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The consequences of self-reporting biases: Evidence from the crash preventability program
Journal of Operations Management ( IF 7.8 ) Pub Date : 2021-06-01 , DOI: 10.1002/joom.1149
Alex Scott 1 , Andrew T. Balthrop 2
Affiliation  

Relying on firms to self-report information is an information-gathering mechanism that often results in biased measures due to the incentives of the reporting firms. What is less commonly understood is that using self-reported information for decision-making results in endogenous selection bias, which creates spurious associations between the measure being reported and factors that influence reporting. Thus, conditioning on self-reported information can lead to inaccurate evaluations of firms and bias predictions of future performance, even when the self-reported measure is not intentionally misrepresented. We examine endogenous selection bias in self-reporting regimes using directed acyclic graphs (DAGs). We illustrate the problem using data from a policy change by the U.S. Department of Transportation that allowed firms to report not-at-fault for accidents. We find that large for-hire firms are much more likely to report not-at-fault for accidents—over 40 times more likely than independent drivers—even after controlling for time, location, and weather. When comparing independent drivers with large firms, the reporting disparities make large firms appear 25% safer when using at-fault accidents versus all accidents while providing no improvement in predicting future accidents. This study highlights the consequences of poorly designed information-gathering mechanisms and the usefulness of DAGs for understanding causality in supply chain research.

中文翻译:

自我报告偏见的后果:来自碰撞预防计划的证据

依靠公司自行报告信息是一种信息收集机制,由于报告公司的动机,经常会导致有偏见的措施。不太常见的是,使用自我报告的信息进行决策会导致内生选择偏差,这会在报告的衡量标准与影响报告的因素之间产生虚假关联。因此,以自我报告的信息为条件可能导致对公司的不准确评估和对未来业绩的偏见预测,即使自我报告的衡量标准不是故意歪曲的。我们使用有向无环图 (DAG) 检查自我报告制度中的内生选择偏差。我们使用美国政策变化的数据来说明问题 交通部允许公司报告事故的无过错。我们发现,即使在控制了时间、地点和天气之后,大型出租公司更有可能报告事故无过失——比独立司机高 40 倍以上。在将独立司机与大公司进行比较时,报告差异使大公司在使用故障事故时比所有事故更安全 25%,而在预测未来事故方面没有改进。这项研究强调了设计不当的信息收集机制的后果以及 DAG 在理解供应链研究中的因果关系方面的有用性。我们发现,即使在控制了时间、地点和天气之后,大型出租公司更有可能报告事故无过失——比独立司机高 40 倍以上。在将独立司机与大公司进行比较时,报告差异使大公司在使用故障事故时比所有事故更安全 25%,而在预测未来事故方面没有改进。这项研究强调了设计不当的信息收集机制的后果以及 DAG 在理解供应链研究中的因果关系方面的有用性。我们发现,即使在控制了时间、地点和天气之后,大型出租公司更有可能报告事故无过失——比独立司机高 40 倍以上。在将独立司机与大公司进行比较时,报告差异使大公司在使用故障事故时比所有事故更安全 25%,而在预测未来事故方面没有改进。这项研究强调了设计不当的信息收集机制的后果以及 DAG 在理解供应链研究中的因果关系方面的有用性。
更新日期:2021-07-14
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