice.

The market-efficiency connection, of course, doesn't pre

clude individual economists from attaching additional values

to markets. For example, an economist's personal values may

make him an advocate of free enterprise on account oflibertar

ian beliefs-the view that the liberty to engage in commerce

with whomever one likes should not be abridged. But these

beliefs originate outside economics. Their advocacy by an

economist gives them no greater credence than their espousal

by an architect or physician. Nor does it preclude the asser

tion, based on specific evidence, that less intervention in mar-

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E C O N O M I C S A N D I T S CR I T I C S

kets i n certain cases may produce benefits beyond efficiency.

For example, economists often argue that the removal of fuel

subsidies in developing countries would enhance distributional

equity alongside efficiency. The reason is that subsidies not

only cause overconsumption of fuel (which is the source of

their inefficiency), but also benefit mostly the well-to-do (who

are the main users of the subsidized fuel). But such arguments

have to be demonstrated empirically, on a case-by-case basis.

Is efficiency a good thing? Yes it is, taken on its own. We

can say without hesitation that efficiency is a consideration-a

value-worth taking into account when we compare alterna

tive social states. But it is certainly not the only one. Equity

would be another contending value, as would be the intrinsic

moral value of other-regarding and socially responsible b ehav

iors. Sometimes these considerations push us in the same direc

tion as efficiency, and therefore reinforce the case for markets.

At other times there may be tensions and trade-offs to consider.

What should and should not be sold on markets is ultimately

a question decided by evaluating trade-offs in many different

dimensions. Different communities are likely to arrive at dif

ferent answers. And the answers may change over time even

within the same community. O nce again, the economist has

no special expertise in making those trade-offs. At best, econo

mists can provide useful input.

For example, economists may contribute to the discussion

of charging solo riders a fee for access to the carpool lane. They

can make educated guesses as to the type of rider that is most

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likely to pay the extra fee; the gains reaped by those who ben

efit (by arriving at their destination quicker) ; the funds gener

ated by the turnpike authority and their possible uses; and the

distributional incidence of the potential congestion costs in

the carpool lane (who pays, and how much?) . The evidence

on these questions may end up swaying most people to the

view that the fee option is, on balance, desirable. The same

kind of analysis for, say, a prison cell upgrade may result in

the opposite conclusion. In neither case would it be j ustifi

able for economists to advocate the market option as a general

solution, without acknowledging the multiple considerations

beyond efficiency.

To be fair to Sandel, his is not a straw man argument.

Economists do get careless and make claims that are broader

than their economist licenses really allow. Remember the list

from the previous chapter of things on which the vast maj or

ity of economists agree? Many of them involve implicit value

judgments. When economists say foreign trade should not be

restricted, outsourcing should not b e prohibited, or agricul

tural subsidies should be eliminated, they've rendered judg

ments on matters that cannot be evaluated solely on grounds

of efficiency. Questions of justice, ethics, fairness, and distribu

tion are tangled up in all of them. Is it necessarily fair to push

for free trade if the , beneficiaries are predominantly wealthy

individuals and the losers are some of the poorest workers in

our society? Is it fair to reap the benefits of outsourcing from

poor countries where workers lack fundamental rights and toil

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E C O N O M I C S A N D I T S CRI T I C S

under hazardous workplace conditions? The 90 -plus percent

of economists who agreed with these statements must either

have been unaware of these questions or consistently subsumed

them under efficiency considerations. Either way, there is a

problem. Even assuming that the efficiency consequences can

be readily and universally predicted-and the concerns I raised

in the previous chapter can be downplayed-economists are,

without doubt, overreaching in these particular areas .

Since their training provides them with no tool to evaluate

alternative social states other than the lens of allocative efficiency,

economists are prone to make this mistake whenever called

upon to comment on public policies. They can easily conflate

efficiency with other social goals. A useful rebuttal would call

the economists' bluff and remind them of the specific ways in

which they're transgressing the boundaries of their expertise. By

the same token, economists must remind the public that many

claims made by politicians and other policy entrepreneurs on

their behalf cannot find full justification in the discipline.

O ne of the earliest and most influential noneconomic argu

ments on behalf of markets was that engagement in market

activities would moderate human temperament. As Albert

Hirschman reminds us in his magisterial book The Passions and

the Interest, the thinkers of the late seventeenth and eighteenth

centuries reasoned that the profit-seeking motive would coun

tervail baser human motivations such as the urge for violence

and domination over other men. The term " doux" (meaning

"sweet") was often appended to "commerce" to suggest that

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commercial activities promoted gentle and peaceful interac

tions . Montesquieu famously said, "Wherever manners are

gentle there is commerce; and wherever there is commerce,

manners are gentle." Thanks to commerce, pointed out Samuel

Ricard, David Ricardo's grandfather, man seeks virtues such as

deliberation, honesty, and prudence. He stays away from vice

lest he lose his credit and become an obj ect of scandal. In this

way, interests could mollify the passions . 8

These early philosophers encouraged the spread of markets

not for reasons of efficiency or for the expansion of material

resources , but because they thought it would produce a more

ethical, more harmonious society. It is ironic that three cen

turies later, markets have come to be associated in the eyes

of many with moral corruption. Just as today's advocates of

markets overlook the limits of efficiency, perhaps the critics

neglect some of the ways in which markets contribute to a

spirit of cooperation.

Lack of Pluralism

O ne of the most frequent complaints about economics labels

it a club that shuns outsiders. This exclusiveness makes the

discipline insular, according to the critics, and closed to new

and alternative perspectives on economics. Economics should

b ecome more inclusive, they argue, more pluralistic and more

welcoming of unorthodox approaches.

This criticism is one that students voice often, partly because

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E C O N O M I C S A N D I T S CR I T I C S

of the way economics is taught. In the fall o f 20 1 1 , fo r exam

ple, a group of students staged a walkout in Harvard's popular

introductory economics course, Economics 10, taught by my

colleague Greg Mankiw. Their complaint was that the course

propagates conservative ideology in the guise of economic sci

ence and helps perpetuate social inequality. Mankiw dismissed

the protesters as "poorly informed." He pointed out that eco

nomics does not have an ideology; it is just a method that

enables us to think straight and reach correct answers, with no

foreordained policy conclusions .9

In April 2014, a student group at Manchester University call

ing itself the Post- Crash Economics Society put out a sixty-page

manifesto advocating substantial reform of economics educa

tion. The report included a foreword by Andrew Haldane, a

high-ranking official of the Bank of England, and received

plaudits from many other economists. It criticized economics

teaching for b eing too narrow and argued for greater pluralism

and an infusion of perspectives from ethics, history, and poli

tics. The monopoly of the standard economic paradigm, the

students wrote, prevented "meaningful critical thinking" and

was therefore harmful to economics on its own terms.*

* Economics, Education and Unlearning: Economics Education at the University of

Manchester, Post-Crash Economics Society (PCES), April 2014, http://www.post

crasheconomics.com/download/778r. The Oxford economist Simon Wren

Lewis has a good discussion of what's right and wrong with the students' criticism

in "When Economics Students Rebel," Mainly Macro (blog), April 24, 2014, http://

rnainlyrnacro.blogspot.co.uk/2014/04/when-econornics-students-rebel.htrnl.

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E C O N O M I C S RUL E S

How do we understand these complaints m light of the

patent multiplicity of models within economics? The trouble

from the students' perspective is that much of what goes on in

an introductory course in economics is a paean to markets. It

gives little sense of the diversity of conclusions in economics, to

which the student is unlikely to b e exposed unless she goes on

to take many more economics courses. Economics professors

are charged with being narrow and ideological because they

are their own worst enemy when it comes to communicat

ing their discipline to outsiders . Instead of presenting a taste

of the full panoply of perspectives that their discipline offers,

they focus on benchmark models that stress one set of con

clusions. This is particularly so in introductory courses, where

the professor is keen to demonstrate how markets work. As the

Oxford economist Simon Wren-Lewis points out, "One of the

sad things about the w:ay economics is often taught is that stu

dents do not. see much of the interesting stuff that is going on

[in the discipline] ."1° Can one fault students for demanding an

alternative perspective?

I myself have frequently flouted conventional wisdom

among economists, but with no apparent damage to my career

(at least I don't think s o ! ) . I may not be sufficiently radical

for many noneconomists , but I am often viewed as unortho

dox within the discipline. An economist colleague at Harvard

would greet me by saying, " How is the revolution going? "

every time he saw me. Yet even though I reach policy con

clusions that differ from prevailing academic views in many

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E C O N O M I C S A N D I T S CR I T I C S

of my writings , I have never really felt discriminated against

in the profession. I don't think my research papers have been

judged more harshly by j ournal editors or by my peers b ecause

of the inferences they drew.

