Behavioral Economics: Implications for Regulatory Behavior
James C. Cooper
George Mason University School of Law - Law & Economics Center
William E. Kovacic
George Washington University - Law School
July 21, 2011
Journal of Regulatory Economics, Vol. 41, No. 1, February 2012
George Mason Law & Economics Research Paper No. 13-13
Behavioral economics (BE) examines the implications for decision-making when actors suffer from biases documented in the psychological literature. This article considers how such biases affect regulatory decisions. The article posits a simple model of a regulator who serves as an agent to a political overseer. The regulator chooses a policy that accounts for the rewards she receives from the political overseer — whose optimal policy is assumed to maximize short-run outputs that garner political support, rather than long-term welfare outcomes — and the weight the regulator puts on the optimal long run policy. Flawed heuristics and myopia are likely to lead regulators to adopt policies closer to the preferences of political overseers than they would otherwise. The incentive structure for regulators is likely to reward those who adopt politically expedient policies, either intentionally (due to a desire to please the political overseer) or accidentally (due to bounded rationality). The article urges that careful thought be given to calls for greater state intervention, especially when those calls seek to correct firm biases. The article proposes measures that focus rewards to regulators on outcomes rather than outputs as a way to help ameliorate regulatory biases.
Number of Pages in PDF File: 19
Keywords: administrative law, antitrust, asymmetric, Bennett, competition, competitiveness, confirmation bias, endowment effect, Farina, Ginsburg, Jolls, Klick, Korobkin, loss aversion, market, merger, Mitchell, Moore, myopia, public choice, regulation, Rachlinski, Rinner, Stone, Stucke, Tor, Ulen, Wright
JEL Classification: K21, K23, L40, L51, D73Accepted Paper Series
Date posted: July 22, 2011 ; Last revised: November 3, 2014
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