ChapterPDF Available

Behavioral Economics, History of



This article reviews the historical development of behavioral economics, with an emphasis on how it has become part of mainstream economics. First I describe the separation between economics and psychology as a historical background against which behavioral economics emerged. Then I introduce critiques of expected utility theory (EUT), and explain how behavioral decision research developed using EUT as an experimental paradigm. I then distinguish ‘old,’ ‘new,’ and ‘second-wave’ behavioral economics, and briefly discuss criticisms of the last.
Provided for non-commercial research and educational use only.
Not for reproduction, distribution or commercial use.
This article was originally published in the International Encyclopedia of the Social
& Behavioral Sciences, 2nd edition, published by Elsevier, and the attached copy
is provided by Elsevier for the author’s benefit and for the benefit of the
author’s institution, for non-commercial research and educational use including
without limitation use in instruction at your institution, sending it to specific
colleagues who you know, and providing a copy to your institution’s administrator.
All other uses, reproduction and distribution, including
without limitation commercial reprints, selling or
licensing copies or access, or posting on open
internet sites, your personal or institution’s website or
repository, are prohibited. For exceptions, permission
may be sought for such use through Elsevier’s
permissions site at:
From Nagatsu, M., 2015. Behavioral Economics, History of. In: James D. Wright
(editor-in-chief), International Encyclopedia of the Social & Behavioral Sciences,
2nd edition, Vol 2. Oxford: Elsevier. pp. 443–449.
ISBN: 9780080970868
Copyright © 2015 Elsevier Ltd. unless otherwise stated. All rights reserved.
Author's personal copy
Behavioral Economics, History of
Michiru Nagatsu, University of Helsinki, Helsinki, Finland
Ó2015 Elsevier Ltd. All rights reserved.
This article reviews the historical development of behavioral economics, with an emphasis on how it has become part of
mainstream economics. First I describe the separation between economics and psychology as a historical background against
which behavioral economics emerged. Then I introduce critiques of expected utility theory (EUT), and explain how
behavioral decision research developed using EUT as an experimental paradigm. I then distinguish old,’‘new,and second-
wavebehavioral economics, and briey discuss criticisms of the last.
Behavioral economics, an increasingly inuential research
program in economics, tries to improve economic theory and
policy by drawing mainly on psychological or behavioral
insights on how real people, as opposed to the idealistically
rational agent, think and behave (Mullainathan and
Thaler, 2001;Camerer and Loewenstein, 2004). Behavioral
economics thus dened has now become part of mainstream
economics, in terms of the numbers of behavioral economists
hired in research institutions, journal articles, and textbooks
published, and prestigious prizes awarded to behavioral
economists. Its practical relevance is increasing as both public
and private sectors use more ndings from behavioral
economics to efciently and effectively change peoples
behavior. Finally, several popular books (e.g., Ariely, 2008;
Poundstone, 2010;Kahneman, 2013) made behavioral
economics well known among the educated general public.
Accordingly, an interest in its history has arisen as well. Sent
(2004) is one of the earliest studies on this subject, and
Angner and Loewenstein (2012) is an informative review.
Heukelom (2014) gives a book-length treatment (see also
Heukelom, 2011, 2012). One of the questions these authors
explicitly and implicitly ask is why behavioral economics has
been so successful. There are several contributing factors, and
the reader is referred to the above mentioned literature to get
a fuller account. In this article, I will highlight one important
reason for the success of behavioral economics, namely that it
adopted mainstream rational economic modeling tools such as
utility maximization and equilibrium analysis of games,
instead of denying them and proposing an altogether different
The article proceeds as follows: Section The Historical
Context briey introduces the historical background against I
proceed as follows: after briey introducing The Historical
Context in which behavioral economics emerged, I describe
Early Criticisms of EUT and describe OldBehavioral
Economics. Then I identify Behavioral Decision Research
(BDR)asabasisofNewBehavioral Economics, and
describe two important results in BDR, which gave rise to
NewBehavioral Economics. Then I illustrate The Second-
WaveBehavioral Economics and its critics, followed by
The Historical Context
Economics as a Separate Science
If behavioral economics is characterized by the use of rich
psychological insights, then its history has to go back at least to
David Hume (171176) and Adam Smith (172390). In fact,
Ashraf et al. (2005) argue that SmithsTheory of Moral
Sentiments (Smith, 2002,rst published in 1759) proposes
what is now called the dual-process cognitive model;
anticipates modern ndings such as loss aversion, willpower,
and fairness; and even suggests new directions for research in
behavioral economics. Even though these claims might well be
true, it is important to remember that contemporary behavioral
economics has emerged against a backdrop of the sharp
separation of economics from psychology that had been
gradually established over 200 years since Smith. This
separation started from John Stuart Mills (180673) deductive
and a priori methodology, and was achieved by successive
neoclassical theoretical innovations such as marginal utility
theory, indifference curve analysis, and revealed preference
theory. As a result, economists became able to model an agents
choice behavior in terms of her preference satisfaction without
referring to the utility concept connected with psychological
valence. Instead, the concept of utility was reinterpreted simply
orderings as dened by preference theory.
Subjective Expected Utility Theory
Preference theory made it possible to explain choice behavior
in terms of preference orderings. In turn, the utility concept in
economics became ordinal,i.e., there was no need to talk
about subjective and unobservable intensities of psychological
utilities for different goods. This situation was somewhat
complicated by the invention of expected utility theory (EUT).