Pluralism with respect to conclusions is one thing; pluralism

with respect to methods is something else. No academic disci

pline is permissive of approaches that diverge too much from

prevailing practices, and economics is unforgiving of those

who violate the way work in the discipline is done . An aspiring

economist has to formulate clear models and apply appropri

ate statistical techniques. These models can incorporate a wide

range of assumptions; without leeway here, it would be impos

sible to reach novel or unconventional conclusions. But not all

assumptions are equally acceptable. In economics, this means

that the greater the departure from benchmark assumptions,

the greater the burden of justifying and motivating why those

departures are needed.

To b e counted as an insider, as someone whose work should

be taken seriously, you have to operate within these rules. If

my work has b een accepted within economics, it is b ecause

I've followed the rules. I do so not because the rules enable

me to display my credentials, but because I find them useful.

The rules have disciplined my research and have ensured that I

know what I 'm talking about. But they have not b een so con

straining as to prevent me from pursuing interests or paths of

analysis that would produce unorthodox conclusions.

So economics offers limited room for methodological plu-

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E C O N O M I C S RUL E S

ralism-much less than it allows for diversity in policy conclu

sions. Most economists would say this is a good thing, because

it provides protection against shoddy thinking and poor empir

ical data. Some methods are better than others. Formal frame

works that explicitly identify cause-effect links are better than

verbal accounts that leave interactions open to diverse interpre

tations. Models that explain social phenomena by analyzing the

behavior of the actors that shape them, as economists do when

they talk about market competition, coordination failures, or

prisoners' dilemmas, are better than those that ascribe agency

to amorphous social movements . Empirical analyses that pay

attention to issues of causality and "omitted variable bias" are

better than those that do not.

For some, these constraints represent a kind of methodologi

cal straitj acket that crowds out new thinking. But it is easy to

exaggerate the rigidity of the rules within which the profes

sion operates:·* In my own experience, I have seen economics

change drastically over a p eriod of three short decades .

Consider the fields that I focused on in graduate school in the

* Even relatively sophisticated accounts of the economics profession by

outsiders typically overstate the rigidity of the discipline and understate

the possibilities of change over time. As an example, see Marion Fourcade,

Etienne Ollion, and Yann Algan, The Superiority of Economists, MaxPo

Discussion Paper 14/3 (Paris: Max Planck Sciences Po Center on Coping

with Instability in Market S ocieties, 2014) . The paper emphasizes the

homogeneity of the discipline even as it cites many of the changes that have

taken place and that I cite below.

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E C O N O M I C S A N D I T S CRI T I C S

mid-1980s. The three i n which I wrote exams were economic

development, international economics, and industrial organi

zation. All three have undergone a dramatic makeover. Most

important, all of them have become predominantly empirical

rather than theoretical subjects . At the time I was working on

my dissertation, the b est and brightest in these fields fo cused on

applied theory, producing mathematical models that attempted

to shed light on a particular facet of the economy. Evidence

was used to motivate the models, and sometimes to buttress

their results. But it was unusual to devote the bulk of the work

to empirical analysis. Only the lesser students, the ones without

bright ideas and theoretical skills, would attempt empirically

testing this or that model.

These days, it is virtually impossible to publish in top j our

nals in two of those fields-development and international

economics-without including some serious empirical analysis.

And industrial organization has become much more empirical

too, though not as empirical as the other two fields. Moreover,

what passes as acceptable empirical analysis has changed for

ever. The standards of the profession now require much greater

attention to the quality of the data, to causal inference from

evidence, and to a variety of statistical pitfalls. All in all, this

empirical turn has been good for the profession. In interna

tional economics, for example, empirical work has generated

new findings on the importance of quality and productivity

differences among firms participating in international trade

and an expanded variety of models to account for them. In

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E C O N O M I C S RU L E S

development economics, new evidence has led to policy inno

vations in health, education, and finance that have the potential

to improve the lives of hundreds of millions of people.

Another way we can observe the transformation of the dis

cipline is by looking at the new areas of research that have

flourished in recent decades . Three of these are particularly

noteworthy: b ehavioral economics, randomized controlled

trials (RCTs) , and institutions. What's striking is that all these

areas have been greatly influenced, and in fact stimulated, by

fields from outside economics-psychology, medicine, and

history, respectively. Their growth disproves the claim that

economics is insular and ignores the contributions of other

cognate disciplines.

In some ways , the rise of b ehavioral economics marks the

greatest departure for standard economics because it under

cuts the benchmark, almost canonical assumption of eco

nomic models: · tliat individuals are rational. The rationality

postulate not only seems sensible in a lot of settings, but also

allows the modeling o f behavior by relying on standard math

ematical optimization techniques in which individuals maxi

mize (or minimize, as the case may b e) well-defined objective

functions under budgetary and other constraints. Using these

techniques , economists derive specific predictions for how

consumers choose which products to buy, how households

save, how firms invest, how workers search for j obs, and so

on-as well as for how these actions depend on the particulars

of the setting.

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The postulate always had its critics from within economics,

such as Herbert Simon, who argued for a limited form of ratio

nality (called " bounded rationality") , and Richard Nelson,

who proposed that firms move by trial and error rather than by

optimization-not to mention Adam Smith himself, who may

have been the first behavioral economist.11 But it was the work

of psychologist Daniel Kahneman and his coauthors that had

the greatest impact on mainstream economics.12 This contribu

tion was recognized by a Nobel memorial prize in economics

given to Kahneman in 2 0 0 2 , the first time that the prize was

awarded to a noneconomist.*

Kahneman and his colleagues' experiments cataloged a long

list of b ehavioral regularities that violated rationality, as the

concept is used in economics . People value an obj ect more

when giving it up than they do when acquiring it (loss aversion) ,

overgeneralize from small amounts of data (overconfidence),

discount evidence that contradicts their b eliefs (confirmation

bias), yield to short-term temptations that they realize are bad

for them (weak self-control), value fairness and reciprocity

(bounded selfishness), and so on. These types of behavior have

important implications in many areas of economics. For exam

ple, the efficient-markets hypothesis in finance (see Chapter 5)

relies on investors having unbiased expectations. When econo

mists b egan to introduce these new findings in their models,

* In 2009 the prize went to Elinor Ostrom, a political scientist, for her

work on institutions and managing common-pool resources.

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E C O N O M I C S RUL E S

they were able to account for financial-market anomalies that

had long resisted explanation. For example, the apparent over

sensitivity of asset prices to news could be explained by the

tendency of people to overreact to recent information.13 These

insights from social psychology were subsequently applied to

many areas of decision making, such as saving b ehavior, choice

of medical insurance, and fertilizer use by poor farmers . 14

B ehavioral economics moved from the fringes to become one

of the liveliest areas of economics, attracting the b est talent in .

the profession.

RCTs are a departure of a different sort. They represent a

giant leap in the direction of empiricism. Their goal is to gen

erate clear-cut, unambiguous evidence from the ground up.

Empirical work in economics has always b een plagued by the

difficulty of uncovering true causal relationships. The world

never stands still to allow the researcher to cleanly pinpoint

how, for example, subsidizing insecticide-treated bed nets

affects malaria incidence. Too many other things change along

the way, confounding the effect we're looking for. Economists

b egan to study such questions using randomization. So, for

example, bed nets could be distributed to a random sample of

recipients (the treatment group) , with nonrecipients constitut

ing a natural control group. The difference between outcomes

for the two groups would then be attributed to the effect of the

intervention. This approach was relatively simple, compared

to complex statistical techniques. It was also quite effective in

identifying what works and what doesn't in a particular set-

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ting. Generalizing from one set o f results remained, a s usual,

more problematic, because it required extrapolating to differ

ent conditions .

Poor countries presented particularly suitable conditions for

carrying out such experiments in the field. There was exten

sive debate about which kinds of remedies would work best in

those settings, and there was room to try out different inter

ventions. The gains from identifying effective interventions

were huge, given the prevailing levels of poverty. S ome aspects

of RCTs remain controversial. Critics have complained that

RCT advocates make exaggerated claims about how much we

can learn from field experiments studying the nature of under

development and the policies required. 15 But few would deny

that this new wave of research has taken economics in a dif

ferent direction and has enriched our understanding of many

aspects of developing societies.

