Behavioral economics and its related area of study, behavioral finance, use social, cognitive and emotional factors in understanding the economic decisions of individuals and institutions performing economic functions, including consumers, borrowers and investors, and their effects on market prices, returns and the resource allocation. The fields are primarily concerned with the bounds of rationality of economic agents. Behavioral models typically integrate insights from psychology with neo-classical economic theory. In so doing they implicate a range of concepts, methods, and fields.[1]
Behavioral analysts are not only concerned with the effects of market decisions but also with public choice, which describes another source of economic decisions with related biases towards promoting self-interest.
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During the classical period, microeconomics was closely linked to psychology. For example, Adam Smith wrote The Theory of Moral Sentiments, which proposed psychological explanations of individual behavior, including concerns about fairness and justice,[2] and Jeremy Bentham wrote extensively on the psychological underpinnings of utility. However, during the development of neo-classical economics economists sought to reshape the discipline as a natural science, deducing economic behavior from assumptions about the nature of economic agents. They developed the concept of homo economicus, whose psychology was fundamentally rational. This led to unintended and unforeseen errors.
However, many important neo-classical economists employed more sophisticated psychological explanations, including Francis Edgeworth, Vilfredo Pareto and Irving Fisher. Economic psychology emerged in the 20th century in the works of Gabriel Tarde,[3] George Katona[4] and Laszlo Garai.[5] Expected utility and discounted utility models began to gain acceptance, generating testable hypotheses about decision making given uncertainty and intertemporal consumption respectively. Observed and repeatable anomalies eventually challenged those hypotheses, and further steps were taken by the Nobel prizewinner Maurice Allais, for example in setting out the Allais paradox, a decision problem he first presented in 1953 which contradicts the expected utility hypothesis.
In the 1960s cognitive psychology began to shed more light on the brain as an information processing device (in contrast to behaviorist models). Psychologists in this field, such as Ward Edwards,[6] Amos Tversky and Daniel Kahneman began to compare their cognitive models of decision-making under risk and uncertainty to economic models of rational behavior. In mathematical psychology, there is a longstanding interest in the transitivity of preference and what kind of measurement scale utility constitutes (Luce, 2000).[7]
In 1979, Kahneman and Tversky wrote Prospect theory: An Analysis of Decision Under Risk, an important paper that used cognitive psychology to explain various divergences of economic decision making from neo-classical theory.[8] Prospect theory is an example of generalized expected utility theory. Although not a conventional part of behavioral economics, generalized expected utility theory is similarly motivated by concerns about the descriptive inaccuracy of expected utility theory.
In 1968 Nobel Laureate Gary Becker published Crime and Punishment: An Economic Approach, a seminal work that factored psychological elements into economic decision making. Becker, however, maintained strict consistency of preferences. Nobelist Herbert Simon developed the theory of Bounded Rationality to explain how people irrationally seek satisfaction, instead of maximizing utility, as conventional economics presumed. Maurice Allais produced "Allais Paradox", a crucial challenge to expected utility.
Psychological traits such as overconfidence, projection bias, and the effects of limited attention are now part of the theory. Other developments include a conference at the University of Chicago,[9] a special behavioral economics edition of the Quarterly Journal of Economics ('In Memory of Amos Tversky') and Kahneman's 2002 Nobel for having "integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty".[10]
Behavioral economics has also been applied to intertemporal choice. Intertemporal choice behavior is largely inconsistent, as exemplified by George Ainslie's hyperbolic discounting (1975) which is one of the prominently studied observations, further developed by David Laibson, Ted O'Donoghue, and Matthew Rabin. Hyperbolic discounting describes the tendency to discount outcomes in near future more than for outcomes in the far future. This pattern of discounting is dynamically inconsistent (or time-inconsistent), and therefore inconsistent with basic models of rational choice, since the rate of discount between time t and t+1 will be low at time t-1, when t is the near future, but high at time t when t is the present and time t+1 the near future.
