Randomness Pre‐Considered: Recognizing and Accounting for “De‐Randomizing” Events When Utilizing Random Judicial Assignment

Dane Thorley

Journal of Empirical Legal Studies, 2020, vol. 17, issue 2, 342-382

Abstract: This article contributes to the growing literature challenging the general assumption of and reliance on random judicial assignment by identifying common court procedures and practices that threaten unbiased causal inference. These “de‐randomizing” events, which include differing probabilities of assignment, post‐assignment judicial changes, nonrandom missingness, and nonrandom assignment itself, should be accounted for when making causal claims but are commonly either ignored or not even recognized by researchers utilizing random judicial assignment. The article explores how these de‐randomizing events violate the key empirical assumptions underlying randomized studies and offers methodological solutions. It also presents original data from a survey of the 30 largest U.S. state‐level criminal courts, outlining their assignment protocols and identifying the extent to which they feature the de‐randomizing events described in the article.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:wly:empleg:v:17:y:2020:i:2:p:342-382

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