This is a tentative and an exploratory analysis to assess the productivity of the Supreme Court of India (SC) under different Chief Justices of India (CJI) in terms of accomplished adjudications, which is its core function. In particular, we study the number of judgements passed by the apex court per day during the tenure of a CJI and its relationship with the proportion of tenure days when at least one judgement was passed by the SC. Our analysis is for the time period of January 26, 1950, until the September 2, 2019. It is important to mention upfront that important questions regarding jurisprudence, quality of judgement and independence of judiciary are beyond the scope of this paper.

Some key observations: 

1. Over this period, the Supreme Court of India has had 46 Chief Justices. We analyse the tenure of each CJI to study the productivity of the apex court and how it varied across CJIs.
2. The Indian Parliament increased the number of Judges in the Supreme Court of India from 8 in 1950 to 11 in 1956. This was further increased to 14 in 1960, 18 in 1978 and 26 in 1986.
3. Accomplished adjudications (Judgements passed): A total of 51,534 judgements have been passed by the SC during this 69-year period. The lowest number of judgements, 48, were passed during the tenure of CJI Amal Kumar Sarkar, who was in office from March 16, 1966 to June 29, 1966. The highest number of judgements, 7069, were passed by the SC during the tenure of CJI K G Balakrishnan who was in office from January 14, 2007 to May 12, 2010. The average number of judgements passed during the tenure of a CJI is 1120 and the standard deviation [SD] was 1311.
4. Length of tenure: There is significant variation in the length of tenure of a CJI. CJI Kamal Narain Singh was in office from November 25, 1991 to December 12, 1991, a total of 17 days. CJI Y V Chandrachud, on the other hand, was in office from February 22, 1978 to July 11, 1985, a total of 2696 days (or a little over seven years). The mean tenure of a CJI was approximately 552 days and the standard deviation was approximately 503.
5. Number of judgements passed per day: We find variations in the number of judgements passed per day by the SC under tenure of a CJI. For example, during the tenure of CJI H J Kania, who was in office from January 26, 1950 to November 6, 1951, a total of 649 days, the SC passed a total of 128 judgements at the rate of approximately 0.20 (128/649) judgements per day of his tenure. At the other end of the distribution is the tenure of CJI K G Balakrishnan. He was in office for 1214 days, when a total of 7069 judgements were passed by the SC at the rate of approximately 5.82 (7069/1214) judgments per day. The average ‘Number of Judgements Passed by the SC per day’ over tenures of all CJIs during the period of the study was 2.24 with SD of 1.35. We present the results for each CJI in Figure 1.
6. Proportion of ‘Judgement days’: Next, we analyse the variations in the proportion of tenure days when at least one (one or more) judgements were passed by the SC during a CJI’s tenure. For example, during the tenure of CJI Y V Chandrachud who was in office for 2696 days, there were 1106 days when at least one judgement was passed by the SC. Therefore, the proportion of ‘judgement days’ during CJI Y V Chandrachud’s tenure was approximately 0.41 (1106/2696). This means that 41% of days under his tenure saw at least one accomplished adjudication by the Supreme Court of India. The remaining 59% days under his tenure saw no accomplished adjudication by the SC. We call this variable ‘Proportion of Judgement Days’ under a CJI. The average proportion of Judgement Days across all CJIs was 0.45 and the SD is 0.12. This is presented in Figure 2.

Figure 1: Number of Judgements Passed by SC per Day under Each CJI

Figure 2: Proportion of Judgement Days to Total Days in CJI Tenure

7. Productivity of Supreme Court of India: To understand the dynamics of productivity (narrowly defined as the total number of judgements passed per day by the SC), we scrutinise the relationship between number of judgements passed per day by the SC (under a given CJI) and the proportion of judgment days when at least one judgement was passed by the SC (under a given CJI). We present this relationship in Figure 3.

Figure 3: Productivity Increasing with Proportion of Judgement Days

In order to derive this relationship, we ran the following regression:

What does the above relationship mean? The observed relationship between the number of judgements passed per day by the SC under a CJI and the proportion of judgement days under that CJI means the following:

a) Number of judgements passed per day by the SC under a CJI is increasing at an increasing rate with the proportion of judgement days under that CJI. The implications of this can be illustrated with the help of an example. Consider two CJIs (say CJI_A and CJI_B), both of whom have the same length of tenure, say 100 days. If the proportion of judgement days under CJI_A was 0.5, while for CJI_B it was 0.6 (so 20% higher than CJI_A)– then the empirical relationship in Figure 3 would imply that the expected number of judgements passed per day by SC under CJI_A would be approximately 2.7, while it would be much higher at 4.7 judgements per day under CJI_B. That is, the number of judgements per day under CJI_B would be approximately 74% higher than number of judgements per day under CJI_A.