In general, desirability of a course of action depends not only
on the value that action intends to deliver, but also on (ones
belief about) the way the world is; for instance, the desirability
of an action of bringing or not bringing an umbrella depends
on what (one thinks) the weather is going to be like. In order to
model decision-making under such uncertainty, the British
philosopher Frank Ramsey (190330) sketched, in 1926, a way
of quantifying and operationalizing degrees of beliefs and
International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Volume 2 443
International Encyclopedia of the Social & Behavioral Sciences, Second Edition, 2015, 443–449
Author's personal copy
desires solely from the observation of the agents simple
choices over lotteries, adopting an idealized folk
psychological scheme in which we act in the way we think
most likely to realize the objects of our desires, so that
a persons actions are completely determined by his desires
and opinions(Ramsey, 1931: 173). The mathematician John
von Neumann (190357), while working on the theory of
strategic interactions and its application to economics,
axiomatized this system as EUT (von Neumann and
Morgenstern, 2004, originally published in 1944). (The full
axiomatization is given in the second edition published in
1947.) von Neumann and Morgenstern (2004) proposed the
objective interpretation of probability (i.e., as relative
frequencies of events in the long run), but anticipated
subjective EUT, admitting that the subjective view of
probability also leads to a satisfactory numerical concept of
utility (3.3.3: fn. 2). The mathematician Leonard Savage
(191771), a war-time assistant of von Neumann at the
Institute for Advanced Study, Princeton, completed the
subjective version of EUT, the foundation of modern decision
theory (Savage, 1954). (The idea of expected utility itself was
already proposed by the Dutch-Swiss mathematician Daniel
Bernoulli (170082) in 1738. Another important founder of
subjective EUT is the Italian statistician Bruno de Finetti
(190685), whose work is acknowledged in Savage (1954).)
As a result, it became possible to talk about the relative
intensity of preferences in an operationally meaningful and
principled way, bringing the cardinalutility back in
economic models of decision-making in a legitimate fashion.
At the same time, Savages theory made it possible to
measure subjective beliefs qua probabilities in an equally
rigorous manner. As we will see below, the birth of EUT
proved to be crucial for the emergence of behavioral
economics. (In what follows, I simply use the term EUT, but
this should be read as a subjective version of the theory
unless otherwise stated.)
Early Criticisms of EUT
Savages EUT is not behavioristic as preference theory
presumably aspired to be, because the former explicitly refers to
psychological constructs such as subjective beliefs and expected
utility. Nevertheless, economists welcomed it because the
axiomatic approach was thought to guarantee the operationally
meaningful and nonarbitrary measurement of these quantities.
EUT thus soon found its application in economics. As early as
1948, Milton Friedman (19122006) collaborated with
Savage, putting forward EUT as an economic hypothesis to
explain the coexistence of insurance and lotteries (Friedman
and Savage, 1948). But no sooner than EUT was completed
as an axiomatic system, several economists expressed serious
doubts on its normative acceptability and empirical
plausibility (Markowitz, 1952;Allais, 1953;Ellsberg, 1961).
These criticisms, however, were based on introspection and
casual observations, rather than the rigorous experimental
studies. This is only natural because back in the days
experimental methods were not part of economiststoolbox
yet. Instead, early experimental tests of EUT, with small but
real monetary incentives, were conducted by the Harvard
statistician Frederick Mosteller (19162006) and his student
Philip Nogee (1951), and by the psychologist Sidney Siegel
(191661), philosophers Donald Davidson (19172003),
and Patrick Suppes (1922 to present) at Stanford (Stanford
Value Theory Project) (1955). Another student of Mosteller,
Ward Edwards (19272005), played a particularly important
role in the rise of behavioral economics, as we will see in the
next section. Before discussing that, I will turn to the so-
called oldbehavioral economics below.
OldBehavioral Economics
Herbert Simon (19162001), one of the earliest critics of
models of rational choice in economics, was more radical than
his contemporary critics of EUT. While these critics formulated
problems as implausibility of specicaxiomsofEUT,suchas
the independent axiom, Simon offered a more programmatic
critique, as part of the broader contribution he made to
the so-called cognitive revolution: a paradigm shift in the
postwar psychology from behaviorism to the computational
modeling of internal cognitive processes. Simon argued that
utility maximization models such as EUT, interpreted as
representational models of cognitive processes of economic
agents, are empirically unsound, drawing on the distinction
between substantive and procedural rationality. The former
concerns an intelligent systems adjustment or adaptation to
its outer environment (e.g., an economic agentsreactionto
the market), whereas the latter concerns the systemsability
determined by its inner knowledge and computation that
constrains the former (Simon, 1996: 25). A key idea is that we
need only substantive rationality to predict behavior of the
system if both its goal and environment are simple; but since
these factors and their interaction are in fact complex, Simon
argued, we have to explicitly consider the procedural
rationality of the system. From this bounded rationality
perspective, economic models of choice are decient because
they assume substantive rationality (individualsutility
maximization and organizationsprotmaximizationinthe
market environment) when in fact these conditions are not
satised, requiring the explicit modeling of the inner workings
of the agent, be it a human being or a rm.
Simons impact on mainstream economics, however, was
limited. Although he received the Nobel Memorial Prize in
Economics in 1978 for his pioneering research into the
decision-making process within economic organizations,his
proposal that individual procedural rationality should be
explicitly modeled was not accepted by mainstream
economics. Neither were his contemporary economists
alternative methods and theories that drew on psychology
and other social sciences. Although already in the 1960s the
term behavioral economicswas used to refer to these
economistsrather heterogeneous research programs (Sent,
2004), their efforts did not have much impact on
mainstream economics, despite the launch of The Journal of
Behavioral Economics in 1972 (continued as The Journal of
Socio-Economics since 1991) and such publications as Katona
and Morgan (1980),Gilad and Kaish (1986) (but see
Hosseini, 2003). For this reason, Sent (2004) calls these lines
of research oldbehavioral economics. (Given contemporary
research such as Altman (2006), perhaps it is more
444 Behavioral Economics, History of
International Encyclopedia of the Social & Behavioral Sciences, Second Edition, 2015, 443–449
Author's personal copy
appropriate to call it heterodox rather than old behavioral
In retrospect, one reason why oldbehavioral economics
never caught on in the mainstream is that it started from the
dismissal of the main methodological tenets of mainstream
economics, such as positivism, deductivism, static equilibrium
analysis, and optimizing models of economic agency (see
Hosseini, 2003: 394). In contrast, as we will see below, new
behavioral economics has its deep root in BDR, which exploi-
ted maximization models such as EUT as experimental
Behavioral Decision Research
Ward Edwards was among the rst psychologists to notice the
relevance of EUT for psychology. He introduced it to psycholo-
gists as behavioral decision theory (Edwards, 1954, 1961;Edwards
et al., 1963), a rational model of individual probability judg-
ment (subjective Bayesianism) and choice under risk. Edwards,
the son of an economist, studied psychology at Harvard under
the inuence of Mosteller, who introduced Edwards to EUT
(Phillips and von Winterfeldt, 2007). In 1958, Edwards moved
to the psychology departmentat the University of Michigan, Ann
Arbor, a then-rapidly expanding research center in mathematical
psychology and decision-making (see Heukelom, 2010). But it
was the following younger generation, including his former
students at Michigan, who developed a subeld in cognitive
psychology called BDR, by demonstrating systematic
violations of the predictions of EUT in a series of experiments,
and by proposing alternative models of individual judgment
and decision-making. Mainstream economic rational choice
models such as EUT were crucial for the development of BDR,
since these models provided clear and crisppredictions to be
experimentally explored (Sent, 2004;Angner and Loewenstein,
2012); the deviations from the predictions could then be
exploited to develop alternative models. In particular, two
developments in BDR are important for the rise of new
behavioral economics.