Field experiments are fine-grained analyses focusing on

specific communities, often one village at a time. The work

on institutional development, by contrast, took both a much

more macro view and a broad historical sweep. It focused on

the institutions that made modern, prosperous capitalism pos

sible: the rule of law, contract enforcement and property rights

protection, political democracy. This research was inspired

directly by work in other disciplines, on comparative politi

cal development and history. But the insights of those disci

plines were refined and formulated into the kinds of models

that economists are used to. In addition, much effort went into

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E C O N O M I C S RU L E S

validating these ideas with sophisticated empirical analysis,

using up-to-date statistical techniques.

The MIT economist Daron Acemoglu and the economics

trained Harvard political scientist James Robinson were the

undisputed leaders of this new wave of work. Their first big

research proj ect that made a splash was a paper called " The

Colonial Origins of Comparative Development," coauthored

with their MIT colleague Simon J ohnson. 16 The paper argued

that patterns of institutions imposed by colonialists many cen- .

turies ago echo to this day. When colonialists settled in the

new territories, they erected institutions that protected prop

erty rights and promoted growth and development. This was

the case of the United States , Canada, Australia, and New Zea

land primarily. When local health conditions did not permit

settlement in large numbers, as in much of Africa, colonial

ists instead set up institutions that were more appropriate for

the expropriation of resources, thereby delaying development.

More than the argument itself, what made the paper inordi

nately successful was the imaginative empirical approach the

authors used to validate their claim. In brief, they leveraged

information on the mortality rates of early Western settlers

(such as military officers and missionaries) to distinguish colo

nies by how hospitable the local environment was to erecting

institutions that protect property rights.*

* The authors argued that early colonizers were more likely to set up

good institutions in places where they encountered fewer mortality risks.

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E C O N O M I C S A N D I T S CRI T I C S

The paper was not without its critics. But it sparked a wave

of new research on political economy, institutional develop

ment, and comparative economic history that harked back to

an earlier era of social science inquiry when economics did

not stand apart as a separate discipline. What were the deeper

causes of capitalist development, beyond economic determi

nants such as saving and capital accumulation? Why did Spain

and Portugal lag in development, after having led the world

in the age of discoveries? What are the long-term economic

implications of ethnic divisions, or of cultural attributes? These

were old questions, even though the methods being used were

new. 17 They were also " big" questions, attesting to the ability

of the profession to successfully engage with some of the most

significant issues in the social sciences.

These new areas of research may not have produced con

clusive results, nor have they changed the face of econom

ics forever. My point, rather, is that they have incorporated

insights from other disciplines and have taken economics in

novel directions. They suggest that the view of economics as

an insular, inbred discipline closed to outside influences is more

caricature than reality.

Moreover, the diseases that killed the Westerners were generally different

from those that affected the native population. These assumptions allowed

the authors to use settler mortality rates as an exogenous source of variation

in the quality of institutions, independent of other determinants, such as

proximity to trade routes, that may have affected long-term development

paths.

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Ambition and Modesty

Much of the criticism of economics boils down to the charge

that economists are using the wrong model. They should be

Keynesians , Marxians, or Minskyans instead of neoclassicals;

demand-siders instead of supply-siders; behavioralists rather

than rationalists; network theorists rather than methodologi

cal individualists; structuralists rather than interactionists. But

simply switching to an alternative framework that itself lacks

universality and captures only a particular slice of reality can

not be the solution. Insights of these alternative p erspectives

are , in fact, readily accommodated within standard modeling

practices of economics, as I 've argued. All these divides can be

bridged by viewing economics as a collection of models, along

with a system of navigation among models.

The discipline's most successful and celebrated practitioners

exemplify this- approach. The French economist Jean Tirole,

who won the 2014 Nobel Prize in Economic Sciences for his

work on regulation, is a goo d example. In typical fashion, he

was deluged after his prize was announced by j ournalists seek

ing a quick take on the research that had brought him the rec

ognition. But his interlocutors were in for some frustration.

" There's no easy line in summarizing my contribution," he

protested. "It is industry-specific. The way you regulate pay

ment cards has nothing to do with the way that you regulate

intellectual property or railroads. There are lots of idiosyn-

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E C O N O M I C S A N D I T S CR I T I C S

cratic factors . That's what makes it all s o interesting. It's very

rich . . . . It's not a one-line thing."18

Economists who remain true to their discipline, like Tirole,

are necessarily humble. Their discipline teaches them that

on only very few matters can they express categorical views.

Their responses to most questions necessarily take the form

of " It depends, " "I don't know," "Give me several years (and

research funds) to study the problem," "There are three views

on this . . . ," or perhaps, "Assume we have n goods and k con-

sumers . . . " In this role they remain vulnerable to the criticism

that they are ivory-tower academics, devoted to abstract math

ematical models and fancy statistics , who fail to contribute to

social understanding and the solution of public problems.

But as the science of trade-offs , economics deftly enlight

ens us on both sides of the ledger-the costs and benefits, the

known and the unknown, the impossible and the feasible, the

possible and the likely. Just as social reality admits a wide range

of possibilities, economic models alert us to a variety of sce

narios. Disagreements among economists are natural under the

circumstances, and humility is the right attitude all around. It

is b etter for the public to be exposed to these disagreements

and uncertainties than to be lulled into a false sense of confi

dence about the answers that economics provides .

Humility would also make economists better citizens i n the

broader academic community of social science. Being up front

about how much (or how little) they really know and understand

209

E C O N O M I C S RUL E S

would help them close some of the gap with other, nonpositiv

ist social science traditions. It might allow better dialogue with

those who examine social reality through cultural, humanist,

constructivist, or interpretive lenses. A core obj ection of the

advocates of these alternative perspectives is that economics has

a universalist, reductionist approach.19 But with the multiplicity

and context specificity of models at the front and center of eco

nomics, the differences become less serious than they first appear.

For example, an economist's answer to the question "What about

culture?" cannot and should not be "Culture is irrelevant." It

should be "OK, let's try to write down a model of it"-meaning

let's be clear about what we're assuming, what the causal chain

is, and what the observable implications are. No sensible social

scientist should turn his back on such a line of inquiry.

Economists still can aspire to greater ambition as public

intellectuals or social reformers. They can be advocates of

specific policies and institutions on many fronts-to improve

the allocation of resources, unleash entrepreneurial energies,

foster economic growth, and enhance equity and inclusion.

They have much to contribute to the public debate in all these

areas . Their exposure to diverse models of social life, capturing

varieties of behavior and social outcomes, render them p er

haps more alert to the possibilities of social progress than other

social scientists are.* But they need to be aware that when they

* This is the "possibilism" that the great economist and social scientist

Albert Hirschman advocated throughout his life . He rej ected the

2 1 0

E C O N O M I C S A N D I T S CRI T I C S

move into this role, they are inevitably stepping outside the

well-defined scientific boundaries of their discipline. And they

need to be explicit about this. Otherwise, they open themselves

up to criticism that they are pushing beyond their expertise and

passing off their own value judgments as science.

Economics provides many of the stepping-stones and ana

lytic tools to address the big public issues of our time. What it

doesn't provide is definitive, universal answers. Results taken

from economics proper must be combined with values, judg

ments, and evaluations of an ethical, political, or practical

nature. These last have very little to do with the discipline of

economics , but everything to do with reality.

deterministic approaches, common to social sciences, that view outcomes as

being rigidly pinned down by "structural" conditions, and instead argued

for the power of ideas and small actions to have decisive effects . Philipp H .

Lepenies, "Possibilism: A n Approach t o Problem-Solving Derived from

the Life and Work of Albert 0 . Hirschman," Development and Change 39,

no. 3 (May 2008): 437-59.

2 1 1

E P I L O G U E

The Twenty C ommandments

Ten Commandments fo r Economists

1 . Economics is a collection of models; cherish their

diversity.

2 . It's a model, not the model.

3. Make your model simple enough to isolate specific causes

and how they work, but not so simple that it leaves out

key interactions among causes.

4. Unrealistic assumptions are OK; unrealistic critical

assumptions are not OK.

5. The world is (almost) always second best.

6. To map a model to the real world you need explicit

empirical diagnostics, which is more craft than science.

213

E C O N O M I C S RUL E S

7. Do not confuse agreement among economists for cer

tainty about how the world works.

8. It's OK to say "I don't know" when asked about the econ

omy or policy.

9. Efficiency is not everything.

10. Substituting your values for the public's is an abuse of

your expertise.

Ten Commandments for Noneconomists

1. Economics is a collection of models with no predeter

mined conclusions; rej ect any arguments otherwise.

2 . Do not criticize an economist's model because of its

assumptions; ask how the results would change if certain

problematic assumptions were more realistic.

3. Analysis requires simplicity; b eware of incoherence that

passes itself off as complexity.

