Insurance and safety after September 11, 2001: Coming to grips with the costs and threats of terrorism

This chapter, originally written as a consequence of the terrorist attacks of September 11, 2001, provides an elementary, everyday introduction to the concepts of risk and insurance. Conceptually, risk has two dimensions: a potential loss, and the chance of that loss being realized. People can, however, transfer risk to insurance companies against the payment of so-called premiums. In practice, however, one needs accurate assessments of both losses and probabilities to judge whether premiums are appropriate. For many risks, this poses little problem (e.g., life insurance); however, it is difficult to assess risks of many other kinds of events such as acts of terrorism. It is emphasized, that through evolution and learning, people are able to handle many of the common risks that they face in life. But when people lack experience (e.g., new technologies, threats of terrorism), risk can only be assessed through imagination. Not surprisingly, insurance companies demand high prices when risks are poorly understood. In particular, the cost of insurance against possible acts of terrorism soared after September 11. How should people approach risk after the events of that day? Clearly, the world needs to protect itself from the acts of terrorists and other disturbed individuals. However, it is also important to address the root causes of such antisocial movements. It is, therefore, suggested that programs addressed at combatting ignorance, prejudice, and social inequalities may be more effective premiums for reducing the risk of terrosrtism than has been recognized to date.Decision making, risk, insurance, terrorism, September 11

The challenge of representative design in psychology and economics

The demands of representative design, as formulated by Egon Brunswik (1956), set a high methodological standard. Both experimental participants and the situations with which they are faced should be representative of the populations to which researchers claim to generalize results. Failure to observe the latter has led to notable experimental failures in psychology from which economics could learn. It also raises questions about the meaning of testing economic theories in “abstract” environments. Logically, abstract tests can only be generalized to “abstract realities” and these may or may not have anything to do with the “empirical realities” experienced by economic actors.Experiments, representative design, sampling, Leex

When "hope springs eternal": The role of chance in risk taking

In most naturally occurring situations, success depends on both skill and chance. We contrast experimental market entry decisions where payoffs depend on skill as opposed to combinations of skill and chance. Our data show differential attitudes toward chance by those whose self-assessed skills are low and high. Making chance more important induces greater optimism for the former who start taking more risk, while the latter maintain a belief that high levels of skill are sufficient to overcome the vagaries of chance. Finally, although we observed “excess entry” (i.e., too many participants entered markets), this could not be attributed to overconfidence.Skill, chance, overconfidence, optimism, competition, risk taking, gender differences

Experiencing simulated outcomes

Whereas much literature has documented difficulties in making probabilistic inferences, it has also emphasized the importance of task characteristics in determining judgmental accuracy. Noting that people exhibit remarkable efficiency in encoding frequency information sequentially, we construct tasks that exploit this ability by requiring people to experience the outcomes of sequentially simulated data. We report two experiments. The first involved seven well-known probabilistic inference tasks. Participants differed in statistical sophistication and answered with and without experience obtained through sequentially simulated outcomes in a design that permitted both between- and within-subject analyses. The second experiment involved interpreting the outcomes of a regression analysis when making inferences for investment decisions. In both experiments, even the statistically naïve make accurate probabilistic inferences after experiencing sequentially simulated outcomes and many prefer this presentation format. We conclude by discussing theoretical and practical implications.probabilistic reasoning; natural frequencies; experiential sampling; simulation., leex

Entrepreneurial success and failure: Confidence and fallible judgement

Excess entry – or the high failure rate of market-entry decisions – is often attributed to overconfidence exhibited by entreprene urs. We show analytically that whereas excess entry is an inevitable consequence of imperfect assessments of entrepreneurial skill, it does not imply overconfidence. Judgmental fallibility leads to excess entry even when everyone is underconfident. Self-selection implies greater confidence (but not necessarily overconfidence) among those who start new businesses than those who do not and among successful entrants than failures. Our results question claims that “entrepreneurs are overconfident” and emphasize the need to understand the role of judgmental fallibility in producing economic outcomes.Excess entry, fallible judgment, overconfidence, skill uncertainty, entrepreneurship, LeeX

Determinants of linear judgment: A meta-analysis of lens model studies

The mathematical representation of Brunswik’s lens model has been used extensively to study human judgment and provides a unique opportunity to conduct a meta-analysis of studies that covers roughly five decades. Specifically, we analyze statistics of the “lens model equation” (Tucker, 1964) associated with 259 different task environments obtained from 78 papers. In short, we find – on average – fairly high levels of judgmental achievement and note that people can achieve similar levels of cognitive performance in both noisy and predictable environments. Although overall performance varies little between laboratory and field studies, both differ in terms of components of performance and types of environments (numbers of cues and redundancy). An analysis of learning studies reveals that the most effective form of feedback is information about the task. We also analyze empirically when bootstrapping is more likely to occur. We conclude by indicating shortcomings of the kinds of studies conducted to date, limitations in the lens model methodology, and possibilities for future research.Judgment, lens model, linear models, learning, bootstrapping

Take-the-best and other simple strategies: Why and when they work 'well' in binary choice

The effectiveness of decision rules depends on characteristics of both rules and environments. A theoretical analysis of environments specifies the relative predictive accuracies of the lexicographic rule 'take-the-best' (TTB) and other simple strategies for binary choice. We identify three factors: how the environment weights variables; characteristics of choice sets; and error. For cases involving from three to five binary cues, TTB is effective across many environments. However, hybrids of equal weights (EW) and TTB models are more effective as environments become more compensatory. In the presence of error, TTB and similar models do not predict much better than a naïve model that exploits dominance. We emphasize psychological implications and the need for more complete theories of the environment that include the role of error.Decision making, bounded rationality, lexicographic rules, Leex

Challenges of mentorship

Mentorship is the fourteenth series of ‘Midwifery basics’ targeted at practising midwives. It aims to provide information to raise awareness of the impact of the work of midwives on student learning and ultimately on women’s experience and encourage midwives to seek further information through a series of activities. In this sixth article Charlotte Kenyon, Stephen Hogarth and Joyce Marshall consider some of the challenges to mentorship and possible solutions to these

Excess entry, ambiguity seeking and competence: An experimental investigation

Excess entry refers to the high failure rate of new entrepreneurial ventures. Economic explanations suggest 'hit and run' entrants and risk-seeking behavior. A psychological explanation is that people (entrepreneurs) are overconfident in their abilities (Camerer & Lovallo, 1999). Characterizing entry decisions as ambiguous gambles, we alternatively suggest–following Heath and Tversky (1991)–that people seek ambiguity when the source of uncertainty is related to their competence. Overconfidence, as such, plays no role. This hypothesis is confirmed in an experimental study that also documents the phenomenon of reference group neglect. Finally, we emphasize the utility that people gain from engaging in activities that contribute to a sense of competence. This is an important force in economic activity that deserves more explicit attention.Competence, excess entry, entrepreneurship, overconfidence, Leex