Behavioral economics

Behavioral economics

Behavioral economics and the related field, behavioral finance, study 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 the resource allocation. The fields are 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.[1]

The study of behavioral economics includes how market decisions are made and the mechanisms that drive public choice. The use of "Behavioral economics" in U.S. scholarly papers has increased in the past few years as a recent study shows.[2]

There are three prevalent themes in behavioral finances:[3]


  • Issues 1
    • Behavioral finance 1.1
      • Quantitative behavioral finance 1.1.1
    • Financial models 1.2
      • Criticisms 1.2.1
    • Behavioral game theory 1.3
    • Economic reasoning in non-human animals 1.4
      • The animal as a human analogy 1.4.1
      • Labor supply 1.4.2
      • Demand 1.4.3
      • Monkey trading behavior 1.4.4
    • Evolutionary psychology 1.5
  • History 2
    • Prospect theory 2.1
    • Intertemporal choice 2.2
    • Other areas of research 2.3
  • Criticisms 3
  • Notable theorists 4
    • Economics 4.1
    • Finance 4.2
  • See also 5
  • Notes 6
  • References 7
  • External links 8


Behavioral finance

The central issue in behavioral finance is explaining why market participants make systematic errors contrary to assumption of rational market participants. Such errors affect prices and returns, creating market inefficiencies. It also investigates how other participants take advantage (arbitrage) of 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 finance, to be behavioral economics' "academic cousin" and to be the theoretical basis for technical analysis.[4]

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.[5] 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.[6] 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.

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.[7] 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,[8] Vladimira Ilieva and Ahmet Duran,[9] and Ray Sturm.[10]

Financial models

Some financial models used in money management and asset valuation incorporate behavioral finance parameters, for example:

  • Thaler's model of price reactions to information, with three phases, underreaction-adjustment-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.[11]


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.[12]

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.[13] 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.

Behavioral game theory

Behavioral game theory analyzes interactive strategic decisions and behavior using the methods of game theory,[14] experimental economics, and experimental psychology. Experiments include testing deviations from typical simplifications of economic theory such as the independence axiom[15] and neglect of altruism,[16] fairness,[17] and framing effects.[18] On the positive side, the method has been applied to interactive learning[19] and social preferences.[20][21] As a research program, the subject is a development of the last three decades.[22]

Economic reasoning in non-human animals

A handful of comparative psychologists have attempted to demonstrate 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.[23] 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.[24]

The animal as a human analogy

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.[25] Researchers in this field advocate for the appropriateness of using animal economic behavior to understand the elementary components of human economic behavior.[26] In a paper by Battalio, Green, and Kagel (1981, p 621),[25] they write

Labor supply

The typical laboratory environment to study labor supply in pigeons is set up as follows. Pigeons are first deprived of food. Since the animals are hungry, food becomes highly desired. The pigeons are 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.[25]


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 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, say we have experimental subjects, rats, in an operant chamber and we require them to press a lever to receive a reward. The reward can be either food (reward pellets), water, or a commodity drink such as cherry cola. Unlike previous pigeon studies, where the work analog was pecking and the monetary analog was reward, in the studies on demand in rats, the monetary analog 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.[27]

In effect, results of demand studies in non-human animals are that, as the bar-pressing requirement (cost) increases, the animal presses the bar the required number of times less often (payment).

Monkey trading behavior

Recent work on economic behavior in non-human animals has focused on capuchin monkeys. Here the researchers seem less inclined toward the behaviorist tradition of the laboratory animal-human behavior analog. Instead, they attempt to adopt a more evolutionary perspective, positing that economic reasoning might be basic, unlearned, and serve some adaptive function.

One recent study [24] involves the introduction of a currency system into a colony of captive capuchin monkeys. The currency is in the form of coins and is redeemable for food and other purchasable items when exchanged with a researcher. Under these conditions, the researchers studied three features of monkey trading: demand, loss aversion, and risk aversion.