b) We also compute the elasticity (Ꜫ) between total number of judgements passed by SC per day and the proportion of judgement days in the tenure of a CJI. We define elasticity (Ꜫ) as the percentage change in total number of judgements passed by SC per day if there was a 1% increase in the proportion of judgement days in the tenure of a CJI. From the observed relationship we compute the following:

For example, we compare CJI_A and CJI_B who have the same length of tenure but differ in terms of the proportion of judgement days in their tenure. If the proportion of judgement days under CJI_A is 0.5 while for CJI_B it is 0.6, then a 1% increase in the proportion of judgement days under CJI_A would imply an increase of approximately 2.8% in the total number of judgements passed by SC per day of tenure of the CJI_A; while for CJI_B, this increase would be approximately 3.4%. This implies that the elasticity is increasing with the proportion of judgement days under a CJI.

c) Based on this robust empirical relationship, we compute a counterfactual from the data: how many more total judgements would have been passed by the SC, if the proportion of judgement days were increased by 10%, given the existing lengths of CJI tenure? Our analysis reveals that approximately 14,359 additional judgements would have been passed by the SC if the proportion of judgement days increased by a mere 10%. This amounts to an increase of approximately 28% of the total SC judgements passed in the lifespan of the apex court since 1950.

d) We do not find a statistically significant relationship between bench strength (in terms of total number judges) and the number of judgements per day.

Conclusion

We analyse publicly available data for the Supreme Court of India to study the variations in its productivity over time under different Chief Justices of India. For reasons of data availability, this analysis is narrow in scope and limited to quantitative measures of productivity of the apex court. We define productivity using number of judgements per day and the proportion of judgement days under a given CJI. This productivity is likely to vary by the quantum of cases at the Supreme Court. Unfortunately, this data is not available, therefore, we standardise it only by the tenure length. While the number of Justices and the number of cases have changed substantially over time, it is interesting to note that the relationship does not vary linearly over time, and moreover, there is no significant relationship between bench strength and number of judgements per day. For example, the court productivity from 1990-2010 improved as compared to 1980 but declined after 2010. The empirical analysis reveals that number of judgements per day is primarily influenced by proportion of judgement days under a given CJI, there was no evidence that increased bench strength has any significant impact on number of judgements per day. The objective of this study is to initiate a set of broader empirical research and discussions to gain greater insights into the judicial administrative ecosystem of the apex court. These can contribute to informed and constructive interventions and needed judicial reforms in the country.

Data Source: India Kanoon website https://indiankanoon.org/. We also compared the number of SC judgements listed on the India Kanoon website with number of judgements listed on the Supreme Court website at https://sci.gov.in/judgments to determine the accuracy of the data. We could not find any discrepancy between the two websites for the random checks performed.

This piece was original published on the Brookings website on 22 October 2019

Recent slowdown of the Indian economy has been a matter of concern for policymakers. The 5 per cent growth rate for the fiscal year 2019-20 is far below the desired double digit growth rate for India, attributable to a mix of both, internal and external factors. India’s economic journey proves to be an example of partial success. The early success was triggered by the liberalization efforts in 1991 entailing the removal of industrial controls and licenses, following a phase of socialist policies for about three decades post-independence (with a Hindu growth rate of 3.5 per cent). After the economic reforms in 1991, the growth rate reached around 5 per cent for the three year period of 1994-97. However, external factors like global economic crisis have dwindled this economic growth, the last one being the global financial crisis in 2008-09. Since the crisis, India has not been able to recover and attain the desired double digit growth, something that China exhibited in its peak years. The unsustainable growth model of India despite the macro-economic reforms reflects the inherent weaknesses of the economy in the form of domestic rigidities.

Land Policy and Governance, an Impediment to India’s Economic Growth

A major area of concern that drags the growth of the economy has been the festering issue of land policy. Issues and challenges surface now and then in the form of widespread land scams, litigation cases, land acquisition hurdles, distorted land pricing mechanism. The root cause of the problem lies in the failure of Indian administration to have evolved from the British era’s land record and revenue measures. Lack of attention given to land record management in India is reflected in the dearth of any major change in the land record management system over the years.

Evolution of Land Record Management: What is the Missing Link?

Under the British, the purpose of land records was tax revenue collection; the format of the records thus was a reflection of that. Over the years, the objective of land based revenue collection has reduced significantly – for one of the largest Indian States, Uttar Pradesh, the land revenue collection as a percentage of total tax revenue has fallen from 40 per cent in 1957-58 to a minuscule proportion of 0.3 per cent in 2019-20. Despite this redundancy, the land records for most of Indian States/UTs continue to exhibit the relevant columns for tax revenue collection details. This signifies lack of priority conferred upon the land record quality and its relevance as per the current needs.

