Behavioral Economics - Sp 11

Introduction

While risk can be quantified, uncertainty simply cannot. By investigating literature on behavioral economics,we will use social, cognitive, and emotional factors to better understand economic decisions of individuals and institutions. Throughout the classical period, psychology and economics were closely linked which can be seen in the Theory of Moral Sentiments. Adam Smith proposed explanations using psychology to demonstrate how different individual’s behavior related to their decisions in the market place. However, neo-classical economics tried to reform this discipline into more of a natural science from simple assumptions and developed the concept of homo economicus. This creation was fundamentally rational so that behavior was now assumed rational. At one end of the spectrum we have mathematical economists and pure theorists which form deductions from a controlled setting with a very small number of assumed as universal laws. This is in attempt to create the ability to regard economics as scientific in which their are exact laws and variables can be controlled. At the other extreme there is tendency to remove abstraction and deduction. This form relies on a descriptive science. This leaves every other opinion and form in between to counter and weigh the different measurements and theories.

Therefore, the study of economics stands as a science of human activities under a given form of organization. This rationalistic view of activity in search theory boils down to the search for the satisfaction of wants and desires of the given entities.

Risk vs Uncertainty

Risk is defined as the possibility that a chosen decision including the choice of not acting will lead to a decrease in utility and an undesirable outcome. The belief implies that a choice having an influence on the outcome exists or existed. Potential losses themselves may also be called risks.

Uncertainty is simply the condition of having doubts with regard to the market. Uncertainty can have serious affects in the market that lead to both positive and negative outcomes. Due to the different effects uncertainty can cause, it is hard to distinguish whether or not it is good or bad for the market. Uncertainty can cause inflation of prices, excess demand, and liquidity traps. However, the uncertainty ever present in the market fuels investment and growth for the possible potential future return.

Knight argues that there is a fundamental difference between risk and uncertainty. Risk is a state of uncertainty in which some of the possibilities involve a loss, a catastrophe, or other possible negative outcomes.

Uncertainty is the lack of complete knowledge and the existence of more that one possible outcome. The true outcome or result is impossible to know.

Knightian Uncertainty is immeasurable and therefore not possible to calculate while Knightian risk is able to be measured

"Uncertainty must be taken in a sense radically distinct from the familiar notion of Risk, from which it has never been properly separated. The term "risk," as loosely used in everyday speech and in economic discussion, really covers two things which, functionally at least, in their causal relations to the phenomena of economic organization, are categorically different. ... The essential fact is that "risk" means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far-reaching and crucial differences in the bearings of the phenomenon depending on which of the two is really present and operating. ... It will appear that a measurable uncertainty, or "risk" proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all. We ... accordingly restrict the term "uncertainty" to cases of the non-quantitive type."(Knight- Risk, Uncertainty and Profit)

In a similar way, we have developed a historic body of theoretical economics, which deals with "tendencies." These tendencies explain what "would" happen under basic conditions. But theoretical economics has been much less successful making the procedure useful, largely because it has failed to make its limitations clear. Studying "perfect competition," which competition are not perfect tries to establish a systematic view of what is needed to establish perfect competition.

Economics is a human science in which its foundations are set in the principles of human behavior, Economic analysis deals with acts adapted to ends and assumes these acts are ruled by conscious motives which are the satisfaction of wants. This behavior is impulsive and unpredictable and economic theory must believe that men's economic activities are rational or planned.

Economics is a human science; its foundations are laid in the principles of human behavior, and consequently we must begin with some observations on the psychology of human conduct which controls economic life. Economic analysis may be truly said to deal with acts adapted to ends, or of the adaptation of acts to ends, in contrast with the broader category of "behavior" in general. It assumes that men's acts are ruled by conscious motives; that, as it is more ordinarily expressed, they are directed toward the "satisfaction of wants." At the very outset the science is thus subjected to notable restrictions, since it is only to a limited extent that our behavior, even our economic behavior, is of this character. Much of it is more or less impulsive and capricious. The conclusions of economic theory must in general be admitted subject to the qualification, in so far as men's economic activities are rational or planned.

