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ECONOMICS & PSYCHOLOGY

Behavioral Economics, Neuroeconomics, Behavioral Finance, Social Psychology
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Marco Carrasco Villanueva

on 1 December 2016

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Transcript of ECONOMICS & PSYCHOLOGY

ECONOMICS & PSYCHOLOGY
BEHAVIORAL ECONOMICS & NEUROECONOMICS:
Beyond the Limits of Human Economic Rationality


SOCIAL PSYCHOLOGY
EXPERIMENTAL ECONOMICS
Economics & Psychology: ¿
PSYCHONOMICS
?
Intersection between Economics and Psychology.
More extensively, the study of the impact of cognitive, social, emotional, and neurobiological factors on economic decisions.
The study of the decision-making biases of economic agents (individuals and institutions) as well as their consequences.
BEHAVIOURAL ECONOMICS
Behavioural Finance
Behavioural Game Theory
Evolutionary Psychology
Experimental Economics
Preferences
Consumption decisions
Neuroeconomics
Cognitive Psychology
Economics of Happiness
& Subjective States
Social Psychology
Neo-institutionalism
SOURCE:
Carrasco, M. (2010).
Psychonomics: Psychología y Economía
. Retrieved from http://thepsychonomics.blogspot.com.
Schuldt, J. (2013).
Civilización del desperdicio: Psicoeconomía del consumidor
. Lima: Universidad del Pacífico.
Neuroscience of Decision-making
NEUROECONOMICS
M.Sc. Marco CARRASCO VILLANUEVA
MASTER of Research in ECONOMICS & MANAGEMENT
Mention in Economics & Psychology
UNIVERSITÉ PARIS 1 PANTHÉON-SORBONNE
Université Paris 5 René Descartes

Neuroeconomics
Behavioral Economics
Behavioral Finance
Behavioral Game Theory
December, 2015
Lima, Peru

Experimental Economics
Economics of Happiness
Cognitive Psychology
Social
Psychology

Neuroscience
BEHAVIORAL ECONOMICS
Adam Smith
In
The Wealth of Nations
, published in 1776, Adam Smith famously argued that economic behavior was motivated by self-interest.
However, 17 years earlier in 1759, Smith had proposed a theory of human behavior that looks anything but self-interested.
In his first book,
The Theory of Moral Sentiments
, Smith argued that behavior was determined by the struggle between “passions” and the “impartial spectator.”
Chapter 1:
Economics "& Psychology?"
BE and Its Applications
Chapter 5:
Current Applications
Amos Tversky & Daniel Kahneman
However, research in cognitive psychology did not come into its own until Daniel Kahneman and Amos Tversky (deceased in 1996) published their findings on judgment and decision-making.
Chapter 3:
The Foundations of
Behavioral Economics
dddghgh
Chapter 7:
Towards a Unified Theory?
Prospect Theory
DANIEL KAHNEMAN
(ISR-USA)
PhD. Psychology
University of California, Berkeley
2002 Nobel Memorial Prize in Economic Sciences

PSYCHOLOGY &
BEHAVIORAL ECONOMICS
Princeton University
AMOS TVERSKY
(ISR)
PhD. Psychology
University of Michigan

