Isolation : A weak link in Indian public health

by Renuka Sane.

1. There are four parts to the public health response to an epidemic: 1) Trace, 2) Test, 3) Isolate, and 3) Treat. Once someone is infected, tracing involves identifying, listing and following up with all the people who have come in contact with the infected person to ensure that they do not further spread the disease.
   
   
2. While tracing is weak in most of India, some states such as Kerala and Karnataka seem to be doing a better job of tracing. This knowledge can be applied more broadly in India.
   
   
3. India's response to testing has been slow. Only recently have private firms been allowed to do tests for Covid-19. Most of the capability in testing in India is in the private sector, but the limitations of government contracting hamper the extent to which this capability can be brought into fighting Covid-19. Once these problems are solved, and testing is done at scale, we will have a clearer picture of infection hot-spots and will be able to design a appropriate health response.
   
   
4. Once a person has tested positive, or if a person comes in contact with someone who has tested positive, there is a need for isolation. This typically requires staying at home, in a room, separate from others in the household.
   
   
5. Such a recipe for isolation has been designed for countries where the number of members living in a dwelling unit is low. This will be infeasible for most people in India. For example, it is estimated that over 9 million people in Mumbai live in slums. The slums in Dharavi alone are estimated to house 1 million people, with a population density of 869,565 people per square mile. It is impossible to people in low-income housing and slums to self-isolate, especially when toilets are shared in a community. Hence, self-isolation at home will not work for most people in India.
   
   
6. Could the government run isolation facilities? A barrier here is the mistrust of the state. Public isolation facilities are generally found to be sub-standard. People have been seen to flee from public quarantine facilities. Hence, at present, the government is not useful as a mechanism for producing isolation services.
   
   
7. All four legs of the public health response -- trace, test, isolate, treat -- are weak in India. There is considerable interest in the problems of tracing and testing. There is a need for fresh thinking on the problem of isolation also. Once millions of people in India have been tested, what are we going to do with the persons who have tested positive?
   

The author is a researcher at NIPFP.

Linking welfare distribution to land records in India: Part 1

by Diya Uday and Bhargavi Zaveri.

Over a year ago, the Union Government announced the PM-KISAN scheme, which is the first centrally sponsored scheme for making direct benefit transfers to farmers. The scheme, which promises an annual transfer of Rs. 6,000 to farmers, is in line with the trend towards substituting in-kind subsidies with direct benefit transfers (DBTs) in welfare programs in India.

For example, in 2018-19, Rs. 2 trillion (around 8% of total government expenditure) was reportedly delivered through DBTs to beneficiary accounts. In the last two years alone, at least four state governments have rolled out DBTs for providing direct income support for farmers (Table 1).

Table 1: Agricultural income support schemes (2018-19)

	Union	Telangana	Andhra Pradesh	Odisha	West Bengal
Name of scheme	PM Kisan	Rythu Bandhu	Rythu Barosa	Kalia	Krishak Bandhu
Year of announcement	2019	2018	2019	2018	2018
Basis of calculation	Absolute	Per acre	Absolute	Absolute	Per acre
Annual amount	6000	10000	7500	4000	5,000
No. of instalments	3	2	2	2	2
Eligibility	Landowners	Landowners	Landowners/tenants	Landowners/tenants	Unclear
Annual budget allocation (INR crores)	75,000	12,000	8,750	5,611	3,000
Intended no. of farmers (in Mn)	120 (households)	6 farmers	4 farmers	7.5 households	7.2 farmers

Source: These features are extracted from the scheme documents available in public domain as on January 2020.

A common theme that runs across these agricultural income support schemes is that they utilise land records. India has had a checkered history in the field of land record administration and welfare distribution. For example, a previous attempt at linking the fertiliser subsidy to digitised land records has reportedly failed. The variation in the quality of land records across states, and of state capacity for the identification of beneficiaries, will affect the working of such schemes. We may anticipate problems such as the time-lags involved in the updation of records, the area of the land parcel where the subsidy is linked to the size of the land and the identification of possessory interests such as renters and share-croppers. For example, a ground truth study conducted across Maharashtra, Rajasthan and Himachal Pradesh, showed substantial lags in the updation of land records on account of a change in ownership (NCAER 2017). In Maharashtra, for instance, it took an average of 85 days to update the revenue records to reflect a change in the ownership of a land parcel on account of a sale transaction, and 110 days to reflect such a change on account of the death of the original owner (IGIDR 2017).

