Behavioral economics, along with the related sub-field behavioral finance, studies the effects of psychological, social, cognitive, and emotional factors on the economic decisions of individuals and institutions and the consequences for market prices, returns, and resource allocation, although not always that narrowly, but also more generally, of the impact of different kinds of behavior, in different environments of varying experimental values.
Behavioral economics is primarily concerned with the bounds of rationality of economic agents. Behavioral models typically integrate insights from psychology, neuroscience, and microeconomic theory; in so doing, these behavioral models cover a range of concepts, methods, and fields.
The study of behavioral economics includes how market decisions are made and the mechanisms that drive public choice. The use of the term "behavioral economics" in U.S. scholarly papers has increased in the past few years, as shown by a recent study.
In 2017, economist Richard Thaler was awarded the Nobel Memorial Prize in Economic Sciences for his contributions to behavioral economics and his pioneering work in establishing that people are predictably irrational in ways that defy economic theory.
There are three prevalent themes in behavioral finances:
- Heuristics: Humans make 95% of their decisions using mental shortcuts or rules of thumb.
- Framing: The collection of anecdotes and stereotypes that make up the mental emotional filters individuals rely on to understand and respond to events.
- Market inefficiencies: These include mis-pricings and non-rational decision making.
- 1 History
- 2 Criticism
- 3 Applied issues
- 4 Notable theorists
- 5 See also
- 6 Citations
- 7 References
- 8 External links
During the classical period of economics, 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, 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.
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, George Katona, and Laszlo Garai. 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 Prize-winner Maurice Allais, for example, in setting out the Allais paradox, a decision problem he first presented in 1953 that 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, 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.
In 1979, Kahneman and Tversky wrote Prospect Theory: An Analysis of Decision Under Risk, that used cognitive psychology to explain various divergences of economic decision making from neo-classical theory. Prospect theory has two stages: an editing stage and an evaluation stage.
In the editing stage, risky situations are simplified using various heuristics of choice. In the evaluation phase, risky alternatives are evaluated using various psychological principles that include the following:
- Reference dependence: When evaluating outcomes, the decision maker has in mind a "reference level". Outcomes are then compared to the reference point and classified as "gains" if greater than the reference point and "losses" if less than the reference point.
- Loss aversion: Losses bite more than equivalent gains. In their 1992 paper, Kahneman and Tversky found the median coefficient of loss aversion to be about 2.25, i.e., losses bite about 2.25 times more than equivalent gains.
- Non-linear probability weighting: Evidence indicates that decision makers overweight small probabilities and underweight large probabilities—this gives rise to the inverse-S shaped "probability weighting function".
- Diminishing sensitivity to gains and losses: As the size of the gains and losses relative to the reference point increase in absolute value, the marginal effect on the decision maker's utility or satisfaction falls.
Prospect theory is able to explain everything that the two main existing decision theories—expected utility theory and rank dependent utility theory—can explain. However, the converse is false. Prospect theory has been used to explain a range of phenomena that existing decision theories have great difficulty in explaining. These include backward bending labor supply curves, asymmetric price elasticities, tax evasion, co-movement of stock prices and consumption, etc.
In 1992, in the Journal of Risk and Uncertainty, Kahneman and Tversky gave their revised account of prospect theory that they called cumulative prospect theory. The new theory eliminated the editing phase in prospect theory and focused just on the evaluation phase. Its main feature was that it allowed for non-linear probability weighting in a cumulative manner, which was originally suggested in John Quiggin's rank dependent utility theory.
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, a special behavioral economics edition of the Quarterly Journal of Economics ("In Memory of Amos Tversky"), and Kahneman's 2002 Nobel Prize for having "integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty".
Behavioral economics has also been applied to intertemporal choice. Intertemporal choice is defined as making a decision and having the effects of such decision happening in a different time. Intertemporal choice behavior is largely inconsistent, as exemplified by George Ainslie's hyperbolic discounting—one of the prominently studied observations—and further developed by David Laibson, Ted O'Donoghue, and Matthew Rabin. Hyperbolic discounting describes the tendency to discount outcomes in the 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 is the near future.
The pattern can also be explained through models of sub-additive discounting that distinguish the delay and interval of discounting: people are less patient (per-time-unit) over shorter intervals regardless of when they occur.
Other areas of research
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. The work on "intrinsic motivation" by Gneezy and Rustichini and "identity" by Akerlof and Kranton assumes that agents derive utility from adopting personal and social norms in addition to conditional expected utility. According to Aggarwal, in addition to behavioral deviations from rational equilibrium, markets are also likely to suffer from lagged responses, search costs, externalities of the commons, and other frictions making it difficult to disentangle behavioral effects in market behavior.
"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 their utility as a function of their own action, even when they have no causal ability to affect those external events.
Behavioral economics caught on among the general public with the success of books such as Dan Ariely's Predictably Irrational. Practitioners of the discipline have studied quasi-public policy topics such as broadband mapping.
