If you dropped a dozen human toddlers on a beautiful Polynesian island with shelter and enough to eat, but no computers, no cell phones,…
Alessandro Cerboni's insight:
As someone who has studied language, cognitive neuroscience, and human evolution, I say that with a tinge of chagrin; my professional career has been about trying to understand the origins and development of the human mind. My colleagues and I are all still struggling to find the answers. Why has pinpointing the origins of human uniqueness proven so difficult?
Abstract: This paper challenges the increasingly common view that the findings of behavioural economics constitute a fourth type of market failure. The market failure framework elevates the standard competitive market model to the status of an ideal. It provides us with tools to identify departures from the ideal model and to deduce a direction policy might take to restore it. Many behavioural phenomena also imply departures from the ideal model. Yet rather than allowing us to deduce a good direction for policy, the findings question the legitimacy and usefulness of this deductive theoretical framework for policy analysis. Two policy problems are highlighted here: the validity of inferring that consumers' choices after an intervention improve outcomes relative to their previous choices, and the potential for distributional consequences when policy alters consumers' choices. The paper concludes that, given these problems, conceiving of the relevant behavioural phenomena as an additional form of market failure is potentially to misunderstand their implications for consumer and competition policy.
HOW TO GET INTO THE AMA JOB MARKET First, at least a couple months before the conference, find where it will be. It’s called the American Marketing Association Summer Educator’s Conference. Strange name, we know. Insiders just call it “The AMA”. Get yourself a room in the conference hotel, preferably on the floor where the express elevator meets the local elevator for the upper floors. You’ll be hanging out on this floor waiting to change elevators anyway, so you might as well start there. Next, create a list of schools at which you would like a job. You can find the top 100 schools ranked by journal publications at: http://jindal.utdallas.edu/the-utd-top-100-business-school-research-rankings . Next, apply to each one you’d go to. In the past, this involved physically mailing application packets, but these days nearly everything is electronic. Some schools have online application portals, and others will take applications by email. How do you find out which one? Hopefully, the school you are applying to will have posted a job at ELMAR (see http://ama-academics.communityzero.com/elmar; and subscribe to their mailing list) or elsewhere, which will specify how to submit your application. Other times, you’ll need to get in touch with a department administrator to find out how to apply. It’s a good idea to apply to schools you like even if they say they aren’t hiring. Sometimes things change suddenly (a tenured faculty member unexpectedly moves to another school), and the only thing you risk is your time.
Despite numerous studies attemptin to link volatility to changing fundamentals, research shows that investor emotions are the root cause of the vast majority of these price changes, according to C........
Particularly germane to implementing behavioral portfolio management is understanding Howard’s views on emotions and volatility, and how he handles them when managing money. Recall that Howard is professor emeritus at Daniels College of Business, University of Denver, and co-founder of AthenaInvest, whose Athena Pure Valuation is one of the top performing portfolios in recent years.
Nudging in action has given us more insight into the way people make decisions. The key now is to use that knowledge to design more realistic policies.Five years ago, Richard Thaler and Cass Sunstein published Nudge: Improving Decisions about Health, Wealth and Happiness, a book that asked us to fundamentally change the way we think about how policy is made. Nudgechallenged the prevailing approaches to policy-making and governance that were grounded in the appealing idea that human beings are rational decision-makers, cognitively sophisticated enough to process all relevant information and unswayed by emotion. It presented several years’ worth of research to demonstrate that, by contrast, our decision-making is surprisingly malleable and therefore dramatically influenced by context. And if that is the case, Thaler and Sunstein asked, is it not possible to create the context that steers people toward the right choice (or at least the one we believe brings about the greatest common good)?
Economic experiments are increasingly being used in a number of research areas and are a major source of data guiding the debate surrounding the nature of human prosociality. The degree to which experiment behavior accurately reflects external behavior, however, has long been debated. A number of recent studies have revealed just how remarkably sensitive participants are to cues of a lack of anonymity. Similarly, others have suggested that the very structure of the experimental context induces participants to choose prosocial options. In order to truly create anonymous conditions and to eliminate the effects of experimental contexts, participants must not be aware of their participation. Here, I present the results of a natural-field Dictator Game in which participants are presented with a believable endowment and provided an opportunity to divide the endowment with a stranger without knowing that they are taking part in an experiment. No participants gave any portion of the endowment to the stranger. Baseline frequencies of prosocial behaviors exhibited under experimental contexts might therefore be substantially inflated compared to those exhibited under natural contexts.
A constituent feature of adaptive complex system are non-linear feedback mechanisms between actors. This makes it often difficult to model and analyse them. Agent-based Computational Economics (ACE) uses computer simulation methods to represent such systems and analyse non-linear processes.
The aim of this thesis is to explore ways of modelling adaptive agents in ACE models. Its major contribution is of a methodological nature. Artificial intelligence and machine learning methods are used to represent agents and learning processes in ACE models.
