It should be noted that this branch of economics, although it was already known to the specialized public, has achieved greater dissemination and included a broader public, due to the appearance of the book “Thinking fast, thinking slowly” by Daniel kahneman, laureate with the Nobel Prize in Economics 2002.

 

La behavioral economics integrates insights from psychological research into economic analysis, especially human judgment, and decision making under uncertainty.

To be clear, it is concerned with studying the specific decision-making process, and this work is carried out with certain particularities. One of these is that the theory is built and tested experimentally. That is, most of what is stated has a proven empirical basis. Debatable, with subtleties, with nothing definitive; but tested.

In addition to the novelty of the topic, another interesting reason, which has directly to do with the section Academic Bridge from our website; It is the way in which economic knowledge and theory are constructed.

When we watch the news or read the newspaper, it is quite common to find phrases like the following: “an increase in the interest rate would favor an increase in savings,” or “if a depreciation of the exchange rate is expected, the public will turn to the purchase of dollars.”

What lies behind these statements is that agents – people – behave rationally. That is, when faced with a given stimulus, which in our examples have been price movements, agents behave by giving the best possible response, conditional on the information they have available. That is, maximizing your profit.

In this way, the rationality hypothesis solves a huge number of difficulties when doing theory. In very general terms, homogeneous behavior is assumed for all agents involved in the economy, highlighting that the differences between the different decisions made lie in the particular restrictions faced by each agent, such as their budget or access to information, or simply because of your tastes.

The problem with the theory, let's say “traditional”, is that according to the criteria of behavioral economics, we rarely behave rationally. Being rational implies having an enormous information processing capacity and behavior permanently oriented towards calculation.

This academic scenario is where the works of Kahneman and Tversky emerge.

Some would argue that the appropriate phrase should be “orthodox economics,” rather than “traditional economics.” However, many non-orthodox schools of thought also implicitly or explicitly use some variant of rationality that goes in this direction.

And it must be clarified: Its use is not necessarily bad or good. Assuming rational behavior allows relevant conclusions to be generated at low cost.

The problem would seem to lie in elucidating at what level of analysis the application of this assumption makes sense, regardless of whether one believes it to be orthodox or non-orthodox, especially taking into account the practical consequences that could arise from misuse.

Finally, another good reason to comment on some aspects of behavioral economics is that this year is a election year. An enormous amount of money and resources are allocated to anticipating who will be the winning candidate, to knowing who will be the favored one to win this wheel of the political game. Citizens vote, and in that ritual they grant enormous power to a distant and diffuse someone, to occupy a chair or a bench and, above all, to make decisions.

According to the above, throughout this note we are going to expose the general guidelines of the theory, seeking to use as an example different interpretations of some aspects of the electoral process. Undoubtedly, the question that will be behind our examples is: how do we decide our vote? They will tell me: out of ideology, out of sympathy for the person, out of interest...

All valid reasons. Without excluding the above, advances in behavioral economics show that the intuitive aspect – not the rational one – has enormous weight, even in decisions such as the exercise of sovereignty through voting.

What's more, if the reader is patient and dares to finish reading this note, I would bet that a question will remain floating in the air: how do our representatives decide?

And then the psychologists appeared

The idea that man can be defined as a rational animal comes from afar. Although the concept has undergone multiple changes since Aristotle's definition to date, it should not be surprising that the variants of this approach have to fight for the podium.

A first problem, it is not to have the intuition that perhaps we-are-not-so-rational, but to demonstrate it. And not only that, it is also giving a better answer to the hypothesis of rationality.

An answer that can also be integrated into the current body of knowledge. That convinces members of a scientific community to abandon some of the concepts with which they have worked with relative success for a long time.

That it passes the technical requirements of a moment, and many others, etc. Undoubtedly, a lot of power relations intervene in this phenomenon, but also evidence.

Without ignoring power relations, let's focus on the latter: there is evidence that shows that in certain circumstances a decision can be rational and evidence that a large part of our decisions are not.

The answer provided by the behavioral economics approach to enable a systematic study of those behaviors perceived as anomalous by conventional economic theory is the splitting of the cognitive structure between two systems of thought.

The architecture proposed in the writings of D. Kahneman and A. Tversky recognizes the existence of two systems called sistema 1 y sistema 2, which can be associated with what is commonly called intuition and reason, respectively.

1. 1. To system 1 The characteristics of being are attributed to it: fast, parallel, automatic, effortless, associative, slow learning and emotional.

1. 1. To system 2 The characteristics of being are attributed to it: slow, serial, controlled, effortful, governed by rules, flexible and neutral.

One of the first findings of the theory is that behavior is not guided by the calculations that can be made, but by the impressions and information that the individual has available at the time of making a decision. A key property of intuitive thoughts is that they come to mind spontaneously.

They are done without conscious search or calculation, and without effort. For this reason, most judgments and decisions are made intuitively, and the rules that govern them are based mainly on visual analogies.

Otherwise, the reasoning It is done deliberately and with effort, which is why we should not be surprised by a description in which agents are not accustomed to thinking rigorously, and are often content with only a plausible judgment.