Preference Reversals and the Construction of Preferences
One of the rst systematic violations of EUT was demonstrated
by Sarah Lichtenstein (1933 to present) and Paul Slovic (1938
to present), Edwardss former students, then working at the
Oregon Research Institute. They conducted a series of experi-
ments on peoples risk assessments of hypothetical gambling,
and discovered a serious anomaly for EUT called preference
reversal (Lichtenstein and Slovic, 1971; see also Lindman,
1971), reported essentially the same result). Preference
reversal is a phenomenon in which the decision-makers pref-
erence over a pair of lotteries seems to be ipped depending on
the method of preference elicitation. For example, when asked
to choose one bet from two, many subjects in Lichtenstein and
Slovics experiments chose a low-payoff, high-probability bet
(the so-called P bet, e.g., 35/36 chance of winning $4) over
a high-payoff, low-probability bet ($ bet, e.g., 11/36 chance
of winning $16); but when asked to state how much they
were willing to pay, the subjects priced the $ bet higher than
the P bet. The subjects seemed to have violated the axiom of
transitivity (as their responses suggested they prefer A to B,
and B to A at the same time), but the problem was deeper
than that since it challenged the procedural invariance principle,
a fundamental assumption of rational choice that preferences
over an identical set of alternatives should not change
depending on how you measure them (e.g., letting subjects
rate, choose between, or state reserve prices for options). This
result was replicated in a eld experiment using real gamblers
incentivized with high-stake money in the Four Sisters Casino
in Las Vegas (Lichtenstein and Slovic, 1973).
Preference reversals caught economistsattention: two Cal-
tech experimental economists challenged this result, with an
explicit attempt to make the phenomenon go away, only to nd
it persisted (Grether and Plott, 1979). This paper was published
in The American Economic Review, stimulating economists to
produce alternative models to EUT that abandon or modify
axiom(s) of EUT. In contrast, Slovic and other behavioral
decision researchers proposed procedural models in which
preferences are constructed in the process of decision-making
(see articles collected in Section III of Lichtenstein and Slovic,
Framing Effects and Prospect Theory
Another series of serious challenges to EUT came from a team of
Israeli-American psychologists Amos Tversky (193796) and
Daniel Kahneman (1934 to present). Tversky completed his
PhD at Michigan in 1965 under the supervision of Clyde
Coombs (191288) and Edwards. Tverskys early research was
on both the representational theory of measurement in
mathematical psychology and empirical investigation into
subjective EUT (Heukelom, 2009: 48). In the late 1960s,
Tversky went back to Israel to teach at Hebrew University,
where Daniel Kahneman had been establishing himself as
a leading researcher in the eld of mental effort. Tverskys
faith in subjective Bayesianism was severely shakenby
conversations with Kahneman (Kahneman, 2003). The rst
series of their collaborative work thus studied individual
probability judgment under uncertainty; how individuals use
mental shortcuts called heuristicssuch as representativeness,
availability, and anchoring and adjustment; and how these
heuristics lead to biases,i.e., deviations from the subjective
Bayesian model, part of subjective EUT. This research
program, known as heuristics and biases,was launched with
their rst collaborative paper (Tversky and Kahneman, 1971),
and further developed in their Science paper (Tversky and
Kahneman, 1974) and other papers collected in Kahneman
et al. (1982) and Gilovich et al. (2002).
Another, perhaps even more important program by Tversky
and Kahneman comprises a series of experiments that
demonstrated framing effects (Tversky and Kahneman, 1981,
1986), and Prospect Theory (Kahneman and Tversky, 1979)as
an alternative to EUT (other important papers are collected in
Kahneman and Tversky, 2000). Broadly speaking, framing
effects refer to another type of preference reversals, in which an
individuals preference over an identical set of alternatives
seems to be ipped depending on how they are described, in
particular as a gain or loss. Framing effects are as serious an
anomaly to EUT as Lichtenstein and Slovics preference
reversals, because they challenged another invariance principle
Behavioral Economics, History of 445
International Encyclopedia of the Social & Behavioral Sciences, Second Edition, 2015, 443–449
Author's personal copy
in rational choice called the descriptive invariance, which states
that the agents preferences over an extensionally identical set
of alternatives should not be affected by how they are inten-
sionally described. An innovation of Prospect Theory con-
sisted in its introduction of the concept of reference points to
explain framing effects and other related anomalies within the
framework of utility theory. One of the central ideas of Prospect
Theory is that an individual evaluates gains and losses relative
to a certain reference point, not absolute quantities, an
application of psychophysics to the perception of money and
other goods. Different frames with different reference points
shift the perception of alternatives as a gain or loss, and affect
individualschoice. With the assumptions that people are
risk-averse toward unlikely loss and likely gain, and
risk-seeking toward likely loss and unlikely gain, Prospect
Theory explained not only framing effects but also other
early problems such as Allaiss paradox, and peoples
simultaneous purchasing of lotteries and insurances that had
been discussed earlier by Friedman and Savage (1952) and
Markowitz (1952). (For a critical assessment of Prospect
Theory and related models of risky choice, see Friedman
et al. (2014).)
Tversky and Kahnemans1979Econometrica paper
(Kahneman (2003) recalls: The choice of venue turned out to
be important; the identical paper, published in Psychological
Review, would likely have had little impact on economics. But
our decision was not guided by a wish to inuence economics.
