How are securities laws enforced in India: some facts from a new data-set of SEBI orders

by Devendra Damle and Bhargavi Zaveri Shah.

Introduction

The Securities and Exchange of Board of India (SEBI) is one of the most powerful regulators in India. As the regulator of one of the world's largest stock markets by market capitalization, SEBI has a variety of enforcement tools at its disposal. These include the imposition of monetary penalties, license cancellation and pursuing criminal proceedings against violators. The law empowers SEBI to issue directions to intermediaries, and more broadly, to persons associated with the securities market. Such directions may be of a prohibitory nature, such as restricting companies from raising capital in the public markets, disqualifying persons from acting on the board of publicly traded issuers and restricting access to the capital market altogether. They may also be of a remedial nature such as disgorging illegal gains made by violators or directing restitution to wronged investors. The grounds for issuing such directions are wide.

How has SEBI used these enforcement powers over time? Has it prioritized enforcement against some kinds of misconduct over others? If yes, have the priorities stayed static or changed over time? Do certain types of violations consistently entail certain types of sanctions? How efficient are the enforcement proceedings in terms of the time taken, and what is the success rate for enforcing such sanctions? Unlike some Indian financial sector regulators, SEBI follows a due process before issuing such orders, involving the issuance of a show cause notice and a hearing and publishes each enforcement order passed by its officials systematically on its website. This transparency in enforcement allows us to establish some basic facts on securities laws enforcement in India over a long observation period. In a new paper, we analyse over 8,000 enforcement orders passed by SEBI over a span of ten years to answer some of the questions we mentioned above. In this article, we summarize the key findings of our work.

Data description

In our study period beginning 1st January, 2011 and ending on 31st December, 2020, SEBI passed 9048 enforcement orders, of which we were able to sucessfully download and parse 8032 orders. We then analysed these orders, using text-mining software we designed ourselves, to arrive at some summary statistics on the frequency and type of enforcement undertaken by SEBI during the study period. To answer more detailed questions on the nature of enforcement, we manually analysed a stratified random sample of about 10% of these orders. The sample was drawn from the set of orders involving four regulations, which are most frequently enforced by SEBI (as per our data), namely, orders pertaining to fraudulent and unfair trade practices in the Indian securities market (FUTP), violations of the Insider Trading regulations, the Takeover Code and Broker regulations.

As mentioned above, the SEBI Act empowers SEBI to pass two types of orders, namely, orders imposing monetary penalties and orders issuing directions. Such orders can be issued against intermediaries, market participants, issuers of capital or persons generally associated with the securities market. Until 2019, monetary penalty orders could be passed only by adjudication officers and directions would be issued by whole time members of the SEBI board. With effect from 2019, the members of the SEBI board have also been empowered to pass orders imposing monetary penalties. In addition to these, the law also empowers SEBI to settle violations upon the payment of a settlement fee, without passing a guilty verdict against the violator. Basis this scheme of the SEBI Act, we categorize the enforcement orders in our data set into three categories shown in the Table. On an average, SEBI issues 250 enforcement orders with directions and double the number of orders imposing monetary penalties each year. The SEBI Act also empowers SEBI to initiate criminal prosecution against persons accused of having violated the SEBI Act or the regulations made by it, but we do not take account of this typology of enforcement proceedings in our study.

Table: Enforcement orders (2011-20)

Type of order	Type of sanction	Total^
Orders by Adjudicating officers	Monetary penalties	4911 (61)
Orders by Chairperson/member	Non-monetary sanctions	2484 (31)*
Settlement orders	Settlement fee	637 (8)
Total		8032 (100)
^Numbers in brackets are a percentage of the total. *We estimate that not more than 30 orders may involve a monetary penalty.

As is evident from the Table, securities law enforcement is largely undertaken in India through monetary penalties, but the proportion of enforcement undertaken through non-monetary sanctions is not trivial. Settlements account for less than 10% of the total enforcement orders in our data. The annual distribution of these types of orders is shown in the Figure. The Figure shows that from 2018 onwards, there has been a sharp increase in the intensity of enforcement, with the number of monetary penalty orders nearly doubling from the previous years. The proportion of settlements has also increased over time, particularly after 2016. While the growth in the size of the market, an increase in the intensity of regulation and enforcement capacity are intuitive explanations for this jump, more precise, causal explanations require further research.

Figure: Year-wise types of enforcement orders (2011-2020)

Findings

SEBI draws its substantive powers from a set of three laws, over and above the SEBI Act, namely, the Companies Act, 2013 (and its preceding legislation), the Securities Contracts (Regulation) Act,1956 (SCRA) and the Depositories Act, 1996. While the Companies Act largely deals with the incorporation of Indian companies and the governance of their affairs, it also governs primary issuances, the requirements to be met by public offer documents and some aspects of the governance of listed companies. These matters under the Companies Act are administered by SEBI. The SCRA governs the conceptual definition of securities and securities contracts, regulates some types of securities contracts and governs the licensing and affairs of stock exchanges. The Depositories Act, 1996 deals with the regulation of depositories and depository participants. Under each of these laws, and in particular under the SEBI Act, SEBI has issued regulations defining the registration and reporting requirements for intermediaries, the kinds of misconduct that will elicit penalties, and so on.

We find that orders against fraudulent and unfair trade practices (FUTP) are the single largest group (15%), followed by orders dealing with violations of the provisions of the Companies Act (11%), insider trading regulations (10%) and the takeover code (9%). The enforcement actions (i.e. the number of orders) under the remaining regulations are few, with some of them having witnessed enforcement not more than once during the study period. Some of these seemingly rarely-enforced regulations, such as the regulations governing alternative investment advisors, are relatively new, which may explain why they do not appear more often in our data. However, others, such as the regulations governing venture capital funds, stock exchanges and clearing corporations, are older, but we see fewer orders issued under these regulations as compared to other regulations. Whether this is because the regulations themselves are not violated as frequently by market participants, or because SEBI chooses not to enforce them, requires further study.