The pattern can actually be explained through models of subadditive discounting which distinguishes the delay and interval of discounting: people are less patient (per-time-unit) over shorter intervals regardless of when they occur. Much of the recent work on intertemporal choice indicates that discounting is a constructed preference. Discounting is influenced greatly by expectations, framing, focus, thought listings, mood, sign, glucose levels, and the scales used to describe what is discounted. Some prominent researchers question whether discounting, the major parameter of intertemporal choice, actually describes what people do when they make choices with future consequences. Considering the variability of discount rates, this may be the case.
Other branches of behavioral economics enrich the model of the utility function without implying inconsistency in preferences. Ernst Fehr, Armin Falk, and Matthew Rabin studied "fairness", "inequity aversion", and "reciprocal altruism", weakening the neoclassical assumption of "perfect selfishness." This work is particularly applicable to wage setting. Work on "intrinsic motivation" by Gneezy and Rustichini and on "identity" by Akerlof and Kranton assumes agents derive utility from adopting personal and social norms in addition to conditional expected utility.
"Conditional expected utility" is a form of reasoning where the individual has an illusion of control, and calculates the probabilities of external events and hence utility as a function of their own action, even when they have no causal ability to affect those external events.[11][12]
Behavioral economics caught on among the general public, with the success of books like Dan Ariely's Predictably Irrational. Practitioners of the discipline have studied quasi-public policy topics such as broadband mapping.[13][14]
Behavioral economics and finance theories developed almost exclusively from experimental observations and survey responses, although in more recent times real world data have taken a more prominent position. Functional magnetic resonance imaging (fMRI) allows determination of which brain areas are active during economic decision making. Experiments simulating markets such as stock trading and auctions can isolate the effect of a particular bias upon behavior. Such experiments can help narrow the range of plausible explanations. Good experiments are incentive-compatible, normally involving binding transactions and real money.
Note that behavioral economics is distinct from experimental economics, which uses experimental methods to study economic questions. Not all economics experiments are psychological. While many experimental economics studies probe psychological aspects of decision making, other experiments explore institutional features or serve as "beta testing" for new market mechanisms. Not all behavioral economics uses experiments, either; behavioral economists rely heavily on theory and on observational studies "in the field."
Three themes predominate in behavioral finance and economics:[15]
Barberis, Shleifer, and Vishny[16] and Daniel, Hirshleifer, and Subrahmanyam (1998)[17] built models based on extrapolation (seeing patterns in random sequences) and overconfidence to explain security market under- and overreactions, though their source continues to be debated. These models assume that errors or biases are positively correlated across agents so that they do not cancel out in aggregate. This would be the case if a large fraction of agents look at the same signal (such as the advice of an analyst) or have a common bias.
More generally, cognitive biases may also have strong anomalous effects in the aggregate if there is social contagion of ideas and emotions (causing collective euphoria or fear) leading to phenomena such as herding and groupthink. Behavioral finance and economics rests as much on social psychology within large groups as on individual psychology. In some behavioral models, a small deviant group can have substantial market-wide effects (e.g. Fehr and Schmidt, 1999).
Models in behavioral economics typically address a particular market anomaly and modify standard neo-classical models by describing decision makers as using heuristics and subject to framing effects. In general, economics continues to sit within the neoclassical framework, though the standard assumption of rational behavior is often challenged.
Critics of behavioral economics typically stress the rationality of economic agents.[18] They contend that experimentally observed behavior has limited application to market situations, as learning opportunities and competition ensure at least a close approximation of rational behavior.
Others note that cognitive theories, such as prospect theory, are models of decision making, not generalized economic behavior, and are only applicable to the sort of once-off decision problems presented to experiment participants or survey respondents.
Traditional economists are also skeptical of the experimental and survey-based techniques which behavioral economics uses extensively. Economists typically stress revealed preferences over stated preferences (from surveys) in the determination of economic value. Experiments and surveys are at risk of systemic biases, strategic behavior and lack of incentive compatibility.
