Multitasking, Multi-Armed Bandits, and the Italian Judiciary

Robert Louis Bray, Decio Coviello, Andrea Ichino, Nicola Giuseppe Persico

Research output: Working paper

Abstract

We model how a judge schedules cases as a multi-armed bandit problem. The model indicates that a first-in-first-out (FIFO) scheduling policy is optimal when the case completion hazard rate function is monotonic. But there are two ways to implement FIFO in this context: at the hearing level or at the case level. Our model indicates that the former policy, prioritizing the oldest hearing, is optimal when the case completion hazard rate function decreases, and the latter policy, prioritizing the oldest case, is optimal when the case completion hazard rate function increases. This result convinced six judges of the Roman Labor Court of Appeals -- a court that exhibits increasing hazard rates -- to switch from hearing-level FIFO to case-level FIFO. Tracking these judges for eight years, we estimate that our intervention decreased the average case duration by 12% and the probability of a decision being appealed to the Italian supreme court by 3.8%, relative to a 44-judge control sample.
Original languageEnglish (US)
PublisherSocial Science Research Network (SSRN)
Number of pages30
StatePublished - Mar 23 2016

Fingerprint

Judiciary
Multi-armed bandit
Hazard rate
Multitasking
Schedule
Bandit problems
Supreme Court
Labor

Cite this

Bray, R. L., Coviello, D., Ichino, A., & Persico, N. G. (2016). Multitasking, Multi-Armed Bandits, and the Italian Judiciary. Social Science Research Network (SSRN).
Bray, Robert Louis ; Coviello, Decio ; Ichino, Andrea ; Persico, Nicola Giuseppe. / Multitasking, Multi-Armed Bandits, and the Italian Judiciary. Social Science Research Network (SSRN), 2016.
@techreport{10abe9f01c1d4d528e49a5859f06ef3d,
title = "Multitasking, Multi-Armed Bandits, and the Italian Judiciary",
abstract = "We model how a judge schedules cases as a multi-armed bandit problem. The model indicates that a first-in-first-out (FIFO) scheduling policy is optimal when the case completion hazard rate function is monotonic. But there are two ways to implement FIFO in this context: at the hearing level or at the case level. Our model indicates that the former policy, prioritizing the oldest hearing, is optimal when the case completion hazard rate function decreases, and the latter policy, prioritizing the oldest case, is optimal when the case completion hazard rate function increases. This result convinced six judges of the Roman Labor Court of Appeals -- a court that exhibits increasing hazard rates -- to switch from hearing-level FIFO to case-level FIFO. Tracking these judges for eight years, we estimate that our intervention decreased the average case duration by 12{\%} and the probability of a decision being appealed to the Italian supreme court by 3.8{\%}, relative to a 44-judge control sample.",
author = "Bray, {Robert Louis} and Decio Coviello and Andrea Ichino and Persico, {Nicola Giuseppe}",
year = "2016",
month = "3",
day = "23",
language = "English (US)",
publisher = "Social Science Research Network (SSRN)",
type = "WorkingPaper",
institution = "Social Science Research Network (SSRN)",

}

Bray, RL, Coviello, D, Ichino, A & Persico, NG 2016 'Multitasking, Multi-Armed Bandits, and the Italian Judiciary' Social Science Research Network (SSRN).

Multitasking, Multi-Armed Bandits, and the Italian Judiciary. / Bray, Robert Louis; Coviello, Decio; Ichino, Andrea; Persico, Nicola Giuseppe.

Social Science Research Network (SSRN), 2016.

Research output: Working paper

TY - UNPB

T1 - Multitasking, Multi-Armed Bandits, and the Italian Judiciary

AU - Bray, Robert Louis

AU - Coviello, Decio

AU - Ichino, Andrea

AU - Persico, Nicola Giuseppe

PY - 2016/3/23

Y1 - 2016/3/23

N2 - We model how a judge schedules cases as a multi-armed bandit problem. The model indicates that a first-in-first-out (FIFO) scheduling policy is optimal when the case completion hazard rate function is monotonic. But there are two ways to implement FIFO in this context: at the hearing level or at the case level. Our model indicates that the former policy, prioritizing the oldest hearing, is optimal when the case completion hazard rate function decreases, and the latter policy, prioritizing the oldest case, is optimal when the case completion hazard rate function increases. This result convinced six judges of the Roman Labor Court of Appeals -- a court that exhibits increasing hazard rates -- to switch from hearing-level FIFO to case-level FIFO. Tracking these judges for eight years, we estimate that our intervention decreased the average case duration by 12% and the probability of a decision being appealed to the Italian supreme court by 3.8%, relative to a 44-judge control sample.

AB - We model how a judge schedules cases as a multi-armed bandit problem. The model indicates that a first-in-first-out (FIFO) scheduling policy is optimal when the case completion hazard rate function is monotonic. But there are two ways to implement FIFO in this context: at the hearing level or at the case level. Our model indicates that the former policy, prioritizing the oldest hearing, is optimal when the case completion hazard rate function decreases, and the latter policy, prioritizing the oldest case, is optimal when the case completion hazard rate function increases. This result convinced six judges of the Roman Labor Court of Appeals -- a court that exhibits increasing hazard rates -- to switch from hearing-level FIFO to case-level FIFO. Tracking these judges for eight years, we estimate that our intervention decreased the average case duration by 12% and the probability of a decision being appealed to the Italian supreme court by 3.8%, relative to a 44-judge control sample.

M3 - Working paper

BT - Multitasking, Multi-Armed Bandits, and the Italian Judiciary

PB - Social Science Research Network (SSRN)

ER -

Bray RL, Coviello D, Ichino A, Persico NG. Multitasking, Multi-Armed Bandits, and the Italian Judiciary. Social Science Research Network (SSRN). 2016 Mar 23.