Conventional economics is predicated on utility maximization, market equilibriums, and economic efficiency. Conventional economics is based on rationality, rationality being defined as being consistent with maximizing wealth or utility, rather than the usual definition of being based on logic. This rationality foundation simplifies economic analysis but leaves out influential factors that affect how people behave. The objective of behavioral economics is to study human behavior regarding economic decisions.
Behavioral economics combines economics with psychology, to explain economical behavior by understanding how people think, perceive, and remember, how they are influenced by their constitution and history, and how they are influenced by external factors, such as social influences. By contrast, conventional economics is based on simplified models that do not account for behavioral complexities. Conventional economics works best in the aggregate but may not predict individual economic decisions. To predict outcomes, behavioral economists concern themselves with understanding the processes that lead to decisions, as well as the outcome of those decisions. Behavioral economics seeks to explain the anomalies and biases in decision-making.
Conventional economics treats economic agents, including people, as being rational. This rational economic agent was sometimes named Homo economicus, or Economic Man. Rationality is a natural assumption, since it would be impossible to formulate rules based on irrationality. But it is obvious that people do not always act in their best interest, that there is at least some irrationality in their decisions; irrationality caused by other psychological factors. Much of this irrationality results from peoples' inadequate or nonexistent knowledge of decision analysis, probability and statistics, and other formal rules of logic.
Much of behavioral economics examines how the mind makes decisions, which derives from the limitations of the mind and how it is structured. This might be called psychoeconomics, because it examines decision making from behavioral observations.
Decision-making is also observed on the neuronal level. In some experimental economics experiments, the activation of neurons, or some proxy of neuronal activity, such as blood flow in the brain, is observed as a subject makes a decision or as the result of some other influence. This study of neuroeconomics will no doubt greatly expand, especially as better tools become available.
Economic models are typically based on such economic variables as prices, income, interest rates, and so on. But these variables do not provide a full explanation for how people think and respond. Rational choice models often do work, but not always. Behavioral economics seeks to explain the not always. The problem with conventional economics is not that the assumptions are unrealistic, but that they don't account for human behavior, because it is not easily quantified, and thus, cannot be easily incorporated into economic models.
The propensity for simplified models occurs because economists, like other scientists, like to quantify their theories using mathematics, so variables not easily quantifiable are often abstracted out. This propensity creates a bias for certain types of models, regardless of how well they predict the real world or how consistent they are. While the truth is always consistent, consistent assumptions may not easily be quantified. This favoring of mathematical models over observational details is sometimes called blackboard economics.
Conventional economics treats households and firms as a black box, where given inputs will yield a consistent output, since this leads to simpler models. But these black box models assume that economic agents have perfect knowledge, unbounded knowledge. Unbounded knowledge means that people know everything relevant to the decision. This is a common assumption made about the stock market, that prices reflect all available information. Obviously, unbounded knowledge certainly is not true, since no one has the time and resources to know everything about every decision, which is why satisficing, being satisfied enough, and heuristics, which are rules of thumb for making decisions, are crucial factors in decision-making. Part of this unbounded knowledge paradigm is the ability to forecast the future. Although some predictions are accurate, i.e. the sun will come up tomorrow, nebulosity and uncertainty always cloud future predictions, obscuring the effect of any future forecast on present decision-making.
Behavioral economics incorporates insights from psychology, sociology, neuroscience, politics, and the law. Incentives matter, but the basis of decisions is more complex than assumed in conventional economics. Conventional economics posits that people always make decisions that increase their expected utility or wealth, but behavioral economics observes that this is not always the case. Conventional economics is built on models based on simplified assumptions, but behavioral economists believe these too simplified assumptions yields less reliable predictions. For instance, conventional economics posits that a higher minimum wage increases unemployment because it increases the cost of labor. However, a behavioral economist may argue that a higher minimum wage will improve morale and motivation, causing workers to work harder and more efficiently.
Realistic assumptions also can help differentiate between effects due to a cause-and-effect correlation, a common-cause correlation, or a spurious correlation, which is a coincidental correlation.
Does a firm always maximize profits and productivity? Is it not often the case that individuals within the firm or organization maximizes their own profit at the expense of the firm or organization? Conventional economics argues that firms must be maximizers because they have competition. However, if every firm is subject to the self-serving actions of its corporate officers and executives, and even its employees, then competition will not necessarily lead to profit maximizing behavior, since every firm is subject to the self-serving interests of its managers, thus leading to a lower productive level of competition.
Conventional economics assumes that institutions are efficient, but many are not. Often, institutions are set up to benefit the owners or the workers of the institution over those served by the institution. This lowers the economic benefit of such institutions to society.
