“The Rule of Law and maintenance of order is the science of governance”
– Kautilya’s Arthashastra, 4th century B.C.
“No branch of knowledge and policy is of any avail if the Rule of Law is neglected”
– Kamandak’s Nitisara, 4th century A.D.
Arguably the single biggest constraint to ease of doing business in India is now the ability to enforce contracts and resolve disputes. This is not surprising given the 3.5 crore cases pending in the judicial system. Much of the problem is concentrated in the district and subordinate courts. Contrary to conventional belief, however, the problem is not insurmountable. A case clearance rate of 100 per cent (i.e. zero accumulation) can be achieved with the addition of merely 2,2 79 judges in the lower courts and 93 in High Courts even without efficiency gains. This is already within sanctioned strength and only needs filling vacancies. Scenario analysis of efficiency gains needed to clear the backlog in five years suggest that the required productivity gains are ambitions, but achievable. Given the potential economic and social multipliers of a well-functioning legal system, this may well be the best investment India can make.
5.1 The relationship between economic governance and the Rule of Law (Dandaniti) has been emphasized by Indian thinkers since ancient times. It is seen as the key to prosperity, and a bulwark against Matsyanyaya (i.e. law of the Юsh/jungle). It should be no surprise, therefore, that the Preamble to the Constitution of India deЮnes that the Юrst role of the State is ‘to secure for all its citizens: Justice, social, economic, and political’. In other words, it is well accepted that economic success and prosperity are closely linked to the ability to enforce contracts and resolve disputes.
5.2 Last year’s Economic Survey (2017- 18) presented evidence of the backlog of cases that weighs down the Indian judiciary, economic tribunals and the tax department, thereby constraining economic growth. It also highlighted how the government’s efforts to improve the present regime, by introducing the Insolvency and Bankruptcy Code and the adoption of the Goods and Services Tax, have had a profound impact on improving Ease of Doing Business (EODB) in India1.
5.3 This progress notwithstanding, India continues to lag on the indicator for enforcing contracts, climbing only one rank from 164 to 163 in the latest report of EODB, 2018. In spite of a number of actions to expedite and improve the contract enforcement regime, economic activity is being affected by the long shadow of delays and pendency across the legal landscape2. Contract enforcement remains the single biggest constraint to improve our EODB ranking. This is ironical for a country that has long idealized contract enforcement. As Tulsi Ramayana puts it, “praan jayi par vachan na jayi” i.e., “one’s promise is worth more than one’s life”.
5.4 The Indian judicial system has over 3.53 crore pending cases3 (see Figure 1). At first glance, this number looks very large and insurmountable, but this Chapter will argue it is a potentially solvable problem. Indeed, given the potential benefits, this may be the best investment that the Indian economy can make.
5.5 Given that District and Subordinate courts (D&S courts) account for 87.54 per cent of pending cases, this chapter will focus on this segment and evaluate its performance on parameters such as disposal time, pendency time, case types and case clearance rate. The Chapter further analyses the requirement of additional judges and efficiency gains across the various levels of courts to achieve 100 per cent clearance rate as well as to eliminate the stock of pendency in the next five years.
5.6 The following sections provide an overview of the performance of D&S courts, using metrics that quantify different aspects of the litigant’s experience. These include average age of cases, (both pending and disposed), the number of days between hearings, and the average amount of time spent on the life cycle of cases.
5.7 The pendency of a case on a given date is the time since the date of filing. The distribution of ages of pending cases as on May 31, 2019 is shown in Figure 2. It reveals that the distribution of pendency of both civil
and criminal cases is more or less the same. More than 64 per cent of all cases are pending for more than one year. Figure 3 shows the inter-state variation in average pendency of cases in D&S courts. It reveals that Odisha, Bihar, West Bengal, Uttar Pradesh and Gujarat have higher average pendency for both civil and criminal cases as compared to the national averages whereas Punjab and Delhi have the least average pendency of cases. It may not be a coincidence that the worst performing states are usually (albeit not always) also the poorest.