The implementation of such schemes is complicated by the fact that while the land records are generally maintained by the Revenue Department of the state government, the Agriculture Department is responsible for the implementation of the income support scheme. The efficacy of such schemes would thus depend on the extent to which these departments are able to collaborate.

A new study on the Rythu Bandhu scheme in Telangana

Telangana is an interesting place to study the implementation of an agriculture income support scheme delivered through DBT by entirely relying on land records. This is because unlike the other states that have rolled out similar schemes, the state government of Telangana, before rolling out the Rythu Bandhu scheme (RBS), undertook a state-wide land records updation drive. Referred to as the Land Records Updation Program (LRUP), the drive involved officers of the Revenue Department visiting each village for rectifying errors, updating the land records and issuing a new de-facto land record, referred to as Pattadar Passbooks, to the owners of agricultural land parcels.

While some have acclaimed the RBS as a success story for providing relief to farmers and innovating in the space of agriculture support (here and here), the scheme has been equally criticised for excluding landless and tenant farmers from its purview.

These developments bring up many interesting questions:

• How was the LRUP done?
• To what extent did it contribute towards the design and the implementation of the RBS?
• What are the co-ordination and information sharing mechanisms set up between the Revenue and Agriculture Departments?
• Has the reliance on land records for the identification of beneficiaries resulted in exclusion and inclusion errors? What is the extent of such errors? 
• What is the impact of linking the entitlement under the RBS to the size of the land parcel?

Answering these questions will help in understanding the state capacity required for conducting a state-wide land records updation drive, the problems that arise in linking land records to welfare distribution, and the design and operationalisation of DBTs which use land records for the purpose of identification of beneficiaries.

We investigated these questions through a series of interviews, focus group discussions and matching of land records with beneficiary databases in Telangana, over a period of six months. In a two part series of articles here on The Leap Blog, we unveil our key findings. A more detailed version of this work is visible in Thomas et. al., 2020.

In this first part, we describe how the Telangana government undertook a state-wide land records updation program, the outcomes of the updation program and its potential impact on the identification of beneficiaries under the Rythu Bandhu scheme. The LRUP, which primarily aimed to cover agricultural land, achieved fairly large coverage in terms of area (86%). All districts, except Hyderabad (which does not comprise agricultural land) were covered under the LRUP. The number of disputed land parcels was surprisingly low (~5%), and a fresh revised digital land record could be issued to ~93% of the land parcels that were covered and undisputed.

We argue that the scale and efficiency of the LRUP and the rate of disputed land parcels, is attributable to two factors: the lack of a survey that measures the boundaries of land parcels; and restricting the nature of rights and interests in the updated digital land record. We further argue that these constraints have influenced the design and scope of the RBS, restricting its benefits to land owners, and excluding tenants and share-croppers whose interests are no longer recorded on the land record used for the identification of RBS beneficiaries.

In the next article, we will look at the implementation of the RBS, the payment mechanisms used, the overall satisfaction levels and the extent of errors in the identification of beneficiaries under the RBS.

Our study supplements theoretical perspectives on state capacity in India, generates fresh insights into the kind and quantum of capacity required for the upgradation of land records, a probem that is believed to be a significant challenge to India's development. It also contributes to the literature on state capacity and welfare programs in India (Muralidharan et al (2016); Totapally et al (2019)).

Our study involved interviews with government officials of departments of the State Government which were involved in the implementation of the LRUP and the RBS, namely, the Revenue Department, the Agriculture Department and the Finance Department. We interviewed officials of these Departments at the level of the state, two sample districts and sample villages in each of these districts respectively. Additionally, we interviewed officials of the Finance Department and the Integrated Tribal Development Agency (ITDA), which is the department within the government responsible for the delivery of services to tribal communities in scheduled tribal areas.

The districts of Nalgonda and Mulugu were selected as sample districts for the study, owing to the concentration of a large number of small and marginal landholdings and the population of scheduled castes and scheduled tribes in these districts. To obtain insights into the overall satisfaction levels with the RBS, we conducted focus group discussions with beneficiaries and non-beneficiaries in the two selected villages in these districts. Finally, for the purpose of estimating the extent of errors, if any, in the coverage of beneficiaries under the RBS, we compared the base land records in each of these villages with the RBS beneficiaries lists.

