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Simple, transparent rules are often frowned upon while complex, black-box models are seen as holding greater promise. Yet in quickly changing situations, simple rules can protect against overfitting and adapt quickly. We show that the surprisingly simple recency heuristic forecasts more accurately than Google Flu Trends (GFT) which used big data analytics and a black-box algorithm. This heuristic predicts that “this week’s proportion of flu-related doctor visits equals the proportion from the most recent week.” It is based on psychological theory of how people deal with rapidly changing situations. Other theory-inspired heuristics have outperformed big data models in predicting outcomes, such as U.S. presidential elections, or other uncertain events, such as consumer purchases, patient hospitalizations, and terrorist attacks. Heuristics are transparent, clearly communicating the underlying rationale for their predictions. We advocate taking into account psychological principles that have evolved over millennia and using these as a benchmark when testing big data models.

A fundamental assumption of expected utility models is that agents make predictions by formulating rational expectations. Building on this assumption, the literature has addressed to what extent rational choice or behaviorally informed utility models best describe intertemporal substitution of labor and leisure, focusing on the taxi market. Using data from 10 million taxi trips, we find that hourly earnings are barely predictable. Under such uncertainty, satisficing models predict behavior of drivers better than utility models. These models do not require calculating expected earnings and terminate shifts when reaching an aspiration level on shift duration or earnings.

Zusammenfassung Wissen um die Vor- und Nachteile einer erwogenen Krebsfruherkennung ist unerlasslich fur Arzt und Patient, will man eine informierte Entscheidung treffen. Wir zeigen, dass der Wissensstand vieler Arzte und Patienten alarmierend gering ist. Nur rund 5 Prozent der Patienten konnen den Nutzen verschiedener Fruherkennungsmasnahmen richtig einschatzen, die anderen uberschatzen diesen um Grosenordnungen oder konnen ihn nicht benennen. Verlasst sich der Patient in seiner Unwissenheit ganz auf den Arzt, kann er ebenfalls schnell verlassen sein. Ein Drittel der von uns untersuchten Gynakologen wissen nicht, wie hoch der Nutzen des Mammographie-Screenings ist, und 79% verstehen nicht, was ein positiver Mammographiebefund bedeutet (der positive pradiktive Wert). Aber auch Patienten-Broschuren sind nicht Garant fur Wissenszuwachs, da nur wenige Broschuren evidenz-basiert und transparent uber die Vor- und Nachteile der Krebsfruherkennung informieren. Unter diesen Voraussetzungen ist derzeit der informierte Konsensus bei der Krebsfruherkennung nur begrenzt moglich. Mehr Evidenz und Transparenz fur Patienten sowie eine bessere Ausbildung im statistischen Denken fur Arzte sind notwendig, wenn wir dem Ideal des informierten Entscheidens im Bereich der Medizin naher kommen wollen.

How do firms set prices when faced with an uncertain market? Analyzing the pricing strategies of used car dealers using online data and interviews, we find that dealers employ an aspiration level heuristic similar to a Dutch auction. At the same time, the aggregate market is well described by a model of equilibrium price dispersion. Unlike the equilibrium model, the heuristic correctly predicts systematic pricing characteristics such as high initial price, price stickiness, and the “cheap twin paradox.” We also find first evidence that heuristic pricing can generate higher profits given uncertainty than the equilibrium strategy.

A good representation can be crucial for finding the solution to a problem. Gigerenzer and Hoffrage (Psychol. Rev. 102 (1995) 684; Psychol. Rev. 106 (1999) 425) have shown that representations in terms of natural frequencies, rather than conditional probabilities, facilitate the computation of a cause's probability (or frequency) given an effect – a problem that is usually referred to as Bayesian reasoning. They also have shown that normalized frequencies – which are not natural frequencies – do not lead to computational facilitation, and consequently, do not enhance people's performance. Here, we correct two misconceptions propagated in recent work (Cognition 77 (2000) 197; Cognition 78 (2001) 247; Psychol. Rev. 106 (1999) 62; Organ. Behav. Hum. Decision Process. 82 (2000) 217): normalized frequencies have been mistaken for natural frequencies and, as a consequence, “nested sets” and the “subset principle” have been proposed as new explanations. These new terms, however, are nothing more than vague labels for the basic properties of natural frequencies.

