Learning versus Unlearning: An Experiment on Retractions
Widely discredited ideas nevertheless persist. Why do we fail to "unlearn"? We study one explanation: beliefs are resistant to retractions (the revoking of earlier information). Our experimental design allows us to identify updating from retractions - unlearning - and to compare it with updating from equivalent new information - learning. Across different kinds of retractions - for instance, those consistent or contradictory with the prior, or those occurring when prior beliefs are either extreme or moderate - subjects do not fully unlearn from retractions and update approximately one-third less from them than from equivalent new information. While we document a number of well-known biases in belief updating in our data, our results are inconsistent with any explanation that does not treat retractions as inherently different. Instead, our analysis suggests that retractions are harder to process, for instance, due to the intimate reliance on conditional reasoning.
For helpful comments, we thank Andreas Aristidou, Vittorio Bassi, Dan Benjamin, Aislinn Bohren, Isabelle Brocas, Gabriele Camera, Juan Carrillo, Alessandra Casella, David Cooper, Giorgio Coricelli, Mark Dean, Laura Doval, Martin Dufwenberg, Ben Enke, Dan Friedman, Mira Frick, Guillaume Frechette, Jonas Hjort, John Horton, Judd Kessler, Brian Libgober, Muriel Niederle, Kirby Nielsen, Charles Noussair, Pietro Ortoleva, Jacopo Perego, Matthew Rabin, Joao Ramos, Martin Rotemberg, Joel Sobel, Charlie Sprenger, Dmitry Taubsinky, Michael Thaler, Severine Toussaert, Sevgi Yuksel, and seminar audiences at NYU, Caltech, USC, and the SWEET Conference. Jeremy Ward and Malavika Mani provided outstanding research assistance. Funding from IEPR is gratefully acknowledged. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.