Behavioural Economics

Sujoy Chakravarty Centre for Economic Studies and

Planning

What is behavioural economics? Behavioural economics is a new branch of economics that uses

theories, tools and techniques of analysis from social sciences such as psychology or anthropology that are used to enrich the model of human behaviour that has been used tradiBonally in neo-classical economics.

As it stresses observed agent behaviour rather than logical opBmizaBon algorithms, behavioural economists are oIen also experimental economists, who conduct lab and eld experiments in the vein of psychologists.

ObservaBons of deviaBon from theory predicBons may provide insights into building new theories, that improve upon exisBng ones. Eg.- herd behaviour, saBscingbehaviour, ecological raBonality, other-regarding preferences and prospect theory

Why do we need this?

Though economic theory predicts behaviour in a large number of economic problems, the predicBons are quite narrow in scope.

In the real world however we see a vast number of behavioural realizaBons:

The amount of contribuBon made to chariBes. The proclivity towards acquiring resources through corrupt

means.

CooperaBon displayed towards teammates and co-workers The wherewithal to take on monetary risks.

ConsumpBon and saving behaviour.

Economic Theory Over the last century has concerned itself more with raBonal

benchmarks and less with trying to model empirically observed behavior.

According to Smith (1989) most economists feel that economics is an a-priori science rather than an observaBonal one.

According to Milgrom and Roberts (1987, p. 185) no mere fact was a match in economics for a consistent theory. Thus most economic theorists believe that economic problems and agent behavior therein can be fully conceptualized by thinking about them.

Accordingly aIer the thinking has produced sucient technical rigour, internal coherence and interpersonal agreement, economists can then apply this to the world of data. (Smith, 1989, p. 152)

The bo[om line

The raBonal agent thus modeled is a self-interested maximizer always taking a decision that maximizes his expected wealth.

But from casual empiricism if we look around us we see serious violaBons of this behavioural norm.

Human beings are prone to voluntary acts of kindness someBmes moBvated by altruism.

Most people cooperate with their neighbours in the upkeep of their neighbourhoods.

Most would trust another human being uncondiBonally oIen suering negaBve consequences from this trusBng behavior.

Predictably or systemically irraBonal Are most people then irraBonal?

If that were the case shouldnt theory reect this divergence from the norm especially as this divergence is oIen systemaBc and not random?

Ariely (2008) refers to these divergences as predictably irraBonal ones.

Basu (1983), Sugden (1986) and Coleman (1990) have a[ributed social norms (especially those that inculcate values and a sense of morality) as modiers on our desire to maximize our material wealth.

Early glimmers of behaviourism

Adam Smith in The Theory of Moral Sen7ments (1759) builds on the work of David Hume (A Trea7se of Human Nature, 1739)

Here, Smith writes about an important psychological moBvaBon that governs the way that economic agents conduct exchange.

The parBcular moral senBment that Smith describes at length is sympathy, i.e. the feeling of compassion or concern for others.

This tempers self-interest in socio-economic transacBons and leads us to sacrice narrow proteering in order to maintain Bes of aecBon with our fellow human beings.

So then why do we need economic theory at all?

Economists have tradi7onally avoided explaining behavior as less than ra7onal for fear of developing many fragmented theories of mistakes.Erev and Roth (1998, p. 848)

Economic theory provides a behavioural (raBonal) benchmark of great generality against which we may compare observed behaviour.

The role of experiments The eld of experimental economics (not to menBon

experimental social psychology) stands at the centre of this debate on observed behavioural deviaBons from raBonal theoreBcal predicBon.

The method of controlled experiments from the Iies onwards has allowed us to test game theoreBc models as well as individual choice models with human subjects in the laboratory.

Observed economic behaviors are compared to raBonal theoreBcal benchmarks, divergences from the raBonal norm are noted and in certain cases theories are advanced to explain these deviaBons.

A dierence in approach A fundamental point of divergence between psychology/

cogniBve science and economics is related to the theoreBcal underpinnings behind various results.

Most economists dont really need a precise and accurate theory at the individual level, just as long as it is general enough to explain some of the observed behaviour accurately and generate an aggregate predicBon that is more or less accurate.