Scope of the LRUP and capacity deployed

The LRUP was envisaged as a three month exercise to improve land records in respect of agricultural land in Telangana through two phases:

1. First phase : This phase covered (a) land parcels with no disputes and (b) land parcels where there were undisputed errors on the records, such as errors of names and surnames.
2. Second phase: The second phase was designed to cover disputed land parcels, such as land parcels in respect of which disputes are pending in the revenue or civil courts, or land parcels that belonged to a Wakf (land belonging to a religious charity and administered by a statutory board) or had boundary disputes with the Forest Department. The key here was that there was a finite list of categories of "disputes" that were identified by the State Government for the purpose of excluding land parcels from Phase 1.

Table 2 gives an overview of the coverage of the LRUP. It shows that except for one district, namely, Hyderabad, which has no agricultural land, the LRUP covered all the districts aggregating to 86% of the area of the state.

Table 2: Coverage under the LRUP

Unit	Coverage	Total	Coverage (%)
Districts	32	33	96.77
Mandals	573	584	97.26
Revenue Villages	10,823	10,343*	Unclear
Area (in acres)	2,38,18,551	2,76,94,830	86
Source: Revenue Department (June 2019) *As per Census 2011.

The coverage indicated in Table 2 was achieved in three months, with the Revenue Department officers having been divided into teams led by the Tehsildar (an official of the Revenue Department in charge of a cluster of villages). The Collector of each district was responsible for the formation of appropriately sized teams for the district, with the mandate of covering 250 acres per day per team. Table 3 gives an overview of the resources deployed for the purpose of the LRUP.

Table 3: Overview of resources deployed for the LRUP

Duration of the project	15th September, 2017-31st December, 2017
Total number of revenue officers involved in the project	3,500
No. of teams	1,507
No. of villages assigned to each team	9
Estimated area to be covered per day	250 acres per team
Estimated No. of days per village	10
Estimated No. of days per district	100
Source: MCR Human Resource Development Institute of Telangana and interviews.

We find that four distinct records are maintained at the level of the village (Table 3a) and the village-level exercise involved updating one of the records, namely, the Record of Rights and the issuance of digital Pattadar Passbooks (explained below) to each land owner.

Table 3a: Overview of land records maintained at the village level

Sethwar	A record containing details of cultivable area on each agricultural land parcel.
Khasra Pahani	A record containing the details of crops on each agricultural parcel of land.
Pahani	A record containing parcel-level information on the ownership, non-ownership interests, area, cultivable and non-cultivable portions, cropping patterns on each agricultural land parcel.
Record of Right (Form 1B)	A record containing a sub-set of the information from the Pahani records, with a focus on the ownership, area, manner of acquisition of each agricultural land parcel
Pattadar Passbook	A record containing information on the ownership of the land parcel.

Each team was part of a training conducted by the District Collectors on (a) the objectives of the exercise; (b) step by step processes involved in the exercise; (c) the formats for the collection of information; (d) the statutory processes to be followed for the correction and modification of the records; and (d) the daily progress reports to be sent to district and state. A state level control room and multiple district-level control rooms were set up to deal with questions that cropped up during the exercise. The reporting heirarchy was clear. The Tehsildars would prepare daily reports for the District Collector, who in turn, was responsible for compiling the village-wise reports in her District. Each report contains information on (a) the details of missing serial numbers for entry in the the Pahani; (b) the extent of variation in the area of the land parcel reflected in the Sethwar and the Pahani; (c) unsettled disputes and issues in the village; (d) details of the land assigned by the government; and (e) list of land parcels put to non-agricultural use in the village.

Budget deployed for the LRUP

An analysis of the financial statements of the Telangana Government shows that while the budget does not separately allocate funds for the LRUP, there is a significant increase in the budget allocation for overall 'land reforms' for the year of implementation of the LRUP, namely, financial year 2017-18 and the financial year 2018-19 (Table 4). In the absence of specific information on the extent to which this allocation was utilised for the LRUP, it is difficult to draw any insights. However, our interviews yielded more specific, although rough, information on the amounts spent for the implementation of the LRUP (Table 4a).

Table 4: Overview of budget estimates for land reform in rural areas (2015-2020)

Financial year	Budget estimate (INR lakhs)	Year-on-year change (%)
2015-16	1363.03*
2016-17	1256.56	-7
2017-18	1335.85	6.31
2018-19	1502.20	12.45
2019-20	1506.18	0.26
Source: Annual Financial Statements. *This is the actual amount spent on land reforms in 2015-16.