Applications for behavioral economics include the modeling of the consumer decision-making process for applications in artificial intelligence and machine learning. The Silicon Valley-based start-up Singularities is using the AGM postulates proposed by Alchourrón, Gärdenfors, and Makinson—the formalization of the concepts of beliefs and change for rational entities—in a symbolic logic to create a "machine learning and deduction engine that uses the latest data science and big data algorithms in order to generate the content and conditional rules (counterfactuals) that capture customer's behaviors and beliefs".
Critics of behavioral economics typically stress the rationality of economic agents. 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.
A notable concern is that despite a great deal of rhetoric, there is no real consistent behavioral theory yet. Behavioral economics scholars also have no unified theory. Until that happens, it is a collection of loosely related or unrelated observations. What is missing is a foundational behavioral theory that can be tested in many domains as a competitor to neoclassical theory.
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 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 investigating neuroeconomics, which is entirely experimental and cannot yet 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 epistemological, ontological, and methodological components of behavioral economics are increasingly debated, in particular by historians of economics and economic methodologists.
According to some researchers, when studying the mechanisms that form the basis of decision-making, especially financial decision-making, it is necessary to recognize that most decisions are made under stress because, "Stress is the nonspecific body response to any demands presented to it".
From a biological point of view, human behaviors are essentially the same during crises accompanied by stock market crashes and during bubble growth when share prices exceed historic highs. During those periods, most market participants see something new for themselves, and this inevitably induces a stress response in them with accompanying changes in their endocrine profiles and motivations. The result is quantitative and qualitative changes in behavior. However, this is only one example of where behavior affecting economics and finance can be observed and variably-contrasted using behavioral economics, and it is a mistake to think of its usefulness as only applying within such environments tested-in or -of conditions similar to stock exchanges specifically. Also, often selfish-reasoning, 'adult behaviors', and similar, can be identified within criminal-concealment(s), and legal-deficiencies and neglect of different types can be observed and discovered. Awareness of indirect consequence (or lack of), at least in potential with different experimental models and methods, can be used as well—behavioral economics' potential uses are broad, but its reliability need scrutiny. An underestimation of the role of novelty as a stressor is the primary shortcoming of current approaches for market research. So, it is necessary to account for the biologically determined diphasisms of human behavior in everyday low-stress conditions and in response to stressors.
The central issue in behavioral finance is explaining why market participants make irrational systematic errors contrary to assumption of rational market participants. Such errors affect prices and returns, creating market inefficiencies. The study of behavioral finance also investigates how other participants take advantage (arbitrage) of such errors and 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 finance to be behavioral economics' "academic cousin" and the theoretical basis for technical analysis.
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. It may also help explain why housing prices rarely/slowly decline to market clearing levels during periods of low demand.
Benartzi and Thaler, applying a version of prospect theory, claim to have solved the equity premium puzzle, something conventional finance models so far have been unable to do. Experimental finance applies the experimental method, e.g., creating an artificial market through some kind of simulation software to study people's decision-making process and behavior in financial markets.
Quantitative behavioral finance
Quantitative behavioral finance uses mathematical and statistical methodology to understand behavioral biases. In marketing research, a study shows little evidence that escalating biases impact marketing decisions. Leading contributors include Gunduz Caginalp (Editor of the Journal of Behavioral Finance from 2001–04), and collaborators include 2002 Nobel Laureate Vernon Smith, David Porter, Don Balenovich, Vladimira Ilieva and Ahmet Duran, and Ray Sturm.
Some financial models used in money management and asset valuation incorporate behavioral finance parameters. Examples:
- Thaler's model of price reactions to information, with three phases (underreaction, adjustment, and overreaction), creating a price trend.
- One characteristic of overreaction is that average returns following announcements of good news is lower than following bad news. In other words, overreaction occurs if the market reacts too strongly or for too long to news, thus requiring adjustment in the opposite direction. As a result, outperforming assets in one period are likely to underperform in the following period. This also applies to customers' irrational purchasing habits.
- The stock image coefficient.
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.
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. In response, 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.
Behavioral game theory, invented by Colin Camerer, analyzes interactive strategic decisions and behavior using the methods of game theory, experimental economics, and experimental psychology. Experiments include testing deviations from typical simplifications of economic theory such as the independence axiom and neglect of altruism, fairness, and framing effects. On the positive side, the method has been applied to interactive learning and social preferences. As a research program, the subject is a development of the last three decades.
