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Title
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Behavioral Economics
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Author
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Hochman, Guy
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Ariely, Dan
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Research Area
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Cognition and Emotions
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Topic
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Decision Making
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Abstract
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Standard economic models portray decision makers as perfectly rational agents who act selfishly to maximize their total earnings. In contrast, ample evidence in behavioral research suggests that people systematically deviate from the extreme rational assumption of such economic models. Behavioral economics is aimed at identifying the forces which shape the economic decisions that people make, in order to provide important insights of the human nature. This type of research often deals with questions such as how the presentation of information effect decision making, how different types and valances effect behavior, and what are the social, emotional, and situational factors that underlie economic decision making. This article describes foundational research in behavioral decision making and economics that lead to the emergence of behavioral economics; outline cutting‐edge research on applied behavioral economics, debiasing techniques, and neuroeconomics; and discusses key issues for future research, such as the use of field experiments and tailor‐made methodologies, and focusing on a more comprehensive approach. Our hope is that as behavioral economics advances it will examine not only the nature of the decisions people make but also their underlying cognitive processes.
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Choice Architecture (Psychology), Adrian R. Camilleri and Rick P. Larrick
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Identifier
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extracted text
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Behavioral Economics
GUY HOCHMAN and DAN ARIELY
Abstract
Standard economic models portray decision makers as perfectly rational agents
who act selfishly to maximize their total earnings. In contrast, ample evidence in
behavioral research suggests that people systematically deviate from the extreme
rational assumption of such economic models. Behavioral economics is aimed at
identifying the forces which shape the economic decisions that people make, in
order to provide important insights of the human nature. This type of research often
deals with questions such as how the presentation of information effect decision
making, how different types and valances effect behavior, and what are the social,
emotional, and situational factors that underlie economic decision making. This
article describes foundational research in behavioral decision making and economics
that lead to the emergence of behavioral economics; outline cutting-edge research
on applied behavioral economics, debiasing techniques, and neuroeconomics; and
discusses key issues for future research, such as the use of field experiments and
tailor-made methodologies, and focusing on a more comprehensive approach. Our
hope is that as behavioral economics advances it will examine not only the nature
of the decisions people make but also their underlying cognitive processes.
INTRODUCTION
Traditional economic models portray individuals as having perfect memory,
limitless computational abilities, and no emotions. As such, individuals are
assumed to have the ability to maximize each and every one of their decisions. Behavioral economics, by contrast, does not hold such an assumption.
Instead, behavioral economics empirically examines the psychological factors that influence human behavior, especially economic behavior, and uses
this knowledge for building a better understanding of human nature. In this
essay we summarize the lines of research which laid the groundwork for the
emergence of behavioral economics, identify its central lines of research and
going forward, point to key questions that remain unanswered, and conclude
with a discussion of major application of the field.
An upsurge in well-documented suboptimal and irrational behaviors, as
well as marked deviations from standard economic models served as the
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.
1
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
spark that lit the flames of behavioral economics. Insights from psychology,
sociology, economics, decision making, as well as other social and cognitive sciences, had led to the realization that people are not as rational and
cognitively competent as suggested by the standard economic models. This
realization has given birth to behavioral economics, which given its broad
empirical grounds, is more a school of thought with roots in psychology, economics, and decision research, than a distinct subfield of economics.
At the core of behavioral economics research is the realization that individuals are not perfectly rational, and that a better understanding of the cognitive, emotional, and social underpinnings of behavior, especially of economic
decision making, is crucial for the understanding of human nature. Most
research in behavioral economics is concerned with fundamental questions
such as the nature of the choices that people make, how preferences are being
formed, what effect incentives bare, and how people manage their assets,
debts, and saving accounts. These investigations often generate theoretical
and practical insights that are aimed to build a better understanding of the
human nature, better predict behavior, and suggest tailor-made policies that
facilitate more optimal decision making.
