Decision-Making under the Gambler's Fallacy: Evidence from Asylum Judges, Loan Officers, and Baseball Umpires

Daniel L. Chen, Tobias J. Moskowitz, and Kelly Shue


We find consistent evidence of negative autocorrelation in decision making that is unrelated to the merits of the cases considered in three separate high-stakes field settings: refugee asylum court decisions, loan application reviews, and Major League Baseball umpire pitch calls. The evidence is most consistent with the law of small numbers and the gambler’s fallacy—people underestimating the likelihood of sequential streaks occurring by chance—leading to negatively autocorrelated decisions that result in errors. The negative autocorrelation is stronger among more moderate and less experienced decision makers, following longer streaks of decisions in one direction, when the current and previous cases share similar characteristics or occur close in time, and when decision makers face weaker incentives for accuracy. Other explanations for negatively autocorrelated decisions such as quotas, learning, or preferences to treat all parties fairly are less consistent with the evidence, though we cannot completely rule out sequential contrast effects as an alternative explanation


Daniel L. Chen, Tobias J. Moskowitz, and Kelly Shue, Decision-Making Under the Gambler’s Fallacy: Evidence From Asylum Courts, Loan Officers, and Baseball Umpires, IAST working paper, n. 16-43, July 2016.

Published in

The Quarterly Journal of Economics, vol. 131, n. 3, August 2016, pp. 1181–1241