Chance, Bias, and Decision-Making
"...anybody who has taken a class in statistics should be able to tell you that there is a 50% chance of flipping a head even after five consecutive tosses of tails. However, when the task is subtle enough, even statistically sophisticated social scientists exhibit biases due to belief in the law of small numbers (e.g. Tversky & Kahneman, 1971)...People may be more inclined to 'blame the victim' of unfortunate rare tragedies, on the premise that the victim must have been engaging in risky behaviors for a long time. Similarly, people may be willing to attribute rare and lucky successes to the notion that a person had been working towards that outcome for a long time and thus deserved it. In another vein, people who are biased in their estimates of how many trials preceded a perceived rare or common outcome might budget their time and resources inefficiently, akin to the planning fallacy (Buehler, Griffin & Ross, 1994)." [Oppenheimer & Monin, Judgment and Decision Making, August 2009]
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The relative influence of advice from human experts and statistical methods on forecast adjustments
Dilek Önkal, Paul Goodwin, Mary Thomson, Sinan Gönül & Andrew Pollock
Journal of Behavioral Decision Making, October 2009, Pages 390-409
Abstract:
Decision makers and forecasters often receive advice from different sources including human experts and statistical methods. This research examines, in the context of stock price forecasting, how the apparent source of the advice affects the attention that is paid to it when the mode of delivery of the advice is identical for both sources. In Study 1, two groups of participants were given the same advised point and interval forecasts. One group was told that these were the advice of a human expert and the other that they were generated by a statistical forecasting method. The participants were then asked to adjust forecasts they had previously made in light of this advice. While in both cases the advice led to improved point forecast accuracy and better calibration of the prediction intervals, the advice which apparently emanated from a statistical method was discounted much more severely. In Study 2, participants were provided with advice from two sources. When the participants were told that both sources were either human experts or both were statistical methods, the apparent statistical-based advice had the same influence on the adjusted estimates as the advice that appeared to come from a human expert. However when the apparent sources of advice were different, much greater attention was paid to the advice that apparently came from a human expert. Theories of advice utilization are used to identify why the advice of a human expert is likely to be preferred to advice from a statistical method.
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Kenneth Kovash & Steven Levitt
NBER Working Paper, September 2009
Abstract:
Game theory makes strong predictions about how individuals should behave in two player, zero sum games. When players follow a mixed strategy, equilibrium payoffs should be equalized across actions, and choices should be serially uncorrelated. Laboratory experiments have generated large and systematic deviations from the minimax predictions. Data gleaned from real-world settings have been more consistent with minimax, but these latter studies have often been based on small samples with low power to reject. In this paper, we explore minimax play in two high stakes, real world settings that are data rich: choice of pitch type in Major League Baseball and whether to run or pass in the National Football League. We observe more than three million pitches in baseball and 125,000 play choices for football. We find systematic deviations from minimax play in both data sets. Pitchers appear to throw too many fastballs; football teams pass less than they should. In both sports, there is negative serial correlation in play calling. Back of the envelope calculations suggest that correcting these decision making errors could be worth as many as two additional victories a year to a Major League Baseball franchise, and more than a half win per season for a professional football team.
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The Use of Narrative Evidence and Explicit Likelihood by Decisionmakers Varying in Numeracy
Nathan Dieckmann, Paul Slovic & Ellen Peters
Risk Analysis, forthcoming
Abstract:
Decisionmakers are often presented with explicit likelihood assessments (e.g., there is a 10% chance that an attack will occur over the next three months) and supporting narrative evidence in forecasting and risk communication domains. Decisionmakers are thought to rely on both numerical and narrative information to the extent that they perceive the information to be diagnostic, accurate, and trustworthy. In two studies, we explored how lay decisionmakers varying in numeracy evaluated and used likelihood assessments and narrative evidence in forecasts. Overall, the less numerate reported higher risk and likelihood perceptions. In simple probabilistic forecasts without narrative evidence, decisionmakers at all levels of numeracy were able to use the stated likelihood information, although risk perceptions of the less numerate were more affected by likelihood format. When a forecast includes narrative evidence, decisionmakers were better able to use stated likelihood in a percentage as compared to frequency or verbal formats. The more numerate used stated likelihood more in their evaluations whereas the less numerate focused more on the narrative evidence. These results have important implications for risk analysts and forecasters who need to report the results of their analyses to decisionmakers. Decisionmakers varying in numerical ability may evaluate forecasts in different ways depending on the types of information they find easiest to evaluate.
