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Improving Labor Courts: Fighting Corruption with Competition
Last registered on October 08, 2019

Pre-Trial

Trial Information
General Information
Title
Improving Labor Courts: Fighting Corruption with Competition
RCT ID
AEARCTR-0004826
Initial registration date
October 07, 2019
Last updated
October 08, 2019 1:48 PM EDT
Location(s)

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Primary Investigator
Affiliation
ITAM
Other Primary Investigator(s)
PI Affiliation
UC Berkeley
PI Affiliation
UC Berkeley
PI Affiliation
ITAM
Additional Trial Information
Status
On going
Start date
2019-10-01
End date
2021-02-28
Secondary IDs
Abstract
Labor courts are essential for addressing grievances adequately and for well-functioning labor markets. Unfortunately, courts in developing countries function poorly. In Mexico, the law indicates that all lawsuits should be adjudicated within 3 months, but courts face backlogs of about 4 years. Delays are mostly due to the fact that a trial cannot start without the defendant first being notified in person by a court employee (notifier). But a notifier will often fail to notify a defendant because the defendant has paid him a bribe not to, or because delay helps him extract bribes from the plaintiff. In recent years, due to lack of effective notification, only in 30% of cases is the first hearing held on the date initially assigned when the case is filed. On average the first hearing is postponed 3 times, taking well over one year to be concluded. We propose an intervention to increase notification rates and reduce corruption in the labor courts. Notifiers are currently assigned to areas within which they act as the sole notifier, giving them monopoly control over notifications in their area. Thus, a notifier is well positioned to extract bribes from both the defendant and plaintiff. The notifier can guarantee the defendant that a notification will never take place and can simultaneously threaten the plaintiff with never making the notification. Our intervention will randomly rotate notifiers across areas. Under a rotation scheme, a notifier cannot guarantee to the defendant that, in exchange for a bribe today, a notification will continue to fail in the future. The defendant will likely need to bribe additional notifiers to keep the notification from happening. Similarly, under the rotation scheme the notifier cannot threaten the plaintiff with the notification failing in the future if a bribe is not paid today. Our main hypothesis is that the elimination of exclusive control by notifiers will decrease corruption and increase notification rates. We will measure the effect of our intervention on the probability that a case is notified (reflected in administrative data), on the speed of notification, and for which types of workers, firms, and notifiers the increase is largest. We will also measure effort, proxied by the number of firms visited per day and kilometers traveled by the notifier. This information will be captured by a GPS-enabled smartphone that the courts plan to introduce for all notifiers to use. We will gather survey-audit data on firms to determine if the address of the defendant exists, if firms were visited by the notifier, and if notifiers asked for a bribe. We will also collect worker surveys to measure if their lawyer asked them for a bribe for the notifier. The policy is scalable and of current relevance as the Mexican congress has recently passed a major labor reform that includes a notifier rotation policy for initial conciliation hearing notifications.
External Link(s)
Registration Citation
Citation
Dal Bo, Ernesto et al. 2019. "Improving Labor Courts: Fighting Corruption with Competition." AEA RCT Registry. October 08. https://doi.org/10.1257/rct.4826-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2019-11-04
Intervention End Date
2020-12-31
Primary Outcomes
Primary Outcomes (end points)
Notification rate for first hearing, notification rate for subsequent hearings, time to notification, incidence of reported bribed or attempts to offer or collect a bribe.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The experimental design consists of determining a number of zones in the jurisdiction of the court, to minimize the variance of a typical notification route. A number of notifiers equal to double the number of zones will participate in the trial. Exactly half will be randomly assigned to remain in one zone each during the trial. These notifiers will receive exactly half, randomly chosen, of the notifications required in their assigned zone, during the trial period. In each case the notifier will have a specified maximum period of time in which to carry out the notification, and will be monitored using an electronic application to identify when she attempts the notification, whether she visits the exact location of the firm, and whether the attempt is successful. Notifiers assigned to rotate will be successively rotated for each route they undertake, and supervised in the same way as the non-rotating notifiers. Over the course of the experiment we will monitor more than 10,000 casefiles which are assigned randomly to the rotating versus the non-rotating regime. Outcomes we will measure will include attempts to notify, success in notification, time to notification, delay in progress of the lawsuit, and incidence in reported bribes or request for bribes.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Casefile
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
Clustering can be carried out at the notifier level, with 120 notifiers, or at the day level, with approximately 200 days involved in the trial. Finally, we could cluster at the zone level, which would imply 60 clusters.
Sample size: planned number of observations
10,000 casefiles
Sample size (or number of clusters) by treatment arms
5000 casefiles assigned to non-rotating regime, 5000 casefiles assigned to rotating regime.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Institutional Review Board ITAM
IRB Approval Date
2019-07-03
IRB Approval Number
N/A