Behavioural economics attempts to understand the effect of individual psychological processes, including emotions, norms, and habits on individual decision-making in a variety of economic contexts.
Behavioral economics is primarily concerned with the bounds of rationality of economic agents. Behavioral models typically integrate insights from psychology, neuroscience and microeconomic theory. The study of behavioral economics includes how market decisions are made and the mechanisms that drive public choice.
All economic behaviour involves decision-making by individuals, and traditional (neo-classical) theories of economic behaviour assume that economic agents apply rational thought to each and every decision to achieve the maximisation of personal benefit (utility) or, in the case of producers, the maximisation of profits. The assumption of the rational individual (‘economic man’ or homo economicus) is central to most micro-economic theory, and can be seen most clearly in marginal analysis. Marginal analysis suggests that economic agents carefully weigh-up the expected costs and benefits of alternative decisions based on accurate information, and select the option that maximises their personal gain. In other words, individual economic agents are driven by self-interest, and if all agents are driven by self-interest based on all the information they have, each marginal decision will be rational.
This idea underpins the theory of how markets work to allocate scarce resources, and is the basis of micro-economics, yet the real world seems full of examples of where decision making does not seem rational, nor in the individual’s self-interest. The cases of cigarette smoking, over-eating, and failing to save enough for retirement are just a few of the apparently irrational decisions routinely made by individuals across the developed world. Behavioural economics challenges the long held view in mainstream economics that individuals are ‘unemotional’ maximisers who make rational decisions rational actors being identified as homo economicus. It also offers suggestions as to how individuals can be ‘nudged’ towards more effective decision-making.
Challenging the assumptions of traditional economics
Behavioural economists identify at least three questionable assumptions contained in traditional theory.
- They the use ‘unbounded willpower’ to convert wants into actions and consumption (or production), and have absolute self-control when confronted with choices. In other words, they can resist making ‘poor’ choices.
- That individuals make decisions based on ‘unbounded (unlimited) rationality’ accurately processing all the information at their disposal.
- They are driven by ‘unbound selfishness’ to achieve maximum benefit for themselves.
Conventional economics assumes that all people are both rational and selfish. In practice, this is often not the case, which leads to the failure of traditional models. Behavioral economics studies the biases, tendencies and heuristics that affect the decisions that people make to improve, tweak or overhaul traditional economic theory. It aids in determining whether people make good or bad choices and whether they could be helped to make better choices. It can be applied both before and after a decision is made.
Before a decision is made, there needs to be a minimum of two options. Behavioral economics employs search heuristics to explain how a person may evaluate their options. Search heuristics is a school of thought that suggests that when making a choice, it is costly to gain information about options and that methods exist to maximize the utility that one might get from searching for information. While each heuristic is not wholistic in its explanation of the search process alone, a combination of these heuristics may be used in the decision-making process. There are three primary search heuristics.
Satisficing is the idea that there is some minimum requirement from the search and once that has been met, stop searching. Following the satisficing heuristic a person may not necessarily acquire the most optimal product (i.e. the one that would grant them the most utility), but would find one that is “good enough”. This heuristic may be problematic if the aspiration level is set at such a level that no products exist that could meet the requirements.
Directed cognition is a search heuristic in which a person treats each opportunity to research information as their last. Rather than a contingent plan that indicates what will be done based on the results of each search, directed cognition considers only if one more search should be conducted and what alternative should be researched.
Elimination by aspects
Whereas satisficing and directed cognition compare choices, elimination by aspects compares certain qualities. A person using the elimination by aspects heuristic first chooses the quality that they value most in what they are searching for and sets an aspiration level. This may be repeated to refine the search. i.e. identify the second most valued quality and set an aspiration level. Using this heuristic, options will be eliminated as they fail to meet the minimum requirements of the chosen qualities.
Heuristics and Cognitive effects
Outside of searching, behavioral economists and psychologists have identified a number of other heuristics and other cognitive effects that affect people’s decision making. Some of these include:
Mental accounting refers to the propensity to allocate resources for specific purposes. Mental accounting is a behavioral bias that causes one to separate money into different categories known as mental accounts either based on the source or the intention of the money.
Anchoring describes when people have a mental reference point with which they compare results to. For example, a person who anticipates that the weather on a particular day would be raining, but finds that on the day it is actually clear blue skies, would gain more utility from the pleasant weather because they anticipated that it would be bad.
This is a relatively simple bias that reflects the tendency of people to mimic what everyone else is doing and follow the general consensus. It represents the concept of “wisdom of the crowd”.
Stereotypes and anecdotes that act as mental filters are referred to in behavioral economics as Framing effects. People may be inclined to make different decisions depending on how choices are presented to them.
Biases and fallacies
While heuristics are tactics or mental shortcuts to aid in the decision-making process, people are also affected by a number of biases and fallacies. Behavioral economics identifies a number of these biases that negatively affect decision making such as:
Present bias reflects the human tendency to want rewards sooner. It describes people who are more likely to forego a greater payoff in the future in favour of receiving a smaller benefit sooner. An example of this is a smoker who is trying to quit. Although they know that in the future they will suffer health consequences, the immediate gain from the nicotine hit is more favourable to a person affected by present bias. Present bias is commonly split into people who are aware of their present bias (sophisticated) and those who are not (naive).
Also known as the Monte Carlo fallacy, the gambler’s fallacy is the unmerited belief that because an event occurs more frequently in the past it is less likely to occur in the future (or vice versa), despite the probability remaining constant. For example, if a coin had been flipped three times and turned up heads every single time, a person influenced by the gambler’s fallacy would predict tails simply because of the abnormal number of heads flipped in the past, even though of course the probability of a heads is still 50%.
Narrative fallacy is undue influence of a presented story or “narrative”. For example, a startup may get funding because investors are swayed by a narrative that sounds plausible, rather than by a more reasoned analysis of available evidence.
Loss aversion refers to the tendency to place greater weight on loss than disappointment. In other words, they are far more likely to try to assign a higher priority on avoiding losses than making investment gains. As a result, some investors might want a higher payout to compensate for losses. If the high payout is not likely, they might try to avoid losses altogether even if the investment’s risk is acceptable from a rational standpoint.
When a person places greater expectation on a particular outcome simply because that outcome had just occurred, that person may be affected by recency bias. To return to the coin flipping example, given that the previous one or two flips were heads, a person affected by recency bias would continue to predict that heads would be flipped.
Confirmation bias reflects the tendency to favour information or results that support one’s own beliefs or values.
Familiarity bias simply describes the tendency of people to return to what they know and are comfortable with. Familiarity bias discourages affected people from exploring new options and may limit their ability to find an optimal solution.
Status quo bias
Status quo bias describes the tendency of people to keep things the way they are. It is a particular aversion to change in favor of remaining comfortable with what is known.