So elegance and generality are generally desirable in economic theory, whereas psychologists and cogniBve scienBsts are interested in modeling the precise nuances of behavior displayed by individuals.

An example A typical economics experiment on aitudes towards risk

would have the researcher make an assumpBon about the form of the uBlity funcBon (say constant relaBve risk aversion or CRRA) that the agents purportedly follow.

Using this funcBon and the choice response in the experiment, one can calculate some measure (maybe Arrow-Pra[) of risk aversion and then compare this across agents, over Bme, cross-culturally etc.

If anyone quesBons the validity of using this funcBonal form over another one, most of the Bme the answer that a theorist or an experimental economist would give you would be that it doesnt ma,er as long as everyones a2tude to risk is measured using the same CRRA specica

The as-if approach to behaviour

Most psychologists and cogniBve scienBsts would be quite unhappy with this as if way of evaluaBon and would be more interested in the cogniBve processes that govern the choice made by the decision maker.

Economists on the other hand, some measure which has good internal validity but potenBally scanty external support.

According to Camerer (1995), most economists have a one-size-ts-all approach to studying economic problems vis--vis psychologists.

if a task involves elicitaBon of a probability, most psychology experiments would frame the problem in a natural seing using a vigne[e. This would anchor the tasks to certain specic sBmuli.

Most economists would go ahead and a[empt to elicit the same probability using a more decontextualised device such as a pair of dice or a bingo cage.

This is in keeping with the insBtuBon free pedagogy of neoclassical economics where elicitaBon of a probability is coming up with a specic staBsBcal measure rather than an assessment of a contextualized measure of uncertainty.

One-size ts all

Bounded raBonality The origin of this boundedly raBonal approach is from Simons

(1955) idea of procedural raBonality whereby agents follow reasonable heurisBcs and on average achieve close to opBmal outcomes.

This is disBnct from substanBve raBonality, where the agent considers the enBre set of variables to make her decision.

The idea of bounded raBonality was one of failed opBmizaBon. Agents are unable to compute the opBmum and se[le for a second best saBscing outcome.

The more modern idea of ecological raBonality (Gigerenzer and Brighton, 2009) strongly opposes this idea that all heurisBcs are examples of failed opBmizaBon.

HeurisBcs: A new look at bounded raBonality NoBce that the idea of bounded raBonality implies that heurisBcs, which

do not a[empt to opBmize an objecBve funcBon with respect to all the relevant variables is a result of cogniBve limitaBons which force the decision maker to perform shoddy second best computaBons.

In contrast Gigerenzer and Brighton (2009) nd that heurisBcs are ecient cogniBve processes that ignore informaBon.

In contrast to the widely held view that less processing reduces accuracy, their study of heurisBcs shows that less informaBon, computaBon, and Bme can in fact improve accuracy. Gigerenzer and Brighton specically show that there is a trade-o between bias and variance. More variables decrease bias but increase variance.

According to this fast and frugal or ecologically raBonal approach to computaBon, Homo HeurisBcus has a biased mind and ignores part of the available informaBon, yet a biased mind can handle uncertainty more eciently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies.

What exactly is a controlled experiment in econ ? It is a way of obtaining data on how economic agents behave (i.e.- the

acBons they take) in a game, decision problem or a market.

Subjects are recruited in a randomized way to be agents in a stylized environment that studies a parBcular economic problem.

The interacBon is described to the parBcipaBng subjects (i.e.- the economic agents) with the help of laboratory instrucBons that present in detail the tasks that he or she needs to perform.

Monetary incenBves are provided in a salient way, so that agents can map the acBon space to the payos.

In other words, the laboratory interface is a real market or game that has agents moBvated by nancial incenBves.

Examples include a laboratory double aucBon market, an oligopoly game or a two-player Prisoners Dilemma.

Findings from experimental studies Game theory people are not as hyper-raBonal as predicted by

theory. Though self interest is an important moBvator for decisions made, it is by no means the only one. People display preferences for altruism, reciprocity, spite and mutualism. E.g.- cooperaBon in prisoners dilemma, egalitarian shares in bargaining games. Culture and norms play a role in shaping agent behaviour.