To answer more specific questions of these enforcement orders, we manually analysed a random sample of 818 orders (approximately 10% of the total sample) from amongst the orders against the following types of violations: (1) FUTP, (2) insider trading, (3) violations of the takeover code and (4) violations of brokers' regulations. Some findings from this micro-study are summarised below:

1. Duration of the enforcement proceedings: The formal enforcement process at SEBI begins with the appointment of an investigating authority who investigates the facts and reports her findings to the SEBI board. If the findings are adverse, a show cause notice is issued to the accused by the adjudication officer (where the proposed sanction is a monetary penalty) or a whole time member of the SEBI board (where the proposed intervention is a direction). We find that the median time for the issuance of a show cause notice is a little more than three years from the date on which the violation was committed. Further, the median time from the date of issuance of a show cause notice to the date of an order imposing monetary penalties is a year and a half. It is a little more than two years for orders issuing directions. A regulation-wise analysis of the duration suggests no relationship between the complexity of the violation involved and the duration of the enforcement proceeding.
2. Subject and outcome of enforcement: A bulk of the enforcement actions are in respect of unregulated entities, that is, entities that are not SEBI-licensed intermediaries. This phenomenon could be attributed to the type of violations that are most often enforced against, namely FUTP and insider trading. Both these practices would likely involve traders and market participants that are not SEBI-licensed intermediaries. Further, in nearly 80% of the cases, SEBI found the person(s) guilty of all the violations that they were charged with, with a marginally higher conviction rate for unregulated entities compared to regulated entities. The conviction rate for violations of the Takeover Code is also marginally higher, compared to violations under the three sets of regulations. It is hard to comment on the optimality of this high conviction rate as these enforcement proceedings are undertaken and decided by SEBI officers themselves. All orders of SEBI, except those rejecting an application for settlement, are appealable to the Securities Appellate Tribunal (SAT). The rate of appeals and the outcome of appeals before the SAT could be a rough proxy to evaluate the optimality of this conviction rate and would be a good direction for further research.
3. Proportionality of sanction: We find a lot of variation in the amount of penalty levied across cases. While the median (i.e. typical) size of the penalty is in the range of Rs 5,00,000, the average is in the range of Rs. 57,00,000. This difference indicates that while there are few cases where large penalties are issued, the size of these penalties is very large compared to the typically-imposed penalties. One explanation that could account for this variation is the amount involved in the violation. The SEBI Act requires an Adjudicating Officer to take into account, among other factors, the amount of disproportionate gain or unfair advantage made as a result of the default or the amount of loss caused to investors as a result of such default. However, we find that in a vast majority of the cases in our sample (90%), the size of the violation was not calculated.

   We similarly find a lot of variation in the orders that impose sanctions other than monetary penalties. Out of 118 such orders, 82 orders restricted the market access of the accused. The duration of such restrictions varied from 15 days to 4 years, and we could not discern any relationship between the duration of the restriction on the one hand and the violation or the purpose of the restriction on the other. Further, courts have repeatedly held that SEBI's direction making powers are remedial and preventive in nature, and not punitive. However, it is unclear at what point an order that operates to restrict market access starts to become punitive in nature, since none of the orders in our data clearly draw the line between remedial and punitive measures.

Conclusion

In India, the field of securities laws is often studied from the perspective of a specific case, individual legislative amendments or specific judgements of courts. While such analysis is useful, a slightly different, more quantitative approach is necessary to gain a systematic understanding of the manner in which the regulator uses the wide variety of enforcement tools available to it, the manner in which it seeks to enforce against different kinds of misconduct and the efficiency of its enforcement functions. The consistent publication of easily accessible enforcement orders by SEBI on its website makes it possible to undertake such systematic research on securities laws enforcement in India. This paper is one such effort to begin developing more systematic knowledge on enforcement of private law in India.

The data used for this analysis can be found here. The data-set can be cited as Zaveri Shah, Bhargavi; Damle, Devendra (2022), "Securities law enforcement in India", Mendeley Data, V1, doi: 10.17632/ppdk9pzfdp.1.

Devendra Damle is an independent researcher. Bhargavi Zaveri Shah is a doctoral candidate at the National University of Singapore.

Bringing gender equality in the Hindu Succession Act: An overdue reform

by Devendra Damle and Ajay Shah.

One element of the gender problem in India is the Hindu Succession Act, 1956 (HSA). This law governs intestate succession for Hindus, Buddhists, Jains and Sikhs (i.e. 80% of Indian citizens), and discriminates against women. Under the rules governing the devolution of property, the relatives of a woman's husband have a stronger claim to her property than her parents and siblings. This is not true of the property belonging to a man. This unequal treatment is inconsistent with equal treatment by the state as envisioned in Articles 14 and 15(1) of the Constitution of India.

This question has just come back into prominence. In an ongoing case — Kamal Anant Khopkar vs Union of India [WP(C) 1517/2018] — the Supreme Court of India issued an order on 7th December 2021 directing the Solicitor General to provide the Union Government's view on these discriminatory provisions (See: here). A brief by the Amicus Curiae — Meenakshi Arora — highlighting the discriminatory provisions prompted the Supreme Court to take this action. The bench noted that this discrimination has remained in the statute books for a long time. The Court also noted that a judicial and/or legislative intervention is necessary to remedy it.