Econometrica just happened to be the journal where the best
papers on decision-making to date had been published, and
we were aspiring to be in that company.) and their 1981
Science paper were hailed as having altered the intellectual
history of economics; they brought the behavioral
economics research program into the mainstream(Laibson
and Zeckhauser, cited in Angner and Loewenstein, 2012:
662). This reputation of Prospect Theory is due not only to
its empirical success, but also to its unique hybrid nature: on
the one hand, it is a psychologically informed cognitive
process model in which alternatives are mentally editedas
gains and losses before choice; on the other, it is presented
as a utility maximization model with a peculiar utility curve,
representing different subjective valuations of likely and
unlikely outcomes in gain and loss domains. Unlike old
behavioral economics and other BDR, Prospect Theory
demonstrated an appealing, paradigmatic way of
incorporating insights from cognitive psychology into
economic models of choice.
‘New’ Behavioral Economics
The success of Prospect Theory encouraged a number of young
economists to challenge the standard models of rational
choice. In Toward a Positive Theory of Consumer Choice (1980),
for example, Richard Thaler (1945 to present) discussed,
drawing on Tversky and Kahnemans work, various aspects of
consumer behavior (e.g., underweighting of opportunity costs,
failure to ignore sunk costs, regret, and self-control) that
would become central themes in behavioral economics.
Thaler spent the 198485 academic year visiting the
University of British Columbia to work with Kahneman,
who recalls that That was the year that behavioral
economics began(Poundstone, 2010: chapter 17). Thaler
also contributed to the dissemination of empirical ndings
challenging economic models of choice, and helped
mainstream economists to see the relevance of these results,
through publishing, in collaboration with psychologists and
economists, Anomaliescolumns in the Journal of Economic
Perspectives, between 1987 and 1991 (later collected in
Thaler, 1992), and 19952001 (see Heukelom, 2012:fn.16).
Two private foundations, the Sloan Foundation and Russell
Sage Foundation, also played a key role in developing behav-
ioral economics as a thriving subeld of economics, through
nancially supporting the behavioral economics program
(198492), including projects such as nonresidential working
groups, the visiting researchers program, and the Russell Sage
Foundation Behavioral Economics Books Series (Heukelom,
2012). Eric Wanner (1942 to present), a former Harvard
cognitive psychologist, who had a clear goal to apply cognitive
science to economics, played a pivotal role as a director of the
behavioral economics program at both foundations. Wanner
involved Tversky, Kahneman, and Thaler from early on at the
preparatory stage of the program. Although Wanner initially
understood the program as a development of Simons
behavioral economics that was highly critical about the
mainstream neoclassical economics, he quickly adopted
several strategies to bring new behavioral economics to the
mainstream. For example, he emphasized applications of
behavioral insights to the study of economically important
domains such as nancial markets. Wanner also solicited
prominent and promising economists for applications,
including Kenneth Arrow (1921 to present), Vernon Smith
(1927 to present), George Akerlof (1940 to present), and
Robert Shiller (1946 to present) (Heukelom, 2012). (Smith,
who shared the 2002 Nobel Prize with Kahneman, however,
was critical about the direction of the behavioral economics
program by the 1990s; his prize was awarded for a distinct
research program called experimental economics.) Simon, one
of Wanners 40 invitees in 1985, criticized Wanners program
for taking too seriously the premises of contemporary
economic methodology that theories (models)comerst and
empirical work afterward; for Simon, the problem was that
mainline economists continue to ignore vast bodies of
relevant evidence in their preferred pursuit of armchair model
building(Simons 1986 letter to Wanner cited in Heukelom
(2012)). Wanner and his advisors, however, seem to have
been aware that a key to the success of behavioral economics
was to accommodate psychological ndings without giving up
economistsway of model building.
The ‘Second-Wave’ Behavioral Economics
Matthew Rabin (2002: 658) observed the rise of second-wave
behavioral economics,which moves beyond pointing out
problems with current economic assumptions, and even
beyond articulating alternatives, and on to the task of
systematically and formally exploring the alternatives with
much the same sensibility and mostly the same methods that
economists are familiar with.As examples, he mentions the
models of time preferences and social preferences. (In the
446 Behavioral Economics, History of
International Encyclopedia of the Social & Behavioral Sciences, Second Edition, 2015, 443–449
Author's personal copy
domain of risk preferences, Tversky and Kahnemans (1992)
Cumulative Prospect Theory can be seen as a second-wave
upgrade of their original Prospect Theory.) In the following
two subsections, I illustrate these models in turn, and in the
last subsection I briey discuss recent criticisms of these
Modeling Dynamically Inconsistent Preferences
Since important economic behavior such as saving concerns
consumption that are to be made over an extended period of
time, economic theory needs to explicitly model how
consumers value delayed as well as immediate consumptions.
Paul Samuelson (19152009) proposed the discounted utility
model (DUM), which had become the standard model of time
discounting (Samuelson, 1937). One of the fundamental
assumptions of DUM is that [d]uring any specied period of
time, the individual behaves so as to maximie the sum of all
future utilities, they being reduced to comparable magnitudes
by suitable time discounting(p. 156). As a suitable time-
discountingfunction, Samuelson proposed, without any
commitment to its empirical or normative plausibility, the
following exponentially declining discount function:
where 0 <d<1. An exponential discount function is char-
acterized by a constant discount rate for all future events. Thaler
(1981), however, using a survey method, showed that the
per-period discount factor ddeclined over time. Later studies
have conrmed this result (see Frederick et al., 2002,for
a review). Intuitively put, this is because people value the
present and future very differently. People obviously value
present consumption (at time t) more than future
consumption at tþ1, but an exponential discount function
suggests that the discount rate between tand tþ1isthesame
as that between tþ1andtþ2.Butsincetheformercaseis
a comparison between the present event and a future one,
while the latter between two future events, the former should
show more pronounced discounting. To capture this feature
of time discounting, Laibson (1997) adopted a quasi-
hyperbolicdiscount function, which had been used in
a model of intergenerational altruism by Phelps and Pollak
where 0 <d<1, and 0 <b<1. Hyperbolic discount functions
imply discount rates that decline as the discounted event is
moved further away in time, capturing familiar problems of
impulsive behavior and procrastination. Note that hyperbolic
discounting generalizes the standard assumption of expo-
nential discounting, i.e., (2) reduces to (1) if b¼1, while
retaining Samuelsons assumption about the existence of
a time-additive utility function. Laibson (1997) adopted
a discrete, rather than continuous, version of a hyperbolic
discount function (hence the quasiqualication), in order to
[mimic] the qualitative property of the hyperbolic discount
function, while maintaining most of the analytical tractability
of the exponential discount function(p. 450). This is the
kind of sensibilityand the methods that economists are
familiar with.
