Archivio per 16 luglio 2016

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Probabilistic Recognition Heuristic by Martin Egozcue, Luis Fuentes García, Konstantinos V. Katsikopoulos, Michael Smithson :: SSRN

See on Scoop.itBounded Rationality and Beyond

Abstract: According to the recognition heuristic, people infer that an object they recognize has a higher value on a criterion of interest than an object they do not recognize. This model has been analyzed and conditions for the less-is-more effect- where recognizing fewer objects increases inferential accuracy have been derived. We extend previous studies by modelling this heuristic including the probabilistic recognition of objects and provide a number of results: First, we derive closed-form expressions for the parameters of the original model, in terms of the distributions of recognition and other cues over the objects. Second, we use the expressions to analyze the less-is-more effect. Third, we assume that the vectors of objects is random and use the expressions to calculate and compare the expected accuracy probability of success and derive the conditions under which the model equal or surpass the accuracy of random inference. Our results are general and can thus be linked to any model of recognition-based inference.

See on papers.ssrn.com

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Extending the Recognition Heuristic: A Three-State Model by Martin Egozcue, Luis Fuentes García, Konstantinos V. Katsikopoulos, Michael Smithson :: SSRN

See on Scoop.itBounded Rationality and Beyond

Abstract: According to the recognition heuristic, people infer that an object they recognize has a higher value on a criterion of interest than an object they do not recognize. This model has been analyzed mathematically and conditions for the less-is-more effect – where recognizing fewer objects increases inferential accuracy – have been derived. We propose an extension of the heuristic that incorporates the empirical finding that people recognize some objects for which they believe they have low criterion value. We call these recognized objects unsatisfying, in contrast to recognized-satisfying objects which the inference-maker believes to have a high criterion value. We analyze the model and provide a number of results: First, we derive closed-form expressions for the parameters of our model, as well as for the parameters of the original model, in terms of the distributions of recognition and other cues over the objects. Second, we use the expressions to analyze the less-is-more effect for both models. Third, we use the expressions to calculate and compare the accuracy of the two models and derive conditions under which the models equal or surpass the accuracy of random inference. Our results are general and can thus be linked to any model of recognition-based inference.

See on papers.ssrn.com

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Taking Uncertainty Seriously: Simplicity versus Complexity in Financial Regulation by David Aikman, Mirta Galesic, Gerd Gigerenzer, Sujit Kapadia, Konstantinos V. Katsikopoulos, Amit Kothiyal, Emma…

See on Scoop.itBounded Rationality and Beyond

Abstract: 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. 

See on papers.ssrn.com

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As-If Behavioral Economics: Neoclassical Economics in Disguise? by Nathan Berg, Gerd Gigerenzer :: SSRN

See on Scoop.itBounded Rationality and Beyond

Abstract: For a research program that counts improved empirical realism among its primary goals, it is surprising that behavioral economics appears indistinguishable from neoclassical economics in its reliance on “as-if” arguments. “As-if” arguments are frequently put forward in behavioral economics to justify “psychological” models that add new parameters to fit decision outcome data rather than specifying more realistic or empirically supported psychological processes that genuinely explain these data. Another striking similarity is that both behavioral and neoclassical research programs refer to a common set of axiomatic norms without subjecting them to empirical investigation. Notably missing is investigation of whether people who deviate from axiomatic rationality face economically significant losses. Despite producing prolific documentation of deviations from neoclassical norms, behavioral economics has produced almost no evidence that deviations are correlated with lower earnings, lower happiness, impaired health, inaccurate beliefs, or shorter lives. We argue for an alternative non-axiomatic approach to normative analysis focused on veridical descriptions of decision process and a matching principle – between behavioral strategies and the environments in which they are used – referred to as ecological rationality. To make behavioral economics, or psychology and economics, a more rigorously empirical science will require less effort spent extending “as-if” utility theory to account for biases and deviations, and substantially more careful observation of successful decision makers in their respective domains.

See on papers.ssrn.com

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Nudges That Fail by Cass R. Sunstein :: SSRN

See on Scoop.itBounded Rationality and Beyond

Abstract: Why are some nudges ineffective? Focusing primarily on default rules, this essay emphasizes two reasons. The first involves strong antecedent preferences on the part of choosers. The second involves successful “counternudges,” which persuade people to choose in a way that confounds the efforts of choice architects. Nudges might also be ineffective for five other reasons. (1) Some nudges produce confusion. (2) Some nudges have only short-term effects. (3) Some nudges produce “reactance” (though this appears to be rare) (4) Some nudges are based on an inaccurate (though initially plausible) understanding on the part of choice architects of what kinds of choice architecture will move people in particular contexts. (5) Some nudges produce compensating behavior, resulting in no net effect. When a nudge turns out to be ineffective, choice architects have three potential responses: (1) Do nothing; (2) nudge better (or different); and (3) fortify the effects of the nudge, perhaps through counter-counternudges, perhaps through incentives, mandates, or bans.

See on papers.ssrn.com




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