Misattribution and uncertainty about Beliefs Prevent Learning

Working Paper
Published on 7 December 2022


We study how incorrect and uncertain beliefs about product quality can persist in equilibrium, using the example of fertilizer in East Africa. Farmers believe much local fertilizer is counterfeit or adulterated, but are uncertain of the rate of bad fertilizer; however, multiple studies find little evidence of poor quality fertilizer. We develop a learning model to explain how these incorrect beliefs persist. We show that when the production process is stochastic, agents misattribute idiosyncratic outcomes to bad inputs. Variable outcomes also interfere with updating, and allow beliefs to remain uncertain. Our learning model and simulations show that learning about quality is not possible when misattribution and multiple priors are present.


Jessica B. Hoel

Colorado College

Hope Michelson

University of Illinois at Urbana-Champaign

Ben Norton

Cornell University

Victor Manyong

International Institute of Tropical Agriculture