In this work, a general reinforcement learning framework is developed and realised in a simulation system. This system is used to implement three models of increasing complexity in two different economic domains. One of these domains are iterative games in which agents meet repeatedly and interact. In an experimental labour market, it is shown how statistical discrimination can be generated simply by means of the learning algorithm used. The aim of this model is mainly to illustrate the features of the learning framework. The results resemble actual patterns of observed human behaviour in laboratory settings. The second model treats strategic network formation. The main contribution here is to show how agent-based modelling helps to analyse non-linearity that is introduced when assumptions of perfect information and full rationality are relaxed. The other domain has a Health Economics background. The aim here is to provide insights of how the approach might be useful in real-world applications. For this, a general model of primary care is developed, and the implications of different consumer behaviour (based on the learning features introduced before) analysed.
People search for information that confirms their view of the world and ignore what doesn't fit.
In an uncertain world, people love to be right because it helps us make sense of things. Indeed some psychologists think it's akin to a basic drive.
One of the ways they strive to be correct is by looking for evidence that confirms they are correct, sometimes with depressing or comic results:
A woman hires a worker that turns out to be incompetent. She doesn't notice that everyone else is doing his work for him because she is so impressed that he shows up every day, right on time.A sports fan who believes his team is the best only seems to remember the matches they won and none of the embarrassing defeats to inferior opponents.A man who loves the country life, but has to move to the city for a new job, ignores the flight-path he lives under and noisy-neighbours-from-hell and tells you how much he enjoys the farmer's market and tending his window box.
We do it automatically, usually without realising. We do it partly because it's easier to see where new pieces fit into the picture-puzzle we are working on, rather than imagining a new picture. It also helps shore up our vision of ourselves as accurate, right-thinking, consistent people who know what's what.
Psychologists call it the confirmation bias and it creeps into all sorts of areas of our lives. Here are a few examples:
Roughly speaking there are only two reasons you do anything in life:
Because you want to.Because someone else wants you to.
The first category of internally motivated activities might include things like eating, socialising, hobbies and going on holiday. The second category of externally motivated activities might include working a job, studying, or loading the dishwasher.
The reason I say 'roughly speaking' and 'might include' is because the two types of motivation can be difficult to disentangle. Yes, you enjoy your work, but would you do it for less money or for free? Maybe, maybe not. Yes, my wife wants me to load the dishwasher, but maybe I'd do it anyway. Or maybe not.
We can’t completely plan out everything that happens in our lives. Instead a lot of the situations we find ourselves in we have to respond to spontaneously – which requires a certain amount of fast and creative thinking on the spot.
When we try to plan too much, we often over-think and over-analyze, which leads us to hesitate and not take action. For example, if you’re having a conversation with a new girl or boy you like, you may often find yourself thinking in your head, “What should I say?” which takes you out of the moment and usually ends with you not saying much of anything at all.
For some people, it’s really difficult to get “outside of their heads” and into the moment. However, one way we can practice being more spontaneous is by practicing improvisation exercises to make our minds think faster and more freely.
In the present essay we introduce in a model the concept of macroculture and the formation of new values within the particular macroculture that arose during the 8th to 4th century BC in Ancient Greece. We analyse the conditions and the context for the emergence of the heavy infantryman, the hoplite, and the new tactical formation, the phalanx, and the trireme warship. We apply the coordination and cooperation as behavioural mechanisms to the phalanx and the triremes to show how a specific set of new values emerged. Then, taking into account bounded rationality, as a second behavioural mechanism we analyse how these values were taken over from the military into the political field and thus were crucial for the emergence and development of democracy.
Is Behavioral Economics the Death of Living Wills? Forbes As a physician who conducts research on decision-making, I have been asked many times: What does behavioral economics teach us about the role of living wills in medical care?
As modern portfolio theory fades in reputation from intense pressure from behavioral finance, many researchers are seeking to fill the void with behavioral finance applications. Behavioral portfoli..Seeking to bridge the divide between modern portfolio theory and behavioral finance, is C. Thomas Howard’s“Behavioral Portfolio Management.” Howard is professor emeritus at Daniels College of Business, University of Denver, and co-founder of AthenaInvest. Application of his behavioral portfolio management has resulted in Athena’s longest running portfolio, Athena Pure Valuation, generating a return over 11 years of 26.1%. Compare that to the Russell 2000 benchmark, which returned 10.6%. Further, Athena Pure is the top performing portfolio in the country over this time period when compared to the active equity mutual fund universe.
“For the past five years we’ve been running the largest behavioral science experiment in the world,” says Alex Laskey in today’s TED Talk, given at this year’s 2013 conference in Long Beach. “And, it’s working.”