Table 4a: Budget estimates for implementation of the LRUP

Aggregate budget (INR crores)	100
Amount used for printing Digital Pattadar Passbooks	40-60
Amount allocated per district for title verification, etc.	1-2
Source: Interviews conducted with state government officials (June 2019)

Table 4a shows that a blanket amount of Rs. 1-2 crores was allocated per district for the process of conducting the title verification, and the overall implementation of the LRUP. This was in addition to the regular budget of the Revenue Department. The allocation was uniform across all districts without regard to their size or other factors which might complicate the implementation further such as fragmented land parcels and vast forest areas. In the absence of district-level data on the usage of these additional funds, it is difficult to ascertain the sufficiency of these amounts or the extent to which a uniform allocation poses problems for the larger or more complex districts.

Digital Pattadar Passbooks

One of the key components of the LRUP was the issuance of digital Pattadar Passbooks (PPBs) to all the owners of agricultural land whose land was found to be undisputed during the LRUP. The PPB is a land record unique to the erstwhile unified state of Andhra Pradesh. Originally, it recorded the interests of owners, Pattadars (defined, under the land revenue laws, as the person who pays the land revenue), mortgagees, and tenants on the land parcel. The purpose of this document was to facilitate farmers' access to credit. For example, the AP Rights in Land and Pattadar Passbooks Act, 1971 allows farmers to apply for credit on the basis of the passbook; and empowers the Collector to recover, on behalf of the lender, an unpaid loan obtained on the basis of the passbook.

The State of Telangana adopted the AP Rights in Land and Pattadar Passbooks Act, 1971 and renamed it as the Telangana Pattadar Passbooks Act, 1971. In 2018, Telangana made two critical amendments to the Telangana Pattadar Passbooks Act, 1971: first, it dispensed with recording the interests of tenants and occupants who are not owners on the PPBs. The reason for this is unclear. However, the current law governing agricultural land tenancies in Telangana, which confers superior rights to protected tenants (namely, tenancies created in 1950) reportedly led to insecurity among owners of agricultural land parcels. It is possible that this was the motivation for restricting the set of rights that were recognised in Pattadar Passbooks.

Second, it specifically provided that loans could be made on the basis of the electronic record of rights, and that the production of the PPB should not be insisted upon for advancing a loan on the security of land, the interest of the owner in land or the crops growing on it (Table 5).

Table 5: Recording of interests in Pattadar Passbooks: pre and post 2018 amendment

	Pre-2018	Post 2018
Pattadar	Yes	Yes
Mortgagee	Yes	No
Tenant	Yes	No

The non-inclusion of tenancies and other interests in the PPB is an important amendment as it ultimately affects the identification of beneficiaries under the RBS.

Disputes uncovered in Phase 1 of the LRUP

Contrary to the popular notion of land being a highly disputed area, nearly 95% of the area covered under the LRUP was cleared as free of disputes related to ownership during the first phase (Table 6).

Table 6: State-level outcomes under the LRUP

LRUP outcomes: in acres and gunthas
Total extent verified	2,38,53,248.36
Total extent clear	2,28,77,333 (94.65)
Total extent not clear	9,75,915.34 (4.09)
LRUP outcomes: in number of land parcels
No. of Survey Nos. verified	1,96,78,844
No. of Survey Nos. cleared	1,87,60,272 (95.33)
No. of Survey Nos. not cleared	9,18,572 (4.66)
Total No. of Khatas covered	71,71,409
Total No. of cleared Khatas	67,68,151 (94.37)
Agricultural Khatas	60,00,509
Non-agricultural and govt. assets	7,67,642
Total No. of Khatas not cleared	4,03,258 (5.62)
Source: Revenue Department, Government of Telangana. Numbers in brackets are percentages of the total of the head under which they appear.

It is possible that the speed of implementation of the LRUP, the coverage and the high clearance rate is attributable to the manner in which the verification process was conducted. Since the LRUP was not preceded by a survey, the entries in the land records with respect to the area and parcel boundaries, were verified on a self-declaration basis. In the article that follows this one, we demonstrate the discrepancies in the area recorded in the base land records and the Rythu Bandhu beneficiary lists. Second, the LRUP involved the updation of a limited number of fields of information in a PPB. As mentioned above, interests other than ownership were not recorded in the revised PPBs. Since interests such as tenancy and possession, which are inherently more difficult to record, were not within the scope of the program, this might have contributed to the wide coverage, low disputes and speed of implementation of the program.

