“You inched towards the dark side,” joked one behavioural economist after he read a recent column in which I hinted that his field has some merits. It was a quip that got me thinking, because behavioural economics does indeed have a dark side. Behavioural economists study the psychology of economic decision-making, and if they are any good at their task they will discover something the unscrupulous salesman could use to his advantage.
A behavioural economist turned rogue would exploit the “endowment effect” – a tendency for people to put a higher value on something that they feel they already own. He or she would also try to create the sense that consumers would lose out if they did not buy, because people seem to hate the idea of losing £5 much more than they like the idea of gaining £5.
Third, our rogue economist would attempt to suggest an “anchor” value that was much higher than the asking price, which would make the product seem cheap. It doesn’t seem to be hard to create such anchor values: they can be produced by inviting experimental subjects to write down the last two digits of their social security number.
Fourth, he or she would make the pricing as complex as possible so that people struggled to compare one offer with a rival offer. Fifth, he or she would try to create a sense of social approval – everyone is buying this. Finally, a rogue economist would throw in something free.
I’m happy to see James back on the blogging circuit…take a look at his latest post.
Excerpt via James Montier:
However, any consideration of the purchase of insurance should not be divorced from a discussion of the price of the insurance. Cheap insurance is wonderful, and clearly benefits portfolios in terms of robustness. However, the key word is that the insurance must be cheap (or at very worst fair value). Buying expensive insurance is a waste of time. I used to live in Tokyo and was constantly amazed that the day after an earth tremor the cost of earthquake insurance would soar, as would the demand!
You should really only want insurance when it is cheap, as this is the time when no one else wants it, and (perversely) the events are most likely. Buying expensive insurance is just like buying any other overpriced asset … a path to the permanent impairment of capital. Rather than wasting money on expensive insurance, holding a larger cash balance makes sense. It preserves your dry powder for times when you want to deploy capital, and limits the downside.
This paper will develop the efficient markets model in Section I to clarify some theoretical questions that may arise in connection with the inequality (1) and some similar inequalities will be derived that put limits on the standard deviation of the innovation in price and the standard deviation of the change in price. The model is restated in innovation form which allows better understanding of the limits on stock price volatility imposed by the model. In particular, this will enable us to see (Section II) that the standard deviation of p is highest when information about dividends is revealed smoothly and that if information is revealed in big lumps occasionally the price series may have higher kurtosis (fatter tails) but will have lower variance. The notion expressed by some that earnings rather than dividend data should be used is discussed in Section III, and a way of assessing the importance of time variation in real discount rates is shown in Section IV. The inequalities are compared with the data in Section V.
Excerpted Abstract (by Malena Johnsson, Henrik Lindblom, & Peter Platan)
The thesis supports, to some extent, the assumption that even though a majority of the investors during 1998 to 2000 seem to have realized the seriousness of the speculative bubble they nevertheless continued their investment activities knowing that the risk for a collapse was imminent. A more common understanding of factors underlying speculative bubbles and the way in which psychological factors affect our decision making should help to avoid the occurrence of such phenomenon and enhance the efficiency of today’s global financial markets.
Abstract: (A. O. I. Hoffmann, Hersh Shefrin, Joost M.E. Pennings, Via SSRN )
Existing studies on individual investors’ decision-making often rely on observable socio-demographic variables to proxy for underlying psychological processes that drive investment choices. Doing so implicitly ignores the latent heterogeneity amongst investors in terms of their preferences and beliefs that form the underlying drivers of their behavior. To gain a better understanding of the relations among individual investors’ decision-making, the processes leading to these decisions, and investment performance, this paper analyzes how systematic differences in investors’ investment objectives and strategies impact the portfolios they select and the returns they earn. Based on recent findings from behavioral finance we develop hypotheses which are tested using a combination of transaction and survey data involving a large sample of online brokerage clients. In line with our expectations, we find that investors driven by objectives related to speculation have higher aspirations and turnover, take more risk, judge themselves to be more advanced, and underperform relative to investors driven by the need to build a financial buffer or save for retirement. Somewhat to our surprise, we find that investors who rely on fundamental analysis have higher aspirations and turnover, take more risks, are more overconfident, and outperform investors who rely on technical analysis. Our findings provide support for the behavioral approach to portfolio theory and shed new light on the traditional approach to portfolio theory.
Some of the best researchers on behavioral economics….
Introduction (via George Loewenstein and Peter Ubel @ NYT)
IT seems that every week a new book or major newspaper article appears showing that irrational decision-making helped cause the housing bubble or the rise in health care costs.
Such insights draw on behavioral economics, an increasingly popular field that incorporates elements from psychology to explain why people make seemingly irrational decisions, at least according to traditional economic theory and its emphasis on rational choice. Behavioral economics helps to explain why, for example, people under-save for retirement, why they eat too much and exercise too little and why they buy energy-inefficient light bulbs and appliances. And, by understanding the causes of these problems, behavioral economics has spawned a number of creative interventions to deal with them.
But the field has its limits. As policymakers use it to devise programs, it’s becoming clear that behavioral economics is being asked to solve problems it wasn’t meant to address. Indeed, it seems in some cases that behavioral economics is being used as a political expedient, allowing policymakers to avoid painful but more effective solutions rooted in traditional economics.