It appears that a relatively small fraction of the activities of civilized man are devoted to the gratification of needs or desires having any foundation beyond the mere fact that an impulse exists at the moment in the mind of the subject. Most human motives tend on scrutiny to assimilate themselves to the game spirit. It is little matter, if any, what we set ourselves to do; it is imperative to have some objective in view, and we seize upon and set up for ourselves objectives more or less at random—getting an education, acquiring skill at some art, making money, or what-not. But once having set ourselves to achieve some goal it becomes an absolute value, weaving itself into and absorbing life itself. It is just as in a game where the concrete objective—capturing our opponents' pieces, carrying a ball across a mark, or whatever it may be—is a matter of accident, but to achieve it is for the moment the end and aim of being. And, as in a game again, so with life generally, the social situation furnishes much of the driving power, though again there are many who can become intensely interested in solitaire.

Expected Utility Theory

Over the past three hundred years, the foremost model for individual behavior under uncertainty has been the Expected Utility Theory (EUT). Introduced by Daniel Bernoulli in 1738, the EUT is a key building block for a vast range of behavioral economic choice theory. The model was axiomatized by von Neumann and Morgenstern, integrated into subjective probability by Savage, and applied to risk aversion by Arrow and Pratt. It has applications in the theory of insurance, theory of games, theory of investment and capital markets, theory of search, decision theory, statistics, and the economics of uncertainty.

The theory- which models betting preferences with regard to uncertain outcomes-is a function of payouts, probabilities of occurrence, risk aversion, and personal preferences and assets. In its simplest form, EUT is an expected value equation, in which utility, (U), is a function of monetary payoff, (x), with a probability (p). The expected utility preference function of the form is: . The value of expected utility, therefore, is based on the sum of utilities of a specific monetary payoff multiplied by the probability of the payoff. Risk aversion is built into the model as well. The properties of the utility as a function of the payoff serve to model individuals attitudes towards risk. For instance:

•will display a preference for shifting probability from lower to higher outcome values if utility is an increasing function of monetary payoff.

•will display risk aversion if utility is a concave function of monetary payoff.

Allais Paradox

Maurice Allais came up with a choice problem he titled, The Allais Paradox. In this problem the choices of participants in two different situations are recorded in which they have the opportunity to decide between two gambles in each, A or B, or C or D. The purpose of the paradox is to illustrate “an inconsistency of actual observed choices with the predictions of expected utility.” It has been studied that when presented with the choice of 1A and 1B, the majority of the participants choose 1A. In addition in situation 2, the majority choose 2D. According to Maurice Allais it was absolutely rational to choose 1A alone or 2D alone. What Allais questioned, however, was the fact that, according to expected utility theory, the participant should choose either 1A and 2C or 1B and 2D.

Indecision and Inefficiencies in the market

Throughout the classical period, psychology and economics were closely linked which can be seen in the Theory of Moral Sentiments. Adam Smith proposed explanations using psychology to demonstrate how different individual’s behavior related to their decisions in the market place. However, neo-classical economics tried to reform this discipline into more of a natural science from simple assumptions and developed the concept of homo economicus. This creation was fundamentally rational so that behavior was now assumed rational. Under these presumptions that man are inherently irrational, I will seek to explain from a classical standpoint how people’s decisions are made through the use of the following:

• Heuristics: People often make decisions based on approximate rules of thumb and unbounded logic involving different variables such as perception, effort, and past experiences.

• Market inefficiencies:These include herd behavior, panic and non-rational decision making involving stock bubbles.

Cognitive Bias

Cognitive biases may also have strong random effects in the aggregate if there is social contagion of ideas and emotions which can cause collective euphoria or fear causing 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 which can be quite problematic. The central issue in behavioral finance is explaining why market participants make systematic errors. Such errors affect prices and returns, creating market inefficiencies. This concept investigates how other participants arbitrage such market inefficiencies and use them to their advantage. Behavioral finance highlights inefficiencies such as under or over reactions to information as causes of market trends which can culminate into bubbles and crashes in extreme cases. These cases are usually attributed to limited investor attention, overconfidence, over optimism, and herding. Heuristics refer to a set of techniques related to experiences which all one to solve problems, learn, and discover new things. This technique is used to identify the best solution as fast as possible. There are many different methods, which include “rule of thumb,” intuitive judgment, common sense, and educated guesses (Armstrong). In detail, these heuristics stand as strategies that are easy accessed information used to control problem solving by both human beings and machines as well. One of the most basic heuristics is trial and error, which involves searching for an answer based on a limited number of right answers and applying all solutions until the optimal solution is found (Armstrong). Other heuristics include drawing a picture, working backwards with a possible solution, and trying to examine a concrete example of a problem before a more abstract version.

