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Published June 2020 | public
Journal Article

Ignorance and bias in collective decisions

Abstract

We study theoretically and experimentally committee decision making with common interests. Committee members do not know which of two alternatives is optimal, but each member can acquire a private costly signal before casting a vote under either majority or unanimity rule. In the experiment, as predicted by Bayesian equilibrium, voters are more likely to acquire information under majority rule, and vote strategically under unanimity rule. As opposed to Bayesian equilibrium predictions, however, many committee members vote when uninformed. Moreover, uninformed voting is strongly associated with a lower propensity to acquire information. We show that an equilibrium model of subjective prior beliefs can account for both these phenomena, and provides a good overall fit to the observed patterns of behavior both in terms of rational ignorance and biases.

Additional Information

© 2017 Elsevier. Received 15 February 2016, Revised 8 December 2016, Accepted 9 December 2016. Available online 27 December 2016. The authors thank CONACYT (grant 61501) and Asociación Mexicana de Cultura for financial support. Palfrey is grateful for financial support from the NSF (SES-1426560), the Gordon and Betty Moore Foundation (SES-1158), and the Russell Sage Foundation for a visiting scholar grant. The paper also benefited from comments and suggestions from audiences at the 2012 Latin American Meetings of the Econometric Society at University of the Pacific, Lima, the University of Technology, Sydney, the Department of Industrial Engineering at University of Chile, Cornell University, University of Cambridge, George Mason University, Columbia University, the 2014 Santa Barbara Conference on Experimental and Behavioral Economics, the 2014 Wallis Political Economy Conference at the University of Rochester, the 2015 Behavioral Political Economy Workshop at NYUAD, and the 2016 Behavioral Models of Politics Conference at the University of Pittsburgh. The authors especially thank Navin Kartik and Sourav Bhattacharya for detailed comments. Kirill Pogorelskiy provided excellent research assistance. Formerly SSWP 1386.

Additional details

Created:
August 19, 2023
Modified:
October 17, 2023