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Using the Statistical Concept of “Severity” to Assess the Compatibility of Seemingly Contradictory Statistical Evidence (With a Particular Application to Damage Estimation)
Journal of Competition Law & Economics ( IF 1.3 ) Pub Date : 2021-08-10 , DOI: 10.1093/joclec/nhab017
Peter Bönisch , Roman Inderst

When parties present divergent econometric evidence, the court might either combine such evidence in an ad hoc way or view such evidence as contradictory and thus ignore it completely, without conducting closer analysis of the possible sources of the contradiction. We believe that the reasons for this development are (i) that the statistical evidence is often interpretated in a simplistic manner and (ii) that the fact is ignored that any statistical test tests within the boundary of a prespecified model which might be wrong. Contradictory evidence might therefore either occur by chance or because the underlying assumptions contradict each other. Based on the concept of severity, we propose a method to avoid common fallacies in the interpretation of empirical evidence. We further set out a simple method for distinguishing between actual and merely apparent contradiction based on the statistical concept of the “severity” of the furnished evidence. Our chosen application is that of damage estimation in follow-on cases.

中文翻译:

使用“严重性”的统计概念来评估看似矛盾的统计证据的兼容性(特别适用于损害估计)

当各方提出不同的计量经济学证据时,法院可能会临时将这些证据组合起来,或者将这些证据视为矛盾的,从而完全忽略它,而不对矛盾的可能来源进行更深入的分析。我们认为,这种发展的原因是(i)统计证据通常以简单的方式解释,以及(ii)忽略了这样一个事实,即在预先指定的模型边界内进行的任何统计测试都可能是错误的。因此,相互矛盾的证据可能是偶然发生的,或者是因为潜在的假设相互矛盾。基于严重性的概念,我们提出了一种避免经验证据解释中常见谬误的方法。我们进一步提出了一种简单的方法,用于根据所提供证据的“严重性”的统计概念来区分实际矛盾和表面矛盾。我们选择的应用是后续案例中的损害估计。
更新日期:2021-08-10
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