Nicola Lacetera

Welcome to my web page. I am an Associate Professor at the University of Toronto, chief scientist at Behavioural Economics in Action @ Rotman, research associate at the National Bureau of Economic Research, and a fellow at CESifo, the U of T Centre for Ethics, the Canadian Centre for Health Economics, and the Bureau of Research on Innovation, Knowledge and Complexity.

My research concerns the ethical constraints to markets, the motivations for altruistic behavior, and various topics in industrial and innovation economics.

Working papers and current research

  • Paying for Kidneys? A Randomized Survey and Choice Experiment (with Julio Elias and Mario Macis). Revise & Resubmit, American Economic Review . Older version: Efficiency-Morality Tradeoffs in Repugnant Transactions: A Choice Experiment. NBER WP 22632. AEA RCT Registry (RCT ID AEARCTR-0000732)
  • Enhancing Organ Donor Registration Rates through Strengthening ServiceOntario Customer Representatives’ Motivations: Observational Studies and Field Interventions (with Julian House, Audrey Laporte, Mario Macis, Frank Markel and Nina Mazar).
  • Altruism, Ethics and Markets: A Behavioral and Neuroscientific Experimental Study (with Mario Macis, Vikram Chib and Jeffrey Kahn).
  • Opt-out choice framing attenuates gender differences in the choice to compete (with Joyce He and Sonia Kang).
  • Does Scientific Progress Affect Culture? A Digital Text Analysis (with Michela Giorcelli and Astrid Marinoni).
  • The Making of Moral Repugnance (with Matt Feinberg and Lisa Kramer).

Published and forthcoming papers (click on titles to open)

Other publications

Note: All published articles are the sole copyright of the respective publishers. Materials are provided for educational use only. Downloading of materials constitutes an agreement that the materials are for personal use only. Also, most of the data used in the studies reported above are part of proprietary or confidential datasets. Researchers interested in these data can contact me to make arrangements on how to access and use the data.