The discriminatory provisions in the HSA have profoundly impacted many Hindu women. Some examples help us understand the unfairness in play:

1. Consider an ongoing case in the High Court of Punjab and Haryana (See: here). One Devina Bhardwaj and her husband Chetan Bhardwaj jointly purchased a home in Gurgaon in 2014. Devina bore most of the expense. Both contracted COVID-19 in early 2021. Chetan died intestate in April 2021. As a result, his property devolved to Devina and his parents in equal parts. Shortly after that, Devina also died intestate. Devina's mother-in-law sought to gain access to Devina and Chetan's assets (estimated to be worth INR 2.7 crore), a significant portion of which were Devina's self-acquired property. The concerned revenue department officials declared her the sole-legal heir to Devina's assets. This is in line with the scheme of devolution under the HSA.
   Devina's mother has filed a petition in the High Court of Punjab and Haryana claiming her right to Devina's share of assets, and challenging the constitutional validity of the relevant provision of the HSA. The High Court has issued a notice to the Union Government seeking its reply. (See: here)

2. The Supreme Court dealt with a similar issue in the landmark case Om Prakash v. Radhacharan [(2009) 15 SCC 66]. In this case, one Narayani Devi's husband died shortly after their marriage. Her in-laws banished her from the matrimonial home. She returned to her parents, who supported her and provided her with an education. She went on to amass a significant amount of property of her own, and died childless and intestate. Her mother and her late husband's nephews filed competing claims over her self-acquired property. The matter eventually reached the Supreme Court. The Supreme Court, relying on a plain reading of the HSA, granted all of Narayani's' property to her late husband's nephews, while her mother received nothing. The story would have been very different if Narayani had been a man.

In an NIPFP working paper, we describe how devolution schemes under the HSA differ for men and women. We describe how courts have interpreted these provisions, and their validity under Articles 14 and 15(1) of the Constitution of India. We describe the previous attempts at reform and where they have fallen short. We propose an amendment to the HSA to make it more gender-equitable. Several other authors have pointed out the disparity between how a man's and woman's property is treated under the HSA, and the consequences of this discrimination (See: here and here).

Devolution of property under HSA

The HSA prescribes different rules of devolution for property belonging to men and women. The devolution scheme for a man is governed by Section 8 of the HSA. It states that Class-I heirs — his mother, wife, and lineal descendants — have the first claim to his property. Class-II heirs — his father, siblings, lineal descendants of his siblings, and the siblings of his parents — have a claim if there are no surviving Class-I heirs. The Schedule to the Act contains a detailed list of heirs in each class and sub-class. All property belonging to the man devolves as per this scheme, and it largely keeps all the man's property within his natal family.

The devolution scheme for a woman's property is different. Section 15(2) applies to any property the woman inherited from her husband, her husband's family and her parents. Under Section 15(2)(a), if a widow dies childless, any property she inherited from her husband or his family returns to the heirs of the husband. 'Heirs of the husband' refers to the list of heirs given in Section 8. Section 15(1) gives a general devolution scheme, which applies to all other properties. Under Section 15(1), a woman's husband and children have the first claim to her property. The heirs of her husband are next in line, followed by her parents, followed by other heirs of her parents.

Under Section 15(1), if a widow dies childless, the heirs of the husband have a stronger claim than her parents and siblings over all her property that she did not inherit from her parents. This includes all self-acquired property, gifts, bequests through wills, and property inherited from siblings and other relatives. There are no reciprocal provisions in the devolution scheme for a male deceased's property. There is no scenario where a woman's family has a claim over the husband's property.

Constitutional challenge to Section 15 of the HSA

Article 14 of the Constitution of India guarantees all persons equal treatment under the law and Article 15(1) explicitly prohibits the state from discriminating between citizens solely based on religion, race, caste, sex, or place of birth. This means the state cannot make laws that treat citizens differently solely based on the aforementioned distinctions, except in specific circumstances. It appears clear that the provisions of the HSA — which are part of Hindu personal law — discriminate between men and women, but does this violate Article 14 and 15(1)?

In Mamta Dinesh Vakil v. Bansi S. Wadhwa [LNIND 2012 BOM 748] the Bombay High Court termed this unequal treatment unconstitutional. It concluded that the discrimination in HSA is solely based on sex and cannot plausibly be said to serve any other rational purpose. The Court, however, referred the question of constitutionality to a larger bench, which has yet to be constituted. While the question of constitutionality may not be settled, judgments such as Om Prakash v. Radhacharan highlight the fact that discrimination under HSA is, in the least, extremely unfair to women. Specifically, Hindu widows with no surviving children.

India's international commitments

The discrimination under HSA falls afoul of India's commitments under the United Nations Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW). India became a signatory to the CEDAW in 1980, and the Parliament ratified it in 1993. Removing gender-based discrimination in property-related legislation is one of the core requirements of the CEDAW.

The Supreme Court has, in multiple cases, ruled that the legislature, administration and judiciary must give due regard to India's international commitments under treaties such as the CEDAW. In C Masilamani Mudaliar & Ors v Idol of Sri Swaminathaswami Thirukoil & Ors [(1996) 8 SCC 525], the Supreme Court ruled that the obligations under CEDAW to eliminate gender-based discrimination in legislation are binding on the government. The Supreme Court has made similar rulings in several other cases, such as Madhu Kishwar & Ors. v State of Bihar & Ors. [(1996) 5 SCC 125], and Githa Hariharan and Ors. v Reserve Bank of India and Ors. (MANU/SC/0117/1999).

Past attempts at reform

There have been some attempts at reform in the past, but so far, they have been piecemeal, limited in their scope, and unsuccessful. The Law Commission of India, in their 207th Report (2008) and their Consultation Paper on Family Law (2018), recognised the issue of disparity in the treatment of men's and women's self-acquired property and proposed amendments. However, instead of instituting a common devolution scheme, they proposed adding another subsection to Section 15 to govern the devolution of a woman's self-acquired property.

The Law Commission's proposal has three issues. First, it does not define self-acquired property. Second, it retains Section 15(2)(b), which requires the property that a woman has inherited from her husband to be passed to the husband's heirs if she dies childless. Third, it ignores the fact that the heirs of the husband will be preferred over the woman's natal family if she has inherited the property in question from relatives other than her parents, such as her siblings or grand-parents, since it will continue to be governed by Section 15(1).