Take, for example, our nation’s obesity epidemic. The fashionable response, based on the belief that better information can lead to better behavior, is to influence consumers through things like calorie labeling — for instance, there’s a mandate in the health care reform act requiring restaurant chains to post the number of calories in their dishes.
Next time you’re on the phone with a call center, listen carefully to what the rep says. Chances are you’ll hear your name several times, hear a tone of empathy, maybe an “I’m sorry.” It would be nice to think the rep really cares — but of course she’s probably just following a script. That can be a bad idea, we’ve found. In our recent HBR article “Stop Trying to Delight Your Customers”, we explored how customer service drives loyalty, including the role of managing the emotional side of customer interactions. Here’s some further insight about that delicate dance.
Excerpts (via Dixon & Thomas @ Harvard)
Recently, we ran a series of experiments across two separate groups of customers to better understand the impact word choice can have on a customer interaction:
In one experiment, the rep had to authorize a customer banking account before the customer could transfer funds. But the rep explaining “you can’t transfer funds until you go through these steps to authorize the account” scored significantly lower than the rep explaining “let me walk you through these steps to authorize the account.” While the language is subtly different, customers rated the latter as 82% higher quality and 73% lower effort.
In another experiment, customers were told they had to bring their new bicycles to a certified repair shop. The performance of the rep who simply stated “you’re best off bringing it into a repair shop” was rated significantly lower than that of the rep who noted that they’d “pass the customer’s feedback to the engineering department,” “check the database to see if a simple fix is possible,” and “recommend the customer bring the bicycle to the shop.” The latter scored 67% higher quality and 77% lower customer effort.
Such approaches go well beyond traditional soft skills. Instead, these rely on careful language choice to frame answers in the best possible way. This isn’t simply being empathetic — it’s calculated and anticipatory. We call it experience engineering.
Beyond simple word choice, we’ve seen other experience engineering approaches work well. For instance, LoyaltyOne (also referenced in the article) practices an idea called alternative positioning. This approach is premised on learning some basic information about a customer during the interaction, and then using that information to reframe a not-so-great option as an acceptable option. The company’s customer survey scores have improved 15%+ as a result of this practice.
Alternatives positioning isn’t revolutionary — in fact, sales reps have been framing product features in light of customer benefits since commercial interactions began. But, applying this method to service scenarios is quite innovative and generally defensible.
Introduction (via Money Science)
The traditional finance researcher sees financial settings populated not by the error-prone and emotional Homo sapiens, but by the awesome Homo economicus. The latter makes perfectly rational decisions, applies unlimited processing power to any available information, and holds preferences well-described by standard expected utility theory.
Anyone with a spouse, child, boss, or modicum of self-insight knows that the assumption of Homo economicus is false. Behavioralists in finance seek to replace Homo economicus with a more-realistic model of the financial actor. Richard Thaler, a founding father of behavioral finance, captured the conflict in a memorable National Bureau of Economic Research (NBER) conference remark to traditionalist Robert Barro: “The difference between us is that you assume people are as smart as you are, while I assume people are as dumb as I am.” Thaler’s tongue-in-cheek comparison aptly illustrates how the modest substantive differences in traditionalist and behavioralist viewpoints can be exaggerated by larger differences in framing and emphasis, bringing to mind the old quip about Britain and America being “two nations divided by a common tongue.” (For what it is worth, when confirming this account of the exchange, Thaler reports that Barro agreed with his statement.)
The purpose of this article is to guide readers through this debate over fundamental assumptions about human behavior and indicate some directions behavioralists might pursue. The article provides general map of research in finance and describes in greater detail the similarities and differences between behavioral and traditional finance. I then the disagreements between the two camps in the context of the philosophy of science: Behavioralists argue, à la Thomas Kuhn, that behavioral theories are necessary to explain anomalies that cannot be accommodated by traditional theory. In return, traditionalists use a philosophy of instrumental positivism to argue that the competitive institutions in finance make deviations from Homo economicus unimportant, as long as simplifying assumption is sufficient to predict how observable variables are related to one another.
A brief history of behavioral research in financial reporting then shows that while these two philosophical perspectives are powerful, they are incomplete. The success of behavioral financial reporting also depends heavily on sociological factors, particularly the commingling of behavioral and traditional researchers within similar departments. Because most finance departments lack this form of informal interaction, behavioralists must redouble their efforts to pursue a research agenda that will persuade traditionalists. The last section proposes a research agenda that behavioralists can use to address both their substantive and sociological challenges: developing and testing models explaining how the influence of behavioral factors is mediated by the ability of institutions (like competitive markets) to scrub aggregate results of human idiosyncrasies. Such research should establish common ground between traditionalists and behavioralists, while also identifying settings in which behavioral research is likely to have the most predictive power.
We discuss the literatures on behavioral economics, bounded rationality and experimental economics as they apply to firm behavior in markets. Topics discussed include the impact of imitative and satisficing behavior by firms, outcomes when managers care about their position relative to peers, the benefits of employing managers whose objective diverges from profit-maximization (including managers who are overconfident or base pricing decisions on sunk costs), the impact of social preferences on the ability to collude, and the incentive for profit-maximizing firms to mimic irrational behavior.