5.8 Disposal time is measured as the time span between the date of Юling and the date when the decision is passed. The age-wise distribution of the disposal time for D&S courts in 2018 is presented in Figure 4. It
reveals that 74.7 per cent of the civil cases and 86.5 per cent of the criminal cases are disposed within three years. Further, the distribution of state-wise disposal rate is presented in Figure 5. It shows that Bihar, Odisha and West Bengal have higher average disposal time than the national average for
both civil and criminal cases. Further, Punjab and Delhi have the lowest average disposal time. These trends are consistent with the distribution of average pendency age across states. Again, the states in eastern India perform poorly although Gujarat too has higher disposal time.
5.9 International comparison of disposal rate is presented in Figure 6. The data reveals that the average disposal time for civil and criminal cases in Indian D&S courts in 2018 was 4.4 fold and 6 fold higher respectively when compared with the average of Council of Europe members (2016). This indicates that there is huge scope for improvement in the disposal time for Indian D&S courts. The following section provides a detailed analysis of the effectiveness and efficiency of courts using the framework of Case Clearance Rate.
CASE CLEARANCE RATE
5.10 The Case Clearance Rate (CCR) is the ratio of the number of cases disposed of in a given year to the number of cases instituted in that year, expressed as a percentage. It may be noted that the cases disposed of need not have been Юled in the same year, as some proportion of them will typically be backlog from previous years – clearance rate
is mainly used to understand the efficiency of the system in proportion to the inflow of cases.
5.11 Figure 7 shows the relationship between the institution, disposal of cases, and CCR at all India level. While the number of cases instituted each year in D&S courts has gone up, so has the number of disposals. However, the gap between institution and disposals allows cases to accumulate and results in an increase in pendency. This is because the CCR remains structurally below 100 per cent. An encouraging sign was that the CCR had increased from 86.1 per cent in 2015 to 90.5 per cent in 2017, but then declined to 88.7 per cent in 2018.
5.12 The international comparison of CCR is presented in Figure 8. It shows that the CCR for civil and criminal cases in India was 94.76 per cent and 87.41 per cent respectively in 2018 while the COE member has already achieved the CCR above 100
per cent in 2016 for both civil and criminal cases. With a CCR below 100 per cent and a heavy backlog of pre-existing cases, Indian courts suffer from increasing delays. USA’s district courts have better CCR of 98 per cent and 92 per cent for civil cases and criminal cases respectively. While criminal courts in the UK’s England and Wales court system perform relatively well, with a clearance rate of roughly 100 per cent, their civil courts fare poorly in comparison to India, the USA, and the COE average, with a clearance rate of just 62 per cent.
CAN THE LEGAL LOGJAM BE CLEARED?
5.13 There are two key issues at hand that need to be dealt with in order to make the judiciary more efficient. Firstly, to achieve a 100 per cent clearance rate must be achieved so that there is zero accumulation to the existing pendency. Secondly, the backlog of cases already present in the system must be removed. The following analysis is done to solve the above mentioned issues by using the concept of an input–output matrix of cases at different court levels. It is recognized that the disposal rate can be increased. However, productivity is assumed to be constant for the purpose of this analysis.
5.14 Using a simple input-output model, the survey estimates the number of additional lower court judges that would be needed to stop further accretion of pendency and clear the backlog. The D&S courts received 1.5 crore additional cases in 2018 and had a backlog of 2.87 crore (as on January 1, 2018). The number of cases disposed of in 2018 was 1.33 crore. Thus, the closing balance in end-2018 was 3.04 crore. There are currently 17,891 judges compared to the sanctioned strength of 22,750. On average, a judge disposes 746 cases. Chart 1 shows the
calculation for the requirement of additional judges in D&S courts. In order to reach 100 per cent CCR in 2018, the D&S courts needed 2,279 additional judges. This is within the sanctioned strength! However, in order to clear all the backlog in the next five years, further 8,152 judges are needed. This is no more than a rough calculation, but it shows that efficiency gains are also required.