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Why are maximizers less happy than satisficers? Because they maximize positive and negative outcomes
Evan Polman
Journal of Behavioral Decision Making, forthcoming
Abstract:
Although extant research suggests maximizing is related to objectively positive outcomes (e.g., job offers), I propose maximizing may be simultaneously and positively related to objectively negative outcomes (e.g., job rejections). Specifically, I argue maximizers bear more instances of positive and negative outcomes than satisficers, and that in spite of their positive outcomes — yet because of their negative outcomes — maximizers are less happy than satisficers. In Study 1, participants took the alternate uses test; as expected, maximizing was related to seeking alternatives, yet, maximizing was also related to seeking low-quality alternatives. Moreover, the number of low-quality alternatives partially mediated the relationship between maximizing and negative affect. In Study 2, the impact of maximizing on experiencing negative affect was further assessed by examining whether maximizing is related to seeking and choosing low-quality alternatives. Participants played the Iowa Gambling Task; it was found maximizing was related to alternating among decks, and in particular, sampling bad decks; ultimately, maximizing was related to winning less money, and experiencing more negative affect. Finally, in Study 3, participants responded to questionnaires about positive and negative life outcomes; it was found that maximizing was simultaneously related to experiencing more positive and more negative outcomes, and that negative outcomes predicted happiness to a greater degree than positive outcomes. These findings suggest an irony of maximizing: It produces both positive and negative outcomes, contributing to literature explaining why maximizers are less happy than satisficers, and ultimately whether happiness is a matter of choice.
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Katherine Burson, Richard Larrick & John Lynch
Psychological Science, September 2009, Pages 1074-1078
Abstract:
The scales used to describe the attributes of different choice options are usually open to alternative expressions, such as inches versus feet or minutes versus hours. More generally, a ratio scale can be multiplied by an arbitrary factor (e.g., 12) while preserving all of the information it conveys about different choice alternatives. We propose that expanded scales (e.g., price per year) lead decision makers to discriminate between choice options more than do contracted scales (e.g., price per month) because they exaggerate the difference between options on the expanded attribute. Two studies show that simply increasing the size of an attribute's scale systematically changes its weight in both multi-attribute preferences and willingness to pay: Expanding scales for one attribute shifts preferences to alternatives favored on that attribute.
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Publication Bias in Political Science: An Investigation of Two Literatures
Alan Gerber, Neil Malhotra, Conor Dowling & David Doherty
Yale Working Paper, January 2009
Abstract:
Publication bias occurs when the probability a paper enters the scholarly literature is a function of the magnitude or significance levels of the coefficient estimates. We investigate publication bias in two large literatures in political behavior, economic voting and negative campaigning. We find that the pattern of published estimates is consistent with the presence of publication bias. We consider the possible causes and find some evidence that papers systematically employ one-sided hypothesis tests in response to failure to meet the more demanding critical values associated with two-tailed tests, a practice that leads to misleading reports of the probability of Type I errors.
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Fear and loathing in Las Vegas: Evidence from blackjack tables
Bruce Carlin & David Robinson
Judgment and Decision Making, August 2009, Pages 385-396
Abstract:
This paper uses proprietary data from a blackjack table in Las Vegas to analyze how the expectation of regret affects peoples' decisions during gambles. Even among a group of people who choose to participate in a risk-taking activity, we find strong evidence of an economically significant omission bias: 80% of the mistakes at the table are caused by playing too conservatively, resulting in substantial monetary losses. This behavior is equally prevalent among large-stakes gamblers and does not change in the face of more complicated strategic decisions.