That the simplified assumptions of conventional economics are often wrong, can be demonstrated by the 2007-2009 Great Recession. Conventional economists predict that when interest rates go down, aggregate demand increases. Interest rates did go down significantly during the Great Recession, but it took a while for aggregate demand to increase significantly. When consumer confidence is depressed and people and businesses are deeply in debt, then lower interest rates will not increase aggregate demand, at least in the short term. Consumer and business confidence, what John Maynard Keynes called animal spirits, must be considered, as well as other factors, such as the status of economic agents. When people are depressed because of significant debt, and their confidence about the future are low, then they will be reluctant to spend, regardless of low interest rates. Likewise, businesses will not invest, not only because they, too, are in debt, but because they have less business.
Behavioral economics does not dispute that money or incentives matter; rather, it recognizes that there are other factors in people's decisions. Thus, behavioral economics supplements conventional economics rather than displacing it.
Brief History of Behavioral Economics
Behavioral economics can be said to begin with the history of probability theory, since many economic decisions are based on probability. A gambler, for instance, wants to know the odds of winning. A higher probability of winning an award means that the expected value of that strategy will be higher, so a rational basis for choosing an option is to choose those options with higher expected values. Expected utility, as explained by John von Neumann and the economist Oskar Morgenstern in their 1944 book Theories of Games and Economic Behavior, is the value of an outcome multiplied by the probability of its occurrence.
Expected Utility = Outcome Value × Probability of Occurrence
However, expected value does not explain many decisions. For instance, if someone were offered $10 if the flip of a fair coin yields heads, but they would have to pay $5, if it is tails, most people would take this bet, because given the equal probability of heads or tails, the higher payoff for the heads yields a higher expected return. However, if the amount of money was increased, such that the $10 is now $10,000 and the $5 is $5000, experiments have shown that many people would not take that bet.
The mathematician and physicist Daniel Bernoulli posited that people place different values on a particular good, such as money. For instance, poorer people value money more highly than rich people, so they are more loss averse. Fewer poor people than rich people would take the $10,000/$5000 bet. Eventually, economists developed the idea of utility, that people make decisions to maximize their utility, which is the subjective value they attribute to a good or service rather than its absolute value.
Rational choice models are based on maximizing one's utility. To test rational choice models, Vernon Smith, in the early 60s, developed simulations of markets that could be studied in the laboratory, what is now called experimental economics. Experimental economics seeks to understand decision-making, based on what people know and value as observed in the laboratory setting under precise conditions.
Experimental methods are based on incentives, on freedom from external influences, and on not deceiving the experimental subjects. Consequently, incentives are usually provided by paying money to the experimental subjects, letting them know what is being investigated, and how they will be paid.
Nobel laureate Herbert Simon, considered 1 of the originators of behavioral economics, argued that economic models must be based on realistic assumptions. Realistic assumptions would not only improve predictions but would also explain the real world better. The rules of economic models must accurately reflect how people behave and how they decide. Assumptions need to account for peer pressure, norms, culture, religion, gender, hierarchical relationships, and differences in preferences.
Another concept developed during the 1950s, 1960s, and 1970s, is that people use heuristics, rather than formal logic, to make most decisions. Heuristics are rules of thumb used in decision-making to compensate for limited time, limited knowledge, and limited ability. For instance, most people do not know the probability of a given event, and even if they assume a ballpark figure, they usually do not know how to calculate the true probability mathematically, precisely. Most people base their assessment of probability on their intuition, which, in turn, is used to determine expected utility or expected value. Heuristics often yield correct results, but they also result in many decision-making errors and biases. Some examples of heuristics are the 1/N heuristic, where the probability or apportionment of available options is equalized, and the availability heuristic, which relies on what is more easily remembered. It has been reported that Harry Markowitz, the developer of modern portfolio theory, used a 1/N heuristic to allocate his retirement funds among a selection of portfolios. This diversification scheme is usually effective, but some heuristics lead to incorrect results, at least some of the time. For instance, during the early 1970s, Daniel Kahneman and Amos Tversky asked subjects what was more likely, a word that starts with K or where K is the 3rd letter. Most of the subjects said that words that start with K were more common, presumably because these words are more easily remembered, but, in actuality, words with K in the 3rd position are twice as common.
The Essence of Behavioral Economics
To summarize, conventional economics assumes that perfectly rational people with unlimited knowledge and time and without external influences are making economic decisions to maximize their utility or wealth. Although this simplifies economic modeling, it, obviously, does not reflect reality. That people often regret many of their decisions indicates that there were errors in their judgment, that they lacked information, or that they were unduly influenced by irrelevant factors. Behavioral economics seeks to explain this reality:
- bubbles and busts
- how people handle uncertainty
- how decisions are affected by:
- heuristics, which are rules of thumb, and how they can sometimes lead people astray
- experience and intuition
- the framing of options
- the identity and background of the individual
- how the probability of certain events is ascertained
- rewards and punishments, and
- social influences and social status.
While it is more difficult to account for these factors in economic models, they do yield insight into the economic decisions people actually make. Behavioral economics studies these factors in greater detail. By understanding the faults in economic decision-making, behavioral economics can also demonstrate better ways of making decisions that could benefit everyone, and, therefore, the economy.