Modeling Prosocial Preferences
Another growing domain of research in behavioral economics
is the study of prosocial behavior. Although the default
assumption in the theory of public goods since Samuelson
(1954) had been selsh individuals, viz., that individuals
care only about self-interest narrowly dened in terms of own
material gains and losses, the eld evidence such as successful
voluntary provision of public goods and charitable giving
prompted economists to propose alternative models of
nonselsh preferences that better explain the observations
(e.g., Becker, 1974;Sugden, 1984). Experimental economists
and psychologists have also tested since 1980s so many
different variations of prisoners dilemma and public goods
games that there is now substantial body of evidence against
the selshness assumption (see Ledyard, 1995;Chaudhuri,
However, the business of modeling prosocial preferences
boomed with the inventions ofother games from which one can
more straightforwardly infer playersbeliefs and preferences. The
ultimatum game (Güth et al., 1982) is a game in which one player
(the Proposer) makes a take-it-or-leave-it offer, as a division of
a sum of money between herself and another player. If the
second player (the Responder) accepts the division, then both
players earn the specied amounts. If the Responder rejects it,
they both get nothing. The standard prediction (rational play
plus selsh preference) is that the Proposer will offer
a minimum divisible sum of the money, which will be
accepted by the Responder: for the Responder, any positive
sum is better than zero (money maximization); since the
Proposer knows this, she proposes the smallest amount to
maximize her own money. Evidence from experiments shows
that Proposers offer on average 3040% of the money (modal
and median offers are 4050%); and Responders reject small
offers below 20% about half the time. These results clearly
falsify the standard prediction. Even in the game in which the
Responder has no choice but to accept the offer (the dictator
game,Kahneman et al. (1986)), the Dictator offers on average
about 20% of the sum (see Camerer, 2003).
Models of social preferences try to accommodate the data
across these experimental games, as well as prisoners dilemma
and public goods games. Rabin (1993), employing psycholog-
ical game theory, proposed a model of reciprocal fairness,where
one player matches anothersintention,which is inferred
from the payoff structure of the game. For example,
a responder in an ultimatum game may act mean(reject) if
she thinks the proposer to be meanfor offering, say 20%,
because he could have offered her 40%, if not 50%. Fehr and
Schmidt (1999) offered another model of inequality aversion,in
which players have a preference for egalitarian distribution of
the payoffs. For example, an inequality-averse player may give
a substantial portion of the pie to the second player in
a dictator game.
Recent Criticisms of the Second-WaveModels
In recent years, these models of second-wavebehavioral
economics attracted mainly two types of methodological
criticism. The rst concerns its single-minded modication of
functional forms instead of explicitly modeling plausible
Behavioral Economics, History of 447
International Encyclopedia of the Social & Behavioral Sciences, Second Edition, 2015, 443–449
Author's personal copy
psychological processes (e.g., Rubinstein, 2003). In particular,
social preference theoristsconviction that [f]or modeling
purposes, behaviorally relevant emotions can be captured by
appropriate formulations of the utility function(Camerer
and Fehr, 2004: 80) have been challenged on several
conceptual and methodological grounds (Heap and
Varoufakis, 2004;Guala, 2006;List, 2007). Accordingly,
models that draw more directly on cognitive and social
psychology have been proposed (e.g., Bicchieri, 2006).
The second type of criticism concerns the specic ways in
which behavioral economists interpret the data from experi-
ments. In particular, Ross (2014) criticizes their strategy to
identify central tendencies in a small sample and explain them
in terms of common psychological dispositions of individuals,
or utility functions that represent such tendencies (pp. 156,
233, 250). Ross instead advocates the approach to econo-
metrically estimate the structure of heterogeneity in the data-
generating processes in the large data set, in order to predict
how such heterogeneity respond to policy interventions at
the population level (see Andersen et al., 2008).
In this article, I briey sketched the historical development of
behavioral economics, which is nicely summarized as what
Camerer and Loewenstein (2004:7)callarecipeof behav-
ioral economics:
First, identify normative assumptions or models that are ubiqui-
tously used by economists, such as Bayesian updating, expected
utility, and discounted utility. Second, identify anomalies i.e.,
demonstrate clear violations of the assumption or model, and
painstakingly rule out alternative explanations (such as subjects
confusion or transactions costs). Third, use the anomalies as
inspiration to create alternative theories that generalize existing
models. A fourth step is to construct economic models of
behavior using the behavioral assumptions from the third step,
derive fresh implications, and test them.
My narrative has along the way emphasized a key to the
academic success of behavioral economics, namely its adop-
tion of standard economic modeling techniques such as utility
maximization and equilibrium analysis. But the prominence
of behavioral economics might not be as stable as it appears
now, for it faces challenges from both psychology and
economics, as briey discussed in Section Recent Criticisms of
the Second-WaveModels: one the one hand, the psycholog-
ical critique suggests the limits of modeling individual psycho-
logical processes using existing economic methods; on the other,
the economic (or econometric, to be more specic) critique
points to the limits of modeling aggregate-level data-generating
processes using a single representative functional form. It
remains to be seen how behavioral economists will address
these distinct challenges, and how their disciplinary identity
will be affected as a consequence.
See also: Behavioral Economics; Behavioral Theories of
Organization; Decision and Choice: Random Utility Models of
Choice and Response Time; Expectations, Economics of;
Experimental Economics; Microeconomics, History of;
Neuroeconomics; Personality and Economics.
Allais, M., 1953. Le comportement de lhomme rati onnel devant le risque: critique
des postulats et axiome s de lecole americaine. Econometrica 21 (4), 503546.
Altman, M., 2006. Handbook of Contemporary Behavioral Economics: Foundations
and Developments. M.E. Sharpe, Armonk, NY.
