Behavioural economics

2011-04-15 – 2017-09-17
Maybe related 🤷:

To discuss: the pointlessness of behavioural economics as modified classical economics, when large data applications make this a predictive science

A new paradigm for the introductory course in economics:

Our intro courses fail to reflect the dramatic advances in economics — concerning information problems and strategic interactions, for example — since Samuelson’s paradigm-setting 1948 textbook. Missing, too, is any sustained engagement with new problems we now confront and on which economics has important insights for public policy — climate change, innovation, instability and growing inequality amongst them. This column introduces a free online interactive text — now used as the standard intro at UCL, Sciences Po, and Toulouse School of Economics — which responds.

Collective behavioural economics

In financial markets we have some elegant models of collective human behaviour in, e.g. Black-Scholes formulae etc.

In more general contexts, what do we do? A population of mis-specified Bayesian learners? (Shalizi 2009) A bunch of partially informed voters? Distributed learners?

Concepts to think about: Bounded rationality, rational inattention, institutions as stable orbits in behavioural systems, devious negotiation strategies …

Individual models

See marketing psychology.

Risk Perception

See the risk perception page.

References

Bernheim, B. Douglas, and Antonio Rangel. 2009. “Beyond Revealed Preference: Choice-Theoretic Foundations for Behavioral Welfare Economics*.” The Quarterly Journal of Economics 124 (1): 51–104.
Charness, Gary, and Matthias Sutter. 2012. “Groups Make Better Self-Interested Decisions.” Journal of Economic Perspectives 26 (3): 157–76.
Edelmann, Joe. 2022. “Values, Preferences, Meaningful Choice.”
Hausman, Daniel M. 2011. “Mistakes about Preferences in the Social Sciences.” Philosophy of the Social Sciences 41 (1): 3–25.
Montrey, Marcel, and Thomas R. Shultz. 2019. “Outgroup Homogeneity Bias Causes Ingroup Favoritism.” arXiv:1908.08203 [Econ, q-Bio], August.
Peters, Ole. 2019. “The Ergodicity Problem in Economics.” Nature Physics 15 (12): 1216–21.
Peterson, Joshua C., David D. Bourgin, Mayank Agrawal, Daniel Reichman, and Thomas L. Griffiths. 2021. “Using Large-Scale Experiments and Machine Learning to Discover Theories of Human Decision-Making.” Science 372 (6547): 1209–14.
Polman, Evan. 2010. “Why Are Maximizers Less Happy Than Satisficers? Because They Maximize Positive and Negative Outcomes.” Journal of Behavioral Decision Making 23 (2): 179–90.
Roughgarden, Tim. 2018. “Complexity Theory, Game Theory, and Economics.” arXiv:1801.00734 [Cs, Econ], January.
Schwartz, Barry, Andrew Ward, John Monterosso, Sonja Lyubomirsky, Katherine White, and Darrin R. Lehman. 2002. “Maximizing Versus Satisficing: Happiness Is a Matter of Choice.” Journal of Personality and Social Psychology 83 (5): 1178–97.
Shalizi, Cosma Rohilla. 2009. “Dynamics of Bayesian Updating with Dependent Data and Misspecified Models.” Electronic Journal of Statistics 3: 1039–74.
Sharpe, Keiran. 2015. “On the Ellsberg Paradox and Its Extension by Machina.” SSRN Scholarly Paper ID 2630471. Rochester, NY: Social Science Research Network.
Valentine, Melissa A, Daniela Retelny, Alexandra To, Negar Rahmati, Tulsee Doshi, and Michael S Bernstein. 2017. “Flash Organizations: Crowdsourcing Complex Work by Structuring Crowds As Organizations.” In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 3523–37. ACM.
Wojtowicz, Zachary, Nick Chater, and George Loewenstein. 2019. “Boredom and Flow: An Opportunity Cost Theory of Attention-Directing Motivational States.” SSRN Scholarly Paper. Rochester, NY.

Download bibliography

No comments yet. Why not leave one?

GitHub-flavored Markdown & a sane subset of HTML is supported.