Two private member's bills — the first introduced by Anurag Singh Thakur in 2013 and the second introduced by Dushyant Chautala in 2015 — also sought to resolve this issue. However, both these proposed amendments suffered from the same problems as the proposal of the Law Commission. What is necessary is a comprehensive reform of the devolution scheme in the HSA.

Better examples before us

There are two existing Indian succession laws that do far better than the HSA in terms of gender-equality. Devolution schemes in the Indian Succession Act, 1925 (ISA) and the Goa Succession, Special Notaries and Inventory Proceeding Act, 2012 (GSSNIP) are gender-neutral. ISA applies to Christians and Parsis, and GSSNIP applies to all persons domiciled in Goa. The British Colonial Government enacted the ISA in 1925. The progenitor of the GSSNIP — the Portuguese Civil Code — was enacted in Goa in 1870. The ISA is still on the statute books, and the GSSNIP replaced the Portuguese Civil Code in Goa in 2018.

Conclusion

The provisions of the HSA discriminate against Hindu women by prescribing different rules for the devolution of property held by men and women. These provisions unfairly prioritise the husband's family over the woman's own family, even when the woman has acquired the property in question through her skill or effort. The legislation is a product of an era when it was inconceivable for Indian women to own and acquire property. However, these biases continue to be perpetrated upon Hindu women in India today. This discrimination is probably ultra vires of Articles 14 and 15 of the Constitution of India. It violates India's commitments under the CEDAW. It is unfortunate that the Parliament has allowed this discrimination to persist despite knowing of the existence of more equitable laws such as the GSSNIP and ISA in our own country.

The Supreme Court's notice to the Union Government is an indication of India's evolving jurisprudence on questions of gender-equity. This is an opportunity for the Court and the Parliament to, once and for all, eliminate discrimination in a law that affects a majority of Indian women.

References

1. Gender discrimination in devolution of property under Hindu Succession Act, 1956 (NIPFP Working Paper No 305), by Devendra Damle, Siddharth Srivastava, Tushar Anand, Viraj Joshi and Vishal Trehan, May 2020.
2. Equal treatment for women on inheritance, by Ajay Shah, in Business Standard, 2020.
3. A law that thwarts justice, by Prabha Sridevan, in The Hindu, 2011.
4. Childless Hindu widow's death leads to flawed property succession: Supreme Court, in The Times of India, 2021.
5. HC seeks Centre's reply on petition challenging validity of section 15 of Hindu Succession Act alleging gender discrimination, in LegitEye, Aug 2021.
6. Proposal to amend Section 15 of the Hindu Succession Act, 1956 in case a female dies intestate leaving her self acquired property with no heirs (Report No 207), by Law Commission of India, 2008.
7. Consultation Paper on Family Law, by Law Commission of India, 2018.
8. Manju Narayan Nathan v. Union of India and another [CWP No. 14305 of 2021 (O&M)], High Court of Punjab and Haryana, August 2021.

Devendra Damle is researcher at the National Institute of Public Finance and Policy. Ajay Shah is researcher at xKDR Forum and Jindal Global University.

Author: Devendra Damle

Devendra Damle is a researcher at the National Institute of Public Finance and Policy.

On this blog:

• Bringing gender-equality in the Hindu Succession Act: An overdue reform, 14 December 2021.
• Litigation in public contracts: some estimates from court data, 26 May 2021.
• Estimating the impact of the draft drone regulations, 19 March 2018.
• Replace voice votes, 11 April 2017.
• Does the NCLT Have Enough Judges?, 6 April 2017.
• How well is India's land record digitisation programme doing: Findings from Rajasthan, 14 December 2017.

Litigation in public contracts: some estimates from court data

by Devendra Damle, Karan Gulati, Anjali Sharma and Bhargavi Zaveri.

Introduction

Public contracts are contracts executed by the government and its agencies to procure goods, services and works. Public contracts in India are perceived to be litigation prone. There is evidence that more than half the road projects awarded by the government of India were the subject matter of litigation before the courts and arbitration tribunals, and that a significantly large value of infrastructure projects are stuck in litigation for prolonged periods. This article seeks to estimate and understand the volume and nature of litigation relating to public contracts by observing litigation in one high court in India.

Understanding the volume, value and nature of litigation arising in public contracts is critical. First, the government is an active procurer of goods, services and works in several large sectors such as natural resources and infrastructure. The state's litigation propensity in contracts is a key factor in the ease of doing business in such sectors. Second, the propensity of each government department and agency, such as the union, states, urban local bodies, CPSEs and SPSEs, to engage in litigation may vary. Assessing the litigation propensity of different government departments and agencies helps contractual counterparties assess the costs of dealing with them. Third, estimating the volume, value, costs and outcomes of government litigation helps understand its impact on the exchequer. It can serve as a useful feedback loop in planning the litigation policy of the government and its agencies.

Our analysis suggests that the government is a counterparty to more than half the civil commercial litigation in the Delhi High Court. However, a small proportion of this litigation can be linked to disputes in public contracts. Second, we find that the government is not a major initiator of, but is a large defender in litigation involving public contracts. However, more than 50% of the cases filed by the government against businesses are of one type, namely, challenges to arbitration awards passed in disputes arising in public contracts. Finally, we find that businesses are not using the standard legal remedy of suits for enforcing contractual claims against the government or its agencies. This suggests that most of this litigation is related to the pre-award stages of the business-government engagement. This could also be attributed to the procedural simplicity of proving claims in writ petitions and the relatively quicker duration within which they get disposed.

The popular discourse on government litigation has focused on the volume and pendency of the litigation to which the government or its agencies are a counterparty. Our findings, although limited to observations to the Delhi High Court, provide a foundation for drawing up data-backed country-level estimates of the government's propensity to litigate, and the time, costs and court capacity consumed in litigation relating to public contracts.