5.15 Applying the same framework to higher courts, we found that the numbers are even smaller (note that the data sets here are from July-June). As of June 2017, High Court judges were working at 62 per cent of their sanctioned strength. With a case clearance rate of 88 per cent, each judge achieved an average disposal rate of 2,348 cases per year. The backlog of cases as on June, 2018 was 44.40 lakh. In order to reach 100 per cent CCR, they needed just 93 additional judges. This is already within the present sanctioned strength for High Courts. To clear all backlogs in the next five years, the High Courts need a further 361 additional judges.
5.16 As of October 2018, Supreme Court judges were working at 90 per cent of their sanctioned strength. With a high case clearance rate of 98 per cent, each judge disposes 1,415 cases per year on average. The backlog of cases as on October 2018 was 56,320. In order to reach 100 per cent CCR, the Supreme Court would have needed only one extra judge in 2018. To clear all backlog in the next five years, an additional eight judges are required. In May 2019, three additional judges were appointed to the Supreme Court raising their number to the full sanctioned strength of 31. To clear backlog, the Supreme Court needs to increase its sanctioned strength by six.
5.17 The main point of this analysis is that a major hurdle to economic growth and social well-being can be stabilized through a relatively small investment in the legal system. The numbers above are illustrative, but it shows that the much debated judicial logjam is solvable.
HOW SHOULD THEADDITIONAL JUDGES BE ALLOCATED?
5.18 In order to optimally allocate these additional D&S judges, the following section has analysed common case types in both civil and criminal pendency. This will help understand which case types require additional judges.
5.19 The types of civil and criminal cases, based on their subject matter and the legislation under which they have been Юled, can result in signiЮcant variation along with the metrics used in this chapter. The complexity and gravity of a case type can determine the stages and process that it must go through. A snapshot of the distribution of common pending case type for both civil and criminal cases at the national level in D&S courts is presented in Table 1 below:
5.20 Table 1 reveals that as on May 31, 2019, the civil cases contribute a mere 28.38 per cent of total pendency while criminal cases contribute about 71.62 per cent in D&S
Table 1: Common Cases Types Weight in Total Pendency (As on May 31, 2019)
|Common Case Types|
|A. Civil cases|
|Civil Original Suits||Civil Suit||14.00|
|Total Civil Original Suits||20.60|
|Total Civil Suits||28.38|
|B. Criminal cases|
|Criminal Original Suits||Warrant/ Summons||56.63|
|Total Criminal Original Suits||64.26|
|Total Criminal Applications||5.80|
|Total Criminal Suits||71.62|
Source: NJDG, 2019.
courts. Further, civil suit, civil execution, warrant! summons and criminal application are common case types stuck in the backlog. These contribute 14 per cent, 4.21 per cent, 55.63 per cent and 2.8 per cent share in total backlog, respectively. We calculate case type clearance rate in D&S courts for 2018, so as to understand which of these cases have a tendency to have backlogs. This is presented in Table 2 below:
5.21 Table 2 reveals that average CCR for all civil and criminal cases in D&S courts for 2018 was 94.76 per cent and 87.41 per cent
Table 2: Case Type Institution, Disposal and CCR for D&S courts in 2018
|Common Case Types||Institution||Disposal||CCR (%)|
|A. Civil cases (Overall)||32,96,242||3 1,23,642||94.76|
|Civil Original Suits||21,77,722||21,09,102||96.85|
|Civil Appeal||1,74,283||1,7 1,790||98.57|
|B. Criminal cases (Overall)||1,16,23,439||1,01,60,317||87.41|
|Criminal Original Suit||86,10,411||73,44,58 1||85.30|
|Warrant/ Summons||76,28,227||64,52,3 14||84.58|
Source: NJDG, 2019.
