Learning From Decision Making Researcher Dan Goldstein
One of our readers, an expert in behavioral finance, recommended I start following Dan Goldstein. Below is a quick intro and some recommended readings.
Introduction (Via Dan Goldstein)
Dan Goldstein is Assistant Professor of Marketing at London Business School. He edits Decision Science News and is co-founder of the Economics of Behaviour and Decision Making seminar series.
Recommended Goldstein Papers
Abstract: M. R. Dougherty, A. M. Franco-Watkins, and R. Thomas (2008) conjectured that fast and frugal heuristics need an automatic frequency counter for ordering cues. In fact, only a few heuristics order cues, and these orderings can arise from evolutionary, social, or individual learning, none of which requires automatic frequency counting. The idea that cue validities cannot be computed because memory does not encode missing information is misinformed; it implies that measures of co-occurrence are incomputable and would invalidate most theories of cue learning. They also questioned the recognition heuristic’s psychological plausibility on the basis of their belief that it has not been implemented in a memory model, although it actually has been implemented in ACT-R (L. J. Schooler & R. Hertwig, 2005). On the positive side, M. R. Dougherty et al. discovered a new mechanism for a less-is-more effect. The authors of the present article specify minimal criteria for psychological plausibility, describe some genuine challenges in the study of heuristics, and conclude that fast and frugal heuristics are psychologically plausible: They use limited search and are tractable and robust.
Abstract: Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon’s notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: onereason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the authors held a competition between the satisficing “Take The Best” algorithm and various “rational” inference procedures (e.g., multiple regression). The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference.
3. Measuring Consumer Risk-Return Tradeoffs– Via SSRN – Click Here To Access The Paper
Abstract: Consumer choice occurs over multiple products and services, each comprising multiple risks. In this paper, we present a new market research technique to measure consumers’ preferences over large spaces of risks. We first describe the method, present its psychological and analytical motivation, and then report the results of empirical tests of reliability and validity, both within testing sessions and across the span of one year. The method is used to estimate the coefficient of relative risk aversion and the loss aversion parameter for a sample of adults saving for retirement. The new technique passes tests of reliability and validation and captures individual differences based on age and income. It also identifies two sub-populations, one best fit by a more classical model of risk preference, and the other by a behavioral model which incorporates loss aversion.
Abstract: Sinnce 1995, more than 45,000 people in the United States have died waiting for a suitable donor organ. Although an oft-cited poll (1) showed that 85% of Americans approve of organ donation, less than half had made a decision about donating, and fewer still (28%) had granted permission by signing a donor card, a pattern also observed in Germany, Spain, and Sweden (2–4). Given the shortage of donors, the gap between approval and action is a matter of life and death. What drives the decision to become a potential donor? Within the European Union, donation rates vary by nearly an order of magnitude across countries and these differences are stable from year to year. Even when controlling for variables such as transplant infrastructure, economic and educational status, and religion (5), large differences in donation rates persist. Why?
5. Partitioning Default Effects: Why People Choose Not to Choose – Via SSRN – Click Here To Access The Paper
Abstract:Defaults options have important applications within public policy programs concerning retirement savings, organ donation, and for consumer choice. Past research has theorized several potential reasons why no-action defaults have a profound effect on choice: (i) effort, (ii) implied endorsement, and (iii) reference dependence and its effect on preference construction. However, while the first two of these reasons have been experimentally demonstrated, the latter has not. In two experiments, we produce default effects and simultaneously measure the impact of these three factors. We examine choices between two environmentally consequential alternatives: a cheap but inefficient or an expensive but efficient, light bulb. The results demonstrate that reference dependence can play a leading role in mediating observed default effects. Specifically, we find that the queries formulated by the defaults produce differences in constructed preferences.