Andersen, S., Harrison, G.W., Lau, M.I., Rutström, E.E. , 2008. Eliciting risk and time
preferences. Econometrica 76 (3), 583618.
Angner, E., Loewenstein, G., 2012. Behavioral economics. In: Mäki, U. (Ed.),
Philosophy of Economics, Handbook of the Philosophy of Science, vol. 13.
Elsevier, pp. 641689.
Ariely, D., 2008. Predictably Irrational: The Hidden Forces That Shape Our Decisions,
rst ed. Harper, New York.
Ashraf, N., Camerer, C.F., Loewenstein, G., 2005. Adam smith, behavioral econo-
mist. Journal of Economic Perspectives 19 (3), 131145.
Becker, G.S., 1974. A theory of social interactions. The Journal of Political Economy
82 (6), 10631093.
Bicchieri, C., 2006. The Grammar of Society. Cambridge University Press,
Cambridge, England.
Camerer, C.F., 2003. Behavioral Game Theory. Princeton University Press,
Princeton, NJ.
Camerer, C.F., Fehr , E., 2004. Measuring social norms and preferences using
experimental games: a guide for social scientists. In: Henrich, J., Boyd, R.,
Bowles, S., Camerer, C., Fehr, E., Gintis, H. (Eds.), Foundations of Human
Sociality: Economic Experiments and Ethnographic Evidence from Fifteen Small-
scale Societies. Oxford University Press, Oxford, pp. 5595 (Chapter 3).
Camerer, C.F., Loewenstein, G., 2004. Behavioural economics: past, present, future.
In: Camerer, C.F., Loewenstein, G., Rabin, M. (Eds.), Advances in Behavioral
Economics. Princeton University Press, Princeton, NJ, pp. 351 (Chapter 1).
Chaudhuri, A., 2011. Sustaining cooperation in laboratory public goods experiments:
a selective survey of the literature. Experimental Economics 14 (1), 47 83.
Davidson, D., Siegel, S., Suppes, P., 1955. Some Experim ents and Related Theory on
the Measurement of Utility and Subjective Probability. Technical Report Prepared
for Ofce of Naval Research. Stanford University, Stanford.
Edwards, W., 1954. The theory of decision making. Psychological Bulletin 41,
Edwards, W., 1961. Behavioral decision theory. Annual Review of Psychology 12,
Edwards, W., Lindman, H., Savage, L.J., 1963. Bayesian statistical inference for
psychological research. Psychological Review 70, 193242.
Ellsberg, D., 1961. Risk, ambiguity, and the savage axioms. The Quarterly Journal of
Fehr, E., Schmidt, K.M., 1999. A theory of fairness, competition, and cooperation.
The Quarterly Journal of Economics 114 (3), 817868.
Frederick, S., Loewenstein, G., ODonoghue, T., 2002. Time discounting and time
preference: a critical review. Journal of Economic Literature 40 (2), 351401.
Friedman, D., Isaac, R.M., James, D., Sunder, S., 2014. Risky Curves: On the
Empirical Failure of Expected Utility. Routledge, New York.
Friedman, M., Savage, L.J., 1948. The utility analysis of choices involving risk.
Journal of Political Economy 56 (4), 279304.
Friedman, M., Savage, L.J., 1952. The expected-utility hypothesis and the
measurability of utility. Journal of Political Economy 60 (6), 463474.
Gilad, B., Kaish, S., 1986. Handbook of Behavioral Economics. JAI Press,
Greenwich, CT.
Gilovich, T., Grifn, D.W., Kahneman, D., 2002. Heuristics and Biases: The
Psychology of Intuitive Judgement. Cambridge University Press, Cambridge, UK.
Grether, D., Plott, C.R., 1979. Economic theory of choice and the preference reversal
phenomenon. American Economic Review 69, 623638.
Guala, F., 2006. Has game theory been refuted? The Journal of Philosophy 103 (5),
Güth, W., Schmittberger, R., Schwarz e, B., 1982. An experimental analysis of ulti-
matum bargaining. Journal of Economi c Behavior & Organization 3 (4), 367388.
Heap, S.H., Varoufakis, Y., 2004. Game Theory: A Critical Text, second ed., rev. ed.
Routledge, London.
Heukelom, F., 2009. Kahneman and Tversky and the Making of Behavioral
Economics. Ph.D. thesis. University of Amsterdam.
448 Behavioral Economics, History of
International Encyclopedia of the Social & Behavioral Sciences, Second Edition, 2015, 443–449
Author's personal copy
Heukelom, F., 2010. Measurement and decision making at the University of Michigan
in the 1950s and 1960s. Journal of the History of the Behavioral Sciences 46 (2),
Heukelom, F., 2011. Building and dening behavioral economics. In: Biddle, J.E.,
Emmett, R.B. (Eds.), Research in the History of Economic Thought and Meth-
odology, vol. 29. Emerald Group Publishing Limited, pp. 129.
Heukelom, F., 2012. A sense of mission: the Alfred P. Sloan and Russell Sage
foundationsbehavioral economics program, 19841992. Science in Context 25,
Heukelom, F., 2014. Behavioral Economics: A History. Cambridge University Press,
Hosseini, H., 2003. The arrival of behavioral economics: from Michigan, or the
Carnegie School in the 1950s and the early 1960s? Journal of Socio-Economics
32 (4), 391409.
Kahneman, D., 2003. Biographical.
Kahneman, D., 2013. Thinking, Fast and Slow, rst pbk. ed. Farrar, Straus and
Giroux, New York.
Kahneman, D., Knetsch, J.L., Thaler, R.H., 1986. Fairness and the assumptions of
economics. The Journal of Business 59 (4), S285S300.
Kahneman, D., Slovic, P., Tversky, A., 1982. Judgment under Uncertainty: Heuristics
and Biases. Cambridge University Press, Cambridge.
Kahneman, D., Tversky, A., 1979. Prospect theory: an analysis of decision under risk.
Econometrica 47 (2), 263292.
Kahneman, D., Tversky, A., 2000. Choices, Values, and Frames. Russell Sage
Foundation, New York.
Katona, G., Morgan, J.N., 1980. Essays on Behavioral Economics. Survey Research
Center, Institute for Social Research, University of Michigan, Ann Arbor, MI.