COGNITIVE PSYCHOLOGY &
BEHAVIORAL ECONOMICS
Hebrew University &
Stanford University
Optical illusions
Chapter 2:
Illusions, Biases and Heuristics
Chapter 4A:
Prospect Theory and Beyond
Behavioral
Public Economics
: Welfare and Policy Analysis with Nonstandard Decision-Makers
(
B. Douglas Bernheim and Antonio Rangel
)
Peter Diamond (USA)
MIT, University of California, Berkeley
Political economics, Welfare economics, Behavioral economics
2002 Nobel Memorial Prize in Economic Sciences
Eric Maskin (USA)
Harvard University, MIT, Princeton University, University of Cambridge
Game theory
2007 Nobel Memorial Prize in Economic Sciences
Psychology and
Development Economics
(
Sendhil Mullainathan
)
Behavioral
Law
and Economics
(
Christine Jolls
)
Fairness, Reciprocity, and
Wage Rigidity
(
Truman F. Bewley
)
Behavioral Economics and
Health Economics
(
Richard G. Frank
)
Behavioral Economics of
Organizations
(
Colin F. Camerer
and
Ulrike Malmendier
)
WRAP-UP PANEL
(
Eldar Shafir
,
Jean Tirole
,
Timothy D. Wilson
and
Peter Diamond
)
How much does all of this really matter to everyday decision making? How does it alter what we would conclude by applying mainstream analysis?
SAVING
: Increase savings and donations by making participation the default option (Ariely). To investigate saving and retirement behavior using a quasi-hyperbolic discounting models.
BEHAVIORAL FINANCE
: Test the Efficient Market Hypothesis. It does not always hold (Shiller, 2013). Important role of biases, such as overconfidence and emotions.
MARKETING & ORGANIZATIONAL BEHAVIOR
: Marketing employs techniques that are consistent with some finding of BE. Organizational behavior stands out as a field that has incorporated many of the results (Bazerman).
LABOR ECONOMICS
: Stress the importance of fundamental psychological, sociological and cultural foundations of labor supply decisions.
LAW AND ECONOMICS
: The ties between economics and law have been increasing, based on rational choice theory. Some prominent lawyers and economists are attempting to modify the movement to incorportate the emerging findings from behavioral economics: e.g. initial distribution of property does matter in the way we behave, emotions have a role, etc.
TAX INCENTIVE ALTERNATIVES
: Economic psychologists have long shown that framing of tax forms and the accompanying instructions offered can lead to differences in the way in which information is perceived and the degree of tax compliance.
MONETARY POLICY
: Impact of MP also is influenced by differences in the intertemporal discount rate employed by different groups in the economy.
MACROECONOMIC ANALYSIS
: Promising potential suggested by the works on saving, the advances in behavioral finance, and the contributions in discovering better micro assumptions underlying macroeconomic theory.
NUDGES & PUBLIC POLICY
: To improve empirical predictions and policy decisions. Behavioral economics can contribute by offering new policy tools, improving predictions about the effects of existing policies, and generating new welfare implications.
EXPECTED UTILITY
Risk averse
Risk
seeking
w(p)
p
w(p) = p
Pessimistic & Risk averse
= -Risk averse
Optimistic & Risk averse
= +Risk averse
Pessimistic & Risk seeking
= +Risk seeking
Optimistic & Risk seeking
= -Risk seeking
w(p)
w(p)
w(p)
p
p
p
Pessimistic
w(p)<p
Optimistic
w(p)>p
*While most authors in the theoretical literature of RDU assume a probability weighting function that underweights all probabilities—convexity—, empirical research has found mostly inverse S-shapes functions (Wakker, 2010)
CUMULATIVE PROSPECT THEORY
CPT, a revised version of the original PT (Tversky & Kahneman, 1992) integrates the idea of weighted probability functions with the former extensions of PT.
It replaces the utility function by a value function which depends on relative pay-offs, v(x), while also replaces cumulative prob. with weighted cumulative ones, w(p).
The value function in CPT has two main parameters. "Sigma" represents the curvature of the value function (risk aversion in EUT). "Lambda" indicates the degree of loss aversion.
GAINS
LOSSES
w(p)
p
v(x)
x
SOURCE:
Schwartz, H. (2008).
A Guide to Behavioral Economics.
Virginia, USA: Higher Education Publications, Inc.
In mainstream economics, risk aversion is commonly evaluated assuming the EU maximization framework (Harrison & Rutström, 2008).
In this framework, a linear utility function corresponds to a risk neutral individual, while convex and concave utility functions correspond to risk seeking and risk averse individuals, respectively.
The degree of risk aversion is measured based on the normalization of the second derivative of the utility function, u(W), which leads to the common Arrow-Pratt measures of absolute and relative risk aversion (Arrow, 1965; Pratt, 1964).
What would you most prefer?
18 chocolates now (7 pm)
20 chocolates in an hour (8 pm)
What would you most prefer?
18 chocolates next week at 7 pm
20 chocolates next week at 8 pm
SOURCE:
Story, G. W., Vlaev, I., Seymour, B., Darzi, A., & Dolan, R. J. (2014). Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.
Frontiers in Behavioral Neuroscience
, 8.
Laibson, D. (2011).
Lecture: Quasi-hyperbolic discounting
. Harvard University.