FOUNDATIONAL RESEARCH
CLASSIC AND NEOCLASSICAL ECONOMICS
The basic principles of behavioral economics are deeply rooted in classical
economics. Indeed, many of the forefathers of economics acknowledged the
important role that psychological principles play in choice behavior. Prime
examples are the suggestions that utility formations are subjective, impacted
by beliefs and emotions, and that social considerations are highly effect economic decisions. Notwithstanding, partly because at the time psychology
was not yet a well-established science, and partly due to economists’ desire
to become closer to the natural sciences, a departure of standard economics
from psychology developed at the turn of the twentieth century into the era
of the neoclassical economics.
Throughout the first half of the twentieth century, psychology had started
to gradually disappear from economic theories, and in its place came mathematical models that focused not on the way people make economic decision
but rather on how optimal agents should operate in an economic environment. In this economic point-of-view, people are perfectly rational agents,
who hold well-defined preferences over all outcomes, and act to maximize
their utilities by choosing the best alternative in any given moment. In about
the 1950s, important developments and advancements in psychology and
decision-making research started to bring back the focus of psychological
Behavioral Economics
3
factors to economic models and initiated the rise of behavioral economics.
These developments are outlined in the next subsections.
BOUNDED RATIONALITY
The cognitive revolution during the 1950s and 1960s had freed psychology
from the almost exclusive dominance of the behaviorist approach, and made
room for an approach that examined not only behavior but also cognitive
processes such as perception, information-processing, and thinking. Among
other important developments, the cognitive revolution also led to the emergence of behavioral decision research, a branch in cognitive psychology that
contributed most directly to the development of behavioral economics.
One important milestone in the emergence of behavioral economics that
resulted directly from the cognitive revolution is Simon’s (1957) notion on
bounded rationality. According to Simon, individuals cannot be fully rational
as they work with limited information under the constraints of their cognitive
capacity and processing ability. In order to facilitate these constraints, individuals adopt simple cognitive shortcuts (rules of thumb) that use partial
information and limited cognitive processing to evaluate the environment
and make judgments and decisions effortfully and quickly. According to the
bounded rationality account, individuals are not completely irrational, but
because we are forced to make decisions anyway, we do the best with our
bounded abilities to process and evaluate our surroundings and make satisfactory rather than optimal decisions.
A different form of bounded rationality came from the revolutionary
heuristics and biases approach, put forward by the psychologists Tversky
and Kahneman (1974). Much like Simon’s approach, heuristics and biases
does not assume that people aim to be irrational in their judgments and
decisions. Instead, under this approach, individuals tend to rely on a small
set of simplified cognitive strategies (heuristics), rather than on “cold”
statistical and mathematical calculations, which in turn leading to systematic departures from rational thinking. The novelty of the heuristics and
biases approach was not only in challenging the descriptive adequacy of
the economic models but also in that that it offered a more detailed way to
understand the ways in which decisions deviate from the normative (and
rational) solution. Thus, this approach revolutionized not only the field of
psychology but it also had a large effect on theory and practice across a wide
range of disciplines such as law, economics, and medicine.
Originally, the heuristics and biases approach included three general
heuristics that underlie many of the judgments people make: the availability heuristic, the representativeness heuristic, and the anchoring and
adjustment heuristic. These heuristics represent simplified rules that use
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
intuitive judgments and limited information (rather than complex and
exhaustive calculations) to make evaluations and provide estimations for
questions such as what is the frequency of fatal car accidents (availability
heuristic), what is the profession or political view of someone you have
just met (representativeness heuristic), or what is the distance between the
Statue of Liberty and the Rockefeller Center (anchoring and adjustment).
The merits of these heuristics for making good approximations in many
real-life situations notwithstanding, they often lead to systematic biases and
erroneous judgments as they are based on accessible and easily retrieved
information that is often not ideal to resolve the decision at hand. Soon after,
however, many additional heuristics (e.g., the affect heuristics; Gilovich,
Griffin, & Kahneman, 2002), as well as underlying biases, were found.