Herd Behavior

Herd behavior and panic characteristics cause at times irrational and unexplainable behavior that completely alters the subconscious of its human actors (Knight). Herd behavior describes how individuals in a group can act together without planned direction. The term pertains to the behavior of animals in herds, flocks and schools, and to human behavior during activities such as stock market bubbles and crashes, street demonstrations, sporting events, and even everyday decision making and opinion forming (Zak). Recently an integrated approach to herding has been proposed, describing two key issues, the mechanisms of transmission of thoughts or behavior between individuals and the patterns of connections between them (Knight). It has been proposed that bringing together a multitude of different theoretical approaches of herding behavior allows the applicability of the concept to be applied many domains, ranging from cognitive neuroscience to economics. Asymmetric aggregation of animals under panic conditions has been observed in many species allowing for theoretical models to demonstrate symmetry breaking similar to observations in scientific studies (Cassidy). For example when panicked individuals are trapped to a room with two equal exits, a substantial majority will tend to favor one exit while the minority will favor the other (Cassidy). There are distinct characteristics of a herd in a state of panic. These include individuals moving faster than normal, physical interactions by individuals, exits become clogged, fallen individuals become obstacles, and alternative exits are usually overlooked (Cassidy). In The Theory of the Leisure Class, Thorstein Veblen explained economic behavior in terms of social influences such as "emulation," where some members of a group mimic other members of higher status (Armstrong). Emulation occurs in many different situations and at different degrees. One of the most classic examples of emulation is in the form of herd behavior which occurs most noticeably in the stock market. These bubble trends usually begin with low interest rates and a positive economic outlook on the future. As the market begins to slowly rise, more individuals notice of the crowd following the growing surge. Emotions and irrational exuberance take grip of the market as individuals begin to ignore possibly signs of weakness and continue to drive the market higher and higher. This frenzy of buying over a specified time period is then followed by a deluge of selling as the fear of the crash overwhelms the market and causes mass destruction in the form of tumbling security prices. Some followers of the technical analysis school of investing see the herding behavior of investors as an example of extreme market sentiment (Cassidy). More specifically individuals, acting often on the foundation of private information as well as using the behavior of the public even if their choice may in turn be the socially undesirable option.

Heuristics

From a psychological standpoint, heuristics are much more straightforward. Characterized by efficient rules and evolutionary processes, heuristics are used to explain why people make certain decisions, form judgments, and solve problems that are usually void of certain information making them more complex (Tversky and Kahneman). Although these rules work well under most condition, certain variables or instances can cause systematic errors and cognitive biases that create anomalies that can be unexplainable and unpredictable. Amos Tversky, Daniel Kahneman, and Gerd Gigerenzer have accomplished the majority of the work concerning human decision-making and judgment. Kahneman proposed that heuristics work through a process known as attribute substitution, which occurs completely void of conscious awareness. Under this pretense, a judgment is made by an individual that is computationally intense and complex, and the individual substitutes this complex variable for an easier calculated heuristic attribute. This allows for the individual to cognitively developing a simpler problem to answer without the individual realize this strategy is even occurring, as he is consciously unaware of this substitution. This theory shows why cases of judgment are unable to show regression towards the mean. This is one of the reasons heuristics are considered to reduce the level of complexity of clinical judgments in the business world as well as why heuristic algorithms are used as they appear to work without have ever been proven mathematically or meet a predetermined set of requirements (Gigerenzer). A common pitfall can occur in which an engineer employs a model but fails to recognize that the data being used does not necessarily represent future system outputs. Although the algorithm can process the data over and over, one must realize that it is much more important to make sure the date being projected is concurrent with the data input. The engineer must understand the requirements of the data to insure the output data is not solely reflective of the input data but the output data as well. Statistical analysis is often used when employing these techniques in the form of p-values to measure the probability of incorrect outcomes. Another function of behavioral economics includes the use of framing. Framing relates itself to heuristics, as it is a social theory consisting of the concept of interpretation of a collection of anecdotes and stereotypes that individuals use to understand and respond to events. (Druckman 2001A) Through the use of framing, people develop emotional mental filters that are used to make sense of the world and in turn make choices that are influenced from this frame of reference. This social construction is a selective influence over someone’s perception, which deals directly with the meaning attributed to specific words or phrases that invoke certain emotions or rationalizations. This frame can encourage or discourage certain decisions depending on the individual’s history and preference. Due to framing being a heuristic and subconscious shortcut, humans are “cognitive misers” meaning they prefer to do as little as thinking as possible and rely heavily on these subconscious decision formulas that allow them to make split second decisions in multitudes of different scenarios (Druckman 2001A). Framing allows for quick and easy decisions to be obtained and to understand incoming stimuli. This gives the sender and framer of the information enormous power to use these schemas to influence how the receivers will interpret the message (Druckman 2001B)