Although adhering to the tradition of cognitive psychology, Kahneman’s research has equally well been directed towards economists. Many of his articles have been published in economics journals; one article, Kahneman and Tversky (1979), even has the highest citation count of all articles published in
Econometrica
, by many considered the most prestigious journal in economics.
Chapter 6:
The Rise of Behavioral Economics?
Behavioral Economics and Behavioral/Decision Science Program/Groups
Source:
Samson, A. (2014). The Behavioral Economics Guide 2014 (1st edition). Retrieved from http://www.behavioraleconomics.com.
MSc. Marco CARRASCO VILLANUEVA
marco.carrascovillanueva@outlook.com
INSTITUTO RAÚL PORRAS BARRENECHEA
Universidad Nacional Mayor de San Marcos

Chapter 2:
The Threshold of Decision Making
Chapter 1:
Neuroscience
Neuroscience is the scientific study of the nervous system.
Traditionally, it has been seen as a branch of biology.
It is currently an interdisciplinary science that collaborates with other fields such as chemistry, cognitive science, computer science, engineering, linguistics, mathematics, medicine (including neurology), genetics, and allied disciplines including philosophy, physics, and psychology.
It also exerts influence on other fields, such as neuroeducation, neuroethics, neurolaw, and neuroeconomics.
Methods in Neuroscience
Chapter 5:
Current Methods
Chapter 3:
Neuroscience of Decision Making
Chapter 6:
Some Experiments
If we, as
scholars, were to be so bold as to discard
Friedman's as if
assumption and instead hypothesize that the
computations businessm
en, billiard players, and regular choosers
appear to perform
are actually being performed by their brains (where
else they
could be performed I myself simply cannot imag
ine), then
we gain something important: we gain the ability to te
st our
economic theories with both neurobiological and be
havioral
tools.
Chapter 7:
Towards a Hard Theory?
Chapter 4:
The Realm of the Brain
NEUROSCIENCE
BEHAVIORAL GAME THEORY
COGNITIVE PSYCHOLOGY
ECONOMICS OF HAPPINESS AND SUBJECTIVE STATES
BEHAVIORAL FINANCE
ECONOMIC PSYCHOLOGY
Economic
Psychology