respectively. This means that not only the backlog of criminal cases is about 2.5 fold higher than civil cases, criminal case type also has lower CCR (even lower than the national CCR of 88.7 per cent). This means that the situation for criminal cases is distinctly worsening. The problem is especially acute for criminal original suits such as summons, warrants etc. These contribute 64 per cent of the total pendency as of May 31, 2019 with a clearance rate of 85.3 per cent. This implies that the additional judges need to specialize in these case types so as to speed up the disposal of such cases. Note that this is a case not merely for additional judges and legal reforms, but also for police reforms (a matter we will take up in a future Economic Survey). Lastly, it may be noted that ‘Motor Vehicle’ and ‘Land Reference’ case types have done quite well, maintaining a CCR of 107.58 and 192.66 per cent respectively in 2018. These areas need to maintain the current pace.
5.22 Some economists may take the view that the relatively poor performance of the criminal justice system is of no direct consequence to the economy. However, a behavioural approach would make no distinction since human beings are seen to respond to the overall context. A culture of Rule of Law must pervade as all of the governance and cannot be improved in silos.
5.23 The progress of a case through various stages reveals to a large extent where judicial delays occur and can aid policy formulation to reduce delays and backlog. Analysis of life-cycle can be used to precisely identify causes of delay, whether they are procedural inefficiencies or shortages of human and physical resources. The average per cent of case life-cycle spent in a civil case is presented below. For the purpose of this section, we have used data from eCourts services portal covering District and Sessions Courts across 15 States, extracted between September 18, 2018 and January 29, 2019.
5.24 Figure 9 shows the stages in chronological order, from left to right. However, not all occur at specific points of a stage, as some can occur at any point, such as orders. In addition, not all cases go through all stages, but those that go through a particular stage may spend a significant part of its life in that stage.
5.25 The data from eCourts shows that most of the time is spent in the ‘LCR/R and P’ (Lower Courts Records – Records and Proceedings) stage. Here, cases cannot proceed as the court must first receive the case’s records from the lower court. Civil cases spend an average of 398 days in this stage and 369 days in the ‘Hearing’ stage. This inefficiency consumes a significant proportion of a case’s life, and is a major factor contributing to delays and backlog. The ‘Notice/Summons’ and ‘Evidence’ stages are also time consuming at 322 and 325 days on average, respectively.
5.26 Figure 10 reveals that, as with civil cases, awaiting lower court records causes delays for criminal cases, being the stage in which they spend the largest amount of time of 243 days, on average. The ‘Evidence’ stage and ‘Framing of Charges’ stages consume 235 and 231, respectively, while all other
stages of criminal cases take much less time. The process for both civil and criminal cases can be significantly sped up by targeting the delay in these specific stages.
5.27 Further, Figure 11 shows that state-wise average number of the days between hearings for civil and criminal cases. Its shows that West Bengal, particularly for civil matters, spends much more time between hearings than any other state – approximately 301.4 days, as compared to the average (across 15 states) of 78.1 days for civil cases. The average for all cases is also the highest in West Bengal – 167.7 days between hearings, compared to the 15-state average of 55.1 days.
5.28 Figure 12 shows that Gujarat and Chhattisgarh have clearance rates of above 100 per cent in 2018. These states have achieved a level of efficiency where they are not only able to cope with fresh filings but can also address backlog from previous years. Madhya Pradesh, Assam and Tamil Nadu have impressively high clearance rates of close to 100 per cent. Again, eastern Indian states perform poorly. Bihar, Odisha, and West Bengal have low clearance rates of 55.58 per cent, 62.18 per cent, and 78.63 per cent respectively. Hence, we suggest that these states should be given priority in the appointment of additional judges.
5.29 There is a great amount of variation in the extent to which the subordinate judiciary in each state is capable of dealing with the inflow of new cases. There are, therefore huge gaps between the demand for courts and the current capacity of the subordinate courts in many states – possibly a key factor in the development inequalities between states.