Economic reasoning in non-human animals
A handful of comparative psychologists have attempted to demonstrate quasi-economic reasoning in non-human animals. Early attempts along these lines focus on the behavior of rats and pigeons. These studies draw on the tenets of comparative psychology, where the main goal is to discover analogs to human behavior in experimentally-tractable non-human animals. They are also methodologically similar to the work of Ferster and Skinner. Methodological similarities aside, early researchers in non-human economics deviate from behaviorism in their terminology. Although such studies are set up primarily in an operant conditioning chamber using food rewards for pecking/bar-pressing behavior, the researchers describe pecking and bar-pressing not in terms of reinforcement and stimulus-response relationships but instead in terms of work, demand, budget, and labor. Recent studies have adopted a slightly different approach, taking a more evolutionary perspective, comparing economic behavior of humans to a species of non-human primate, the capuchin monkey.
Non-human animal studies
Many early studies of non-human economic reasoning were performed on rats and pigeons in an operant conditioning chamber. These studies looked at things like peck rate (in the case of the pigeon) and bar-pressing rate (in the case of the rat) given certain conditions of reward. Early researchers claim, for example, that response pattern (pecking/bar-pressing rate) is an appropriate analogy to human labor supply. Researchers in this field advocate for the appropriateness of using animal economic behavior to understand the elementary components of human economic behavior. In a paper by Battalio, Green, and Kagel, they write,
Space considerations do not permit a detailed discussion of the reasons why economists should take seriously the investigation of economic theories using nonhuman subjects....[Studies of economic behavior in non-human animals] provide a laboratory for identifying, testing, and better understanding general laws of economic behavior. Use of this laboratory is predicated on the fact that behavior as well as structure vary continuously across species, and that principles of economic behavior would be unique among behavioral principles if they did not apply, with some variation, of course, to the behavior of nonhumans.
The typical laboratory environment to study labor supply in pigeons is set up as follows. Pigeons are first deprived of food. Since the animals become hungry, food becomes highly desired. The pigeons are then placed in an operant conditioning chamber and through orienting and exploring the environment of the chamber they discover that by pecking a small disk located on one side of the chamber, food is delivered to them. In effect, pecking behavior becomes reinforced, as it is associated with food. Before long, the pigeon pecks at the disk (or stimulus) regularly.
In this circumstance, the pigeon is said to "work" for the food by pecking. The food, then, is thought of as the currency. The value of the currency can be adjusted in several ways, including the amount of food delivered, the rate of food delivery and the type of food delivered (some foods are more desirable than others).
Economic behavior similar to that observed in humans is discovered when the hungry pigeons stop working/work less when the reward is reduced. Researchers argue that this is similar to labor supply behavior in humans. That is, like humans (who, even in need, will only work so much for a given wage), the pigeons demonstrate decreases in pecking (work) when the reward (value) is reduced.
In human economics, a typical demand curve has negative slope. This means that as the price of a certain good increases, the amount that consumers are willing and able to purchase decreases. Researchers studying the demand curves of non-human animals, such as rats, also find downward slopes.
Researchers have studied demand in rats in a manner distinct from studying labor supply in pigeons. Specifically, in an operant conditioning chamber containing rats as experimental subjects, we require them to press a bar, instead of pecking a small disk, to receive a reward. The reward can be food (reward pellets), water, or a commodity drink such as cherry cola. Unlike in previous pigeon studies, where the work analog was pecking and the monetary analog was reward, the work analog in this experiment is bar-pressing. Under these circumstances, the researchers claim that changing the number of bar presses required to obtain a commodity item is analogous to changing the price of a commodity item in human economics.
In effect, results of demand studies in non-human animals show that, as the bar-pressing requirement (cost) increases, the number of times an animal presses the bar equal to or greater than the bar-pressing requirement (payment) decreases.
An evolutionary psychology perspective states that many of the perceived limitations in rational choice can be explained as being rational in the context of maximizing biological fitness in the ancestral environment, but not necessarily in the current one. Thus, when living at subsistence level where a reduction of resources may result in death, it may have been rational to place a greater value on preventing losses than on obtaining gains. It may also explain behavioral differences between groups, such as males being less risk-averse than females since males have more variable reproductive success than females. While unsuccessful risk-seeking may limit reproductive success for both sexes, males may potentially increase their reproductive success from successful risk-seeking much more than females can.
Artificial intelligent machines
Much of the decisions are more and more made either by human beings with the assistance of artificial intelligent machines or wholly made by these machines. Tshilidzi Marwala and Evan Hurwitz in their book,  studied the utility of behavioral economics in such situations and concluded that these intelligent machines reduce the impact of behavioral economics on bounded rational decision making. In particular, they observed that these intelligent machines reduce the degree of information asymmetry in the market, improve decision making and thus making markets more rational.
- Adaptive market hypothesis
- Behavioral operations research
- Confirmation bias
- Cultural economics
- Culture change
- Economic sociology
- Emotional bias
- Fuzzy-trace theory
- Hindsight bias
- Homo reciprocans
- Important publications in behavioral economics
- List of cognitive biases
- Market sentiment
- Methodological individualism
- Nudge theory
- Observational techniques
- Regret theory
- Repugnancy costs
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