4. Do not let math scare you; economists use math not

because they're smart, but because they're not smart

enough.

5. When an economist makes a recommendation, ask what

makes him/her sure the underlying model applies to the

case at hand.

2 1 4

T H E T W E N T Y C O MMA N D M E N T S

6 . When an economist uses the term "economic welfare,"

ask what he/she means by it .

7. Beware that an economist may speak differently in public

than in the seminar room.

8. Economists don't (all) worship markets , but they know

better how they work than you do .

9. If you think all economists think alike, attend one of their

seminars.

1 0 . If you think economists are especially rude to nonecono

mists, attend one of their seminars.

2 1 5

NOTES

I N r R o o u c T 1 o N : The Use and Misuse of Economic Ideas

1. R. Preston McAfee and John McMillan, "Analyzing the Airwaves

Auction," journal of Economic Perspectives 10, no . 1 (Winter 1996): 1 59-

75; Alvin E. Roth and Elliott Peranson, "The Redesign of the Match

ing Market for American Physicians: Some Engineering Aspects of

Economic Design," American Economic Review 89, no . 4 (1999): 748-

80; Louis Kaplow and Carl Shapiro, Antitrust, NBER Working Paper

1 2867 (Cambridge, MA: National Bureau of Economic Research,

2007); Ben Bernanke et al. , Inflation Targeting: Lessons from International

Experience (Princeton, NJ: Princeton University Press, 1999) .

2 . Steven D . Levitt and Stephen ]. Dubner, Freakonomics: A Rogue Econo

mist Explores the Hidden Side of Everything (New York: William Mor

row, 2005) .

c H A P T E R 1 : What Models D o

1 . Ha-Joon Chang, Economics: The User Guide (London: Pelican Books,

2014), 3.

217

N 0 T E S

2 . David Card and Alan Krueger, Myth and Measurement: The New Eco

nom ics of the Minimum Wage (Princeton, NJ: Princeton University

Press, 1997).

3 . Dani Rodrik and Arvind Subramanian, "Why Did Financial Global

ization Disappoint?" IMF Staff Papers 56, no. 1 (March 2009) : 1 1 2-38.

4. Daniel Leigh et al. , "Will It Hurt? Macroeconomic Effects of Fiscal

Consolidation," in World Economic Outlook (Washington, DC: Interna

tional Monetary Fund, 2010) , 93-1 24, http://www.imf.org/external

I pubs/ft/weo/20 1 01021 pdf/ c 3 . p df.

5. Ariel Rubinstein, "Dilemmas of an Economic Theorist," Econometrica

74, no. 4 Guly 2006) : 8 8 1 .

6 . Allan Gibbard and H a l R. Varian, "Economic Models," Journal of Phi

losophy 75, no. 11 (November 1978): 6 6 6 .

7. Nancy Cartwright, "Models: Fables v . Parables," Insights (Durham

Institute of Advanced Study) 1, no. 11 (2008).

8 . The Colombia study I 'm referring to is the well-known paper by

Joshua Angrist, Eric Bettinger, and Michael Kremer: "Long-Term

Educational Consequences of Secondary School Vouchers: Evidence

from Administrative Records in Colombia," American Economic Review

96, no. 3 (2006): 847-::-62 .

9. Nancy Cartwright and Jeremy Hardie, Evidence-Based Policy: A

Practical Guide to Doing It Better (Oxford: Oxford University Press,

2 0 1 2) .

1 0 . Milton Friedman, "The Methodology o f Positive Economics," i n Essays

in Positive Economics (Chicago: University of Chicago Press, 1953) .

1 1 . Paul Pfleiderer, "Chameleons: The Misuse of Theoretical Models in

Finance and Economics" (unpublished paper, Stanford University,

2014).

1 2 . See Gibbard and Varian, "Economic Models," 671 .

1 3 . Nancy Cartwright, Hunting Causes and Using Them: Approaches i n Philoso

phy and Economics (Cambridge: Cambridge University Press, 2007), 217.

2 1 8

N O T E S

14. Thomas C . Schelling, The Strategy of Coriflict (Cambridge, MA: Har

vard University Press, 1960) ; Schelling, Micromotives and Macrobe

havior (New York: W. W. Norton, 1978).

15. Diego Gambetta, " ' Claro ! ' An Essay on Discursive Machismo," in

Deliberative Democracy, ed. Jon Elster (Cambridge: Cambridge Univer

sity Press, 1998), 24.

16. Marialaura Pesce, " The Veto Mechanism in Atomic D ifferential

Information Economies," Journal of Mathematical Economics 53 (2014):

33-45.

17. Jon Elster, Explaining Social Behavior: More Nuts and Bolts for the Social

Sciences (Cambridge: Cambridge University Press, 2007) , 461 .

1 8 . Golden Goose Award, "Of Geese and Game Theory: Auctions,

Airwaves-and Applications," Social Science Space, July 17, 2014,

h t tp : //www. s o c i alsciencespac e . c om/20 1 4/07 I of- g e e s e - a nd-game

-theory-auctions-airwaves-and-applications.

19. Friedman, "Methodology of Positive Economics."

20. Alex Pertland, Social Physics: How Good Ideas Spread-The Lessons from

a New Science (New York: Penguin, 2014), 1 1 .

21 . Duncan ] . Watts, Everything Is Obvious: Once You Know the

Answer (New York: Random House, 2011), Kindle edition, locations

2086-92.

22 . Jorge Luis B orges, "On Exactitude in Science," in Collected Fictions,

trans. Andrew Hurley (New York: Penguin, 1999) .

2 3 . Uskali Maki, "Models a n d the Locus o f Their Truth" Synthese 1 8 0

(20 1 1) : 47-63 .

c H A P T E R 2 : The Science of Economic Modeling

1 . John Maynard Keynes, Essays in Persuasion (New York: W. W. Norton,

1963) , 358-73.

2. Adam Smith, An Inquiry into the Nature and Causes of the Wealth of

Nations, 5 th ed. (1789; repr., London: Methuen, 1904), I .ii. 2 .

2 1 9

N 0 T E S

3 . The pencil example was based on an essay by Leonard E . Read called

"I, Pencil: My Family Tree as Told to Leonard E. Read" (Irvington

on-Hudson, NY: Foundation for Economic Education, 1958), http://

www. econlib. org/library /Essays/ rdPncl 1 .html.

4. Kenneth J. Arrow, "An Extension of the Basic Theorems of Classi

cal Welfare E conomics," in Proceedings ef the Second Berkeley Sympo

sium on Mathematical Statistics and Probability, ed. J. Neyman (Berkeley:

University of California Press, 1 9 5 1 ) , 507-32; Gerard Debreu, " The

Coefficient of Resource Utilization," Econometrica 19 Ouly 1 9 5 1 ) :

273-9 2 .

5 . Paul Samuelson, "The Past and Future of International Trade Theory,"

in New Directions in Trade Theory, eds. A. Deardorff, ]. Levinsohn, and R.

M. Stern (Ann Arbor, MI: University of Michigan Press, 1995), 22.

6 . David Ricardo, On the Principles of Political Economy and Taxation (Lon

don: John Murray, 1 8 17 ) , chap. 7.

7. Dani Rodrik, The Globalization Paradox: Democracy and the Future ef the

World Economy (New York: W. W. Norton, 201 1) , chap. 3 .

8 . David Ricardo, O n the Principles ef Political Economy a n d Taxation,

3rd ed. (London: John Murray, 1 821), chap. 7, para. 7.17, http://www

. econlib.org/library /Ricardo/ricP2a.html.

9. David Card, " The Impact of the Mariel B o atlift on the Miami Labor

Market," Industrial and Labor Relations Review 43, no. 2 Oanuary 1990) :

245-57; George ] . Borjas, "Immigration," i n The Concise Encyclope

dia of Economics, http://www.econlib.org/library/Enc1 /Immigration.

html, accessed December 3 1 , 2014; Orn B. Bodvarsson, Hendrik F.

Van den Berg, and Joshua J. Lewer, "Measuring Immigration's Effects

on Labor Demand: A Reexamination of the Mariel B oatlift" (Univer

sity of Nebraska-Lincoln, Economics Department Faculty Publica

tions, August 2008).

1 0 . James E. Meade, The Theory ef International Economic Policy, vol. 2,

Trade and Welfare (London: Oxford University Press, 1955); Richard G .

2 2 0

N 0 T E S

Lipsey and Kelvin Lancaster, "The General Theory of Second Best,"

Review ef Economic Studies 24, no . 1 (1956-57) : 1 1-32 .