Still, despite the scientific (as well as intuitive) appeal of these bounded
rationality approaches, neoclassical economists mostly ignored these ideas
and findings. For most economists, these findings represented behavioral
quirks, mere reflections of random human errors that only apply to small
scale and unimportant decisions. However, during the early years of the
1970s, Richard Thaler, who was a young economist at the time, had become
increasingly intrigued by these accumulated instances of behavioral anomalies that challenged the basis of neoclassical theory. After coming across the
work of Tversky and Kahneman in 1976, he started to take these anomalies
seriously and documented many of these anomalies in a way closer to the
way economists were thinking about these behaviors (these anomalies were
later published as a series of special columns in the Journal of Economic
Perspective during the late 1980s and 1990s and collected in Thaler, 1994).
The cooperation that started between the three had planted the seeds for the
emergence of behavioral economics as an independent field.
SUBJECTIVE VALUES
Another important advancement in behavioral decision making that is considered one of the cornerstones of behavioral economics is the prospect theory (Kahneman & Tversky, 1979), a model to describe decision making under
conditions of risk. Prospect theory describes how people evaluate potential
positive and negative outcomes (as well as their probabilities), and how these
evaluations are used to choose among alternatives. The theory was introduced as an alternative for expected utility theory.
For several decades, expected utility theory was one of the most important
and influential economic models for decision making under risk. Expected
utility was first introduced by Bernoulli (1738) as a modification to the
expected value notion. In expected value, an outcome of each alternative
is equal to its payoff multiplied by its probability. However, as Bernoulli
Behavioral Economics
5
observed, the values that people attach to outcomes are influenced by several
factors such as probabilities and magnitudes. Thus, he suggested a model
that explains people’s preferences in terms of subjective (utility) rather
than objective evaluations of expected returns. Two centuries later, von
Neumann and Morgenstern (1944) modified the expected utility model and
formulized four axioms of rationality (completeness, transitivity, continuity,
and independence) that were assumed to capture the way in which people
judge the utility of outcomes and choose among available alternatives.
As with most economic models, expected utility assumes that people are
rational maximizers who aim to maximize their utility. Yet, in reality people
exhibit systematic violations of all axioms of the rational model (Allais,
1953; Ellsberg, 1961). In several well-controlled experiments, Kahneman and
Tversky (1979) provided a compelling demonstration of these violations,
and based on these findings developed prospect theory, an empirically supported alternative theory of choice. According to the prospect theory, instead
of subjective utility, people calculate subjective values of alternatives. These
subjective values represent the evaluations of outcomes as gains or losses
relative to the current state of wealth (the reference point). The subjective
value of each outcome is equal to its payoff (relative to the reference point)
times its decision weight. Subjective evaluations of outcomes are based
on a value function, while subjective probabilities (decision weights) are
based on a probability weighting function. The value function is asymmetric
and nonlinear. It is concave for gains and convex for losses and steeper
for losses than for gain. In addition, the probability weighting function is
lower than the objective probabilities for high probabilities and higher than
the objective probabilities for low probabilities. According to the prospect
theory, people are risk averse in the gain domain but risk seekers in the
loss domain. They give stronger weight to losses than to equivalent gains
(loss aversion), and the further away they go from their current state the
less sensitive they become to increases in values (diminishing sensitivity).
Combining all of these features, this model provides a more descriptively
accurate description of economic decision making.
Prospect theory is one of the most influential theories to account for a wide
range of puzzling behaviors that run counter to the predictions of the traditional economic models, and provide basic psychological mechanisms to
explain these behaviors. These notions, alongside the fact that Kahneman and
Tversky (1979) formulated and explained prospect theory in an economic
language, are probably the main reasons why this seminal work had brought
behavioral economics (and its importance) into the attention of many mainstream economists, and contributed tremendously to its emergence.
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
HYPERBOLIC TIME DISCOUNTING
The tradeoffs people make between costs and benefits that occur at different
points in time is of major interest for economics. Because people usually
prefer rewards sooner than later, options that delay rewards are perceived
as less attractive and thus people discount them. The traditional economic
model suggests that people discount future rewards by a fixed percentage for each time unit they need to wait. Thus, according to this model
discounting utility is exponential, depending only on the length of the
wait.