The design of the LRUP and its bifurcation into two phases has important implications for the scale that the program could achieve. As mentioned above, all disputed land parcels were kept out of the purview of the first phase. Thus, for instance, land parcels with respect to which cases are pending in the civil courts or revenue courts or were subject to succession disputes, were kept for Phase 2 of the LRUP. This ensured that digital PPBs could be issued in respect of the bulk of the land parcels (93%) that were cleared of ownership related disputes under the LRUP (Table 7).

Table 7: Number of digital Pattadar Passbooks issued under the LRUP
No. of cleared agricultural Khatas	60,00,509
No. of PPBs issued	55,85,396 (93.08)
No. of Khatas cleared for PPBs, but not yet digitally signed	4,15,113 (6.91)
AADHAAR is available	1,65,055
AADHAAR is not available	2,50,058
Source: Revenue Department, Government of Telangana (June 2019). Nos. in brackets are percentages of the total of the head under which they appear.

Conclusion

The LRUP was envisaged as a speedy and one-time state-wide intervention for the updation of land records and the issuance of updated digital Pattadar Passbooks in Telangana. While the scale and the speed of the program holds important lessons on the importance of planning and capacity, the design and implementation of the program have several unintended consequences affecting the utility of land records generally and the design of the RBS more specifically.

Our study reinforces the notion of the multiplicity of land records at the village level. The ubiquity of the digital Pattadar Passbooks has made them a de-facto land record for ascertaining claims to ownership in Telangana, although their original purpose was restricted to allowing easier access to agriculture credit on the security of the underlying land and crops grown on it. As demonstrated in Table 3a, information about an agricultural land parcel is now spread across the base land records - such as the Pahaani records and the record of rights - which are usually maintained in all states under the respective land revenue laws, and the digital Pattadar Passbooks. This increases the potential for inconsistency in the information across different land records, even as the records are maintained by the same department of the State Government. Given the large-scale digitisation of base land records in Telangana, and the relative ease with which they can be accessed by citizens through digital portals such as MeeSewa, the need to overlay these records with a new land record in the form of Pattadar Passbooks, remains questionable.

Second, the LRUP was not preceded by a state-wide survey. The design of the program restricting the kinds of interests required to be recorded in the updated digital Pattadar Passbooks allowed the program to proceed with relatively higher speed. Counter-intuitively, the level of disputed agricultural land parcels was relatively lower than one might have estimated. However, this seems to be in line with a previous study that sought to investigate the degree of concordance between information recorded in digital land records and reality in Maharashtra, Himachal Pradesh and Rajasthan. The survey found relatively high concordance on ownership between the digital land records and reality. For instance, the study in Maharashtra found that out of the 102 samples land parcels examined across two villages in Maharashtra, 101 of them were owned by the person reflected in the digitised land record. However, the study found higher discrepancies in recording encumbrances and the area of the land parcel as reflected in the digitised land record and the actual area occupied in reality.

In short, the LRUP could achieve this scale within such a short span of time due to the simplification and minimisation of information that was required to be recorded in the Pattadar Passbooks. However, even as the discourse on the formalisation of land records leans towards widening the range of information recorded in land records, the measure of creating a new digital land title record with a restricted set of information would have the unintended consequence of the record being of limited utility.

Finally, the failure to record interests such as tenancy and mortgages on the digital Pattadar Passbooks, might have influenced the design of the Rythu Bandhu scheme. Reliance on the digital Pattadar Passbooks for the identification of beneficiaries leads to exclusion of landless farmers, such as tenants and share croppers, who are cultivating land and incurring expenditure as tenants. To ensure that the agriculture income support is beneficial, the design of the land record that is used as the base for the identification of beneficiaries, is critical. If the land record records interests such as tenancy and occupancy, it is easier to include tenants and actual cultivators within the ambit of the DBT scheme thereby ensuring that the intended benefits under such schemes reach the tiller of the land.

References

Sanand, Gupta and Prabhakar. A Pilot Impact Assessment of the Digital-India Land Records Modernisation Programme, NCAER (2017).

Narayanan et al. Report on the implementation of the Digital India Land Records Modernisation Programme (DILRMP) in the state of Maharashtra, IGIDR (2017).

Muralidharan, Karthik, Paul Niehaus, and Sandip Sukhtankar. 2016. Building State Capacity: Evidence from Biometric Smartcards in India. American Economic Review, 106 (10):2895-2929.

Swetha Totapally, Petra Sonderegger, Priti Rao, Jasper Gosselt, Gaurav Gupta. State of Aadhaar Report 2019. Dalberg, 2019.