Ledyard, J., 1995. Public goods: a survey of experimental research. In: Kagel, J.H.,
Roth, A.E. (Eds.), Handbook of Experimental Economics. Princeton University
Press, pp. 111194.
Laibson, D., 1997. Golden eggs and hyperbolic discounting. The Quarterly Journal of
Economics 112 (2), 443478.
Lichtenstein, S., Slovic, P., 1971. Reversals of preferences between bids and choices
in gambling decisions. Journal of Experimental Psychology 89, 4655.
Lichtenstein, S., Slovic, P., 1973. Response-induced reversals of preference in
gambling extended replication in Las-Vegas. Journal of Experimental
Psychology 101, 1620.
Lichtenstein, S., Slovic, P., 2006. The Construction of Preference. Cambridge
University Press, Cambrid ge.
List, J.A., 2007. On the interpretation of giving in dictator games. Journal of Political
Economy 115 (3), 482493.
Lindman, H.R., 1971. Inconsistent preferences among gambles. Journal of Experi-
mental Psychology 89 (2), 390397.
Markowitz, H., 1952. The utility of wealth. Journal of Political Economy 60 (2),
Mosteller, F., Nogee, P., 1951. An experimental measur ement of utility. Journal of
Political Economy 59 (5), 371404.
Mullainathan, S., Thaler, R.H., 2001. Behavioral economics. In: Smelser, N.J.,
Baltes, P.B. (Eds.), International Encyclopedia of the Social and Behavioral
Sciences. Elsevier, Amsterdam, pp. 10941100.
Phelps, E.S., Pollak, R.A., 1968. On second-best national saving and game-
equilibrium growth. The Review of Economic Studies 35 (2), 185199.
Phillips, L.D., von Winterfeldt, D., 2007. Reections on the contributions of Ward
Edwards to decision analysis and behavioral research . In: Edwards, W. (Ed.),
Advances in Decision Analysis: From Foundations to Applications. Cambridge
University Press, pp. 7180 (Chapter 5).
Poundstone, W., 2010. Priceless: The Myth of Fair Value (and How to Take
Advantage of It), rst ed. Hill and Wang, Ne w York.
Rabin, M., 1993. Incorporating fair ness into game theory and economics. The
American Economic Review 83 (5), 1281 1302.
Rabin, M., 2002. A perspective on psychology and economics. European Economic
Review 46 (45), 657685.
Ramsey, F.P., 1931. Truth and probability. In: Braithwaite, R.B. (Ed.), The Founda-
tions of Mathematics and Other Logical Essays. K. Paul, Trench, Trubner & Co.,
Ltd, pp. 156198 (Chapter 7).
Ross, D., 2014. Philosophy of Economics. Palgrave Macmillan, New York.
Rubinstein, A., 20 03. Economics and psychology? The case of hyperbolic
discounting. International Economic Review 44 (4), 12071216.
Samuelson, P.A., 1937. A note on measurement of utility. The Review of Economic
Studies 4 (2), 155161.
Samuelson, P.A., 1954. The pure theory of public expenditure. The Review of
Economics and Statistics 36 (4), 387389.
Savage, L.J., 1954. The Foundations of Statistics. Wiley, New York.
Sent, E.-M., 2004. Behavioral economics: how psychology made its (limited) way
back into economics. History of Political Economy 36 (4), 735760.
Simon, H.A., 1996. The Sciences of the Articial, third ed. MIT Press, Cambridge, MA.
Smith, A., 2002. The Theory of Moral Sentiments. Cambridge University Press,
Cambridge, UK.
Sugden, R., 1984. Reciprocity: the supply of public goods through voluntary
contributions. The Economic Journal 94 (376), 772787.
Thaler, R., 1980. Toward a positive theory of consumer choice. Journal of Economic
Behavior & Organization 1 (1), 3960.
Thaler, R., 1981. Some empirical evidence on dynamic inconsistency. Economics
Letters 8 (3), 201207.
Thaler, R.H., 1992. The Winners Curse: Paradoxes and Anomalies of Economic Life.
Princeton University Press, Princeton, NJ.
Tversky, A., Kahneman, D., 1971. Belief in the law of small numbers. Psychological
Bulletin 76 (2), 105110.
Tversky, A., Kahneman, D., 1974. Judgement under uncertainty: heuristics and
biases. Science 185, 11241131.
Tversky, A., Kahneman, D., 1981. The framing of decision and the psychology of
choice. Science 211, 453458.
Tversky, A., Kahneman, D., 1986. Rational choice and the framing of decisions. The
Journal of Business 59 (4), S251S278.
Tversky, A., Kahneman, D., 1992. Advances in prospect theory: cumulative repre-
sentation of utility. Journal of Risk and Uncertainty 5, 297323.
von Neumann, J., Morgenstern, O., 2004. Theory of Games and Economic Behavior,
sixtieth anniversary ed. Princeton University Press, Princeton, NJ.
Behavioral Economics, History of 449
International Encyclopedia of the Social & Behavioral Sciences, Second Edition, 2015, 443–449
Author's personal copy
... Behavioral economics, having come about in the latter half of the twentieth century, is currently a hub of reform for the field of economics. Its history has been documented more fully in other places (Sent 2004;Heukelom 2012;Nagatsu 2015), but it is important to note that it has had a history of defiance and marginality that, after a series of successes, flipped the discipline into centrality among many groups, including governments, academies, and various other organizations, such as for-profit companies. ...
... I say that behavioral economics has a defiant tinge to it because it started as an alternative to traditional neoclassical economics and has fought mainstream economics ever since. Nagatsu (2015) observes that what Camerer and Loewenstein (2004, 7) summarized as the process of doing behavioral economics is in fact also a neat road map of its history: ...
... The result was a wildly successful discipline, one that, marginalized and slow growing for a while, is now center stage in many discussions of human behavior. One reason for the success of the discipline is likely its adoption of standard economic modeling techniques (Nagatsu 2015). Angner (2014) points out that for this same reason, when examining the epistemology of behavioral economics, we are faced with an apparent paradox: behavioral economics simultaneously rejects and relies on basic assumptions of neoclassical economic theory. ...
