James Paron

• James Paron, Michael Kahana, Jessica Wachter, Associative Learning and Representativeness. Abstract

  The representativeness heuristic constitutes a striking departure from Bayesian
  updating. According to a strong form of the heuristic, agents reverse
  a conditioning argument: for example inferring that a patient is more
  likely than not to have a rare disease, conditional on a
  positive test result. The correct inference is that a positive test
  result is more likely than not, conditional on
  disease. Recent research implicates representativeness
  in a wide range of financial market anomalies, with potential consequences for
  the real economy. However,
  the cognitive foundations of the representativeness heuristic (RH) remain
  unknown. Here, we show that the RH emerges from a theory of
  associative memory and recognition, leading to a cognitive foundation for the RH, and
  a means of integrating the RH into economic models involving
  decision-making under uncertainty.

Past Courses

• NRSC2273 - Neuroeconomics

  This course will introduce students to neuroeconomics, a field of research that combines economic, psychological, and neuroscientific approaches to study decision-making. The course will focus on our current understanding of how our brains give rise to decisions, and how this knowledge might be used to constrain or advance economic and psychological theories of decision-making. Topics covered will include how individuals make decisions under conditions of uncertainty, how groups of individuals decide to cooperate or compete, and how decisions are shaped by social context, memories, and past experience.

• PSYC2555 - Neuroeconomics

  This course will introduce students to neuroeconomics, a field of research that combines economic, psychological, and neuroscientific approaches to study decision-making. The course will focus on our current understanding of how our brains give rise to decisions, and how this knowledge might be used to constrain or advance economic and psychological theories of decision-making. Topics covered will include how individuals make decisions under conditions of uncertainty, how groups of individuals decide to cooperate or compete, and how decisions are shaped by social context, memories, and past experience.

Knowledge @ Wharton

• Lessons from COVID-19: Health Care’s Progress and Shortcomings Five Years Later, Knowledge @ Wharton - 03/12/2025
• How COVID-19 Changed the World, Knowledge @ Wharton - 03/11/2025
• How Tax Credits in Renewable Energy Finance Distort Outcomes, Knowledge @ Wharton - 03/11/2025
• Why Hybrid Intelligence Is the Future of Human-AI Collaboration, Knowledge @ Wharton - 03/11/2025
• The Psychology of Paying Taxes | Alex Rees-Jones, Knowledge @ Wharton - 03/11/2025
• How Tariffs Are Reshaping Aviation: Supply Chains, Costs, and Consumers, Knowledge @ Wharton - 03/07/2025
• NFL Combine with Kevin Cole, Knowledge @ Wharton - 03/05/2025
• Retail’s Tough Reality: Lessons from Joann’s Closure, Knowledge @ Wharton - 03/05/2025
• Why Does Gender Income Inequality Still Exist in the U.S.?, Knowledge @ Wharton - 03/04/2025
• Women Moving Forward: Collected Insights, Knowledge @ Wharton - 03/04/2025