In other words, rational thinking is possible but comes at a cost, since the mental capacity necessary to do it is limited. Under this same premise, it also makes sense for system 1 to operate by performing world state updates with lower wear and tear than would occur under system 2 command.

And here comes a first example of the electoral scenario. Using the tools provided by behavioral economics, it could be interpreted that the average voter would have a disposition to be more attentive to looking at the photos of the candidates and vulnerable to advertising, than to know the platform or provide a vote according to their own tastes. .

Now, be careful: Political economy theories that assume only a rational individual also cannot explain why a voter would be willing to make an informed decision. The explanation from this point of view is simple.

Getting extensive information to make the best voting decision is an expensive activity, while the benefit of voting well is extremely marginal.

Let's look at a concrete example of the latter. In the legislative elections held on October 27, 2013, some 30.635.464 people were eligible, of whom 23.641.116 voted; that is, 77% of the register. The effective influence of a vote would be 0,00000423%. A very low benefit from the point of view of our hypothetical-rational voter.

Sherlock Holmes and Doctor Watson

Another popular book that uses a very original analogy, and quite easy to remember, is María Konnikova's book precisely titled: How to Think Like Sherlock Holmes?

The scheme proposed in the book is extremely effective, the author suggests that we think about sistema 1 / intuition as if he were Doctor Watson and sistema 2 / reason as if he were Sherlock Holmes.

Fantastic! Not only because both characters fit the description perfectly, but because in the rooms of Baker Street, after a client presents a case and leaves, the characters compare notes and talk. And just as Sherlock retreats into long pauses of silence to meditate on the different aspects of a case, it is Watson who carries the thread of the story. The same thing seems to happen in our heads: we are a Watson.

Let's see then what behavioral economics has to offer about the functioning of intuition, which is a fairly generic way of understanding how we are going to vote on average.

In order to avoid the cost of computing, system 1 reduces the processing of complex tasks to simpler operations, through an attribute substitution mechanism.

It is stated that a representation is mediated by a heuristic, when the individual evaluates a specific attribute of an object of said representation, replacing it with some other property of said object that is easier to interpret.

In this way, the costs that are avoided by giving a quick response to the situation or problem that arises reappear in the form of serious and systematic errors, which in theory are called biases. 

Unlike the theory of rational action, these biases respond to a structure, and therefore are predictable.

Consider, for example, the concept - quite widespread - of “monetary illusion”, which is identified when in a context of inflation agents perceive themselves as richer by seeing their nominal income increase, without taking into account the increase in prices.

The notion of heuristics could contribute to providing a foundation for the existence of the phenomenon, from an extremely novel and enriching level.

In the pioneering works of D. Kahneman and A. Tversky (1974), three mechanisms used in the formulation of judgments under uncertainty are described:

1. 1. La availability/accessibility heuristic, which is used when asking to estimate the frequency of a class or the plausibility of a particular development.

1. 1. La representativeness heuristic, which is usually used when asking to judge the probability that an object or event A belongs to class or process B.

1. 1. El adjustment from an anchor, which is usually used in numerical prediction, when a relevant reference value is available.

The first heuristic describes the ease with which some thoughts reach the mind before others, and consequently provides one of the keys to understanding how intuition works.

Under this mechanism, system 1 reacts more easily when presented with attributes of an object that are familiar to it.

In this way, when imputing probabilities, the heuristic operation replaces the feasibility of the occurrence of an event, weighting not only the expected frequencies, but:

1. 1. Due to the degree of association that the characteristics of that event have with the agent's prior knowledge.

1. 1. Because of its prominence.

1. 1. Or by the temporal distance between the observation and the occurrence of the event that the agent is evaluating.

In other words, from this point of view, an average citizen will analyze the most obvious data and those they find at hand, without delving into a more sophisticated search.

So if the availability heuristic works in this way, one cannot deny the wealth of new questions and intuitions that can be derived from this theory and that, of course, should be evaluated to be conclusive.

Having made the warning, and following the same order of enumeration above, let's see how some of these ideas could be translated into electoral behaviors:

• If a candidate credibly displays certain personal characteristics, whether fictitious or not, that have the particularity of being shared by a part of the electorate, it is highly likely that the candidate will become a figure with greater presence as a feasible option within the that reference group.

• The same applies to those candidates who have a greater relative advertising impact. Something that, due to the amount of resources spent on the campaign, is well known. Even so, be careful again: a rational voter could be tempted to vote for the candidate with more presence, not because he associates more presence with some desirable characteristic, but because he may be calculating that in this way he will not throw his vote to another candidate without chance.

• This is an extremely important characteristic, especially for the sector of undecided votes. What is being stated is that when making decisions, the weighting of the latest stimuli received can lead to having a decisive weight in the choice being considered. In other words, a candidate's history, his successes and failures, have a much lower weight than one would expect. That is to say, a large majority of candidates can effectively resist the file just by letting time pass.

Alexander Todorov, from the psychology department at Princeton University, carries out a line of research into how first impressions are formed.