While the exponential model is widely common in economics, a large body
of evidence form behavioral economics demonstrates that people systematically violate this time-consistent model. People prefer smaller rewards now
over larger rewards later, and they discount future rewards at a greater rate
when the delay occurs sooner. For example, most people will prefer $200 now
over $210 tomorrow, but only few will choose $200 in 2 weeks over $210 in 2
weeks and 1 day. Thus, discounting rate decreases as the length of the delay
increases. Research shows that a simple hyperbolic time-discounting function provides the best fit to the data, and capture the declining discount rates
exhibited by people.
Hyperbolic time discounting is considered a robust and central phenomenon in behavioral economics, which accounts for several economic
behaviors that cannot be explained by standard economic models (for
a critical review, see Frederick, Loewenstein, & O’Donoghue, 2002). For
example, hyperbolic discounting explains one of the reasons why credit
card companies are able to charge such high interest rates for credit card
expenditures. Often, when credit cards are used it is because the reward
of buying something now outweighs the discounted displeasure of paying
more for it later, and because this discount rate is so high, credit companies
are able to get away with charging very high interest rates. Similarly,
hyperbolic discounting can also explain why people are willing to accept
low interest rates to saving and retirement plans. Because these saving
plans are for the far future, people are much more patient and are willing
to accept low interest rates. Hyperbolic discounting had also been used to
explain why people exhibit a lack of self-control and low willpower. As
an example, people who wish to live healthier and reduce extra weight
realize the advantages of keeping a strict diet for the long run. However,
the rewards from instant temptations in the form of a chocolate cake or a
greasy bacon cheeseburger loom larger than the discounted reward of better
health in the future. Thus, it is easier to think that tomorrow you will go on
a diet and resist any temptation than to actually turn down an immediate
one.
Behavioral Economics
7
PROSOCIAL AND MORAL BEHAVIOR
Economics traditionally portray economic decision makers as selfish and
self-interested agents who follow the principle of utility maximization.
Under this conceptualization, any form of prosocial behavior such as
fairness, cooperation, reciprocity, or charity giving is simply not existent
(or it can be explained by a selfish underlying motive). Because prosocial
behavior is neither rational nor economically beneficial, it is often ignored
or assumed away by neoclassical economics. However, abundant empirical
evidence from psychology and economics repeatedly demonstrate that
prosocial motives and considerations play an important role in economic
behavior (see e.g., Fehr & Schmidt, 1999).
Some of the most central and interesting findings about prosocial behavior show that people have a strong tendency for cooperation; however, this
tendency decreases if they learn that their cooperators are taking advantage
of them. In addition, research shows that people tend to punish noncooperators and free riders. Interestingly, punishing occurs even if the punishing
is costly and does not provide material benefits for the punishers. Cooperation and reciprocity are not the only prosocial behaviors that effect economic
behavior. Many experiments have demonstrated that individuals are highly
sensitive to fairness far beyond material gain. In contrast to standard economic models, much evidence shows that people forgo a possible incentive
if they feel that the offer is not fair. This tendency was also found among
infants and primates, thus demonstrating how prevailing and robust prosocial considerations are.
Pure altruistic behavior such as donations and charity giving is another
example of a common prosocial behavior that deviates from economic models. In economics, altruistic behavior is considered completely irrational, as
it represent a total waste of resources. In reality, however, most people prefer to give away their hard-earned money (and other resources) in order to
help others, and in fact over 90% of the household in the United States tend
to donate a substantial amount of money to charity a year. Moreover, the
forces that influence the level of giving are far from being purely rational.
For example, the identifiable victim effect demonstrates that people are more
willing to donate to one identifiable victim than to a group of people who
share a similar unfortunate faith (or, as Mother Teresa eloquently expressed,
“If I look at the mass, I will never act. If I look at one, I will”). While economic models cannot explain these ample instances of altruistic and prosocial
behavior, behavioral economics provide several insights to the psychological
and social factors which promote it (e.g., social desirability, sense of accomplishment).
