A Temporal Analysis of the Supreme Court of India's Workload

Indian Law Review 9th July, 2019

57 Pages Posted: 11 Jul 2019 Last revised: 12 Jul 2019

See all articles by Rahul Hemrajani

Rahul Hemrajani

National Law School of India University, Bangalore

Himanshu Agarwal

National Law University Delhi

Date Written: July 9, 2019

Abstract

Empirical research on the workload of the Supreme Court of India remains restricted by data sources. Existing approaches which adopt the count of cases as their primary measure miss the fact that the capacity of the Court is largely time driven. Courts have a limited time to hear cases making judge time a scarce resource. Stating that a court has a certain number of cases pending is insufficient to make inferences about the court’s congestion, capacity or efficiency. Applying a new data collection technique, we develop a dataset which records hearing time for each case in the Supreme Court of India. Using the weighted caseload method, we analyse the disposal rate, pendency and congestion faced by the Court. We find that the Court faces an unsustainable workload given existing resources and efficiency. We further use the model to evaluate the efficacy of common suggestions to reduce pendency in the Court. We conclude by discussing avenues for further research utilising time data.

Keywords: Indian Supreme Court, Pendency, Arrears, Workload, Oral Hearing, Special Leave Petitions

Suggested Citation

Hemrajani, Rahul and Agarwal, Himanshu, A Temporal Analysis of the Supreme Court of India's Workload (July 9, 2019). Indian Law Review 9th July, 2019, Available at SSRN: https://ssrn.com/abstract=3417761 or http://dx.doi.org/10.2139/ssrn.3417761

Rahul Hemrajani (Contact Author)

National Law School of India University, Bangalore ( email )

Bengaluru

Himanshu Agarwal

National Law University Delhi ( email )

Sector-14
Dwarka
New Delhi, New Delhi 110078
India

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
245
Abstract Views
892
Rank
239,659
PlumX Metrics