Simon (1956) proposed an approach to information processing and decision-making based on bounded rationality.
BOUNDED
RATIONALITY
DECISION
MAKING
Edwards (1954) introduced decision-making as a research topic for psychologists, outlining an agenda for future research.
Homo Economicus
VS
Homer Economicus
In recent years, the most prevalent version of rational choice theory, expected utility theory, has been challenged.
SOURCE:
Maafi, H. (2014).
Behavioral Finance
. Université Paris 1 Panthéon-Sorbonne.
Allais (1953) outlined a psychology-based positive theory of choice under uncertainty.
ALLAIS PARADOX
However, until recently Economic theory followed the path of "rational" choice theory (goal-oriented, reflective/evaluative, consistent across time and situations VS random, impulsive, conditioned or adopted by imitation).
E.g. Expected Utility assumptions and axioms (Maafi, 2014):
Tversky, Kahneman and colleagues demonstrated several replicable ways in which human judgments and decisions differ from rational choice theory. They explained human differences in judgement and decision making in terms of heuristics.
Cognitive biases
0. Representativeness.
It is used when making judgments about the probability of an event under uncertainty. People make predictions based on
how representative something is
(similar), rather than based on relative base rate information.
21
Heuristics involve mental shortcuts which provide swift estimates about the possibility of uncertain occurrences. They are simple for the brain to compute but sometimes introduce "
severe and systematic errors
".
Half a century ago:
Allais (1953) outlined a psychology-based positive theory of choice under uncertainty.
Edwards (1954) introduced decision-making as a research topic for psychologists.
Simon (1956) proposed an approach to information processing and decision-making based on bounded rationality.
PROSPECT THEORY
Rank-dependent utility theory introduced the idea to replace cumulative probabilities with its weighted cumulative ones, w(p).
With this addition, it was possible to have an individual with both concave and convex components regarding his risk preference—even assuming an initial linear utility function (Harrison & Rutström, 2008).
RANK-DEPENDENT UTILITY
Characteristics of Prospect Theory:
Reference dependence:
When evaluating outcomes, the decision maker has in mind a "reference level". Outcomes are then compared to the reference point and classified as "gains" if greater than the reference point and "losses" if less than the reference point.
Loss aversion:
Losses bite more than equivalent gains. In their 1979 paper in
Econometrica
, Kahneman and Tversky found the median coefficient of loss aversion to be about 2.25, i.e., losses bite about 2.25 times more than equivalent gains.
Non-linear probability weighting:
Evidence indicates that decision makers overweight small probabilities and underweight large probabilities – this gives rise to the inverse-S shaped "probability weighting function".
Diminishing sensitivity to gains and losses:
As the size of the gains and losses relative to the reference point increase in absolute value, the marginal effect on the decision maker's utility or satisfaction falls.
Prospect theory is able to explain everything that the two main existing decision theories – expected utility theory and rank dependent utility – can explain. However, the converse is false. Prospect theory has been used to explain a range of phenomena that existing decision theories have great difficulty in explaining. These include backward bending labour supply curves, asymmetric price elasticities, tax evasion, co-movement of stock prices and consumption etc.
Chapter 4B:
(Quasi-)Hyperbolic Discounting
Hyperbolic discounting with a high discount rate. At t1, when both rewards are distant, the larger later reward is preferred, i.e., V(l, t3, t1) > V (s, t2, t1), however the smaller sooner reward becomes increasingly desirable as it approaches in time
Given two similar rewards, humans show a preference for one that arrives sooner rather than later. Humans are said to discount the value of the later reward, by a factor that increases with the length of the delay. This process is traditionally modeled in form of exponential discounting, a time-consistent model of discounting. A large number of studies have since demonstrated that exponential discounting is systematically being violated.
Hyperbolic discounting is a particular mathematical model devised as an improvement over exponential discounting, in the sense that it better fits the experimental data about actual behavior. It is a time-inconsistent model of discounting that has been observed in both human and non-human animals.
DAVID LAIBSON
(USA)
PhD. Economics
Massachusetts Institute of Technology

MACROECONOMICS &
BEHAVIORAL ECONOMICS
Harvard University
FINANCIAL MARKETS (2011) (ECON 252)
Behavioral Finance and the Role of Psychology
Min. 40:40 - Chapter 5:
Overconfidence, and Related Anomalies, Opportunities for Manipulation
[https://youtu.be/chSHqogx2CI]
Current Applications:
BEHAVIORAL FINANCE
The more object X is similar to class Y, the more likely we think X belong to Y.
Initial estimated values affect the final estimates, even after considerable adjustments.
The easier it is to consider instances of class Y, the more frequent we think it is.
[...]
Current Applications:
NUDGES & PUBLIC POLICY
ROBERT SHILLER
(USA)
PhD. Economics
Massachusetts Institute of Technology
2013 Nobel Memorial Prize in Economic Sciences