8
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
On the other side of the social spectrum is anti-social or unethical behavior
(e.g., cheating, dishonesty). While unethical behavior is not explicitly
modeled in economics, the self-interested rational assumption of economics
suggests that to the extent that they cannot get caught people should engage
in unethical behavior as long as it increases their utility. Nevertheless,
variety of laboratory and field studies show that peoples’ unethicality
deviates from the predictions of the economic models. While large-scale
cheating instances such as Bernard Madoff’s Ponzi scheme exist, research
suggests that the majority of people restrict the amount of their self-serving
unethical behaviors (see e.g., Ariely, 2012), even when complete privacy is
guaranteed and the probability of being caught is very low. By restricting
the extent of cheating, people are able to resolve the conflict between
their desire to maximize their material profit and their desire to think of
themselves as honest and prosocial. Thus, behavioral economics rejects the
economic point of view and demonstrates that unethicality does not depend
solely on cold calculations of monetary payoff, but rather on a variety of
psychological, social, and contextual factors that shape ethical standards
and moral behavior.
CUTTING-EDGE RESEARCH
Behavioral economics attempts to build a framework for understanding
the rational and irrational elements of human nature. Usually, the starting
point of these attempts includes basic research that tests theoretical ideas in
controlled laboratory experiments. The findings from this basic research are
then applied in several domains to provide a better understanding of how
people actually make real-time mundane and significant decisions. Moving
beyond the laboratory, applied behavioral economics is used to explain
existing behavioral patterns in the world and to better understand the forces
that shape behavior. Throughout the years, behavioral economic principles
have been applied to many different domains and environments, such
as law, health, finance, education, consumer behavior, and organizational
science.
For example, financial decision making uses behavioral research findings
as a prism to examine the psychological factors that shape the financial
decisions that people make. Be they related to debt management, savings,
housing, health care, or other monetary decisions, financial decision-making
research examines how and why so many of the important and fundamental
decisions that people make are irrational. The typical findings suggest that
while making such financial decisions, people are usually focused only on a
small part of the overall picture. Instead of wisely allocating and spending
their resources, people are affected by situational factors, individual traits,
Behavioral Economics
9
and social motivations. They fail to appreciate important concepts such as
interest, compound interest, fungibility, and so forth, and this leads them
to spend their hard-earned money unwisely and irrationally. Thaler (1980)
uses the term mental accounting to describe the way in which people evaluate
goods, organize their monetary assets, and make financial decisions. The
idea is that people create separate, nonfungible, mental accounts for different
goals (e.g., money for food, money for clothing, money for recreation). The
different accounts are nontransferable, and thus spending money from
one account does not affect decisions on spending from other accounts. In
addition, the different account affect the utility that people assign to each
of their assets, and thus affect their consumption behavior. For example, if
someone exhausted her recreational money in a certain week but still has
some money left in her money for clothing account, she will not use it to buy
a concert ticket she wants even if she cannot find a dress she likes.
In a similar vein, behavioral economics tenets are applied in marketing and
consumer behavior research to inform our understanding of how consumers
evaluate brands and products, form and change preferences, think and feel
about their consumption goods, and how marketing strategies can be tailored
to increase efficiency.
A second cutting-edge area of research in behavioral economics is aimed
at developing and identifying debiasing techniques to improve the decisions
that people make. Early research on debiasing was mainly aimed at validating the existence of irrational behaviors, and to demonstrate the robustness
of behavioral biases. However, as the existence of the gap between economic
behavior and the economic assumption that people are rational is increasingly accepted by economists, the focus of debiasing research is changed.
Building on behavioral economics findings, which help to identify the forces
that shape our decisions and lead them astray, debiasing research pinpoints
specific policies, interventions, and choice architectures geared to move people toward more optimal and rational decisions. These debiasing techniques
could be as simple as practical suggestions that can help people better handle
their savings account to more pervasive paternalistic policies and regulations
that lead people to better manage their lives. Latest development in the field
are aimed to help people better manage their savings and debt accounts, and
to increase social and ethical behavior among individuals and societies.