Data and approach

For our analysis, we start with a dataset of cases filed before the Delhi High Court from 1st January 2007 until 30th September 2020 ("study period"). We select the Delhi High Court for our analysis for two reasons. First, the Delhi High Court is one of the five High Courts in India exercising original jurisdiction over contractual disputes. All High Courts in India, except these five, exercise appellate jurisdiction. This means that they restrict themselves to reviewing the lower courts' orders. The Delhi High Court is the first level dispute redressal forum for disputes within its territorial jurisdiction in commercial contracts exceeding Rs. 2 crores. The second reason is the physical proximity of the Delhi High Court to the central government and its agencies.

The objective of our analysis is to understand litigation in public contracts. The Delhi High Court classifies case-types into 288 categories. During the study period, 5,42,355 cases have been filed before the Delhi High Court across these categories. These categories cover every type of case that the court deals with, ranging from admiralty cases to family disputes. We undertake three rounds of data filtering to arrive at a subset of cases that are the closest proxies of contractual disputes involving the government.

Filtering out cases not involving contractual disputes with the government

In the first instance, we filter out all the case-types which are not related to contracts. For instance, we filter out bail and criminal applications, testamentary and tax matters and matters under the Companies Act and contempt petitions. We filter out all appellate matters and references from lower courts. We filter out cases where either of the parties is unknown or the data is not machine-readable. This gives us a dataset of 2.2 lakh civil cases filed in the study period. Of these, 1,37,734 cases (about 62%) have the government or its agencies as a counterparty (Table 1). This dataset includes completed as well as pending cases. 81% of the cases in our dataset are disposed of.

Table 1: Cases in our data to which the state or its agency is a counterparty

Sr.No.	Party-type	As Petitioner	As respondent	Total (% of government cases)
1.	Union of India	8020	58,184	66,204 (48.06)
2.	State Government	2443	31,539	33,982 (24.62)
3.	Municipal bodies/panchayats	2174	16,121	18,295 (13.28)
4.	CPSEs	3908	9021	12,119 (8.79)
5.	SPSEs	1161	3427	4,588 (3.33)
6.	Court	171	833	1,004 (0.72)
7.	Constitutional bodies	189	543	732 (0.53)
Total		18,066	1,19,668	1,37,734 (100)

Constitutional bodies in Table 1 refer to constitutional authorities, such as the Comptroller and Auditor and General of India. The Union of India includes the government of India, statutory authorities set up under a central law such as the National Highways Authority of India (NHAI), and statutory regulators such as SEBI and TRAI. Table 1 demonstrates that a bulk of the civil commercial litigation in the Delhi High Court has the government as a counterparty. It also shows that while the state is not responsible for initiating large amounts of civil commercial litigation, the state and its agencies constitute the largest respondent in such litigation.

We classify the Government-cases in Table 1 into five categories: civil writ petition, civil suits (original side and commercial), miscellaneous petitions (original and civil misc main), arbitration petitions and applications and land acquisition-related disputes (Table 2).

Table 2: Types of government related cases in our data

Sr.No.	Civil writ petitions	Govt. as Petitioner	Govt. as respondent	Total (% of government cases)
1.	Writ petitions	10,476	1,06,179	1,16,655 (84.69)
2.	Miscellaneous petitions	3,493	5,168	8,661 (6.28)
3.	Land Acquisition related cases	3,180	3,663	6,843 (4.9)
4.	Arbitration petitions and applications	221	2,837	3,058 (2.54)
5.	Civil suits	696	1,818	2,514 (1.8)
Total		18,066	1,19,668	1,37,734 (100)

Table 2 shows that civil writ petitions constitute the bulk of the cases involving the government and its agencies. Writ petitions are, by design, cases filed against the government or its agencies for the violation of fundamental rights and not contracts. However, anecdotally, we know that contractual claims against the government and its agencies are often agitated through civil writ petitions. Hence, we retain civil writ petitions for our analysis.

Findings

While the government is a counterparty to 1.4 lakh or 60% of the civil commercial cases in our data-set, a bulk of these cases are by and against individuals and other types of entities such as trade unions or political parties. These disputes would therefore largely pertain to employment matters such as unfair dismissals, denial of promotion in government service or pension and evictions from public premises. The objective of our study is to understand the litigation arising out of public contracts.

Litigiousness

For our study, we characterise only cases filed by or against businesses (body corporates incorporated as private or public limited companies) as public contracts-related litigation. This is because our data covers public contracts whose value exceeds Rs. 2 crores. Public contracts exceeding this threshold value are awarded through a tender process. The condition that a bidder for public contracts should be incorporated as a company is commonly found in government tender documents.

In the sub-set of writ petitions, we retain writ petitions between businesses and a sub-set of government agencies, such as CPSEs (except banks) and SPSEs, and statutory agencies that are engaged in procurement, such as the National Highways Authority of India (NHAI), Airports Authority of India (AAI), the Delhi Metro Rail Corporation (DMRC) and the National Buildings Construction Corporation Limited (NBCC) in our data.

We exclude writ petitions filed against government owned banks as they largely pertain to debt restructuring and not procurement-related disputes. We also exclude the writ petitions filed by businesses against the government of India, constitutional authorities and State Governments from our analysis as a large percentage of them pertain to tax matters, constitutional challenges to laws enacted by the Parliament and state legislatures respectively, and executive actions, such as notifications and circulars issued by the government and state governments respectively. Similarly, a review of a sample of writ petitions filed by businesses against municipal bodies and panchayats suggests that they largely pertain to matters involving eviction from public premises and violations of licensing norms governing commercial establishments operated by such businesses. We also exclude land acquisition-related matters as they are largely challenges to notifications issued by the government notifying land parcels for compulsory acquisition and other actions undertaken by the government under the land acquisition laws.

This exercise of filtering may exclude some contractual disputes between the government and its contractors or vendors. Our findings are therefore based on a conservative estimate of the volume of litigation in public contracts.