BEHAVIORAL FINANCE
Yale University
Rationality
Irrationality
Bounded Rationality
SOURCE:
Glimcher, Paul W. (2010).
Foundations of Neuroeconomic Analysis
. Oxford University Press.
Tetlock, P. E., & Mellers, B. A. (2002). The great rationality debate.
Psychological Science
, 13(1), 94-99.
Why do people behave the ways that they do?
Can we predict the behavioral decisions made by individuals and groups?
What guides human choice?
What are the origins of our preferences; how and why do they change?
SOURCE:
Maafi, H. (2014).
Behavioral Finance
. Université Paris 1 Panthéon-Sorbonne.
SOURCE:
Maafi, H. (2014).
Behavioral Finance
. Université Paris 1 Panthéon-Sorbonne.
BIOLOGÍA
ECONOMÍA
PSICOLOGíA
NUDGES
&
PUBLIC POLICY
SOURCE:
Glimcher, P. W., Camerer, C. F., Fehr, E., & Poldrack, R. A. (Eds.). (2013).
Neuroeconomics: Decision Making and the Brain
. Academic Press.
Two Trends, One Goal
The result was an interesting split that persists in neuroeconomics today.
Nowadays, the two communities, one predominantly behavioral economic and the other predominantly neuroscientific, are approaching a union from two directions.
A group of behavioral economists and cognitive psychologists looked towards functional brain-imaging as a tool to both test and develop alternatives to neoclassical/revealed preference theories.
A group of physiologists and cognitive neuroscientists looked towards economic theory as a tool to test and develop algorithmic models of the neural hardware for choice.
Some neurobiologists outside the emerging neuroeconomic community argued that the complex normative models of economics would be of little value for understanding the behavior of real humans and animals.
Some economists, particularly hardcore neoclassicists, argued that algorithmic-level studies of decision making were unlikely to improve the predictive power of the revealed-preference approach.
Level of complexity
NEUROECONOMICS
gene
biosphere
society
cognition
brain
neuron
IC
Insular
Cortex
LIP
Lateral
IntraParietal
Cortex
CHOICE
OUT
DLPFC
DorsoLateral
PreFrontal Cortex
ACC
Anterior
Cingulate
Cortex
MPFC
Medial
PreFrontal
Cortex
OFC
OrbitoFrontal Cortex
VS
Ventral
Striatum
AMYGDALA
SUBJECTIVE
VALUE IN
FEF
Frontal Eye
Fields
SC
Superior Colliculus
VALUATION
STAGE
CHOICE CIRCUIT
To this end, a neuroeconomist must propose, if he or she is serious, a "Hard theory" of economic behavior -a because theory. We must propose a theory without as ifs. We must propose an explicit theory of mechanism that can be tested simultaneously at the neural, psychological and economic levels of analysis. That simply has to be the structure of any Hard theory of economic behavior that seeks to unite neurobiological, psychological, and economic explanations of behavior under a neuro-economic framework.
A Response to Friedman's
as if
assumption
Neurons (1899)
Neurons (2011)
The scope of neuroscience has broadened to include different approaches used to study the molecular, cellular, developmental, structural, functional, evolutionary, computational, and medical aspects of the nervous system. The techniques used by neuroscientists have also expanded enormously, from molecular and cellular studies of individual nerve cells to imaging of sensory and motor tasks in the brain. Recent theoretical advances in neuroscience have also been aided by the study of neural networks.
DC ---> tDCS
ElectroEncephaloGraphy
Positron Emission Tomography
Transcranial Magnetic Stimulation
Functional Magnetic Resonance Imaging
Magnetic Resonance Imaging
Direct-Current
Transcranial Direct-Current Stimulation
MEG (Cohen, 1968)
Magnetoencephalography
Computed Tomography
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SPATIAL AND TEMPORAL RESOLUTIONS
METHODS
TIMELINE
A Unified Theory of Economic Behavior?
A Unified Theory of Economic Behavior?
WHY NOT?
"If you want a
single, unified theory of economic behavior we already have the best one available
, the selfish, rational agent model. For simplicity and elegance this cannot be beat. [...]
The problem comes if, instead of trying to advise them how to make decisions, you are trying to predict what they will actually do. Expected utility theory is not as good for this task. That is the purpose for which
Kahneman and Tversky's descriptive alternative,
prospect theory, was invented.
[...]
As people make progress filling in the holes in prospect theory we can do a better job of understanding and predicting behavior
, but prospect theory was already more complicated than expected utility theory, and
adding these dimensions further adds to the complexity.
[...] Just as psychology has no unified theory but rather a multitude of findings and theories, so
behavioral economics will have a multitude of theories and variations on those theories
".
—Richard Thaler
RICHARD THALER
PhD. Economics
University of Rochester