Post-independence, a slew of land reforms were proposed and introduced across India. The blueprint for these reforms as laid out by the Centre at the time essentially addressed six essential issues:
a) Abolition of intermediaries
b) Abolition or regulation of tenancy and improving the security of the tenants
c) Fixation of ceilings on landholdings and redistribution of surplus land
d) Payment of compensation for acquired lands
e) Consolidation of holdings
f) Choice of appropriate form of organisation and promotion of cooperatives

However, land being a state subject, the implementation of these reforms varied across states. This has translated into divergent paths of land policy and governance in Indian States/UTs. This disparity is also reflected in the land records across states, characterized by the lack of standardized formats of data collection and recording one comes across in India.

With the objective of land records management for land revenue collection becoming a thing of the past, land revenue officials are also observed to be lax in their attitude towards record keeping and management. Instead of redefining land records as a proof of land/property ownership, these officials have been loaded with miscellaneous work like natural disaster management and municipal duties that gives them lesser time to focus on land records accuracy and quality.

Changing the Objective of Land Record Management

With the transition of country from an agrarian economy to a more industry and services driven economy, it is imperative that land records capture details relevant for the times. Today, accurate land records are the minimum essential requirements for supporting efficient and hassle free development. These records must necessarily reflect ground reality and capture all the possible encumbrances – mortgages, litigation cases, land acquisition proceeding or land-use restrictions – clearly to limit the dispute cases and hence make the transaction efficient.

An assessment of the Digital India Land Record Modernization Program (DI-LRMP) conducted by National Council of Applied Economic Research (NCAER) in Himachal Pradesh revealed that around 72 per cent of cases with a variation between reported and the on-ground possession, were due to excessive joint ownership. With such a scenario, when the on-ground subdivision is not reflected in the land records, the chances of it being used as ownership proof for any possible loan from financial institutions slims down, adversely impacting the growth of mortgage market. Further, unclear ownership also makes acquisition processes tedious and long drawn, causing significant escalation of project costs.

Poor land record management also often serves to be the raison d’être for legal disputes over the land/property. Often, the area/extent of land recorded in the legal documents is found to vary with respect to the ground situation. Surveys/Re-surveys in Indian States/UTs have progressed at a snail’s place or have been stalled due to lack of priority towards such detailing. This lack of attention essentially derives from the fact that land revenue collection is no longer the objective of the land record departments.

NCAER’s recent work on creating a nationwide land records and services index has shown, that barring some instances of mortgages, other restrictions/conditions over a plot of land are seldom noted in the textual records. Only 2 states were found to record civil court cases concerning land parcels, while 8 States/UTs were found to record an instance of revenue court cases. With such a poor record of ongoing court cases, property is likely to exchange hands on illegitimate grounds and can further accentuate the chances of legal disputes.

It is clear that there is an urgent need for land record departments across States/UTs to re-orient their focus on ensuring quality and accuracy of land records. Re-establishing land records as a tool for ensuring well-functioning mortgage market and for limiting the land/property related disputes is essential. Clear land records can be a major step towards removing bottlenecks to land reforms in India, and the sooner it happens, the better the chances of spurring rapid growth in India get.

This piece was originally published in Arthasha-Stree, Prerna Prabhakar’s personal blog.

India’s first Land Records and Services Index is a way to gauge States’ relative performance and help improve services on the ground

The National Council of Applied Economic Research (NCAER) recently released India’s first Land Records and Services Index (N-LRSI), 2020, based on data collected over 2019-20 on two aspects of the supply of records — the extent of digitisation of land records and its quality. The first component, which aims to assess whether a State has made all its records digitally available to citizens, looks at three dimensions — the text (also called the record of rights), the official map associated with a land record (also called cadastral maps) and the property registration process. The second component of the index aims to assess if the data is comprehensive and reliable. Whether ownership details are updated as soon as a sale occurs; the extent of joint ownership; type of land use; size of the plot on the record and on the map and if encumbrances are being recorded (other claims on the property such as mortgages and court cases). All these elements are closely connected to property disputes and to the ease with which transactions can be completed, legally recorded and accessed. Madhya Pradesh, Odisha, Maharashtra, Chhattisgarh and Tamil Nadu are the five best-performing States on the index.

One of the unique features of the N-LRSI, 2020 is its ability to assess the relative performance of States on various components and sub-components of the index. There is no State/UT that emerges victorious on all the parameters of the index as they are at different stages of progress with regard to the extent of digitisation of records and the registration process. For improved land record management, laggard States should extract lessons from the better-performing ones on various parameters, which can possibly drive change in State-level policies. While for textual record digitisation, Dadra Nagar Haveli, Chhattisgarh and Goa appeared to be leading, Lakshadweep, Madhya Pradesh and Chhattisgarh topped the list for spatial record digitisation. For the registration component, Maharashtra emerged as the leader, while Jharkhand, Odisha and Chhattisgarh were front runners due to quality records.