... Given the recent discussion of re-introducing psychological elements in economics mainly in the context of behavioral economics, other papers focus on the history of behavioral economics since WWII. In general, most of the research concentrates to the period that followed the marginalist revolution and only mentions briefly the historical developments before that period (see for instance, Angner and Loewenstein, 2012;Nagatsu, 2015;Earl, 2016). Thus, there is a considerable gap which lies on the earlier ideas on the role of psychology in economics. ...
... Condillac, as well as Galliani and Turgot, may be the first writers who explicitly connect value and utility. 5 David Hartley was another writer who extended the principles of association as those had been formulated by Hobbes, Locke, etc. modern behavioural economics, particularly models of social influence" (Baddeley, 2013, p. 5. See also Nagatsu, 2015). ...
Full-text available
Psychological ideas had always played a role on the formation of economic thought as can be seen in the works of many influential pre-classical and classical authors. Up to the beginning of the 20th century, there was almost no methodological objection regarding the incorporation of ideas from psychology into economic theories. After this period, a fundamental shift in mainstream economics took place which is also known as the Paretian turn. This conceptual change, initiated mainly by Vilfredo Pareto and completed with the emergence of the theories of choice in the first decades of the 20th century, attempted to expel all psychological notions from economic theory. However, in the last three decades, the increasing appeal of subjective well-being research and especially of the new behavioral economics, re-brought the topic onto the surface. In order to better comprehend and to contribute to the recent discussion concerning the relationship between the two disciplines, the study of relevant views found in history of economic thought is necessary. The paper starts with a brief sketch of the history of the relationship between economics and psychology, focusing also to the recent literature which points to a reconsideration of this relationship. After an examination of psychological ideas found in influential pre-marginalist writers, the paper discusses the arguments supporting the case for the interaction between the two fields. It also suggests that the work of Richard Jennings can be seen as the peak of the early interaction between economics and psychology. Finally, it considers the relevance of these arguments for the current debate concerning the relationship between economics and psychology.
... Contemporary Behavioral Economics and Psychology are differentiated areas of knowledge, although they have linkages. Eric Wanner, director of behavioral economics programs at the Sloan and Russell Sage foundations, argues that the success of behavioral economics is due, in part, to adapting psychological findings, without this having meant giving up the form in which economists construct models [1]. ...
Full-text available
Homo Economicus behaves rationally, maximizing his own utility over that of the group. The relationship with non-prosocial behavior seems clear. This behavior, typical of people with high psychoticism, could affect their decision-making. Therefore, not only the situation will be critical when making a decision, but also stable variables related to personality. In the context of the Common Goods Game, a web platform for implementing behavioral games was developed. The system allows users to play collaborative games such as the Common Goods Game. 97 students participated in that game and contributed to a common fund. They had 25 units, corresponding to 25 tenths of one subject final grade score, which can contribute to the common fund to the extent that they wish, knowing that the total amount of the common fund will be doubled and will be distributed equally among all the participants. The results show that the subjects with the lowest levels of consciousness and agreeableness traits adopt the antisocial strategy and are the ones that obtain the most benefits. Although the limitations of the study the results suggest that both types of variables, situational and dispositional, should be taken into account when studying decision-making in behavioral economics.
Full-text available
Neoclassical economics is the mainstream economic paradigm of the present era and has certain assumptions such as rationality, perfect knowledge and unique equilibrium. In this regard, homo economicus, namely rational economic man is the main agent of mainstream economics. However, this main agent has aspects that are inconsistent with reality. In other words, decision units are likely to be irrational in the real word because individuals are emotional and social beings. Considering that this conception of rationality contradicts with the instability of economies and crises that have happened, it seems that the dominant economic view cannot exactly explain current events. This chapter questions the concept of homo economicus, the compatibility of homo economicus with homo sapiens and attempts to reveal the shortcomings of the dominant view. It substantially tries to explore why behavioral economics is necessary and how behavioral economics can make up for the shortcomings of the mainstream economic paradigm by the help of its branches; experimental economics and neuroeconomics.
Technical Report
Full-text available
The goal of this essay is to reexamine the nature and relationship between bounded rationality and AI in the context of recent developments in the application of AI to two-player zero sum games with perfect information such as Go. This is undertaken by examining the evolution of AI programs for playing Go. Given that bounded rationality is inextricably linked to the nature of the problem to be solved, the complexity of Go is examined using cellular automata (CA).
Full-text available
During the second half of the twentieth century, economics exported its logic - utility maximization - to the analysis of several human activities or realities: a tendency that has been called "economic imperialism". This book explores the concept termed by John Davis as "reverse imperialism", whereby economics has been seen in recent years to have taken in elements from other disciplines. Economics and Other Disciplines sheds light on the current state and possible future development of economics by focusing on it from a philosophical perspective, broadening the concept of rationality in economic theory. The beliefs that prevail in the world today make up a physicalist worldview. This book argues that this pervasive view is harmful for economics as a social science. Do new economic currents like behavioral economics, evolutionary economics, neuroeconomics, institutional economics, happiness economics, the capability approach and civil economy, escape this widespread mentality? What would be an adequate underlying economic ethos? Do these approaches fit into this ethos? Ricardo F. Crespo appraises the contributions from a classical philosophy angle, emphasizing their implications regarding practical reason. This volume is of great importance to those who are interested in political economy, economic theory and philosophy, as well as philosophy of social science.
This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions. The theories surveyed assume rational behavior: individuals have transitive preferences ("… if A is preferred to B, and B is preferred to C, then A is preferred to C."), choosing from among alternatives in order to "… maximize utility or expected utility." 209-item bibliography. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Many decisions are based on beliefs concerning the likelihood of uncertain events such as the outcome of an election, the guilt of a defendant, or the future value of the dollar. Occasionally, beliefs concerning uncertain events are expressed in numerical form as odds or subjective probabilities. In general, the heuristics are quite useful, but sometimes they lead to severe and systematic errors. The subjective assessment of probability resembles the subjective assessment of physical quantities such as distance or size. These judgments are all based on data of limited validity, which are processed according to heuristic rules. However, the reliance on this rule leads to systematic errors in the estimation of distance. This chapter describes three heuristics that are employed in making judgments under uncertainty. The first is representativeness, which is usually employed when people are asked to judge the probability that an object or event belongs to a class or event. The second is the availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development, and the third is adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.