5.30 Figure 13 reveals that there is some correlation between vacancy and pendency. This is especially true for Uttar Pradesh and Bihar. In these states, the focus should be on filling vacancies. However, note that West Bengal and Maharashtra have few vacancies but high pendency. This means that the national allocation of judges also has to be revisited.
5.31 It may be further noted that although Gujarat and Madhya Pradesh have high pendency, they have also achieved CCR of 108.59 per cent and 99.94 per cent respectively. NJDG data suggests that this is due to relatively recent improvements. Perhaps the efficiency gains of these states should be studied and replicated.
Note: Pendancy as on June 2, 2019.
MAKING INDIAN COURTS MORE PRODUCTIVE
5.32 The analysis thus far has provided a gauge of how many judges would be needed in order to increase the clearance rate at the existing efficiency rate and the nature of the delays. However, there is a large scope for improving the efficiency of the process. As shown in Table 3, the backlog in lower courts can be cleared in five years at full sanctioned strength with an efficiency gain of 24.5 per cent. At current working strength, it would take an efficiency gain of 58 per cent. With full sanctioned strength, High Courts would need only 4.3 per cent increase in efficiency to clear the backlog although, given high vacancy rates, the required rate at current working strength is 68 per cent. The equivalent numbers for the Supreme Court are 18 per cent and 31 per cent respectively.
5.33 Over the years, many suggestions have been put forward by researchers and official committees for enhancing productivity in the judiciary. Some of the suggestions are discussed below:
Table 3: Scenario Analysis of Required Efficiency Gains
|Institution of cases in 2018||1,50,40,971||17,93,546||33,743|
|Disposal of cases in 2018||1,33,41,478||15,75,435||33,011|
|Backlog of cases||3,03,95,534||42,39,966||56,320|
|Sanctioned Strength of Judges||22,750||1,079||31|
|Working Strength of Judges||17,891||671||28|
|Current Disposal Rate per Judge||746||2,348||1,415 *|
|Case Clearance Rate||89%||88%||98%|
|Scenario I: Constant Productivity|
|Total judges required to reach 100% CCR||20,170||764||29|
|Additional Judges required to reach 100% CCR (above existing working strength)||2,279||93||1|
|Additional Judges required to clear backlog in five years||10,431||454||9|
|Additional Judges required to clear backlog in five years (above existing sanctioned strength)||5,572||46||6|
|Scenario II: Required Productivity Gains|
|Required Productivity Gains to clear backlog in five years at full sanctioned strength||24.5%||4.3%||18%|
|Required Productivity Gains to clear backlog in five years at current working strength||58%||68%||31%#|
|Average number of working days||244||232||190|
Source: Supreme Court Annual Report 2018, Various Court Calenders 2019, NJDG 2019 and Survey calculations.
Note: Data for backlog of cases, sanctioned and working strength of judges for D&S courts, HCs and SC is as on December 2018, June 2018 and October 2018 respectively.
*Adjusted for full year using January-October 2018 data.
# As of May 2019, SC is working at its full sanctioned strength.
a) Increase number of working days: It has often been pointed out that Indian courts close down for significant periods due to vacations. The length of these vacations varies a great deal from court-to-court, but appears to have a palpable impact on the number of working days. For instance, the Supreme Court’s official calendar for 2019 suggests that it would close for 49 days for summer vacations, 14 days for winter break, and a further 18 days for Holi, Diwali and Dussehra. After accounting for weekends and public holidays, it leaves 190 working days for the Supreme Court. In contrast, the average is 232 working days for High Courts and 244 days for Subordinate courts. There is a great deal of variation between states, and many courts make up for vacations by working on Saturdays. For comparison, central government offices will be open for 244 working days in 2019 (note that the above calculations exclude personal leaves).