In general terms, some of their experiments consist of showing photos of candidates who actually competed in an electoral contest in a region of a country; to citizens who live in another region, in order to ensure that the respondents are unaware of the candidates and the results of the elections that took place in the first region.

Todorov's work shows that the impressions caused only by the photos of unknown candidates on the citizens of the second region explain in a statistically significant way the result of the elections in the first. That is, opinions on photos from one population are a good predictor of the results of a vote from another population.

In recent works, the representativeness heuristic appears inserted in a more general class, called prototype heuristics. He prototype of a set is characterized by the average values ​​of the main properties of its members.

The high accessibility of the prototype information fulfills an important adaptive function, by allowing new stimuli to be efficiently categorized by comparing the particular characteristics of an element with those of the set; but at the cost of losing detailed information in that classification.

To make it simpler, the prototype heuristic gives theoretical support to the well-known saying: “tell me who you are with and I will tell you what you are like.” But be careful, only for first impressions.

In the specific case of the representativeness heuristic, probabilities are evaluated by the degree to which A is representative of B, that is, by the degree to which A resembles B.

Thus, when imputing probabilities, the operation of the representativeness heuristic replaces the feasibility of the occurrence of an event, weighting no longer by the expected frequencies, but by an emotional response that enables the extension of attributes from one element to another.

In terms of electoral examples, it is impossible not to think about the difference in knowledge that the average citizen has between the first candidates on the list - or simply the first -, with respect to the candidates that precede them further down. Suppose in this completely hypothetical scenario: let's imagine a list of candidates for deputies, where the first candidate is suitable (whatever that means) to hold the position for which he is running, while the remaining four who follow him, they are not.

If the first candidate manages to capture the attention of the electorate as a potable one, by representativeness heuristics, it is likely that the characteristics of the good candidate will be transferred to the image of the bad candidates, thus obtaining a voting intention that, on average, can reach to be contrary to the preferences of the voter himself, if he considered the global characteristics of the group.

Finally, about the anchoring effect, it cannot be said that it is properly a heuristic, but rather an adjustment procedure from a starting point, whether this is a piece of information, data or initial calculation; to a final estimate, which is entirely dependent on the starting point or anchor.

This means that different starting points generate different estimates that are biased towards the initial values.

The intuitive example that Kahneman uses in his book is the feeling of slowness that a driver experiences when going from driving on the road to driving in the city. The anchoring effect means that when going from a speed of 130 km/h to 40 km/h, the perceived speed seems much lower than those 40 km/h.

In light of the postulation of this model of cognitive system, the contribution made seems to be immense, at the same time that it is difficult to annex within the previous corpus.

Behavioral economics differs from standard economics by using a more realistic and therefore more complex model to explain the behavior of agents in a given context. All of which leads to generality being sacrificed to achieve greater realism.

Indeed, one of the criticisms that Kahneman himself mentions in one of his works is the lack of systematization of his theories into formal and generalizable behavioral models.

In this way, the field of research has been opened. On the one hand, explanations with different levels of rigor are appearing, by the most varied means, which are generating the reaction that “not everything can be explained by behavior.”

It would seem to be logical that this happens: partly the topic is new and has appeal for the reader, partly the alternative explanations based on statistical or econometric procedures are more demanding with the training of the public.

In fact, one of the questions with which Kahneman and Tversky began their joint work was to resolve the question of whether statistical thinking is intuitive or not.

The heuristics y biases (and the corresponding tests) seem to indicate that this is not the case, that the awakening of our system 2 is needed to be able to reach conclusions according to those rules.

However, the game is also open for academic production. There are recent works that show progress in the possibility of formalizing behaviors based on heuristics and biases, mixed with Bayesian analysis.

In subsequent publications in this section, we will try to disseminate some of these works, although the theme of the year will revolve around electoral issues.

For the moment, the question of how we vote remains unclear. However, there remains the feeling of thinking of the voter as someone susceptible to emotions, rather than a reader of platforms.

 

To know a bit more…

Regarding the experiments carried out with photos of candidates, and which are mentioned as an example, they have been based on two works by Alexander Todorov, which are detailed below and which, of course, do not exhaust the topic:

1. 1. Ballew, Charles. & Todorov, Alexander (2007). «Predicting political elections from rapid and unreflective face judgments». PNAS November 13, 2007 vol. 104 no. 46 17948-17953.

1. 1. Todorov, Alexander; Mandisodza, Anesu; Goren, Amir & Hall, Crystal (2005). "Inferences of Competence from Faces Predict Election Outcomes." SCIENCE, June 2005, Vol 308 no. 10.

Finally, The structure of concepts and the order of this article are based on two works by Kahneman. Both are intended as a kind of essay that summarizes the advances that have occurred in the field of behavioral economics.

1. 1. Kahneman, Daniel & Amos Tversky (1974) “Judgment Under Uncertainty: Heuristics and Biases.” Science, 185, 1124-1131.

1. 1. Kahneman, Daniel (2003). “Maps of bounded rationality: Psychology for behavioral economics.” AER, Dec 2003, 1449-1475.