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Last shall be first: A field study of biases in sequential performance evaluation on the Idol series
Lionel Page & Katie Page
Journal of Economic Behavior & Organization, forthcoming
Abstract:
When performances are evaluated they are very often presented in a sequential order. Previous research suggests that the sequential presentation of alternatives may induce systematic biases in the way performances are evaluated. Such a phenomenon has been scarcely studied in economics. Using a large data set of performance evaluation in the Idol series (N = 1522), this paper presents new evidence about the systematic biases in sequential evaluation of performances and the psychological phenomena at the origin of these biases.
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When the best appears to be saved for last: Serial position effects on choice
Ye Li & Nicholas Epley
Journal of Behavioral Decision Making, October 2009, Pages 378-389
Abstract:
Decision-makers often evaluate options sequentially due to constraints on attention, timing, or physical location of the options. Choosing the best option will therefore often depend on people's memories of the options. Because imperfect recall introduces uncertainty in earlier options, judgments of those options should regress toward the category mean as memory decays over time. Relatively desirable options will therefore tend to seem less desirable with time, and relatively undesirable options will tend to seem less undesirable with time. We therefore predicted that people will tend to select the first option in a set when choosing between generally undesirable options, and will tend to select the last when choosing between generally desirable options. We demonstrate these serial position effects in choices among paintings, American Idol audition clips, jellybeans, and female faces, provide evidence of its underlying mechanism, and explain how these findings build on existing accounts.
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Pyramiding: Efficient search for rare subjects
Eric von Hippel, Nikolaus Franke & Reinhard Prügl
Research Policy, forthcoming
Abstract:
The need to economically identify rare subjects within large, poorly mapped search spaces is a frequently encountered problem for social scientists and managers. It is notoriously difficult, for example, to identify "the best new CEO for our company," or the "best three lead users to participate in our product development project." Mass screening of entire populations or samples becomes steadily more expensive as the number of acceptable solutions within the search space becomes rarer. The search strategy of "pyramiding" is a potential solution to this problem under many conditions. Pyramiding is a search process based upon the idea that people with a strong interest in a topic or field tend to know people more expert than themselves. In this paper we report upon four experiments empirically exploring the efficiency of pyramiding searches relative to mass screening. We find that pyramiding on average identified the most expert individual in a group on a specific topic with only 28.4% of the group interviewed — a great efficiency gain relative to mass screening. Further, pyramiding identified one of the top 3 experts in a population after interviewing only 15.9% of the group on average. We discuss conditions under which the pyramiding search method is likely to be efficient relative to screening.
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Hyperbolic discounting is rational: Valuing the far future with uncertain discount rates
J. Doyne Farmer & John Geanakoplos
Yale Working Paper, August 2009
Abstract:
Conventional economics supposes that agents value the present vs. the future using an exponential discounting function. In contrast, experiments with animals and humans suggest that agents are better described as hyperbolic discounters, whose discount function decays much more slowly at large times, as a power law. This is generally regarded as being time inconsistent or irrational. We show that when agents cannot be sure of their own future one-period discount rates, then hyperbolic discounting can become rational and exponential discounting irrational. This has important implications for environmental economics, as it implies a much larger weight for the far future.
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Thomas Dohmen, Armin Falk, David Huffman, Felix Markleind & Uwe Sunde
Journal of Economic Behavior & Organization, forthcoming
Abstract:
Many economic decisions involve a substantial amount of uncertainty, and therefore crucially depend on how individuals process probabilistic information. In this paper, we investigate the capability for probability judgment in a representative sample of the German population. Our results show that almost a third of the respondents exhibits systematically biased perceptions of probability. The findings also indicate that the observed biases are related to individual economic outcomes, which suggests potential policy relevance of our findings.