Alex Laskey: How behavioral science can lower your energy billLaskey’s company Opower partners with utility companies to deliver personalized home energy reports, all based off the insight that people are more inclined to take action on an issue when they think other people are doing better than they are. People’s energy consumption changes for the better after receiving these reports — either in the mail or through their app and website — and the effects appear to be long-lasting. This year, Laskey says, Opower expects to inspire 2 terawatt hours (TWh) in saved electricity. That’s enough to power a city of more than a quarter million people for a year.
Abstract: In this paper the theory of semi-bounded rationality is proposed as an extension of the theory of bounded rationality. In particular, it is proposed that a decision making process involves two components and these are the correlation machine, which estimates missing values, and the causal machine, which relates the cause to the effect. Rational decision making involves using information which is almost always imperfect and incomplete as well as some intelligent machine which if it is a human being is inconsistent to make decisions. In the theory of bounded rationality this decision is made irrespective of the fact that the information to be used is incomplete and imperfect and the human brain is inconsistent and thus this decision that is to be made is taken within the bounds of these limitations. In the theory of semi-bounded rationality, signal processing is used to filter noise and outliers in the information and the correlation machine is applied to complete the missing information and artificial intelligence is used to make more consistent decisions.
Many dynamical networks, such as the ones that produce the collective behavior of social insects, operate without any central control, instead arising from local interactions among individuals. A well-studied example is the formation of recruitment trails in ant colonies, but many ant species do not use pheromone trails. We present a model of the regulation of foraging by harvester ant (Pogonomyrmex barbatus) colonies. This species forages for scattered seeds that one ant can retrieve on its own, so there is no need for spatial information such as pheromone trails that lead ants to specific locations. Previous work shows that colony foraging activity, the rate at which ants go out to search individually for seeds, is regulated in response to current food availability throughout the colony's foraging area. Ants use the rate of brief antennal contacts inside the nest between foragers returning with food and outgoing foragers available to leave the nest on the next foraging trip. Here we present a feedback-based algorithm that captures the main features of data from field experiments in which the rate of returning foragers was manipulated. The algorithm draws on our finding that the distribution of intervals between successive ants returning to the nest is a Poisson process. We fitted the parameter that estimates the effect of each returning forager on the rate at which outgoing foragers leave the nest. We found that correlations between observed rates of returning foragers and simulated rates of outgoing foragers, using our model, were similar to those in the data. Our simple stochastic model shows how the regulation of ant colony foraging can operate without spatial information, describing a process at the level of individual ants that predicts the overall foraging activity of the colony.
Delegate. Develop others. Build consensus. Be decisive. Think strategically. Ah, yes, the keys to being an effective manager and leader all tied up in such neat little buzzwords and phrases. So neat, in fact, that it can be hard to unpack these concepts and dive into what it actually means to effectively delegate or develop others.
Decoding the most important but hard-to-explain qualities that set the best leaders apart from the rest is the focus of a new column on the newly-launched BBC Capital.
Turns out, you can learn a lot from the world of professional golf about delegation. Consider the relationship between golfers and their caddies.
“Caddies don’t just carry around a pro-golfer’s bag. They spend hours doing course research so they can suggest which club to use on each shot,” writes Eric Barton in Leader Board.
And it doesn’t always work out, as Barton details in the debut column, “Real delegation requires something unexpected.” Sometimes, the caddie suggests a shot and it goes all wrong. But it’s rare for a golfer to place blame on his caddie or regret delegating such a big decision. That’s largely because the relationship is built on trust and, ahem, letting go of control of important tasks—even when the outcome impacts you directly.
The caddie-golfer relationship is an example of all that goes right with effective delegation, writes Barton. Too often managers want to hand out only secondary assignments to the people who work for them, keeping the best or key tasks as their own. It’s human nature—we want to be responsible for our own professional fates. But the most effective delegators hand down plumb assignments and support employees while they figure out how to complete them. The key: Hiring and developing people you can trust.
This paper investigates whether preference interactions can explain why risk preferences change over time and across contexts. We conduct an experiment in which subjects accept or reject gambles involving real money gains and losses. We introduce within-subject variation by alternating subjectively liked music and disliked music in the background. We find that favourite music increases risk-taking, and disliked music suppresses risk-taking, compared to a baseline of no music. Several theories in psychology propose mechanisms by which mood affects risktaking, but none of them fully explain our results. The results are, however, consistent with preference complementarities that extend to risk preference. --
Abstract: We develop a dynamic model where people decide in the presence of moral constraints and test the predictions of the model through two experiments. Norm violations induce a temporal feeling of guilt that depreciates with time. Due to such fluctuations of guilt, people exhibit an endogenous temporal inconsistency in social preferences—a behavior we term conscience accounting. In our experiments people first have to make an ethical decision, and subsequently decide whether to donate to charity. We find that those who chose unethically were more likely to donate than those who did not. As predicted, donation rates were higher when the opportunity to donate came sooner after the unethical choice than later. Combined, our theoretical and empirical findings suggest a mechanism by which prosocial behavior is likely to occur within temporal brackets following an unethical choice.