In this study, monkeys are presented with an amount of money and are shown a certain amount of food or other goods. The monkeys must take the money and hand it to the experimenter in exchange for goods. In one condition of the experiment, after the monkey has paid for the goods, it has the option to take a sure amount of food now, or wait until the experimenter alters the amount of food presented. In this circumstance, the experimenter can either increase or decrease the amount of food given. Thus, this experimental setup allows the researchers to look at the gambling behavior of the animals. The experimenters can therefore ask the following questions: will the monkey take the sure amount of food? Will the monkey “gamble” by waiting until the experimenter changes the amount of food present? Does the decision of the animal depend on the circumstances? Results indicate that the monkeys are risk-averse: they prefer to take the initial amount of food than wait for the experimenter to change the amount presented.

The experimenters introduce several other manipulations, including changing the allocated budget, changing the cost of certain items, changing the items themselves. Specifically, the researchers found an increase in item purchase and consumption when that item decreases in value, a result consistent with those found in human economics.[24]

Taken together, the results of this study indicate that capuchin monkeys are not only risk-averse, but are also sensitive to constructs such as price, budget, and payoff expectation. According to the researchers, the animals are not trained to behave in this way; these behaviors arise naturally in the trading environment. As a result, these researchers argue that basic economic behavior and reasoning might be unlearned, innate, and subject to natural selection.

Evolutionary psychology

An evolutionary psychology perspective is that many of the seeming 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 have meant death it may have been rational to place a greater value on losses than on gains. It may also explain 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 much more than females from successful risk-seeking.[28]


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,[29] 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

  • The Behavioral Economics Guide
  • Overview of Behavioral Finance
  • The Institute of Behavioral Finance
  • Stirling Behavioural Science Blog, of the Stirling Behavioural Science Centre at University of Stirling
  • Society for the Advancement of Behavioural Economics
  • Behavioral Economics: Past, Present, Future – Colin F. Camerer and George Loewenstein
  • A History of Behavioural Finance / Economics in Published Research: 1944–1988
  • MSc Behavioural Economics, MSc in Behavioural Economics at the University of Essex
  • Behavioral Economics of Shipping Business

External links

Augier, Mie. Simon, Herbert A. (1916–2001). 
Bernheim, B. Douglas; Rangel, Antonio. Behavioral public economics. 
Bloomfield, Robert. Behavioral finance. 
Simon, Herbert A. Rationality, bounded. 
  • Ainslie, G. (1975). "Specious Reward: A Behavioral /Theory of Impulsiveness and Impulse Control". Psychological Bulletin 82 (4): 463–496.  
  • Benartzi, Shlomo;  
  • Cunningham, Lawrence A. (2002). "Behavioral Finance and Investor Governance". Washington & Lee Law Review 59: 767.  
  • Diamond, Peter A., and Hannu Vartiainen, ed. (2007). Behavioral Economics and its Applications. Description and preview.
  • Daniel, K.;  
  • Garai Laszlo. Identity Economics – An Alternative Economic Psychology. 1990–2006.
  • E McGaughey, 'Behavioural Economics and Labour Law' (2014) SSRN
  • Hens, Thorsten; Bachmann, Kremena (2008). Behavioural Finance for Private Banking. Wiley Finance Series.  
  • Hogarth, R. M.; Reder, M. W. (1987). Rational Choice: The Contrast between Economics and Psychology. Chicago: University of Chicago Press.  
  • Kirkpatrick, Charles D.; Dahlquist, Julie R. (2007). Technical Analysis: The Complete Resource for Financial Market Technicians. Upper Saddle River, NJ: Financial Times Press.  
  • Kuran, Timur (1995). Private Truths, Public Lies: The Social Consequences of Preference Falsification, Harvard University Press. Description and chapter-preview links.
  • The New Palgrave Dictionary of Economics (2008), 2nd Edition. Abstract links:


  1. ^ Search of behavioural economics at (2008–) The New Palgrave Dictionary of Economics Online.[1]
  2. ^
  3. ^ Shefrin 2002
  4. ^ Kirkpatrick 2007, p. 49
  5. ^ Genesove & Mayer, 2001
  6. ^ Benartzi 1995
  7. ^ J. Scott Armstrong, Nicole Coviello and Barbara Safranek (1993). "Escalation Bias: Does It Extend to Marketing?". Journal of the Academy of Marketing Science, 21 (3): 247–352.  
  8. ^ "Dr. Donald A. Balenovich". Indiana University of Pennsylvania, Mathematics Department. 
  9. ^ "Ahmet Duran". Department of Mathematics,  
  10. ^ "Dr Ray R. Sturm, CPA". College of Business Administration. 
  11. ^ Tang, David (6 May 2013). "Why People Won’t Buy Your Product Even Though It’s Awesome". Flevy. Retrieved 31 May 2013. 
  12. ^ Fama on Market Efficiency in a Volatile Market
  13. ^ See Freeman, 2004 for a review
  14. ^ R. J. Aumann (2008). "game theory," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
  15. ^  
  16. ^ James Andreoni et al. (2008). "altruism in experiments," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
  17. ^ H. Peyton Young (2008). "social norms," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
  18. ^   Pdf version.
  19. ^ * William H. Sandholm (2008). "learning and evolution in games: an overview," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
       * Teck H. Ho (2008). "Individual learning in games," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
  20. ^ Martin Dufwenberg and Georg Kirchsteiger (2004). "A Theory of Sequential reciprocity," Games and Economic Behavior, 47(2), pp. 268–298. Abstract.
  21. ^ * Faruk Gul (2008). "behavioural economics and game theory," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
       * Colin F. Camerer (2008). "behavioral game theory," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
  22. ^   Description, preview ([ctrl]+), and ch. 1 link.
       * _____, Matthew Rabin, ed. (2003). Advances in Behavioral Economics, Princeton. 1986–2003 papers. Description, contents, and preview.
       * Drew Fudenberg (2006). "Advancing Beyond Advances in Behavioral Economics," Journal of Economic Literature, 44(3), pp. 694–711.
       * Vincent P. Crawford (1997). "Theory and Experiment in the Analysis of Strategic Interaction," in Advances in Economics and Econometrics: Theory and Applications, pp. 206–242. Cambridge. Reprinted in Camerer et al. (2003), Advances in Behavioral Economics, Princeton, ch. 12.
       * Martin Shubik (2002). "Game Theory and Experimental Gaming," in R. Aumann and S. Hart, ed., Handbook of Game Theory with Economic Applications, Elsevier, v. 3, pp. 2327–2351. Abstract.
       • Charles R. Plott and Vernon L. Smith, ed. (2008). Handbook of Experimental Economics Results, v. 1, Elsevier, Part 4, Games preview and ch. 45–66 preview links.
       * Games and Economic Behavior, Elsevier. Aims and scope.
  23. ^ Ferster, C. B.; et al. (1957). Schedules of Reinforcement. New York: Appleton-Century-Crofts. 
  24. ^ a b c Chen, M. K.; et al. (2006). "How Basic Are Behavioral Biases? Evidence from Capuchin Monkey Trading Behavior".  
  25. ^ a b c Battalio, R. C.; et al. (1981). "Income-Leisure Tradeoffs of Animal Workers".  
  26. ^ Kagel, J. H.; et al. (1995). Economic Choice Theory: An Experimental Analysis of Animal Behavior. New York: Cambridge University Press.  
  27. ^ Kagel, J. H.; et al. (1981). "Demand Curves for Animal Consumers".  
  28. ^ Paul H. Rubin and C. Monica Capra. The evolutionary psychology of economics. In Roberts, S. C. (2011). Roberts, S. Craig, ed. "Applied Evolutionary Psychology". Oxford University Press.  
  29. ^ Nava Ashraf, Colin F. Camerer, and George Loewenstein (2005). "Adam Smith, Behavioral Economist," Journal of Economic Perspectives, 19(3), p. 142. [pp. 131–145.
  30. ^ Tarde, G. Psychologie économique (1902),
  31. ^ The Powerful Consumer: Psychological Studies of the American Economy. 1960.
  32. ^ Garai,L. Identity Economics – An Alternative Economic Psychology. 1990–2006.
  33. ^ "Ward Edward Papers". Archival Collections. Archived from the original on 16 April 2008. Retrieved 2008-04-25. 
  34. ^ Luce 2000
  35. ^ Kahneman 2003
  36. ^ Hogarth 1987
  37. ^ "Nobel Laureates 2002". Archived from the original on 10 April 2008. Retrieved 2008-04-25. 
  38. ^ Aggarwal, Raj (2014). "Animal Spirits in Financial Economics: A Review of Deviations from Economic Rationality". International Review of Financial Analysis 32 (1): 179–187.  
  39. ^ Grafstein R (1995). "Rationality as Conditional Expected Utility Maximization". Political Psychology 16 (1): 63–80.  
  40. ^ Shafir E, Tversky A (1992). "Thinking through uncertainty: nonconsequential reasoning and choice". Cognitive Psychology 24 (4): 449–474.  
  41. ^ "US National Broadband Plan: good in theory". Telco 2.0. March 17, 2010. Retrieved 2010-09-23. ... Sara Wedeman's awful experience with this is instructive.... 
  42. ^ Gordon Cook, Sara Wedeman (July 1, 2009). "Connectivity, the Five Freedoms, and Prosperity". Community Broadband Networks. Retrieved 2010-09-23. In this report, Gordon Cook interviews Sara Wedeman, a mapping expert who also works in behavioral economics 
  43. ^ see Myagkov and Plott (1997) amongst others
  44. ^ Rabin & 1998 11–46
  45. ^ a b Sarapultsev, A., & Sarapultsev, P. (2014). Novelty, Stress, and Biological Roots in Human Market Behavior. Behavioral Sciences, 4(1), 53-69. doi:10.3390/bs4010053
  46. ^ Zhukov, D.A. Biologija Povedenija. In Gumoral’nye Mehanizmy [Biology of Behavior. Humoral Mechanisms]; Rech: St.-Petersburg, Russia, 2007
  47. ^ Selye, H. Stress in Health and Disease; Butterworths: Boston, MA, USA, 1976.
  48. ^ "". 
  49. ^ "Predictably Irrational". Dan Ariely. Archived from the original on 13 March 2008. Retrieved 2008-04-25. 
  50. ^ Bernheim, Douglas; Rangel, Antonio (2008). "Behavioural public economics". The New Palgrave Journal of Economics (2). 