1 1 . Avinash Dixit, "Governance Institutions and Economic Activity,"

American Economic Review 99, no. 1 (2009): 5-24.

1 2 . Thomas C. Schelling, The Strategy of Conflict (Cambridge, MA: Har

vard University Press, 1960); Schelling, Micromotives and Macrobehavior

(New York: W. W. Norton, 1978).

13. For an excellent discussion with practical applications, see Avinash K.

Dixit and Barry J. Nalebuff, The A rt ef Strategy (New York: W. W.

Norton, 2008).

14. Joseph E . Stiglitz and Andrew Weiss, "Credit Rationing in Markets

with Imperfect Information," American Economic Review 7 1 , no . 3 Qune

1 9 8 1 ) : 393-410.

1 5 . Andrew Weiss, Efficiency Wages: Models of Unemployment, Layoffs,

and Wage Dispersion (Princeton, NJ: Princeton University Press ,

1 9 9 0) .

16. Itzhak Gilboa, Andrew Postlewaite, Larry Samuelson, and David Sch

meidler, "Economic Models as Analogies" (unpublished paper, Janu

ary 27, 2 0 1 3) , 6-7.

17. S ee, for example, my online debate for the Economist magazine with

Harvard Business School professor Josh Lerner, July 1 2-17, 2010,

http : //www. economist. com/ debate/ debates/ overview/177.

1 8 . Carmen M. Reinhart and Kenneth S. Rogoff, Growth in a Time efDebt,

NBER Working Paper 1 5639 (Cambridge, MA: National Bureau of

Economic Research, 2 0 1 0) .

1 9 . Thomas Herndon, Michael Ash, and Robert Pollin, "Does High Pub

lic Debt Consistently Stifle Economic Growth? A Critique of Rein

hart and Rogoff'' (Amherst: University of Massachusetts at Amherst,

Political Economy Research Institute, April 1 5 , 2013).

20. R. E . Peierls, "Wolfgang Ernst Pauli, 1900-1 9 5 8 ," Biographical Memoirs

ef Fellows of the Royal Society 5 (February 1960) : 1 8 6 .

2 2 1

N 0 T E S

2 1 . Albert Einstein, "Physics a11d Reality," in Ideas and Opinions of Albert

Einstein, trans. Sonja Bargmann (New York: Crown, 1954), 290, cited

in Susan Haack, " Science, Economics, 'Vision,' " Social Research 7 1 , no.

2 (Summer 2004) : 225.

c H A P r E R 3 : Navigating among Models

1. David Colander and Roland Kupers, Complexity and the Art of Public

Policy (Princeton, NJ: Princeton University Press, 2014), 8.

2. Dani Rodrik, "Goodbye Washington Consensus, Hello Washington

Confusion?: A Review of the World Bank's Economic Growth in the

1990s: Learning from a Decade of Reform," journal of Economic Litera

ture 44, no. 4 (December 2006): 973-87.

3 . Ricardo Hausmann, Dani Rodrik, and Andres Velasco, "Growth

Diagnostics," in The Washington Consensus Reconsidered: Towards a New

Global Governance, eds. J. Stiglitz and N. Serra (New York: Oxford

University Press, 2008).

4. The process is explained in greater detail, with examples from many

countries, in Ricardo Hausmann, Bailey Klinger, and Rodrigo Wag

ner, Doing Growth Diagnostics in Practice: A "Mindbook", CID Working

Paper 177 (Cambridge, MA: Center for International D evelopment at

Harvard University, 2 0 0 8) .

5 . Ricardo Hausmann, Final Recommendations o f the International Panel

on ASGISA , CID Working Paper 161 (Cambridge, MA: Center for

International Development at Harvard University, 2 008) .

6 . Ricardo Hausmann and Dani Rodrik, " Self-Discovery in a Develop

ment Strategy for El Salvador,'' Economia: journal of the Latin American

and Caribbean Economic Association 6, no. 1 (Fall 2005): 43-10 2 .

7 . Douglass C . North and Robert Paul Thomas, The Rise of the Western

World: A New Economic History (Cambridge: Cambridge University

Press, 1973).

8. Rochelle M . Edge and Refet S. Giirkaynak, How Useful Are Estimated

DSGE Model Forecasts? Finance and Economics Discussion Series

222

N 0 T E S

(Washington, DC: Divisions of Research & Statistics and Monetary

Affairs, Federal Reserve B oard, 2 0 1 1) .

9. Barry Nalebuff, "The Hazards of Game Theory," Haaretz, May 1 7 , 2006,

http : //www. haaretz. com/business/economy-finance/the-hazards-of

-game-theory- 1 . 187939. See also Avinash Dixit and Barry Nalebuff,

Thinking Strategically: The Competitive Edge in Business, Politics, and

Everyday Life (New York: W. W. Norton, 1993), chap 1 .

1 0 . S antiago Levy, Progress against Poverty: Sustain ing Mexico's Progresa

Opo rtunidades Program (Washington, D C : B rookings I nstitution,

2 0 0 6 ) .

1 1 . Mexico-PROGRESA: Breaking the Cycle of Poverty (Washington, DC:

International Food Policy Research Institute, 2 0 02) , http: //www

.ifpri .org/sites/default/files/pubs/pubs/ib/ib6.pdf.

1 2 . Edward Miguel and Michael Kremer, "Worms: Identifying Impacts

on Education and Health in the Presence of Treatment Externalities,"

Econometrica 72 , no. 1 (20 04) : 1 59-2 17.

13. Esther Duflo, Rema Hanna, and Stephen P. Ryan, "Incentives Work:

Getting Teachers to Come to School," American Economic Review 102,

no. 4 (June 2 0 1 2) : 1 241-7 8 .

1 4 . David Roodman, "Latest Impact Research: Inching towards Gen

eralization," Consultative Group to Assist the Poor (CGAP), April

1 1 , 2 0 1 2 , http : //www. cgap.org/blog/latest-impact-research-inching

-towards-generalization.

1 5 . Joshua D. Angrist, "Lifetime Earnings and the Vietnam Era Draft Lot

tery: Evidence from Social Security Administrative Records," Ameri

can Economic Review 80, no. 3 (June 1990): 313-3 6 .

1 6 . Donald R. Davis and David E . Weinstein, "Bones, B ombs, a n d Break

Points: The Geography of Economic Activity," American Economic

Review 9 2 , no. 5 (20 02): 1 2 69-89.

17. David R. Cameron, "The Expansion of the Public Economy: A Com

parative Analysis," American Political Science Review 72 , no. 4 (Decem

ber 1 978) : 1 243-61 .

223

N 0 T E S

1 8 . Dani Rodrik, "Why Do More Open Economies Have Bigger Govern

ments?" Journal of Political Economy 106, no . 5 (October 1998) : 997-1 032 .

19. Robert Sugden, "Credible Worlds, Capacities and Mechanisms"

(unpublished paper, S chool of Economics , University of East Anglia,

August 2 0 0 8) .

c H A P T E R 4 : Models and Theories

1. Andrew Gelman, "Causality and Statistical Learning," American Journal

of Sociology 1 17 (20 1 1) : 955-66; Andrew Gelman and Guido Imbens,

Why Ask Why? Forward Causal Inference and Reverse Causal Questions,

NBER Working Paper 19614 (Cambridge, MA: National Bureau of

Economic Research, 2013).

2 . Dani Rodrik, "Democracies Pay Higher Wages," Quarterly Journal of

Econom ics 1 14, no. 3 (August 1999): 707-3 8 .

3 . Thomas Piketty, Emmanuel Saez, and Stefanie Stantcheva, Optimal

Taxation of Top Labor Incomes: A Tale of Three Elasticities, NBER Work

ing Paper 17616 (Cambridge, MA: National Bureau of Economic

Research, 2 0 1 1) .

4. ] . R . Hicks, "Mr. Keynes and the 'Classics': A Suggested Interpreta

tion," Econometrica 5, no . 2 (April 1937 ) : 147-59.

5. John M. Keynes, "The General Theory ofEmployment," Quarterly Jour

nal of Economics 5 1 , no . 2 (February 1 937) : 209-23, cited by ]. Bradford

DeLong in "Mr. Hicks and 'Mr Keynes and the "Classics": A Suggested

Interpretation': A Suggested Interpretation," June 20, 2010, http://

delong.typepad.com/sdj/2010/06/mr-hicks-and-mr-keynes-and-the

classics-a-suggested-interpretation-a-suggested-interpretation.html.

6 . Robert E. Lucas and Thomas Sargent, "After Keynesian Macroeco

nomics," Federal Reserve Bank of Minneapolis Quarterly Review 3 , no . 2

(Spring 1 979) : 1-1 8 .