The main finding is that increasing the number of working days may improve productivity of the Supreme Court and in some High Courts, but is unlikely to significantly impact lower courts. Subordinate courts, which account for the bulk of pendency, seem to work almost as many days as government offices.
b) Establishment of Indian Courts and Tribunal Services: Most judicial reforms tend to focus only on the quality and quantity of judges, but a major problem lies with the quality of the administration of the courts system, particularly backend functions and processes. This is critical to reducing the process delays identified earlier in this Chapter. As a recent report by the National Institute of Public Finance and Policy put it, “For effective functioning, courts require competent administration to ensure that processes are followed, documents are submitted and stored, facilities are maintained and human resources are managed. Court administration must support the judges in performing their core judicial function ”4
In the current system, the main responsibility for administration in Indian courts is assigned to the chief judicial officer. In addition to significant demands on his/her time, this approach is not conducive to systemic reforms and gradual accumulation of institutional knowledge on administrative matters. In this context, it has been proposed to create a specialized service called Indian Courts and Tribunal Services (ICTS) that focuses on the administrative aspects of the legal system. The major roles to be played by ICTS would be (i) provide administrative support functions needed by the judiciary (ii) identify process inefficiencies and advise the judiciary on legal reforms (iii) implement the process re-engineering.
The ICTS is not a unique model. Similar, court management services exist in other countries: Her Majesty’s Court and Tribunals Services (UK), Administrative Office of US Courts (US), Court Administration Service (Canada).
c) Deployment of Technology: Technology can significantly improve the efficiency of courts. One major effort in this direction is the eCourts Mission Mode Project that is being rolled out in phases by the Ministry of Law and Justice. This has allowed the creation of the National Judicial Data Grid (NJDG). The system is already able to capture most cases, their status and progress. Most of the analysis in this chapter has been made possible by real time data made publicly available on the NJDG and eCourts portals. The digitalization of cases is now allowing stake-holders to keep track of individual cases and their evolving status. It is not possible yet to statistically measure the efficiency gains from this effort, but it is certainly a big step forward.
5.34 There are significant productivity gains to be derived from better administration, increase in working days, and technology deployment (including likely future applications of Artificial Intelligence). It is difficult to predict the exact improvement, but the purpose of this analysis is to show that the required efficiency gains for clearing the backlog are ambitious but achievable if combined with speeding up appointments. Given the social and economic importance of this issue, it should be given top priority by policy-makers.
|CHAPTER AT A GLANCE|
|> Delays in contract enforcement and disposal resolution are arguably now the single biggest hurdle to the ease of doing business in India and higher GDP growth.|
|> Around 87.5 per cent of pending cases are in the District and Subordinate courts. Therefore, this segment must be the focus of reform.|
|> The study found that 100 per cent clearance rate can be achieved by merely filling out the vacancies in the lower courts and in the High Courts (even without the productivity gains)|
|> Simulations of efficiency gains and additional judges needed to clear the backlog in five years suggest that the numbers are large but achievable.|
|> The states of Uttar Pradesh, Bihar, Odisha and West Bengal need special attention.|
Court News. Publication. Supreme Court of India. 2018. Accessed June 29, 2019. https:// www.sci.gov.in/pdf/CourtNews/COURT_ NEWS_OCTOBER-DECEMBER_20 17. pdf.
Dutta, Pratik, et.al., “How to Modernise the Working of Courts and Tribunals in India.” NIPFP Working Paper Series No. 258, March 25, 2019. Accessed June 29, 2019. https://www.nipfp.org.in/media/ medialibrary/20 1 9/03/WP_20 1 9_25 8.pdf.
European Union. CEPEJ. European Judicial Systems EfЮciency and Quality of Justice. Series 26. Brussels: Council of Europe, 2018.
India. Ministry of Law. Department of Justice. Lok Sabha Unstarred Question No. 675. New Delhi, 2019. 1-40.
____ . Department of Justice. Ministry of Law. National Judicial Data Grid. Accessed June 29, 2019. https://njdg.ecourts.gov.in/ njdgnew/index.php.
Supreme Court. Indian Judiciary: Annual Report 2017–2018. New Delhi, DELHI, 2018.
Source- Economic Survey 2018-19 Volume 1