To address delay and backlog at civil courts, we propose a procedural rule that we refer to as preordered service to replace sequential service of low-profile cases for breach of contract. Courts pre-announce a list that uses uniquely identifying information to rank potential low-profile contracts, like a combination of contracting parties' taxpayer numbers. They use this list to schedule initial hearings of filed low-profile contract cases in that order. In theory, unlike sequential service, preordered service ensures efficiency in a population of investment games through unraveling. Results from a laboratory experiment suggest that it may substantially reduce court caseloads.Many countries' civil courts experience long delay and large case backlog. The time and resources it takes to enforce contracts may discourage investment into profitable business and impede economic prosperity. Slower courts and larger case backlog have been linked to more breaches of contract and less investment, less lending and tighter credit constraints, higher firm financing costs and smaller firms. So, what reforms can help speed up the courts? Among other things, some have suggested that fewer cases for the courts to look at can help reduce the time it takes to resolve civil disputes. To this end, we propose a procedural rule that aims at reducing the number of court case filings associated with a category of contracts of particularly low profile. The implied reduction in the overall caseload should speed up the courts. As the empirical evidence suggests, faster courts in turn are likely to encourage more investment into profitable business of higher profile---business that is more economically significant and legally complex---leading to more lending, more investment, and more firm growth. With this focus, we propose to preorder the service of such low-profile contract cases at the courts, replacing sequential service, which processes them in order of arrival. If nobody wants to be first in line at the courts, then unraveling reduces the number of such low-profile contract cases being filed. As a consequence, more resources can be allocated to the speedier resolution of higher-profile disputes. We provide proof of concept in the context of a population of low-profile contracts, in an experiment.

The methodology used was laboratory economics experiments with 288 undergraduate students of the University of Exeter. We conducted 10 experimental sessions, eight of which had 32 participants while two sessions had 16 participants for a total of 288 participants. A large number of no-shows in one of the scheduled sessions forced us to run the two 16-person sessions. In each of the 32-participant sessions, we ran two separate 16-person economies in parallel. In each session, subjects sat at a booth which did not allow for visual or verbal communication. The experimenter handed written copies of the instructions, which included a quiz to check for understanding. Subjects read the instructions and completed the quiz in their own time; the experimenter checked their answers and clarified any questions individually if necessary. Once all subjects had their questions checked, the experiment started. There were two practice rounds so that subjects could get familiarized with the software interface. After the second practice round ended, the software informed subjects that the incentivized part would begin. The incentivized part of the experiment consisted of 20 rounds, three of which were randomly selected by the computer for payment. We recruited our subjects from a volunteer pool of undergraduate students from the University of Exeter from a variety of majors via email announcements. No subject in the sample took part in more than one session, and nobody in the sample had registered for a trust game experiment before taking part in our experiment. The sessions took place in the FEELE lab at the University of Exeter in October and November 2016. Payoffs in the experiment were denominated in Experimental Currency Units (ECU). One ECU was worth \pounds2; subjects also received GBP 3 for participating. Sessions lasted on average 50 minutes and the average payment was GBP 12.26.