This filtering exercise generates a subset of 9,313 cases between businesses and the government and its agencies (Table 3). We use this subset of cases as a proxy for litigation between the government and businesses in connection with public contracts. Table 3 suggests that such litigation is a small proportion (about 7%) of the overall litigation involving the government. Further, the state is not a major initiator of such litigation. Businesses initiate the bulk of the government-business contractual litigation. The CPSEs account for nearly half of such litigation in the Delhi High Court. This suggests that while CPSEs are a small contributor to the overall commercial litigation involving the government (as shown in Table 1), they are a large contributor to the litigation involving public contracts. The central government and several states have issued policies to manage and curb litigation by the government and its agencies ( example, example and example). These policies have largely taken a top-down approach towards minimising litigation at the level of the union and state governments. Our assessment suggests that there is potential for the government to explore the incentive structures at the level of the departments within the Union government and CPSEs that drive litigation arising from public contracts.

Table 3: Cases between government and businesses

	Business as Petitioner	Business as Respondent	Total (% share)
CPSE	3,329	1,223	4,552 (48.87)
Union	2,027	885	2,912 (30.26)
State	711	249	960 (10.30)
Panchayat/Urban local body	412	124	536 (5.75)
SPSE	239	111	350 (3.75)
Autonomous constitutional	3	0	3 (0.03)
Total (% share)	6,721 (72.16)	2,592 (27.83)	9,313 (100.0)

Case types

Table 4 shows that the bulk of the government initiated litigation is in the 'original miscellaneous petitions' (OMPs) category. Conversations with practitioners and support staff of the judges in the Delhi High Court suggest that as large as 70% of the cases filed as OMPs in the Delhi High court involve challenges to the enforcement of arbitration awards. We also reviewed a small sample of OMPs, which confirmed this perception. Arbitration petitions and applications account for the second-largest type of cases involving the government and businesses. These petitions are generally filed for directions from the court for the appointment of an arbitrator where either party to the dispute fails to appoint one, interim relief during arbitration proceedings and extension of timelines for conducting the arbitration. The high proportion of 'OMPs' and 'arbitration' cases in our data suggests that a significant proportion of government-business contractual litigation is getting resolved by arbitration.

We also find that a bulk of the writ petitions filed by businesses in our dataset (a little more than 84%) are against CPSEs. This pattern holds over the entire window of observation. We estimate that these writ petitions could pertain to disputes in two areas of public procurement. They may pertain to violation by CPSEs of procurement norms in the tendering phase of public procurement. The second possibility is that they could pertain to disputes in the post-award stage, such as delayed payments or other wrongful acts during the term of the contract. This is problematic because writ petitions are a remedy for the enforcement of fundamental rights against the government. Courts have repeatedly denied purely contractual claims against the government through the remedy of writ petitions. However, if the writ petitions against CPSEs indeed pertain to disputes arising post the tender award, it suggests that businesses find it efficient to agitate contractual claims through writ petitions. This may indicate a judicial tendency to prioritise writ petitions over other matters. This could also be attributed to the relatively lower threshold for proving claims in writ petitions.

Table 4: Government to business (G2B) and Business to government (B2G) commercial litigation

	WP	CS	OMP	Arbitration	Others	Total
G2B	69	276	1938	152	157	2,592
B2G	932	895	2704	1973	217	6,721
Total	1,001	1,171	4,642	2,124	374	9,313

Time taken

Approximately 1.7 lakh of the 2.2 lakh cases in our dataset are disposed cases. We find that the average disposal period for a case in our data is about one year from its institution. For this subset of disposed cases, we calculate the average duration for disposal in years based on the year of institution to the year of disposal (Table 5). The average duration for the disposal of writ petitions is lower than that for civil suits and lower than the overall average. This reinforces the notion that counterparties to government contracts may be enforcing their contractual claims through writ petitions.

Table 5: Average duration for disposal (by case-type)

Case-type	Average time for disposal (in years)
Writ petitions (civil)	0.81
Civil suits (original)*	2.30
Civil suits (commercial bench)**	1.01
Miscellaneous petition	1.17
Arbitration petitions, applications, etc.	0.56
Overall	0.98
*Suits disposed of by a regular bench of the court.
**Suits disposed of by the commercial division of the High Court set up under the Commercial Courts Act, 2015.

Table 6 shows the number of years for the disposal of cases in the overall data, cases to which the government is a party, and other cases. Table 6 suggests that a bulk of the commercial cases are disposed of by the Delhi High Court within two years from the date of their institution. We also find that a significantly higher number of commercial cases involving the government are disposed of within a year compared to the other cases. This is contrary to the popular perception that delays prolong government litigation. This does not appear to the case for commercial litigation involving the government. In fact, we find that commercial cases involving the government as a respondent and those not involving the government require, on average, the same number of hearings by the court before their disposal. This suggests that a commercial case involving the government does not, on average, consume more resources of the court than regular cases.

Table 6: Duration of disposed cases (party-wise)

	Number of cases (% share)
Duration (years)	Overall	Govt and businesses	Business and non-govt party
Less than 1	95,962 (54.01)	13,867 (57.75)	19,724 (43.74)
[1, 2)	42,931 (24.16)	5,618 (23.4)	13,521 (29.98)
[2, 3)	17,064 (9.6)	1,902 (7.92)	4,901 (10.87)
[3, 4)	9,475 (5.33)	1,011 (4.21)	2,716 (6.02)
[4, 5)	4,682 (2.64)	467 (1.94)	1,414 (3.14)
[5, 10)	6,807 (3.83)	993 (4.14)	2,576 (5.71)
Greater than 10	745 (0.42)	153 (0.64)	246 (0.55)
Total	1,77,666 (100)	24,011 (100)	45,098 (100)

Conclusion

Our findings are limited to our observations on the government litigation in the Delhi High Court.