See also



Notable theorists

According to some researchers,[45] 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 [46] because, “Stress is the nonspecific body response to any demands presented to it”.[47] 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. 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.[45]

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.

Rabin (1998)[44] 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 yet be verified in the field.

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.

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.

Critics of behavioral economics typically stress the rationality of economic agents.[43] 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.


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.[41][42]

"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.[39][40]

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. According to Aggarwal (2014), 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.[38]

Other areas of research

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.

Behavioral economics has also been applied to intertemporal choice. Intertemporal choice behavior is largely inconsistent, as exemplified by 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.

Intertemporal choice

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,[36] 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".[37]

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.

Prospect theory is able to explain everything that the two main existing decision theories – expected utility theory and rank dependent utility – 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 labour supply curves, asymmetric price elasticities, tax evasion, co-movement of stock prices and consumption etc.

  • (1) 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.
  • (2) Loss aversion: Losses bite more than equivalent gains. In their 1979 paper in Econometrica, Kahneman and Tversky found the median coefficient of loss aversion to be about 2.25, i.e., losses bite about 2.25 time more than equivalent gains.
  • (3) 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".
  • (4) 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.

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:

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.[35] Prospect theory has two stages, an editing stage and an evaluation stage.

Prospect theory

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,[33] 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).[34]

Daniel Kahneman, winner of 2002 Nobel prize in economics.

, a decision problem he first presented in 1953 which contradicts the expected utility hypothesis. Allais paradox, for example in setting out the Maurice Allais respectively. Observed and repeatable anomalies eventually challenged those hypotheses, and further steps were taken by the Nobel prizewinner intertemporal consumption and uncertainty about decision making given hypotheses models began to gain acceptance, generating testable discounted utility and Expected utility [32].Laszlo Garai and [31]