BEHAVIORAL FINANCE
University of Chicago

"I told him that
I was working with Nick Chater on a theory of everything. I actually meant it a little bit tongue in cheek, but not totally.
[...] My view is that
traditional economics is not nearly as unified as it claims to be
because whatever phenomenon the economist is looking at, the utility function metamorphoses to deal with the phenomena that’s important to them. But
I do think that a unifying theory, even a unifying mathematical theory, can be a beautiful thing
. And,
that’s what social science is all about: trying to take disparate social phenomena and come up with a unified account
. That’s when I get a chill up my spine, when disparate things come together. So
my aspiration is for behavioral economics to be grounded on a unified theory
, or maybe a few unified theories".

—George Loewenstein

GEORGE LOEWENSTEIN
PhD. Economics
Yale University

BEHAVIORAL ECONOMICS, NEUROECONOMICS
Carnegie Mellon University
PAUL GLIMCHER
PhD. Neuroscience
University of Pennsylvania & Princeton University

NEUROECONOMICS, COGNITIVE NEUROSCIENCE
New York University
FUTURE
PERP
ECTIVES
Biases & Heuristics in Decision-Making
: Generalizations and applications of discovered biases and heuristics.
Cumulative Prospect Theory and Beyond
(since 1992): Current improvements to PT are beyond CPT.
Behavioral Eco., Experimental Eco. & Neuroeconomics
: Link results to create a unified/strong theory (Is it posible?).
The Role of Emotions
(since 2000s): Loewenstein discusses the possibilities and challenges from incorporating emotions into economic models.
Quantitative Behavioral Finance
(since 2000s): It uses mathematical and statistical methodology to understand behavioral biases in conjunction with valuation.
Internet, Big Data and Behavioral Economics
(since 2010s): Much of big data is, after all, behavioral data continually gathered by
dig
ital devices as we go about our daily
activi
ties. Such data are controversial for
reasons
not limited to a basic concern for
privacy. Beh
avioral data generated
in one context can be
repurpose
d for use in other contexts to infer preferences, attitudes, and psychological traits with accuracy that many find unsettling at best, Orwellian at worst.
SOURCE:
Palminteri, S. (2014).
Introduction to Neuroeconomics
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Introduction to Neuroeconomics
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Introduction to Neuroeconomics
. Université Paris Descartes.
SOURCE:
Borst, G. (2014).
Cognitive Neuroscience
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
SOURCE:
Palminteri, S. (2014).
Valuation and the Brain
. Université Paris Descartes.
The notion of cognitive biases was Introduced by Amos Tversky and Daniel Kahneman in 1972. It grew out of their experience of people's innumeracy, or inability to reason intuitively with the greater orders of magnitude:
Availability
Representativeness
Anchoring
www.facebook.com/BESTeam2016
marco.carrascovillanueva@outlook.com
Economía conductual
Psicología
Neurociencias
Programación
Minería de datos
Análisis cuantitativos
Estadística
Econometría
Big data
Ciencia de datos
Personas con conocimientos o muy interesadas en...
Cultura
Escribir
a...
Marketing
Análisis de datos
TO REMEMBER
Neuroeconomics is not "Neuromarketing".
The best term for Neuroeconomics is "Neuroscience of Decision Making".
Be aware of the "power" of the prefix "neuro", since it could be misused, e.g. "neurocoaching", "neurosales", neuroALL", etc. We tend to blindly trust in explanations with some "neuro" account on them, event when they are false. See:
The Seductive Allure of Neuroscience Explanations
(2009), and
Deconstructing the Seductive Allure of Neuroscience Explanations
(2015).
Don't trust blindly! Demand rigor and depth! I can't not call myself a "Neuroeconomist" (I just know a little bit of NoDM), so do not trust easily in those who call themselves "NeuroSOMETHING".
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