Some of these observations confirm pre-conceived notions of litigation between the state and businesses in India. For example, data from the Delhi High Court demonstrates that so far as concerns civil commercial cases, the government is a party to more than the popularly cited 46% of the cases in courts. However, very little of this litigation is attributable to public contracts between business and the state. Similarly, the usage of writ petitions to enforce contractual claims against the state is documented to some extent in court judgements. Our data demonstrates a high proportion of writ petitions linked to the enforcement of public contracts. This may be partly attributable to the nature of the claim involved and the relatively higher average duration for the disposal of suits. Some of our findings help dispel some pre-conceived notions. For example, the widely held perception that the government prolongs litigation is not true of commercial cases adjudicated before the Delhi High Court, as shown by the average number of hearings taken for commercial cases involving the government and those not involving the government. This may also be reflective of the capacity of the Delhi High Court itself.

A quantitative assessment of the government's litigation is important for identifying the precise bottlenecks that lead to the government being sued and designing a litigation policy that responds to these considerations. Data backed assessments of the litigation load of the government holds important insights into the costs of doing business with the government and the resources required within the state and in courts to deal with such litigation. This work provides a foundational understanding of commercial litigation involving the government in India. Better and deeper country-level insights can be obtained by expanding the assessment to more courts and potentially undertaking a textual analysis of the final orders in such litigation to identify aspects such as the success ratio and litigation costs.

Bhargavi Zaveri is a researcher at xKDR- Chennai Mathematical Institute. Devendra Damle and Karan Gulati are researchers at the National Institute of Public Finance and Policy. Anjali Sharma is at National eGovernance Services Limited.

Estimating the impact of the draft drone regulations

by Devendra Damle and Shubho Roy.

The Directorate General of Civil Aviation (DGCA) recently released draft guidelines for regulating civilian drones, for public comments. Clause 12.21.e) of the guidelines establishes a no-fly zone in all areas within 50 km of India's land border. In this article we try to estimate the footprint of this clause on the economic activity in these areas and on the residents.

The draft guidelines lay out the legal requirements for drone operations in India. They include provisions to classify, license, set safety requirements, and operational parameters for drones including drone pilot licensing. One of the provisions: Clause 12.21.e) of the guidelines states:

12.21 No RPA shall be flown:
...
e) Within 50 km from international border which includes Line of Control (LoC), Line of Actual Control (LAC) and Actual Ground Position Line (AGPL);

[The draft guidelines refer to drones as ``Remotely Piloted Aircraft'' (RPA).]


The drone guidelines are a type of delegated-legislation (regulations are another). The legislature of a modern economy is usually neither equipped, nor has the time to legislate all details of a law. Therefore, the legislature usually creates the broad legal framework, and the authority to fill in the details is delegated to the executive or statutory bodies (like regulators). Since government agencies, unlike legislators, are not elected representatives of the people. Therefore, the regulations/guidelines made by such agencies are not strictly democratic.

To address this democratic deficit, legislatures place certain requirements on government agencies making regulations. Two common requirements are to (i) invite public comments on draft regulations, and (ii) conduct a Cost-Benefit Analysis (CBA). The agency is required to estimate the costs of complying with the regulations, and the benefits arising out of the regulations. Neither inviting public comments nor conducting CBAs is a universal requirement in India. The DGCA, should be commended for inviting public comments on the draft regulations. It has, however, not conducted a CBA of the regulations.

A CBA can sharpen the decision making of a government agency. Even before public consultation is done, a CBA provides the government agency an idea of potential costs and benefits. Consider the way the New Zealand government did a CBA for a proposed regulation on drones. It gave five options for regulation (including ban) and analysed the impact of each one of them. The impact of each option was then measured against the stated objective of the regulation. Another example is the US Federal Aviation Authority's (FAA) proposed regulation on training and licensing of drones. Even on this narrow point the FAA carried out a detailed analysis of the total costs and benefits to society. On the side of costs, the FAA estimates that each pilot will have to spend USD 150 to be trained. This training is expected to result in social benefits of USD 733 million (pessimistic estimate) to USD 9 billion (optimistic estimate) over five years. The FAA provides detailed information about assumptions and methodology for interested parties to do their own calculations.

In this article we try to analyse the impact of one provision of the regulations: the no-fly zone. Such analyses can be used in a CBA of drone regulations.

Impact of the no-fly zone

It is difficult to predict the impact of any new technology. Before the Internet, mobile phones or GPS became ubiquitous it would have been impossible to predict all the innovative ways they would change human life. Similarly, drones are a disruptive innovation that may have a profound impact on us. To estimate the impact of 12.21.e), we examine three sectors in which drones are already changing established processes or hold great promise to do so: (1) general services to the population, (2) agriculture, and (3) infrastructure monitoring.

General services to the population: Drones will change the way goods and services are delivered to the masses. They might be especially effective in border areas which typically suffer from low connectivity. For example, Zipline, a private company that uses drones to deliver blood to hospitals in the mountainous region of Rwanda, has cut down the delivery-time from 4 hours to 45 minutes. Facebook plans to use drones to provide internet connectivity in remote areas. In urban areas, drones can be used for governance. In Gurgaon, for example, drones are being used to conduct land-use surveys, for assessing property tax, checking encroachments, and urban planning. In the private sector, drone have multiple applications which go beyond the obvious courier and delivery services. For example, private construction companies can use them to monitor construction and maintain a safe working environment. Drone photography and videography are a new source of economic activity, which will be denied to people living in border areas.

Agriculture: Many Indians still derive their income from agriculture and drone technology is already changing agriculture in India. In Karnataka and Haryana, drones are going to be deployed for spraying pesticides on crops. Drones can identify plant disease before any visible signs show and alert farmers or spray crops with appropriate pesticides. In Gujarat, Maharashtra, Rajasthan and Madhya Pradesh insurance companies are using drones for quick assessment of crop damage for crop-insurance payouts.

