The Effects of Pre-Trial Detention on Conviction, Future Crime, and Employment: Evidence from Randomly Assigned Judges

Dobbie, Will; Goldin, Jacob; Yang, Crystal

doi:10.3386/w22511

Cited by 128 publications

(231 citation statements)

References 26 publications

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“…Likewise, the participants in our study all assumed the role of a non‐detained defendant. Criminal defendants held in pre‐trial detention have been found to plead guilty faster than those released prior to trial (Dobbie, Goldin & Yang, ; Sacks & Ackerman, ), and a recent vignette study found that pre‐trial detention significantly increased the odds of pleading guilty for innocent mock defendants when compared to those who were non‐detained (Edkins & Dervan, ). It would be of interest to know how loss/gain frame affects the results we report here.…”

Section: Discussionmentioning

confidence: 99%

Disentangling the effects of plea discount and potential trial sentence on decisions to plead guilty

Schneider

Zottoli

2019

Legal Criminol Psychol

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Background Most criminal convictions are a result of guilty pleas. Concerns have been raised that large differentials between plea and potential trial sentences can be coercive to some defendants, especially when the threat of potential trial sentence is very large. The limited research, to date, suggests that the likelihood of pleading guilty goes up with increasing size of potential trial sentence. However, existing studies have failed to separate the effects of trial sentence and plea discount; as a result, in almost all studies, large potential trial sentences are paired with large discounts and small trial sentences with small discounts, making it difficult to know how the threat of trial sentence actually affects defendant decisions. Method In this study, we examined the effects of guilt, magnitude of potential trial sentence (5 years and 25 years), and size of plea discount (20%, 50%, and 75%) in a fully crossed, between‐subjects design, with acceptance of plea offer as the dependent variable. Results We found that potential trial sentence and plea discount had independent and opposite effects on plea decisions, with discount carrying the most weight. Specifically, participants accepted more plea offers in higher relative to lower discount conditions and when potential trial sentence was 5 years rather than 25 years. The pattern of effects was similar for participants in guilty and innocent conditions. Implications Our results run somewhat counter to conventional wisdom on how discount and potential trial sentence affect plea decisions and suggest that, given similar discounts, the likelihood for pleading guilty may be higher for defendants facing less serious charges that carry less severe sentences. We discuss the policy and research implications of these data.

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Section: Discussionmentioning

confidence: 99%

Disentangling the effects of plea discount and potential trial sentence on decisions to plead guilty

Schneider

Zottoli

2019

Legal Criminol Psychol

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“…Annualized costs of jailing a person are on the order of $30,000, in addition to other harms from lost freedom, impacts on families, increased chances of a finding of guilt, and declines in future employment (Abrams and Rohlfs, 2011, Dobbie, Goldin, and Yang, 2016, Gupta, Hansman, and Frenchman, 2016, Stevenson, 2016, Leslie and Pope, 2016). …”

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confidence: 99%

Human Decisions and Machine Predictions*

Kleinberg

Lakkaraju

Leskovec

et al. 2017

The Quarterly Journal of Economics

493

555

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Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior)

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“…Di Tella and Schargrodsky () find that electronic monitoring, instead of incarceration, decreases recidivism. Furthermore, recent work also suggests that pre‐trial incarceration caused by random assignment to magistrates who set high bail amounts is associated with increases in future offending (Dobbie, Goldin and Yang ; Gupta, Hansman and Frenchman ; Stevenson ).…”

Section: Estimating the Causal Impact Of Incarcerationmentioning

confidence: 99%

Economics of Incarceration

Schnepel¹

2016

Australian Economic Review

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Incarceration rates have more than doubled in Australia over the past several decades, with a dramatic increase since 2010. There are many mechanisms by which these changes in imprisonment exert a causal influence on individual behaviour. The threat of incarceration can deter an individual from committing a crime. The experience of incarceration incapacitates a criminal but can also expose a prisoner to more criminal peers and reduce future legal employment opportunities. This article provides students an introduction to a rapidly expanding economics literature that empirically tests the mechanisms of incarceration and estimates its costs and benefits.

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The Effects of Pre-Trial Detention on Conviction, Future Crime, and Employment: Evidence from Randomly Assigned Judges

Cited by 128 publications

References 26 publications

Disentangling the effects of plea discount and potential trial sentence on decisions to plead guilty

Disentangling the effects of plea discount and potential trial sentence on decisions to plead guilty

Human Decisions and Machine Predictions*

Economics of Incarceration

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