7 . John H. Cochrane, "Lucas a n d Sargent Revisited," The Grumpy

Economist (blog), July 17, 2 014, http://johnhcochrane.blogspot.jp/

20 14/07 /lucas-and-sargent-revisited . html.

224

N 0 T E S

8 . Robert E . Lucas Jr., "Macroeconomic Priorities," American Economic

Review 93, no. 1 (March 2003): 1-14.

9. Robert E. Lucas, "Why a Second Look Matters" (presentation at the

Council on Foreign Relations, New York, March 30, 2009) , http://

www.cfr.org/world/why-second-look-matters/p18996.

1 0 . Holman W. Jenkins Jr. , "Chicago Economics on Trial" (interview

with Robert E. Lucas), Wall Street Journal, September 24, 201 1 , http://

online .wsj .com/news/articles/SB 10001424053 1 1 1 90419460 45765 833

82550849232 .

1 1 . Paul Krugman, "The Stimulus Tragedy," New York Times, February

20, 2014, http://www. nytimes.com/20 14/02/21 /opinion/krugman

the-stimulus-tragedy.html.

1 2 . J. Bradford Delong and Lawrence H. Summers, "Fiscal Policy in a

Depressed Economy," Brookings Papers on Economic Activity, Spring

201 2 , 233-74.

13. Edward P. Lazear and James R. Spletzer, "The United States Labor

Market: Status Quo or a New Normal?" (paper prepared for the Kan

sas City Fed Symposium, September 1 3 , 2012) .

1 4 . S cott R. Baker, Nicholas Bloom, and Steven ) . Davis, "Measuring Eco

nomic Policy Uncertainty" (unpublished paper, Stanford University,

June 1 3 , 2013) ; Daniel Shoag and Stan Veuger, "Uncertainty and the

Geography of the Great Recession" (unpublished paper, John F. Ken

nedy School of Government, Harvard University, February 2 5 , 2014).

1 5 . The data are from the US Census Bureau; see "Income Gini Ratio for

Households by Race of Householder, All Races," FRED Economic

Data, Federal Reserve Bank of St. Louis, http : //research .stlouisfed

.org/fred2/series/GINIALLRH#, accessed July 24, 2014.

16. The World Top Incomes Database, http://topincomes.parisschoolof

economics.eu/#Database, accessed july 24, 2014.

17. Edward E . Leamer, Wage Effects of a U. S.-Mexican Free Trade Agreement,

NBER Working Paper 3991 (Cambridge, MA: National Bureau of

Economic Research, 1 9 92) , 1 .

225

N 0 T E S

1 8 . Eli Berman, John Bound, and Zvi Griliches, "Changes in the Demand

for Skilled Labor within US Manufacturing: Evidence from the

Annual Survey of Manufacturers," Quarterly Journal of Economics 1 09,

no. 2 (1994) : 367-97.

19. Robert C. Feenstra and Gordon H. Hanson, "Foreign Direct Invest

ment and Relative Wages: Evidence from Mexico's Maquiladoras,"

Journal of International Economics 42 (1997): 371-94.

20. Frank Levy and Richard J. Murnane, "U. S . Earnings and Earnings

Inequality: A Review of Recent Trends and Proposed Explanations,"

Journal of Economic Literature 30 (September 1992): 1 333-8 1 ; John

Bound and George Johnson, "Changes in the Structure of Wages in

the 1980s: An Evaluation of Alternative Explanations," American Eco

nomic Review 83 Qune 1 992) : 371-9 2 .

21 . Lawrence Mishel, John Schmitt, a n d Heidi Shierholz, "Assessing the

Job Polarization Explanation of Growing Wage Inequality," Economic

Policy Institute, January 1 1 , 20 1 3 , http: //www.epi.org/publication/

wp295-assessing-job-polarization-explanation-wage-inequality.

22. Albert 0. Hirschman, "The Search for Paradigms as a Hindrance to

Understanding," World Politics 22, no. 3 (April 1970): 329-43.

C H A P T E R 5 : When Economists Go Wrong

1 . Thomas J. Sargent, "University of California at B erkeley Graduation

Speech," May 16, 2007, https://files.nyu.edu/ts43/public/personal/

UC_graduation.pdf.

2. Noah Smith, "Not a Summary of Economics," Noahpinion (blog),

April 19, 2014, http : //noahpinionblog.blogspot.com/2014/04/not

summary-of-economics.html; Paul Krugman, " No Time for Sargent,"

New York Times Opinion Pages, April 2 1 , 2014, http://krugman.blogs.

nytimes . com/20 14/04/21 /no-time-for-sargent/?module=BlogPost

Title&version=Blog%20Main&contentCollection=Opinion&action=

Click&pgtype= Blogs&region= Body.

2 2 6

N O T E S

3 . Greg Mankiw, "News Flash: Economists Agree," February 14, 2009,

Greg Mankiw's Blog, http://gregmankiw.blogspot.com/2009/02/news

-flash-economists-agree.html.

4. Richard A. Posner, "Economists on the Defensive-Robert Lucas," Atlantic,

August 9, 2009, http://www.theatlantic.com/business/archive/2009/08/

economists-on-the-defensive-robert-lucas/22979.

5. Robert Shiller, Irrational Exuberance, 2nd ed. (Princeton, NJ: Princeton

University Press, 2005) .

6. Raghuram G. Raj an, "The Greenspan Era: Lessons for the Future"

(remarks at a symposium sponsored by the Federal Reserve Bank

of Kansas City, Jackson Hole, WY, August 27, 2005) , http s : //www

.imf.org/external/np/speeches/2005/082705.htm; Charles Fergu

son, "Larry Summers and the Subversion of Economics," Chronicle

of Higher Education, October 3, 2010, http://chronicle.com/article/

Larry-Summersthe/ 1 2479 0 .

7. Eugene F . Fama, "Efficient Capital Markets: A Review of Theory and

Empirical Work," Journal of Finance 25, no. 2 (May 1970) : 383-417.

8. Edmund L. Andrews, "Greenspan Concedes Error on Regula

tion," New York Times, October 23, 2008, http://www.nytimes

. com/2008/10/24/business/ economy/24panel.html?_r= O .

9. John Williamson, "A Short History of the Washington Consensus"

(paper commissioned by Fundaci6n CIDOB for the conference "From

the Washington Consensus towards a New Global Governance," Bar

celona, September 24-2 5 , 2004).

10. Dani Rodrik, "Goodbye Washington Consensus, Hello Washington

Confusion?: A Review of the World Bank's Economic Growth in the

1990s: Learning from a Decade of Reform ," Journal of Economic Literature

44, no. 4 (December 2006) : 973-87.

1 1 . Dani Rodrik, "Getting Interventions Right: How S outh Korea

and Taiwan Grew Rich," Economic Policy 10, no. 20 (1995) : 53-107;

Rodrik, " S econd-Best Institutions," American Economic Review 98, no .

2 (May 2008) : 1 0 0-104.

227

N 0 T E S

1 2 . Stanley Fischer, "Capital Account Liberalization and the Role of

the IMF," September 19, 1997, https://www.imf.org/external/np/

speeches/1997/091997.htm# l .

1 3 . " The Liberalization and Management o f Capital Flows: A n Insti

tutional View," International Monetary Fund, November 14, 2 0 1 2 ,

http://www. imf.org/external/np/pp/eng/20 1 2 / 1 1 1412 .pdf.

14. Edward Lopez and Wayne Leighton, Madmen, Intellectuals, and Aca

demic Scribblers: The Economic Engine of Political Change (Stanford, CA:

Stanford University Press , 2 0 1 2) .

1 5 . Francisco Rodriguez and D ani Rodrik, "Trade Policy and Economic

Growth: A Skeptic's Guide to the Cross-National Evidence," in Mac

roeconomics Annual 2000, eds. Ben Bernanke and Kenneth S . Rogoff

(Cambridge, MA: MIT Press for NBER, 2 0 0 1) .

1 6 . Mankiw, "News Flash: Economists Agree."

17. Mark R. Rosenzweig and Kenneth I . Wolpin, "Natural 'Natural

Experiments' in Economics," journal of Economic Literature 38, no. 4

(December 2 0 0 0) : 827-74.

18. Dani Rodrik, The Globalization Paradox: Democracy and the Future

of the World Economy (New York: W. W. Norton, 2 0 1 1) , chap. 6 .

See also Rodr-ik, "In Praise o f Foxy Scholars," Project Syndicate,

March 10, 2 0 14, http : //www.project-syndicate.org/commentary/

dani-rodrik-on-the-promise-and-peril-of-social-science-models.