A third cutting-edge area in behavioral economic is neuroeconomics. The
role of behavioral economics is to understand how people make decisions,
while the role of neuroscience is to study the neural underpinnings and brain
mechanisms of human behavior. Neuroeconomics combine economics, psychology, and brain research into a single discipline that employs methods and
insights from these three fields to develop better models of economic behavior that will account not only for how people behave but also provide some
10
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
insights of the underlying processes of this behavior. Owing to the expensive
equipment required, the advanced training needed, and the strict methodological practices, it is still not widely used. However, neuroeconomics is
becoming increasingly popular in behavioral economics in recent years.
Neuroeconomic practices in behavioral economics are usually used to
understand how people evaluate monetary gains and losses, how they react
to different types of incentives, and how subjective values or utilities are
being formed. In addition, behavioral economics is starting to depart from
the exclusive view of decision making as a cold cognitive process, and
to show increasing interest in emotional and effective processes and their
important role in economic decisions. To a large extent, neuroeconomics
serves to identify such emotional processes, and to explain some of the
behavioral deviations from the standard economic models that results
directly from emotional processing (such as fairness and other forms of
prosocial behavior). Relatedly, another recent development in behavioral
research is the dual-system approach, which considers judgment and
decision making as a process of two distinct systems: an intuitive system
that is based on rapid and automatic processes, and a deliberative system,
that is based on more controlled and reflective processes. In recent years,
the dual-system approach has been proposed as a theoretical framework
that explains some of the empirical regularities that differ from standard
economic models (e.g., intertemporal choice, risk aversion). Usually, neuroeconomics is used under this framework to examine automatic and intuitive
processes, which could not be easily quantified and tested with the more
traditional methods in behavioral science.
KEY ISSUES FOR FUTURE RESEARCH
Perhaps the most important insight in behavioral economics is that people
are not perfectly rational actors who simply maximize their expected value.
Traditionally, behavioral economics relied on well-controlled laboratory
experiments to better understand the forces that shape economic decision
making, and to demonstrate marked deviations from rational economic
models. However, laboratory settings often differ significantly from real-life
situations, and in many cases researchers have to rely on hypothetical rather
than real decisions, often creating somewhat superficial and unnatural situations, and using small rather than substantial monetary incentives. Thus,
many of the findings in behavioral economics are challenged by economists
on the ground that behavioral deviations from the economic models do not
reflect actual economic behavior that people exhibit in real life.
To account for this important criticism, studies in behavioral economics
have started to extend their scope of research methods to include larger
Behavioral Economics
11
incentives, and simulate real and important monetary decisions in the
laboratory and, most importantly, examine behavior in real-life settings (e.g.,
field experiments). Indeed, field experiments in behavioral economics have
seen a steady growth in recent years, and to a large extent the findings from
these experiments replicate those in the laboratory. Still, challenges remain
for behavioral economics in planning and conducting field experiment that
will allow the examination of the generalizability of these findings.
Another drawback often raised as a critique of behavioral economics is the
fact that behavioral economics represents a collection of ideas rather than
a unified and comprehensive theory. In a sense, it seems as behavioral economics are more focused on identifying behavioral irregularities and classifying them as new heuristics. However, in some situations these different
heuristics lead to contradicting behavioral tendencies. For example, the gambler’s fallacy (Kahneman & Tversky, 1972) is a term used to describe people’s
tendency to believe that if certain instances of some random process (e.g.,
the result of a coin toss) deviates to one direction, future deviations will
more likely happen to the opposite direction. In contrast, the hot hand effect
(Gilovich, Vallone, & Tversky, 1985) reflects the belief that deviation to one
direction increases the likelihood that future instances will happen in the
same direction.
Indeed, this criticism raises important questions about the true nature and
goal of behavioral economics. Similar to many physical mechanisms (e.g.,
even the visual system includes many components), a realistic theory of economic decision making is likely to be very complex, and a trade-off between
accuracy and parsimoniousness is probably inherent in the nature of behavioral economics. If parsimoniousness is the main goal, behavioral economists
should focus on developing simple yet powerful models. If accuracy and
application is the main goal, however, future research should focus on developing tools and interventions that will lead us to make better decisions. Thus,
a key issue for the future is to consider under which conditions behavioral
economics should be considered a pure science that aims to provide parsimonious models which account for the entire spectrum of human behavior and
under which conditions should behavioral economics be considered a more
applicable school of thought that aims to inform us of the various forces that
shape our behavior, and suggests specific ways to aid people make better
decisions.