Thomas, Uday and Zaveri. Linking welfare distribution to land records: a case-study of the Rythu Bandhu Scheme (RBS) in Telangana, IGIDR (2020).





Diya Uday and Bhargavi Zaveri are researchers at the Finance
Research Group, Mumbai. The study was supported by the Omidyar Network India.

India’s low interest rate regime in litigation

by Karan Gulati and Shubho Roy.

Any judicial adjudication takes time. When claims are finally settled, the successful party has to be compensated for the time value of money. Otherwise, the party is not put in the same position as if the legal harm had not been done. This requires a successful party recovering interest on the monetary claim.

How much interest is the successful party entitled to? The law and the courts must answer this question. There are four possible ways of doing this. (i) Leave it to the discretion of the courts; (ii) calculate the cost of capital of the parties; (iii) enforce a rate agreed to between the parties; or (iv) fix a reference rate in the statute. Each method has its advantages and disadvantages. While discretion of the courts and statutory rates are easier to implement, they do not reflect the cost of delayed payment to the successful plaintiff. This is done when the court awards the opportunity cost of money to the successful party. However, this method is difficult and prone to variation. It may not be feasible to calculate the opportunity cost of a party accurately.

India follows a mixed approach to determine the rate of interest. In some cases, it specifies the rates and leaves it to the discretion of courts in others. The treatment varies depending on whether the case is a general suit or is governed by specialised legislation. Due to multiple laws that were enacted at different points of time, India has ended up with a complicated legislative framework for calculating interest rates. Compounding this problem has been the judicial approach. Jurisprudence on this complicated legal framework is divergent and devoid of underlying economic philosophy. Poor legislative drafting has been interpreted in ways that lead to unpredictable results.

The rate for most civil disputes in India was last amended in 1976. Since then, the economic conditions of India have changed. This has resulted in a scenario where interest granted by courts have become less and less in line with market rates. Overall, both the legislative framework and its judicial interpretation have favored paying lower interest rates than what would be the reasonable cost of capital. This consistent practice of awarding lower interest rates has economic consequences. It generates perverse incentives for litigants.

Since the time the legislation was last amended, India went through multiple economic upheavals. The risk-free rate of return doubled and then went down again. However, the courts continue to award substantially lower interest rates. If the interest rate awarded by the courts is lower than the cost of borrowing for the losing defendant, it can create an incentive to drag out litigation. Every year that a losing defendant is able to delay the eventual judgment, she makes a notional profit. This profit is the difference between the rate at which the party can borrow from the market and the rate awarded by the court at the end of the litigation.

The problem of awarding low-interest rates is further compounded by the uncertainty in the rate that the court will finally award. Indian jurisprudence shows that there is no predictability in whether interest will be awarded, at what rate it will be awarded, and for what period? Courts frequently change the statutory provision through interpretation and even overrule interest rates agreed to by the parties. This causes uncertainty in contracts. Parties are unable to foresee the damages that will be awarded if the commitments under the contract are not honored. Such uncertainty leads to less contracting, or contracting being limited between parties who trust each other, or excessive capital being locked up in guarantees.

In an upcoming paper, we argue that this has important consequences. India’s slow judiciary and poor record in contract enforcement have recently gained prominence. However, most solutions offered for the problem revolve around increasing the size and capacity of the judiciary. We think that perverse incentives caused by awarding low-interest rates and lack of certainty about interest being awarded may contribute to the delay. If this is the case, then increasing the number of judges will not solve the problem. India needs substantial legal changes in awarding interest to successful parties in litigation. Such rates should reflect the economic reality of India and consider the cost of borrowing for average litigants. They should also consider the opportunity cost of money for successful litigants. The law should be a general principle and not be dependent on the nature of the litigation.

The upcoming paper contributes to the literature on analyzing perverse incentives and unintended consequences created by law. Our findings are similar to which shows that laws may have unintended consequences. Starting from, who argued that minimum wage legislation had the opposite effect of reducing income, there is a growing literature showing that legislation has consequences unforeseen by the creators, including precisely the opposite outcome. The paper argues that in addition to the perverse incentive to extend litigation, interest laws in India may be contributing to the problem of judicial delays. In the lines of, judicial delays in India may be a product of incentives rather than a shortage of judges.



Karan Gulati is a researcher at Symbiosis Law School and Shubho Roy is a researcher at the University of Chicago. The paper was presented at the APU-NIPFP workshop Strengthening the Republic #1, January 11, 2020.