C H A P T E R 6 : Economics and Its Critics

1. David Colander, Richard F. Holt, and ] . Barkley Rosser, "The Chang

ing Face of Mainstream Economics," Review of Political Economy 1 6 , no.

4 (October 2004) : 487.

2. For a good overview of the differences between economists' and

anthropologists' perspectives, see Pranab Bardhan and Isha Ray, Meth

odological Approaches in Economics and Anthropology, Q-Squared Work

ing Paper 17 (Toronto: Centre for International Studies, University of

Toronto, 2006).

2 2 8

N O T E S

3. For a sampling of this work, see Samuel Bowles, "Endogenous Prefer

ences: The Cultural Consequences of Markets and Other Economic

Institutions," Journal of Economic Literature 26 (1998) : 75-1 1 1 ; George

A. Akerlof and Rachel E. Kranton Identity Economics: How Our Identi

ties Shape Our Work, Wages, and Well-Being (Princeton, NJ: Princeton

University Press, 2010); Alberto Alesina and George-Marios Angele

tos, "Fairness and Redistribution," A merican Economic Review 95 , no .

4 (2 005): 960-80; Alberto Alesina, Edward Glaeser, and Bruce Sacer

dote , "Why Doesn't the United States Have a European-Style Welfare

State?" Brookings Papers on Economic Activity, no. 2 (2001): 187-254;

Raquel Fernandez, "Cultural Change as Learning: The Evolution of

Female Labor Force Participation over a Century," American Economic

Review 103, no . 1 (20 1 3) : 472-500; Roland Benabou, Davide Ticchi,

and Andrea Vindigni, "Forbidden Fruits: The Political Economy of

Science, Religion, and Growth" (unpublished paper, Princeton Uni

versity, December 2 0 1 3) .

4. Neil Gandal e t a l . , "Personal Value Priorities o f Economists," Human

Relations 5 8 , no. 10 (October 2005) : 1 227-52; Bruno S. Frey and

Stephan Meier, "Selfish and Indoctrinated Economists?" European

Journal of Law and Economics 19 (2005): 165-7 1 .

5 . Michael ] . Sandel, "What Isn't for S ale?" Atlantic, April 2 0 1 2 , http://

www. theatlant i c . c om/magazine/archive/2 0 1 2 /0 4/what-isnt-for

sale/3 08902. See also Sandel, What Money Can't Buy: The Mora l Limits

of Markets (New York: Farrar, Straus and Giroux, 2012) .

6 . Uri Gneezy and Aldo Rustichini, "A Fine I s a Price," Jou rnal of Legal

Studies 29, no. 1 Qanuary 2000) : 1-17; Samuel Bowles, "Machiavel

li 's Mistake: Why Good Laws and No Substitute for Good Citizens"

(unpublished manuscript, 2 014) .

7. Sandel, "What Isn't for Sale?"

8. Albert 0 . Hirschman, The Passions and the Interest: Political A rguments

for Capitalism before Its Triumph (Princeton, NJ: Princeton University

Press, 1977); see also Hirschman, "Rival Interpretations of Market

229

N 0 T E S

Society: Civilizing, D estructive, or Feeble?" Journal of Economic Litera

ture 20 (December 1982) : 1463-84.

9. D ani Rodrik, "Occupy the Classroom," Project Syndicate, December

1 2 , 201 1 , http://www. proj ect-syndicate .org/ commentary I occupy-the

-classroom.

10. Simon Wren-Lewis, "When Economics Students Rebel," Mainly Macro

(blog), April 24, 2014, http://mainlymacro.blogspot.co .uk-2014-04

-when= economocs=students=rebel.html.

1 1 . Herbert A. Simon, "A Behavioral Model of Rational Choice," Quar

terly Journal of Economics 69 (February 1955): 99-1 1 8 ; Richard R. Nel

son and Sidney G. Winter, An Evolutionary Theory of Economic Change

(Cambridge, MA: Belknap Press of Harvard University Press, 1982).

1 2 . Daniel Kahneman, Paul Slovic, and Amos Tversky, Judgement under

Uncertainty: Heuristics and Biases (Cambridge: Cambridge University

Press, 1982).

1 3 . Werner F. M . D e Bondt and Richard Thaler, "Does the Stock Market

Overreact?" Journal of Finance 40, no. 3 (1985): 793-80 5 .

14. David Laibson, "Golden Eggs and Hyperbolic Discounting," Quar

terly Journal of Economics 1 1 2 , no. 2 (1997): 443-77; Brigitte C .

Madrian and Bennis F . Shea, "The Power o f Suggestion: Inertia in

4 0 1 (k) Participation and Savings Behavior," Quarterly Journal of Eco

nomics 1 16 , no . 4 (20 0 0 ) : 1 149-87; Jeffrey Liebman and Richard Zeck

hauser, Simple Humans, Complex Insurance, Subtle Subsidies, NBER

Working Paper 1433 0 (Cambridge, MA: National Bureau of Eco

nomic Research, 2 0 0 8) ; Esther Duflo, Michael Kremer, and Jonathan

Robinson, Nudging Farmers to Use Fertilizer: Theory and Experimental

Evidence from Kenya, NBER Working Paper 1 51 3 1 (Cambridge, MA:

National Bureau of Economic Research, 2009) .

1 5. S ee, for example, Angus Deaton, "Instruments of D evelopment: Ran

domization in the Tropics, and the Search for the Elusive Keys to Eco

nomic D evelopment" (Research Program in D evelopment Studies,

Center for Health and Wellbeing, Princeton University, January 2009):

2 3 0

N 0 T E S

1 6 . Daron Acemoglu, Simon Johnson, and James A. Robinson, "The

Colonial Origins of Comparative Development: An Empirical Inves

tigation," American Economic Review 9 1 , no. 5 (December 2001) :

1 369-140 1 .

17. A good overall synthesis o f this work c a n b e found i n Daron Acemoglu

and James Robinson, Why Nations Fail: The Origins of Power, Prosperity,

and Poverty (New York: Crown, 2012).

1 8 . Binyamin Appelbaum, "Q. and A. with Jean Tirole, Economics Nobel

Winner," New York Times, October 14, 2014 (http://www.nytimes

. com/2014/ 1 0/ 1 5/upshot/q-and-a-with-jean-tirole-nobel-prize-win

ner.html?_r= O&abt=0002&abg=O).

19. See, for example, the essays in Paul Rabinow and William M . Sulli

van, eds . , Interpretive Social Science: A Second Look (Berkeley: University

of California Press, 1987).

231

I NDE X

Page numbers in italics refer to illustrations.

Acemoglu, Daron, 206

advertising, prisoners' dilemma

and, 14-1 5

Africa, Washington Consensus and,

162

agriculture:

subsidies in, 149, 194

subsistence vs. modern, 75, 88

Airbus, 1 5

airline industry, deregulation of,

1 6 8

Akerlof, George, 6 8 , 69n

Algan, Yann, 79n, 200n

Allen, Danielle, xiv

American Economic Review (AER),

30-31

American Political Science Review

(APSR), 30-31

Angrist, Joshua, 108

antelopes, 35n

antipoverty programs, 3-4

cash grants vs . subsidies in, 4

antitrust law, 161

Argentina, 166

arguments, mathematics and, 35n

Arrow, Kenneth, 31, 49-51

Ash, Michael, 77

Asia, economic growth and, 163-

64, 166

asset bubbles, 1 52-58

asymmetric information, 6 8-69,

70, 7 1

Auctions: Theory a n d Practice

(Klemperer), 36n

"Auctions and Bidding: A Primer"

