AEA Papers and Proceedings
ISSN 2574-0768 (Print) | ISSN 2574-0776 (Online)
Algorithmic Recommendations When the Stakes Are High: Evidence from Judicial Elections
AEA Papers and Proceedings
vol. 114,
May 2024
(pp. 633–37)
Abstract
We ask whether increased public scrutiny leads to the more effective use of predictive algorithms. We focus on the context of bail, where judges face heightened public scrutiny during competitive partisan elections. We find that judges up for reelection are much more likely to follow the algorithmic recommendation to detain high-risk defendants just before an election. However, release decisions return to normal shortly after the election, and there is little change in pretrial misconduct rates, indicating that heightened public scrutiny, at least through competitive partisan elections, will not lead to the more effective use of predictive algorithms in bail.Citation
Angelova, Victoria, Will Dobbie, and Crystal S. Yang. 2024. "Algorithmic Recommendations When the Stakes Are High: Evidence from Judicial Elections." AEA Papers and Proceedings, 114: 633–37. DOI: 10.1257/pandp.20241074Additional Materials
JEL Classification
- C45 Neural Networks and Related Topics
- D72 Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
- K41 Litigation Process