Reciprocity

Reciprocity is a form of social psychology in reference to responding to a positive action with another positive action in return as well as responding with a negative action when a negative action precedes this action (Gigerenzer). This reciprocal action differs from altruistic behavior due to they only follow from receiving positive actions. These actions only occur with the expectation that they initial action will receive positive responses at some point in the future. These actions of reciprocity help explain social norms and are an important fundamental of social psychology (Zak). Must human societies consider breaking a social norm as an act of hostility and usually respond with an action to punish this disruption even when it costs the person to administer this punishment, Punishments range from verbal warnings to complete exclusion from society depending on the level and frequency of the infraction. In public good experiments, behavioral economists have demonstrated that the potential for reciprocal actions by players increases the rate of contribution to the public good, providing evidence for the importance of reciprocity in social situations (Druckman 2001A). In mathematics, game theory describes reciprocity as a highly effective strategy for the classic prisoner's dilemma. In this case, cooperating is dominated by selling the other prisoner out, as no matter what the other prisoner does, the other will always be better off by confessing the other person is guilty. Due to in any situation the defector is better off; all rational players will always defect. However, if the simulation can be repeated, it would benefit the players to cooperate with each other so that they could both benefit from reciprocity. But the biggest problem with this simulation is in the final simulation round, one player will no longer reciprocate and someone will end up losing everything. This brings the next idea to light in the form of bounded rationality in which individuals are limited to only the information privy to them at a given time.

Conclusion

Human behavior, limited by time, processing, and knowledge is confined to using heuristics as a tool to make decisions. These processes occur at a rate almost impossible to measure. Humans need heuristics or decisions would be unable to be accomplished in an orderly time such as what clothes to wear to which college to decide. These decisions are affected by a multitude of different variables such as familiarity with situations, decisions of others, and the context in which the decision has to be made. These decisions are not flaw proofed as the irrationality of an individual causes them to at times apply the wrong heuristic or misjudge the variable in question. Examples of this include being over confident in the form of applying a new situation to an incorrect past experience to following the crowd in a herding effect as emotions or panic cause fear to influence the decision. Humans do not have the luxury or the capacity to be able to determine the almost infinite possibilities almost every decision entails. Without heuristics, the phenomenon of crowd behavior, framing, and behavioral economics would not exist. It is due to the fact humans will never act completely like homo economicus and are incapable of disregarding their emotions that the study of heuristics will continue to grow and be closely monitored in order to pinpoint more decision making functions and biases. No one is free from these inefficiencies or premonitions as it is part of our human nature.

References

Works Cited Akerlof, George A., and Robert J. Shiller. Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism. Princeton: Princeton UP, 2009. Print.

Cassidy, John. How Markets Fail: the Logic of Economic Calamities. New York: Farrar, Straus and Giroux, 2009. Print.

Druckman, J. “ Evaluating Framing Effects.” Journal of Economic Psychology; 2001A, 22: 96-101

Druckman J. “Using Credible Advice to Overcome Framing Effects.” Journal of Law, Economics, and Organization: 2001B, 17: 62-82

Gigerenzer, Gerd. Rationality for Mortals: How People Cope with Uncertainty. Oxford: Oxford UP, 2008. Print.

Knight, Jack. Institutions and Social Conflict. Cambridge [England: Cambridge UP, 1992. Print.

Plous, Scott. The Psychology of Judgment and Decision Making. Philadelphia: Temple UP, 1993. Print.

Tversky, A., and D. Kahneman. The Framing of Decisions and the Psychology of Choice. 1981. Print.

Zak, Paul J. Moral Markets: the Critical Role of Values in the Economy. Princeton: Princeton UP, 2008. Print.

Allais Paradox- http://www.medical-answers.org/hd/index.php?t=Allais+paradox