(Milgrom), 3 6 n

2 3 3

I N D E X

auction theory, 36, 168

automobiles, effect of sales tax and

demand on, 1 8 0-81

balanced budgets, 171

Bangladesh, 57-5 8 , 1 23

Bank of England, 197

banks, banking, l n, 2

computational models and,

credit rationing in, 64-65

globalization and, 1 65-66

Great Recession and, 1 52-59

insurance in, 1 5 5

regulation of, 1 5 5 , 1 58-59

shadow sector in, 1 53

bargaining, 1 24-25, 143

Battle of Bretton Woods, The: John

Maynard Keynes, Harry Dexter

White, and the-Making of a New

World Order (Steil), 1 n-2n

bed nets, randomized testing and,

1 0 6 , 2 04

behavioral economics, 69-7 1 ,

1 04-7, 202-4

Berlin, Isaiah, 175

Bernanke, Ben, 1 34-35

Bertrand competition, 6 8

Bhagwati, Jagdish, 182n-83n

big data, 38-39, 40

Bloomberg, Michael, 4

Boeing, 1 5

Bohm-Bawerk, Eugen von, 1 1 9

Bordo, Michael D., 1 27n

Borges, Jorge Luis, 43-44, 8 6

Boston University, 3

Boughton, James M . , 1 n

Boulding, Kenneth, 1 1

bounded rationality, 203

Bowles, Samuel, 7 1 n

Brazil:

antipoverty programs of, 4

globalization and, 166

Bretton Woods Conference (1944),

1-2

Britain, Great, property rights and,

bubbles, 1 52-58

business cycles, 1 25-37

balanced budgets and, 171

capital flow in, 1 27

classical economics and, 1 2 6-27,

1 29, 137

inflation in, 1 26-27, 133, 1 3 5 ,

1 37

new classical models and, 130-

34, 1 36-37

butterfly effect, 39

California, University of:

at B erkeley, 1 07, 1 3 6 , 147

at Los Angeles, 139

Cameron, David, 109

capacity utilization rates, 130

2 3 4

I N D E X

capital, neoclassical distribution

theory and, 1 22, 124

capital flow:

in business cycles, 127

economic growth and, 17-1 8 ,

1 14, 164-67

globalization and, 164-67

growth diagnostics and, 90

speculation and, 2

capitalism, 1 1 8-24, 127, 144, 205,

207

carbon, emissions quotas vs. taxes

in reduction of, 1 88-90,

1 9 1-92

Card, David, 57

Carlyle, Thomas, 1 1 8

carpooling, 1 9 2 , 193-94

cartels, 95

Cartwright, Nancy, 20, 22n, 29

cash grants, 4, 5 5 , 1 05-6

Cassidy, John, 1 57n

Central Bank of India, 1 5 4

Chang, Ha-Joon, 1 1

chaos theory, butterfly effect and,

Chicago, University of, 131, 1 52

Chicago B o ard of Trade, 55

Chile, antipoverty programs and, 4

China, People's Republic of, 1 5 6 ,

1 6 3 , 164

cigarette industry, taxation and,

27-28

Clark, John Bates, 1 19

"Classical Gold Standard, The:

Some Lessons for Today"

(Bordo), 1 27n

classical unemployment, 1 26

climate change, 1 8 8-90, 1 9 1-92

climate modeling, 38, 40

Cochrane, John, 131

coffee, 179, 185

Colander, David, 85

collective bargaining, 1 24-25, 143

Colombia, educational vouchers

in, 24

colonialism, developmental eco

nomics and, 206-7

" C olonial Origins of Comparative

Development, The"

(Acemoglu, Robinson, and

Johnson), 206-7

Columbia University, 2 , 1 0 8

commitment, in game theory, 33

comparative advantage, 52-5 5 , 58n,

59-60, 1 39, 170

compensation for risk models, 1 1 0

competition, critical assumptions

in, 28-29

complementarities, 42

computable general equilibrium

(CGE) models, 41

computational models, 3 8 , 41

computers, model complexity and,

235

I N D E X

Comte, Auguste, 81

conditional cash transfer (CCT)

programs, 4, 105-6

congestion pricing, 2-3

Constitution, U. S . , 187

construction industry, Great

Recession and, 1 5 6

consumers, consumption, 1 19, 129,

130, 132, 136, 167

cross-price elasticity in, 1 80-8 1

consumer's utility, 1 1 9

contextual truths, 20, 174

contingency, 25 , 145, 173-74, 185

contracts, 8 8 , 9 8 , 161 , 205

coordination models, 16-17, 42 ,

200

corn futures, 55

corruption, 87, 89, 91

costs, behavioral economics and, 70

Cotterman, Nancy, xiv

Cournot, Antoine-Augustin, 1 3 n

Cournot competition, 6 8

credibility, in game theory, 3 3

"Credible Worlds, Capacities and

Mechanisms" (Sugden), 172n

credit rating agencies, 1 5 5

credit rationing, 64-65

critical assumptions, 18, 26-29,

94-9 8 , 1 5 0-51 , 1 8 0 , 1 83-84,

202

cross-price elasticity, 1 8 0-81

Cuba, 57

currency:

appreciation of, 60, 167

depreciation of, 1 53

economic growth and, 163-64,

167

current account deficits, 1 53

Curry, Brendan, xv

Dahl, Gordon B . , 1 51 n

D arwin, Charles, 1 1 3

Davis, D onald, 108

day care, 7 1 , 190-9 1

Debreu, Gerard, 49-51

debt, national, 1 53

decision trees, 89-90, 90

DeLong, Brad, 1 3 6

democracy, social sciences and,

205

deposit insurance, 1 5 5

depreciation, currency, 1 53

Depression, Great, 2, 1 2 8 , 1 53

deregulation, 143 , 1 5 5 , 1 5 8-59,

162, 1 6 8

derivatives, 1 53 , 1 5 5

deterrence, in game theory, 3 3

development economics, 75-76,

8 6-93, 90, 1 59-67, 169, 201 ,

202

colonial settlement and, 206-7

institutions and, 9 8 , 161 , 202,

205-7

reform fatigue and, 8 8

2 3 6

I N D E X

diagnostic analysis, 8 6-93, 90, 97,

1 1 0-1 1

Dijkgraaf, Robbert, xiv

"Dirtying White: Why Does B enn

Steil 's History of Bretton

Woods Distort the Ideas

of Harry Dexter White?"

(Boughton), 1 n

distribution, general theory o f, 1 2 1

distribution, neoclassical theory of,

1 2 2 , 124

Dixit, Avinash, xv, 61

Dogan, Pmar, xv

Doing Growth Diagnostics in Practice

(Hausmann, Klinger, and

Wagner), 1 1 1 n

dollar, depreciation of, 1 53

dual economy models, 8 8

Dufl.o, Esther, 1 0 7

duopolies, 1 3 n, 68

Dutch disease syndrome, 60, 61 ,

73, 1 0 0

East Anglia, University of, 172n

Econometrica, 36

econometrics, 133

economic growth, 8 6-93, 9 0 , 97,

1 10-1 1 , 147-49

capital flow in, 17-1 8 , 1 14, 1 64-

currency in, 163-64, 1 67

public spending in, 76-78, 1 14

237

Washington Consensus and,

1 59-67, 169

economics:

ambition, humility and, 208-11

antipoverty programs and, 3-4

behavioral factors in, 69-7 1 ,

104-7, 202-4

business cycles in, 1 25-37

contingent explanations of social

life in, xiii

critical assumptions in, 1 8 ,

26-29, 94-9 8 , 1 50-5 1 , 1 80,

1 83-84, 202

critics and, 177-2 1 1

definitions of, 7

developing economies and, see

development economics

efficiency in, xiii, 14, 2 1 , 34, 48,

50, 51 , 67, 98, 125, 147, 148,

150, 1 56-5 8 , 161, 165, 170,

192-95, 196

errors of commission in, 1 59-67

errors of omission in, 1 52-59

field experiments in, 23-24,

1 05-8 , 173, 202-5

game theory and, 5, 14-1 5 , 33,

36, 61-62, 68, 103-4, 1 33

government policies and, 75-76,

87, 8 8 , 147-48, 149, 1 60-61 ,

171

"hedgehog" vs. "fox" approaches

in, 175

I N D E X

economics (continued )

ignorant vs. calculating peasant

hypotheses in, 75

individual behavior in, 17, 33,

3� 42 , 4� 1 0 1 , 102, 1 3 1 , 1 3�

1 8 1-82

marginalists and, 1 1 9-22

models in, see models

outsider views in, 6

pluralism in, 196-208

points of consensus in, 147-52,

194-95

power and responsibility and,

174-75

predictability in, 6, 26-2 8 , 3 8 ,

40-41 , 8 5 , 1 0 4 , 1 0 5 , 1 0 8 , 1 1 5 ,

1 32 , 1 33 , 1 39-40, 1 57, 175,

1 84-85 , 202

progressive mo deling i n , 63-

psychology and sociology of,

1 67-74

self-interest in, 2 1 , 104, 1 5 8 ,

1 8 6-8 8 , 190

shocks in, 1 30-3 1 , 1 32

social sciences and, xii-xiii, 45,

1 8 1-82, 2 02-7

strengths and weaknesses of, xi

supply and demand in, 3 , 1 3-14,

20, 99, 1 19, 122, 1 28-30, 1 36-

37, 170

trade-offs in, 193-94

twenty commandments for,

2 1 3-1 5

values i n , 186-96