Individual decision making Humans are prone to systemic biases making their behaviour diverge considerably from the model of the expected uBlity maximizer. E.g.- endowment eect, reecBon eect. These are oIen to do with the procedures humans use to aggregate payos.

Since most real world problems involve both individual decision making as well as interacBve components we see procedural as well as preferenBal divergences from theory.

OUTCOMES Prices, allocations

CHOICE BEHAVIOUR

ENVIRONMENT Agent values, costs,

endowment, technology

INSTITUTIONS Language of the market

Rules of communication and contract

Extensive form structure

CULTURE and DEMOGRAPHICS

Social Norms

Pre-1960 institution free theory

Post 1960 institutions matter

Post 1980 culture and demographics matter.

Figure 1: Institutions, culture, environment and behaviour in economics (extended from Smith, 1989)

Prisoners and tragedies The meta analysed cooperaBon in 2 X 2 prisoners dilemma

experiments show cooperaBon rates of greater than 50 %

Public goods games show cooperaBon rates of 20-40 %

ContribuBon to public goods is dependent on cultural norms with some populaBons showing very high cooperaBon and others close to Nash equilibrium behaviour (Henrich, et al., 2001, 2005)

Chakravarty et al. (2013) nd very high rates of cooperaBon (40-50 %) among high alBtude village communiBes in Kumaon.

Altruism and warm glow Altruism Increase in uBlity from giving to an other with no

explicit or implicit reciprocity.

Warm glow Increase in uBlity from the act of giving with no concern regarding the recipient.

In dictator games a meta give rate of 27 % is seen (Engel, 2011)

Dictator giving is sensiBve to contexts, framing, reference points and social environments.

Banerjee and Chakravarty (2014) nd that framing and implied property rights over the endowment determine dictator outcomes.

Trust and reciprocity A trust or investment game is one where a proposer chooses

whether to keep his endowment E or send x, keeping (E-x). The respondent obtains 3x (original investment trebled) and decides the amount [0, 3x] to send back to the proposer.

An ulBmatum bargaining game is one where a proposer decides what part (x) of his endowment (E) he will give to the respondent. If the respondent accepts then the split is (E-x, x) if not then neither get anything (0, 0)

What are the Nash equilibria of the above games?

For TG, in giving x the proposer displays altruism and forward looking reciprocity and in returning y, the respondent displays strong reciprocity.

For UBG, the respondent vetoes only at the cost of making zero payo.

How did experimental subjects behave ?

Trust and reciprocity

Berg at al. (1986) nd that a substanBal number of subjects do not send zero, i.e.- are trusBng and a signicant amount of trust is reciprocated.

UlBmatum bargaining [Bowles, 2004] Game Results Interpreta

A theory of other-regarding or social preferences

Says that an agent is not merely interested in increasing his own payo from a game, but also concerned about the other agents payo, i.e.- he is inequality averse.

Thus Ui = Ui(own, | own other|), increasing in both arguments.

Fehr and Schmidt 1999, Falk and Fischbacher, 1998; Fehr and Schmidt, 1999; Bolton and Ockenfels, 1999; Rabin, 1993; Charness and Rabin, 1999; Levine, 1998 all have models of social preferences.

Some of these models use reciprocity/reputaBon and are not staBc.

Norms and culture A very important intellectual direcBon that emerged out of the

anomalies observed in laboratory experiments was the study of the eect of culture and demographics on economic behaviour through the formaBon and enactment of social norms.

Sen (1973) alludes to social norms when he discusses the prevalence of cooperaBve acBon in the Prisoners Dilemma game.

Arrow (1982) clearly states that The model of laissez-faire world of total self-interest would not survive for ten minutes; its actual working depends on an intricate network of reciprocal obligaBons, even among compeBng rms and individuals.

