A longstanding question in the judgment and decision making literature is whether experts, even in high-stakes environments, exhibit the same cognitive biases observed in controlled experiments with inexperienced participants. Massey and Thaler (2013) claim to have found an example of bias and irrationality in expert decision making: general managers’ behavior in the National Football League draft pick trade market. They argue that general managers systematically overvalue top draft picks, which generate less surplus value on average than later first-round picks, a phenomenon known as the loser’s curse. Their conclusion hinges on the assumption that general managers should use expected surplus value as their utility function for evaluating draft picks. This assumption, however, is neither explicitly justified nor necessarily aligned with the strategic complexities of constructing a National Football League roster. In this paper, we challenge their framework by considering alternative utility functions, particularly those that emphasize the acquisition of transformational players––those capable of dramatically increasing a team’s chances of winning the Super Bowl. Under a decision rule that prioritizes the probability of acquiring elite players, which we construct from a novel Bayesian hierarchical Beta regression model, general managers’ draft trade behavior appears rational rather than systematically flawed. More broadly, our findings highlight the critical role of carefully specifying a utility function when evaluating the quality of decisions.

中文翻译：

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失败者的诅咒和效用函数的关键作用

判断和决策文献中一个长期存在的问题是，即使在高风险环境中，专家是否表现出与没有经验的参与者的对照实验中观察到的相同的认知偏差。Massey 和 Thaler （2013） 声称在专家决策中发现了偏见和非理性的例子：总经理在美国国家橄榄球联盟选秀权交易市场的行为。他们认为，总经理系统性地高估了顶级选秀权，平均而言，与后来的首轮选秀权相比，顶级选秀权产生的剩余价值要少，这种现象被称为失败者的诅咒。他们的结论取决于这样一个假设，即总经理应该使用预期剩余价值作为评估选秀权的效用函数。然而，这种假设既没有明确的合理性，也不一定与构建美国国家橄榄球联盟名册的战略复杂性相一致。在本文中，我们通过考虑替代效用函数来挑战他们的框架，特别是那些强调获得变革型球员的函数——那些能够显着增加球队赢得超级碗的机会的函数。根据我们根据新颖的贝叶斯分层 Beta 回归模型构建的优先考虑获得精英球员概率的决策规则，总经理的选秀交易行为似乎是合理的，而不是系统性的缺陷。更广泛地说，我们的研究结果强调了在评估决策质量时仔细指定效用函数的关键作用。