IMPACT OF LEGAL ACCESS ON DOWNSTREAM JUDICIAL AND ECONOMIC OUTCOMES

Last registered on February 16, 2024

Pre-Trial

Trial Information

General Information

Title
IMPACT OF LEGAL ACCESS ON DOWNSTREAM JUDICIAL AND ECONOMIC OUTCOMES
RCT ID
AEARCTR-0012930
Initial registration date
February 12, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
February 16, 2024, 3:35 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation
Indian Kanoon
PI Affiliation
Toulouse School of Economics

Additional Trial Information

Status
On going
Start date
2024-01-23
End date
2025-01-23
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Indian Judiciary is known to experience issues related to huge caseload and delays. Furthermore, litigants do not have easy access to legal advice which often discourages them from reaching out to courts for resolving disputes and other legal troubles. From a macroeconomic perspective, this can be considered a hurdle to economic growth and improved quality of life for individuals and firms.

To help democratize the access to legal information, Indian Kanoon was rolled out in 2008. The primary goal behind the creation of India Kanoon was to democratize access to legal documents. Before its existence, accessing judgments and other legal documents was difficult for ordinary citizens unless they subscribed to expensive legal databases.One of the key features of India Kanoon is its user-friendly search capability. The platform breaks down judgments into paragraphs and provides direct links to referenced statutes, making it easier for users to understand the context.

Researchers are partnering with the Indian Kanoon team to conduct an RCT that aims to measure the economic and judicial impact of providing access to an improved user-friendly version of the legal search engine. The study involves over 100k users over a period of 1 year from all over India. The study measures the impact on the users’ legal knowledge after access to the website. The users will be linked with cases to track the judicial outcomes. The Researchers will also collect administrative data on the financial outcomes of the firms associated with the users.
External Link(s)

Registration Citation

Citation
Chen, Daniel, Viknesh Nagarathinam and Sushant Sinha. 2024. "IMPACT OF LEGAL ACCESS ON DOWNSTREAM JUDICIAL AND ECONOMIC OUTCOMES ." AEA RCT Registry. February 16. https://doi.org/10.1257/rct.12930-1.0
Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-01-23
Intervention End Date
2024-04-23

Primary Outcomes

Primary Outcomes (end points)
User satisfaction, knowledge of laws and financial outcomes.
Primary Outcomes (explanation)
Knowledge of law will be constructed by the answers to 5 "quiz" questions of basic knowledge on the laws in India, asked during the endline survey.
User satisfaction will be measured through a list of survey questions for rating on a likert scale
Financial outcomes are measured by using administrative data on firm performance

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design

The study uses data obtained from surveying over 100k participants. The participants are randomly assigned to treatment and control groups, with 50,000 in treatment and the rest 50,000 in control. Baseline surveys are conducted at launch and the endline surveys are conducted every 3 months for a year.
Experimental Design Details
Not available
Randomization Method
Computer randomization for selection into a treatment group
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
100000 users
Sample size (or number of clusters) by treatment arms
50000 users in treatment and control each
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number