Preference reversals Problem 1: Choose Between the following two risky bets, A or B:

A. 2,500 with probability of .33, 2,400 with probability of .66,

0 with a probability of .01

B. 2,400 with certainty

---------------------------------------------------------------- Problem 2: Choose between the following risky bets C or D:

C: 2,500 with probability .33, 0 with probability .67

D: 2,400 with probability .34, 0 with probability .66.

N = 72 A [18%] and B [82 %]

Majority display preferences of this type:

U(2,400) > .33U(2,500) + .66U(2,400) --- (I)

N = 72 C [83%] and D [17%]

Thus most people displayed preferences of the form:

.33U(2,500) > .34U(2,400) --- (II)

(I) and (II) are opposite to each other. This was rst documented by Maurice Allais (1953)

Loss domain Problem 3: A: 4000 with prob = 0.8 0 with prob = 0.2

B: 3000 with certainty

Problem 4:

C: - 4000 with prob = 0.8 0 with prob = 0.2

D: - 3000 with certainty

The reecBon eect

Preferences are risk averse over gains and risk preferring over loss domains. We are also loss averse, i.e.- a[ach a greater weight to a loss as compared to a gain.

Chakravarty and Roy (2009) documents this over both risky and ambiguous preferences.

Prospect theory Formulated by Kahneman and Tversky(1979). Its salient points:

People overweight the importance of unlikely events and correspondingly overweight near certain events.

People respond to framing, i.e.-equivalent outcomes are treated dierently depending on the manner in which the outcomes or the decision seing are described.

Provides a conceptual framework for dealing with situaBon-dependence. If the uBlity funcBon is to explain behaviour its arguments should be changes in states or events rather than the states themselves. Thus, the value individuals place on states depends on the rela7onship of the state to the status quo (ini7al wealth, state enjoyed by peers, etc).

Equity Premium Puzzle Given the return of stocks and bonds over the last century, an unreasonably

high level of risk aversion would be necessary to explain why investors are willing to hold bonds at all (Mehra and Presco[ (1985)).

Benartzi and Thaler (1995) combined two behavioral conceptsloss aversion (Kahneman and Tversky (1979)) and mental accounBng (Thaler (1985))to provide a theoreBcal foundaBon for the observed equity premium puzzle.

Thaler et al. (1997), Gneezy and Po[ers (1997), and Gneezy, Kapteyn, and Po[ers (2003) have all observed individual behavior consistent with the Myopic Loss Aversion (MLA) conjecture.

Individuals are loss averse and oIen have myopic (short term) ways in which they evaluate their por~olios. Both of these traits make them choose bonds over equiBes.

It is assumed that with an increase in evaluaBon periods (i.e.- less myopic decision making) may make people hold less of their wealth in bonds.

Equity-premium puzzle experiments Haigh and List (JoF, 2005) conduct an experiment in lo[ery

choices and show that MLA is important in decisions made not just by students but also by 54 professional futures and opBons pit traders from the Chicago Board of Trade.

The traders display more MLA than the students.

Anchoring and reference points Anchoring eects-IniBal impressions become reference points

that anchor subsequent thoughts and judgments.

Salesperson has three items for sale-expensive, medium high priced, and cheap. Show the customer the expensive item rst, which acts as an anchor. Makes it easier to sell the medium high priced item.

DramaBc or easy-to-recall events oIen become strong anchors. For example, the vividness of the horrible events of September 11 caused many to view airline travel as too risky, but many experts believe that travel has never been safer.

When NYSE trading begins traders are more careful but over the day their behaviour becomes more risk preferring and by closing Bme they are almost risk neutral. Why is this happening?

Framing and preferences Tversky and Kahneman (1981) told people to assume there was disease aecBng 600 people and they had two choices:

Program A, where 200 of the 600 people will be saved .

Program B, where there is 33% chance that all 600 people will be saved, and 66% chance that nobody will be saved.

They then oered them another two choices: Program C, where 400 people will die, 200 people live.

Program D, where there is a 33% chance that nobody will die, and 66% chance that all 600 people will die.

Asian Disease Problem

The majority of people selected A, showing a preference for certainty or risk aversion.

Most people now selected D, seeking to avoid the loss of 400 people.