Still, one way that behavioral economics should advance, and accuracy
could be improved without jeopardizing parsimoniousness, is by focusing,
at least to some extent, on the underlying cognitive and affective processes of
these behavioral tendencies. Focusing on the underlying processes and not
just on overt behavior would improve the descriptive and predictive power
12
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
of behavioral models, and provide a more comprehensive and unified theory of human nature. Moreover, such an understanding would facilitate the
development of more successful interventions and debiasing techniques that
will be more suited to the specific needs of the decision makers. Consider, for
example, the case of unethical behavior. While behavioral economics findings show that most people choose to lie or cheat by a little, it is not clear
yet whether people deliberately choose to cheat in order to increase their
utility while maintaining a positive self-esteem, or if they are completely
oblivious to their unethicality because of certain unconscious self-serving
perception-distorting mechanisms.
Of course, much of these drawbacks are not entirely unique for behavioral
economics. For example, neoclassical economics is also more a collection of
idea than a unified theory, and many disciplines can benefit from a more
profound understanding of the processes that underlie human behavior.
Currently, behavioral economics is more a school of thought deeply rooted
in economics, psychology, and decision research, than an independent
field in social sciences. Addressing some of these drawbacks of behavioral
economics could make it a more distinct and independent discipline that
parsimoniously explain a range of behavioral data and provide practical
tools that would aid individual to better manage their life and financial
assets.
REFERENCES
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Fehr, E., & Schmidt, K. M. (1999). A theory of fairness, competition, and cooperation.
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Gilovich, T., Griffin, D., & Kahneman, D. (2002). Heuristics and biases: The psychology
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misperception of random sequences. Cognitive Psychology, 17, 295–314.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under
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Thaler, R. (1980). Toward a positive theory of consumer choice. Journal of Economic
Behavior and Organization, 1, 39–60. doi:10.1016/0167-2681(80)90051-7
Thaler, R. H. (1994). The winner’s curse: Paradoxes and anomalies of economic life. New
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biases. Science, 185, 1124–1131.
Von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior.
Princeton, NJ: Princeton University Press.
FURTHER READING
Ariely, D. (2008). Predictably irrational: The hidden forces that shape our decisions
(Revised and expanded ed.). New York, NY: Harper Perennial.
Camerer, C., Loewenstein, G. F., & Prelec, D. (2005). Neuroeconomics: How neuroscience can inform economics. Journal of Economic Literature, 43, 9–64.
Camerer, C., Loewenstein, G. F., & Rabin, M. (2004). Advances in behavioral economics.
Princeton University Press.
Kahneman, D., & Tversky, A. (2000). Choices, values, and frames. Cambridge,
England: Cambridge University Press.
Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297–323.
GUY HOCHMAN SHORT BIOGRAPHY
Guy Hochman is a Post-doc fellow at Duke University and an Adjunct Assistant Professor of Psychology at the Interdisciplinary Center (IDC) Herzliya.
Hochman’s research interests are heuristics and biases, process models, organizational behavior, and management.
DAN ARIELY SHORT BIOGRAPHY
Dan Ariely is James B. Duke Professor of Psychology and Behavioral Economics at Duke University and the founder of The Center for Advanced
Hindsight. Ariely is the author of three New York Times best sellers Predictably irrational, The upside of irrationality, and The honest truth about dishonesty. His research interest spans a wide range of behaviors, and his unusual
and creative experiments are interesting, amusing, and informative.
Personal webpage: www.danariely.com
Curriculum vitae:
http://people.duke.edu/∼dandan/webfiles/arielycv.pdf
Center for Advanced Hindsight: http://advanced-hindsight.com/
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