Recently, the Bhojpur district court of Bihar was in discussion. It delivered the verdict on a land dispute case filed 108 years ago, making it one of the oldest cases in the country. The case was registered in 1914, the year Mahatma Gandhi returned to India from South Africa!
Of course, this is just one of many such cases going on in Indian courts for decades. According to some estimates, it will take 324 years for district courts to settle all their pending cases, at the current rate of disposal. Just last month, Prime Minister Narendra Modi and Chief Justice of India NV Ramana stressed the need for “expedited” justice at a joint conference of chief ministers of states and chief justices of high courts.
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Several explanations have been given for this unusually large amount of judicial pendency. A major view is regarding Judicial Vacancies. Till two years ago, about 37% of judicial posts in high courts and 21% in subordinate courts were vacant. India has 20 judges per million people, which is extremely low (51 in the UK and 107 in the US). The need to increase the working days of the judiciary, adopt technology and create special tribunals is also being discussed (for example, the government’s recent proposal to set up special courts to close 3.3 million check-bounce cases). Reducing the complexity of legal processes is another popular cry.
Then there are other, demand side explanations. Pending rates will be closely related to filing rates, which in turn may depend on population, legal awareness, education, and income levels of people. But this requires empirical research, which is scant in this area of investigation. Some work done in Western countries shows that higher incomes increase litigation rates (if more contracts are signed, more are broken). The answer is not so clear in low-income areas. For example, recent studies in Kenya and India indicate that high-income areas have less overcrowding of court cases. This could be because of the improved capacity of wealthy-regional courts, a boom in money-driven cases, or perhaps because a growing economy has so much to offer the people, so there is less need to break any laws. Is.
Despite their urgent need, such useful empirical studies are hard to come by, given the constraints of data inadequacy in India. Others focus on larger jurisdictions and propose mostly one-size-fits-all principles. We try to map the district-level caseloads in the country. Of the 470 million cases pending in Indian courts, about 87% are in district and subordinate courts. We wanted to see if there are spatial patterns at the district level that can inform policy making.
We used data in the National Judicial Data Grid to map the number of cases (both civil and criminal) pending for more than 10 years in district courts in 2021. The map shows the total. We observed that the total number of criminal cases pending for 10+ years (2.5 million+) is 3.5 times as compared to civil cases (about 700,000).
But three other findings were more shocking.
First, there is a high correlation between the cases pending at the district level in criminal and civil cases. Courts in which there is delay in one type of case are likely to happen in another type as well. This implies that pendency may be a better function of which district court the case is filed in, whether civil or criminal.
Second, there are some concentrated areas of ‘high-pending’ courts (see for example Uttar Pradesh and Bihar). This implies that there may be some dispersion of district court cultures in case of delay. If the spillover rate is high (more research is needed to ascertain this), then this spread in these areas should be stopped immediately. When we mapped district-level data for cases pending for more than 10 years per 100,000 population, the clustering and other views did not change much.
Third, and perhaps most important, despite a few clusters of ‘high-pending’ jurisdictions, there is no state-wide pattern. Some districts of the same state are performing very well, while the neighboring districts have poor performance. This random distribution of ‘high-pending’ 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 a state or national level issue.
The last point deserves a deeper engagement. For too long, policy-making in most regions has been dominated by country or state design considerations, which have come to 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 historical and each has its own development and social trajectory. Thus it is important to decentralize both the identification of policy problems and their solutions in Indian districts. At our Center for Knowledge Alternatives, we perform district-level data and culture mapping to implement policy. For example, in the available data, we find that around 62% of the cases are pending for 10+ years, which are lying in only 10% of the districts. It would be most efficient and effective to focus on these.
Smriti Jalihal and Yugank Goel are respectively a research associate at the Center for Knowledge Alternatives; and Associate Professor and Founding Director of the Center at Flamm University.