NoBce how the framing makes the dierence. Prospects A and C are the same, and B and D are the same.

Framing the prospect as a gain makes people risk averse. Framing the prospect as a loss makes people risk takers.

Status quo bias and endowment eect The endowment eect is peoples tendency to value

something more highly when they own it than when they dont

Example: experiment in which median owner value for mugs was roughly twice the median non-owner valuaBon

Some economists think this reects something fundamental about the nature of preferences

IncorporaBng the endowment eect into standard theory implies an indierence curve kinked at the consumers iniBal consumpBon bundle Smooth changes in price yield abrupt changes in consumpBon

Endowment Eect Half the parBcipants were given mugs available at the campus bookstore

for $6 The other half were allowed to examine the mugs Each student who had a mug was asked to name the lowest sale price Each student who did not have a mug was asked to name the highest

purchase price Supply and demand curves were constructed and the equilibrium price

was obtained Trade followed There were four rounds of this

Bias Toward the Status Quo: Default Eect

When confronted with many alternaBves, people someBmes avoid making a choice and end up with the opBon that is assigned as a default

Example: Experiment showing that more subjects kept $1.50 parBcipaBon fee rather than trading it for a more valuable prize when the list of prizes to choose from was lengthened

Possible explanaBon is that psychological costs of decision-making rise as number of alternaBves rises, increasing number of people who accept the default

ReBrement saving example illustrates the default eect when the stakes are high

13-40

Default eect: reBrement

Prior to April 1, 1998, the default opBon was nonparBcipaBon in the reBrement plan

AIer April 1, 1998, all employees were by default enrolled in a plan that invested 3% of salary in money market mutual funds

Only the default opBon changed

Dynamic inconsistency

Hyperbolic discounBng-people generally prefer smaller, sooner payos to larger, later payos when the smaller payos would be imminent; but when the same payos are distant in Bme, people tend to prefer the larger, even though the Bme lag from the smaller to the larger would be the same as before.

When given a choice, some people would prefer $50 today to $100 one year from now, but would choose $100 six years from now versus $50 ve years from now.

Examples Lots of people want the IT dept. to withhold more

than they owe in taxes so they get a big refund check. This behavior amounts to giving the IRS an interest free loan.

School teachers who work 9 months are given the opBon of receiving their salary over 9 months or over 12 months. Many choose the 12 monthly checks because they dont trust themselves. They lose interest income.

Before you choose a college think of the reputaBon the college has: is it a diploma mill or does it require hard work?

Most people prefer the college to have a good reputaBon, but once they arrive, they oIen prefer easy classes.

Poverty and cogniBon Recent work by Shar and Mullainathan (2013) Poverty and all

its related concerns require so much mental energy that the poor have less remaining brainpower to devote to other areas of life.

As a result, people of limited means are more likely to make mistakes and bad decisions that may be amplied by and perpetuate their nancial woes.

Their work could explain a conundrum of public policy: If you give an individual Rs. 1000, why does he not invest it (his marginal uBlity of a Rupee is high) and instead buy alcohol?

Chakravarty and Warglien (unpublished, 2013) demonstrate that poor people may be much more myopic in their evaluaBon of Bme.

Minor temptaBons Ariely and his colleagues gave thousands of people 20 number

problems. When they tackled the problems and handed in the answer sheet, people got an average of four correct responses.

When they tackled the problems, shredded their answers sheets and self-reported the scores, they told the researches they got six correct responses. They cheated a li[le, but not a lot.

He put cans of Coke and plates with dollar bills in the kitchens of college dorms. People walked away with the Cokes, but not the dollar bills, which would have felt more like stealing.

He had one blind colleague and one sighted colleague take taxi rides. The drivers cheated the sighted colleague by taking long routes much more oIen than they cheated the blind one, even though she would have been easier to mislead. They would have felt guilty cheaBng a blind woman.

So Given that these minor moral transgressions are in of

themselves largely innocuous there is no real reason for us to correct them.

However if everyone in the populaBon performs them, can we end up with harmful social outcomes?

How can we prevent these ?

Dan Ariely (2012) The (Honest) Truth About Dishonesty.