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Judicial delays and the need for intervention at the district level | May 22, 2022
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This is, of course, one of many such cases languishing in Indian courts for decades. By some estimates, at the current rate of disposal, district courts will take 324 years to dispose of all their pending cases. Just last month, Prime Minister Narendra Modi and Chief Justice of India N.V. Ramana, in a joint conference of state chief ministers and chief justices of high courts emphasized the need for “speedy" justice.

A range of explanations for this unusually large amount of judicial pendency has been given. A prominent view is about judicial vacancies. Until two years ago, around 37% of judicial posts in high courts and 21% in subordinate courts were lying vacant. India has 20 judges per million people, which is extremely low (the corresponding figure in the UK is 51 and in the US, 107). There are also discussions on the need to increase working days of the judiciary, adopt technology, and on creating specialized tribunals (for instance, the government’s recent proposal to set up special courts to close 3.3 million cheque-bounce cases). Reducing the complexity of legal procedures is another popular cry.

Then there are other, demand side explanations. Pendency rates will be closely related to filing rates, which may in turn depend on population, legal awareness, education, and income levels of the people. But it requires empirical research, which is scanty in this field of inquiry. Some work done in Western countries suggests that higher incomes increase litigation rates (if more contracts are signed, more get broken). The answer is not so clear in low-income regions. Recent studies in Kenya and India, for instance, indicate that congestion in court cases is lower in higher-income regions. This could be due to the better capacity of richer-area courts, money-driven case acceleration, or maybe because a rising economy has much to offer people so fewer feel the need to break any law.

Despite their urgent need, such useful empirical studies, are hard to come by, given constraints of data inadequacy in India. Others are focused on bigger courts and mostly propose one-size-fits-all theories. We make an attempt to map district-level caseload in the country. Of the 47 million cases pending in Indian courts, around 87% are in district and subordinate courts. We wanted to see if there are spatial patterns at the district level that can inform policymaking.

We used data in the National Judicial Data Grid to map the number of cases (both civil and criminal) pending for over 10 years in district courts in 2021. The map shows the total. We noticed that the total number of criminal cases (2.5 million+) with 10+ years of pendency is 3.5 times that of civil cases (almost 700,000).

But three other findings were more striking.

First, district-level pendency in criminal and civil matters are highly correlated. Courts that have delays in one type of matter are likely to have it in the other type as well. This implies that pendency may be a better function of which district court the case is filed in than whether it is civil or criminal.

Secondly, there are a few concentrated pockets of ‘high-pendency’ courts (see for instance Uttar Pradesh and Bihar). This implies that there may be some spillover of district court cultures in terms of delays. If the spillover rates are high (more research is needed to find this out), then arresting this spread should be done urgently in these regions. When we mapped the district-level figures for cases pending for more than 10 years, per 100,000 population, the clustering and other visuals did not change much.

Third, and perhaps most importantly, despite some clustering of ‘high-pendency’ courts, there is no state-wide pattern. Some districts in the same state do very well, while adjoining ones perform poorly. This random distribution of ‘high-pendency’ courts implies that district-level interventions rather than state- or national-level policies may yield quicker and better results to address the problem. Pendency is a district-level problem, and not state or national level.

The last point deserves a deeper engagement. For far too long, policymaking in most fields has been dominated by country or state design ideas plastered over a large number of districts without considering their unique challenges. What if each district is telling us a different story?

Our districts are huge. They are also historic and each has had its own development and social trajectory. It is thus important to decentralize both identification of policy problems and their solutions to Indian districts. At our Centre for Knowledge Alternatives, we do district-level data and culture mapping for policy application. In the available data, for instance, we realize that almost 62% of cases pending for 10+ years are lying in just 10% of the districts. Focusing on these would be most efficient and impactful.

Smriti Jalihal & Yugank Goyal are, respectively, a research associate at Centre for Knowledge Alternatives; and associate professor and founding director of the Centre at Flame University.