Rabin (1998)[19] dismisses these criticisms, claiming that consistent results are typically obtained in multiple situations and geographies and can produce good theoretical insight. Behavioral economists have also responded to these criticisms by focusing on field studies rather than lab experiments. Some economists see a fundamental schism between experimental economics and behavioral economics, but prominent behavioral and experimental economists tend to share techniques and approaches in answering common questions. For example, behavioral economists are actively investigating neuroeconomics, which is entirely experimental and cannot be verified in the field.
Other proponents of behavioral economics note that neoclassical models often fail to predict outcomes in real world contexts. Behavioral insights can influence neoclassical models. Behavioral economists note that these revised models not only reach the same correct predictions as the traditional models, but also correctly predict some outcomes where the traditional models failed.
The central issue in behavioral finance is explaining why market participants make systematic errors. Such errors affect prices and returns, creating market inefficiencies. It also investigates how other participants arbitrage such market inefficiencies.
Behavioral finance highlights inefficiencies such as under- or over-reactions to information as causes of market trends (and in extreme cases of bubbles and crashes). Such reactions have been attributed to limited investor attention, overconfidence, overoptimism, mimicry (herding instinct) and noise trading. Technical analysts consider behavioral economics' academic cousin, behavioral finance, to be the theoretical basis for technical analysis.[20]
Other key observations include the asymmetry between decisions to acquire or keep resources, known as the "bird in the bush" paradox, and loss aversion, the unwillingness to let go of a valued possession. Loss aversion appears to manifest itself in investor behavior as a reluctance to sell shares or other equity, if doing so would result in a nominal loss.[21] It may also help explain why housing prices rarely/slowly decline to market clearing levels during periods of low demand.
Benartzi and Thaler (1995), applying a version of prospect theory, claim to have solved the equity premium puzzle, something conventional finance models have been unable to do so far.[22] Experimental finance applies the experimental method, e.g. creating an artificial market by some kind of simulation software to study people's decision-making process and behavior in financial markets.
Some financial models used in money management and asset valuation incorporate behavioral finance parameters, for example:
Critics such as Eugene Fama typically support the efficient-market hypothesis. They contend that behavioral finance is more a collection of anomalies than a true branch of finance and that these anomalies are either quickly priced out of the market or explained by appealing to market microstructure arguments. However, individual cognitive biases are distinct from social biases; the former can be averaged out by the market, while the other can create positive feedback loops that drive the market further and further from a "fair price" equilibrium. Similarly, for an anomaly to violate market efficiency, an investor must be able to trade against it and earn abnormal profits; this is not the case for many anomalies.[23]
A specific example of this criticism appears in some explanations of the equity premium puzzle. It is argued that the cause is entry barriers (both practical and psychological) and that returns between stocks and bonds should equalize as electronic resources open up the stock market to more traders.[24] In reply, others contend that most personal investment funds are managed through superannuation funds, minimizing the effect of these putative entry barriers. In addition, professional investors and fund managers seem to hold more bonds than one would expect given return differentials.
Quantitative behavioral finance uses mathematical and statistical methodology to understand behavioral biases. Leading contributors include Gunduz Caginalp (Editor of the Journal of Behavioral Finance from 2001–2004) and collaborators including 2002 Nobelist Vernon Smith, David Porter, Don Balenovich,[25] Vladimira Ilieva and Ahmet Duran[26] and Ray Sturm.[27]
The research can be grouped into the following areas:
Behavioral game theory is a subject that analyzes interactive strategic decisions and behavior using the methods of game theory,[28] experimental economics, and experimental psychology. Experiments include testing deviations from typical simplifications of economic theory such as the independence axiom[29] and neglect of altruism,[30] fairness,[31] and framing effects.[32] On the positive side, the method has been applied to interactive learning[33] and social preferences.[34][35] As a research program, the subject is a development of the last three decades.[36]
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