The findings will enable States to make efforts in the direction of creating more comprehensive and accurate records, by adopting the initiatives that successful States have made. In addition, the index brings out certain areas where no State/UT has taken any initiative. Effective integration across departments is one such area. The N-LRSI analysis has brought out the poor synergy across land record departments — revenue department as the custodian of textual records, the survey and settlement department managing the spatial records and the registration department. The N-LRSI design entails a sub-component of updating of ownership (within Quality of Records component), which gauges the extent of integration between registration and textual records — swiftness of the process of updating ownership as the result of registration of a transaction, the phenomenon which is commonly known as mutation. The information obtained from all the State/UT sources in this regard revealed that no State/UT has the provision for mutation on the same day as the registration. Moreover, there are only seven States/UTs that have the second-best alternative wherein a note indicating the registration appears in the textual record copy. The study also brought out the weak linkage that exists between the revenue department and survey and settlement department. This creates a huge divergence between the land area reported by the textual and spatial record, enhancing the chances of legal disputes over the definition of boundaries and extent of a land plot. With such poor inter-departmental synergy, aspiring for updated and accurate records will always be a distant goal and States/UTs should strive to undertake necessary actions to have the appropriate systems in place.

With varied recommendations for land record management, the N-LRSI, 2020 holds immense significance for a number of related factors. It is likely to be a helpful tool to assess the quality of key Government services like PM-Kisan, that are dependent on land record details. The efforts by States to improve land record digitisation and quality are expected to increase the chances of accurate identification of PM-Kisan beneficiaries and enhance the scheme’s effectiveness.

The index can be a signalling factor for investors, as a clear title is one of the prerequisites for land acquisition that a firm envisions for setting up an industrial unit. An improved quality of land records, with accurate information that mirrors the ground reality, is expected to provide the necessary push to the underdeveloped mortgage market in India. As per the Committee on Household Finance, 2017 mortgages account for only 23 per cent of total liabilities in India. One of the primary reasons for this dismal situation is the inferior quality of land records, which are often not updated, indicating a high possibility of disputes. Without clear titles, it is not possible for banks to give out loans against the land/property. For instance, if the record does not get updated to reflect the subdivision of property, it cannot be used by the on-ground owner to request for a bank loan. With serious challenges of availability and use of data and information confronting the land policy and governance, the index promises to offer a pivotal solution to improve the existing situation.

The writer is Associate Fellow, NCAER and this piece was originally published in the Daily Pioneer on 14 March 2020.

The National Council of Applied Economic Research (NCAER) recently released India’s first Land Records and Services Index(link is external). The NCAER Land Records and Services Index (N-LRSI) 2020 is based on data collected over 2019-20 on two aspects of the supply of land records—the extent of digitisation of land records and the quality of these land records. The first component, which aims to assess whether a state has made all its land records digitally available to citizens, looks at three dimensions—the text of the land records (also called the record of rights), the official map associated with a land record (also called cadastral maps), and the property registration process.

The second component of the Index aims to assess if the land records are comprehensive and reliable–are ownership details updated as soon as a sale occurs, the extent of joint ownership, type of land use, land area on the record and on the map, and are encumbrances being recorded (other claims on the property such as mortgages and court cases). All these elements are closely connected to land disputes and to the ease with which transactions in land can be completed and legally recorded and then conveniently accessed.

Madhya Pradesh, Odisha, Maharashtra, Chhattisgarh, and Tamil Nadu are the five best-performing States on the N-LRSI 2020 (Figure 1).

While for the textual record digitization, Dadra Nagar Haveli, Chhattisgarh and Goa appeared to be the leading states, Lakshadweep, Madhya Pradesh and Chhattisgarh topped the list for spatial record digitization. For the registration component, Maharashtra emerged as the leader, while Jharkhand, Odisha and Chhattisgarh were the front-runners on the quality of their land records. The findings of the index 2019-20 exercise is likely to enable states go make efforts in the direction of creating more comprehensive and accurate land record, by adopting the initiatives that successful states have made in this direction.

The N-LRSI 2020 data would soon be made available on a land data portal that can be accessed through NCAER’s website. In addition to the N-LRSI State/UT wise scores and rankings, the portal would offer a platform to create your own N-LRSI by selecting specific (sub) components to visualize sensitivity of your state’s performance to these parameters.

For the next phase of N-LRSI, a demand-side survey of citizens will be added to the supply side information, to gauge the level of public awareness and satisfaction in using digital land records and associated services.

This piece was originally published in Land Portal on 04 March 2020.