Distinguishing between risk and uncertainty, this paper draws on the psychological literature on heuristics to consider whether and when simpler approaches may outperform more complex methods for modelling and regulating the financial system. We find that: (i) simple methods can sometimes dominate more complex modelling approaches for calculating banks’ capital requirements, especially if limited data are available for estimating models or the underlying risks are characterised by fat-tailed distributions; (ii) simple indicators often outperformed more complex metrics in predicting individual bank failure during the global financial crisis; and (iii) when combining information from different indicators to predict bank failure, ‘fast-and-frugal’ decision trees can perform comparably to standard, but more information-intensive, regression techniques, while being simpler and easier to communicate.

This research evaluates Minimal Economic Knowledge (MEK) in Germany - that is, basic knowledge of economic facts, concepts, and causal relationships needed for understanding and successfully participating in the economy. It is addressed to gain an understanding of the level of Minimal Economic Knowledge in the German public. To fulfill this goal we conducted three studies: The first study developed a scale for measuring MEK using a Delphi method approach. The resulting questionnaire comprises 24 questions in four economic domains: finance, labor economics, consumption, and state economics, testing for three kinds of knowledge within each domain - facts, concepts, and causal relationships. Our second study tested the MEK level in a representative sample of German adults (N=1,314), with a mean result of 59.4 (of 100) indicating a considerable lack of economic knowledge. It further analyses the influence of demographic drivers such as gender and age. A third, explorative study (N=243) determined additional drivers for MEK such as a person's origin, life experience, use of media, and social circumstance.

Bank customers are not financial experts, and yet they make high-stakes decisions that can substantively affect personal wealth. This raises questions about how non-experts actually make financial decisions. How do investors search for information? How does the information they look up map into decisions? Using data collected from financial advisors and bank customers at several branches of an Italian mutual bank, this paper aims to reveal new insights about the decision processes of average investors: their investment goals, the information sets they consider, and the factors that ultimately influence decisions about investment products. We designed four portfolio choice tasks based on data collected directly from financial advisors and their clients. Our subjects were actual bank customers with investment accounts at those banks containing 40,000 euro or more. Most subjects used a limited set of information, ignoring factors that conventional economic models usually assume drive investor behavior. We suggest that non-compensatory decision-tree models, which make no trade-offs among investment features, be considered as parsimonious descriptions of investor behavior useful in marketing applications and policy contexts alike.

The perceptual constancy view posits that children perceive rectangular areas dependent on shape, whereas adults do not. Following Brunswik (1934a) , we call this dependency the “limited perceptual constancy of area under variation of shape.” A series of four experiments (with 150 children and 80 adults) using ordinal paired comparisons rejected the general equation a i = ( A i , S i ) as a model of limited area constancy ( a i is the perceived area, A i and S i the physical area and shape of rectangle i). Children judged area dependent on shape, but dependent on the covariation C set of area and shape in the experimental set of rectangles, rather than on the particular shape of the rectangle judged. A quantitative version of this covariation mechanism that seems to generate limited area constancy is proposed, and its relation to Parducci's range-frequency theory is discussed. Not one child's judgments could be predicted from a height + width rule (assuming identical linear psychophysical functions). We demonstrate and correct serious errors in Anderson and Cuneo's (1978a, 1978b) claims for a height + width rule in children. Our results support a three-step developmental model for paired comparisons of area: (1) centering on one side of the rectangle, (2) limited area constancy, that is, a i = f ( A i , C set ), and (3) area constancy.