We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

NUDGE: IMPROVING DECISIONS ABOUT HEALTH, WEALTH, AND HAPPINESS by Richard H. Thaler and Cass R. Sunstein Penguin Books, 2009, 312 pp, ISBN 978-0-14-311526-7This book is best described formally as a general explanation of and advocacy for libertarian paternalism, a term coined by the authors in earlier publications. Informally, it is about how leaders, systems, organizations, and governments can nudge people to do the things the nudgers want and need done for the betterment of the nudgees, or of society. It is paternalism in the sense that "it is legitimate for choice architects to try to influence people's behavior in order to make their lives longer, healthier, and better", (p. 5) It is libertarian in that "people should be free to do what they like - and to opt out of undesirable arrangements if they want to do so", (p. 5) The built-in possibility of opting out or making a different choice preserves freedom of choice even though people's behavior has been influenced by the nature of the presentation of the information or by the structure of the decisionmaking system. I had never heard of libertarian paternalism before reading this book, and I now find it fascinating.Written for a general audience, this book contains mostly social and behavioral science theory and models, but there is considerable discussion of structure and process that has roots in mathematical and quantitative modeling. One of the main applications of this social system is economic choice in investing, selecting and purchasing products and services, systems of taxes, banking (mortgages, borrowing, savings), and retirement systems. Other quantitative social choice systems discussed include environmental effects, health care plans, gambling, and organ donations. Softer issues that are also subject to a nudge-based approach are marriage, education, eating, drinking, smoking, influence, spread of information, and politics. There is something in this book for everyone.The basis for this libertarian paternalism concept is in the social theory called "science of choice", the study of the design and implementation of influence systems on various kinds of people. The terms Econs and Humans, are used to refer to people with either considerable or little rational decision-making talent, respectively. The various libertarian paternalism concepts and systems presented are tested and compared in light of these two types of people. Two foundational issues that this book has in common with another book, Network of Echoes: Imitation, Innovation and Invisible Leaders, that was also reviewed for this issue of the Journal are that 1 ) there are two modes of thinking (or components of the brain) - an automatic (intuitive) process and a reflective (rational) process and 2) the need for conformity and the desire for imitation are powerful forces in human behavior. …

Nudge: Improving Decisions about Health, Wealth, and Happiness

/pdf/the-theory-of-industrial-organization-19bejph0ej.pdf

The Theory of Industrial Organization

This paper studies risk attitudes using a large representative survey and a complementary experiment conducted with a representative subject pool in subjects’ homes. Using a question asking people about their willingness to take risks \"in general\", we find that gender, age, height, and parental background have an economically significant impact on willingness to take risks. The experiment confirms the behavioral validity of this measure, using paid lottery choices. Turning to other questions about risk attitudes in specific contexts, we find similar results on the determinants of risk attitudes, and also shed light on the deeper question of stability of risk attitudes across contexts. We conduct a horse race of the ability of different measures to explain risky behaviors such as holdings stocks, occupational choice, and smoking. The question about risk taking in general generates the best all-round predictor of risky behavior.

/pdf/individual-risk-attitudes-measurement-determinants-and-2j4cjvjdkm.pdf

Individual Risk Attitudes: Measurement, Determinants and Behavioral Consequences

By using graphical representations of simple portfolio choice problems, we generate a very rich dataset to study behavior under uncertainty at the level of the individual subject. We test the data for consistency with the maximization hypothesis, and we estimate preferences using a two-parameter utility function based on Faruk Gul (1991). This specification provides a good interpretation of the data at the individual level and can account for the highly heterogeneous behaviors observed in the laboratory. The parameter estimates jointly describe attitudes toward risk and allow us to characterize the distribution of risk preferences in the population.

/pdf/consistency-and-heterogeneity-of-individual-behavior-under-3re8x93lpz.pdf

Consistency and heterogeneity of individual behavior under uncertainty

We report on the results of a large-scale field experiment that enables us to test for consistency with utility-maximizing behavior and to investigate the correlation between individual behavior and demographic and economic characteristics. We conducted the experiment with the CentERpanel (a representative sample of over 2,000 Dutch households), using procedures similar to those used by Choi, et al. (2007b) in a setting with risk. We find a high level of consistency in the individual-level decisions. There is also considerable heterogeneity in subjects’ consistency scores. High-income and high-education subjects display greater levels of consistency. Men are more consistent than women, and young subjects are more consistent than those who

Who is (more) rational

We report a laboratory experiment that enables us to estimate four prominent models of ambiguity aversion — Subjective Expected Utility (SEU), Maxmin Expected Utility (MEU), Recursive Expected Utility (REU), and α-Maxmin Expected Utility (α-MEU) — at the level of the individual subject. We employ graphical representations of
three-dimensional budget sets over bundles of Arrow securities, one of which promises a unit payoff with a known probability and two with unknown (ambiguous) probabilities. The sample exhibits considerable heterogeneity in preferences, as captured through parameter estimates.
Nonetheless, there exists a strong tendency to equate the demands for the securities that pay off in the ambiguous states. This feature is more easily accommodated by the α-MEU model than by the REU model.

/pdf/estimating-ambiguity-aversion-in-a-portfolio-choice-i2oohzb4jt.pdf

Estimating Ambiguity Aversion in a Portfolio Choice Experiment

Estimating ambiguity aversion in a portfolio choice experiment

Given the role of human behavior in the spread of disease, it is vital to understand what drives people to engage in or refrain from health-related behaviors during a pandemic. This paper examines factors associated with the adoption of self-protective health behaviors, such as social distancing and mask wearing, at the start of the Covid-19 pandemic in the USA. These behaviors not only reduce an individual's own risk of infection but also limit the spread of disease to others. Despite these dual benefits, universal adoption of these behaviors is not assured. We focus on the role of socioeconomic differences in explaining behavior, relying on data collected in April 2020 during the early stages of the Covid-19 pandemic. The data include information on income, gender and race along with unique variables relevant to the current pandemic, such as work arrangements and housing quality. We find that higher income is associated with larger changes in self-protective behaviors. These gradients are partially explained by the fact that people with less income are more likely to report circumstances that make adopting self-protective behaviors more difficult, such as an inability to tele-work. Both in the USA and elsewhere, policies that assume universal compliance with self-protective measures-or that otherwise do not account for socioeconomic differences in the costs of doing so-are unlikely to be effective or sustainable.

/pdf/socio-demographic-factors-associated-with-self-protecting-2dwjazuywy.pdf

Syngjoo Choi

Papers

Consistency and heterogeneity of individual behavior under uncertainty

Who is (more) rational

Estimating Ambiguity Aversion in a Portfolio Choice Experiment

Estimating ambiguity aversion in a portfolio choice experiment

Socio-demographic factors associated with self-protecting behavior during the Covid-19 pandemic.