Infrastructure: Drones can be used for inspection and monitoring of infrastructure projects. The Prime Minister, Narendra Modi, recently suggested using drones to monitor rural road construction projects and to keep illegal mining in check. Power companies are using drones to monitor power lines in remote and inaccessible areas. Similarly, the Gas Authority of India Ltd. is using drones to inspect sections of gas pipelines that pass through difficult terrain. The no-fly zone effectively bans this kind of drone usage in the border districts, many of which have difficult terrain.

Methodology

Our approach to measuring the impact was mapping the 50 km no-fly zone using geo-spatial analysis, and then, estimating how many people, how many urban areas, and how much land, agricultural area and infrastructure are situated in the zone.

Estimation scheme:

As sub-district level geo-spatial data for administrative borders are not available, we estimate at the district-level for population, agricultural workers, agricultural area, and operational land holdings in the no-fly zone. To account for the lack of sub-district level data we make three estimates: pessimistic, realistic and optimistic. To make our estimates—

1. We split the districts into three categories, based on the percentage area of the district covered by the no-fly zone as: X, Y & Z. Category X districts are those where the no-fly zone covers less than 50% of the land area. For Category Y districts, the coverage is between 50–90%. Category Z are districts where the coverage is more than 90%.
2. For the pessimistic estimates, we assume that the percentage of the population, agricultural workers, agricultural area, and operational land holdings falling in the no-fly zone are the same as the percentage of the district's land area covered by it. For example, if the no-fly zone covers 40% of a district's land area, then we assume that 40% of its total population, agricultural area, and operational land holdings lie in the no-fly zone.
3. For the realistic estimates, we halve the pessimistic estimates for all Category X districts. For Category Y and Z districts we take the same values as the pessimistic estimate.
4. For the optimistic scenario, we use a scheme similar to the realistic estimate, but we halve the pessimistic estimates for Category X and Category Y districts. For Category Z districts we use the same value as the pessimistic estimates.

Data Sources:

For the analysis we used the following openly-accessible data:

• Census 2011 — for population, and for number of cultivators and agricultural labourers;
• Agricultural Census 2010–11 — for agricultural area and number of operational land holdings;
• Datameet — for shape-files of borders of States and Districts in India based on the 2011 Census (Note: Shape-file is a commonly used file format for storing and exchanging geo-spatial data. See here for details.);
• Open Street Maps — for the shape-files of Actual Ground Position Line, for infrastructure, and locations of urban areas; and
• ESRI's A-16 Federally Derived Data, Open Data Catalogue — for shape-files of Line of Control and Line of Actual Control.

The number of districts has increased since 2011, from 640 to the current number of 707. We have considered the population, number of districts, and district boundaries as given in the 2011 Census.


Plotting the no-fly zone
 

• We made a base-map using state and district borders from Datameet;
• We then added the LoC and LAC, downloaded from the ESRI database and AGPL from Open Street Maps;
• To demarcate all areas in India within 50 km from the land border (and from the LoC, LAC and AGPL in Jammu and Kashmir), we plotted a 50 km inward buffer. This represents the no-fly zone.

Calculating the impact
 

• We calculated the area of overlap between the no-fly zone and each district, to calculate what percentage of the district's land area is inside the no-fly zone.
• To estimate the population, number of farmers, agricultural area, and operational land holdings in the no-fly zone, we multiplied the respective totals for the district by the percentage of the district's land area lying within the no-fly zone, along with the applicable discounts.
• We used the previously plotted no-fly zone as a filter, to extract urban areas (cities and towns), canals, roads, railway stations and bridges falling in the no-fly zone from the Open Street Maps data dump for all of India (downloaded on 17/12/2017). The operation is analogous to using a cookie-cutter to cut out a shape from a flat piece of dough.

Results

Here is the data (geo-spatial and tables) to reproduce the results.

The following figure shows the total area of India covered under the 50km no-fly zone.

Figure: Area covered by drone ban

More than a quarter of India's districts (168 out of 640) across 18 states fall at least partially within the 50 km no-fly zone. In more than 10% of India's districts (65 out of 640) the no-fly zone covers more than 90% of their land area. Of these, 39 districts fall completely inside the no-fly zone. Table 1 shows the population, number of farmers, land area, and agricultural land covered by the no-fly zone.

Table.1: Summary of area covered by the 50 km no-fly zone

Indicator	Pessimistic estimate		Realistic estimate		Optimistic estimate
	Total	% of India	Total	% of India	Total	% of India
No. of Districts	168	26.21	-	-	-	-
Land Area*	420.88	12.80	-	-	-	-
Agricultural Area*	122.56	8.89	106.85	7.75	88.98	6.45
Population^	141.27	10.67	129.22	9.76	115.82	8.75
Cultivators^	10.95	8.60	9.92	7.79	8.44	6.63
Agricultural Labourers^	14.25	9.88	13.06	9.05	11.44	7.93
Operational Land Holdings^	13.35	9.65	12.29	8.88	10.64	7.69

* in '000 sq.km.
^ in millions

As Table 1 shows, 8–10% of the total population of India will be affected by the no-fly zone. It will impact between 6–9% of all the farmers in India. The total affected population in the pessimistic scenario (141.27 million), is greater than the total population of the 75 largest cities in India put together (140.33 million).

Jammu & Kashmir (20 out of 23), and Assam (20 out of 27) have the highest number of affected districts followed by Uttar Pradesh (15 out of 71) and Bihar (14 out of 38). In terms of percentage of total number of districts affected, Mizoram, Sikkim, Tripura are at the top, at 100%. This means that every single district in these states is at least partially by the no-fly zone. These three states are followed by Jammu & Kashmir (91%), Manipur (89%), and Meghalaya (86%).

In terms of percentage of total land area covered, the ban disproportionately affects the northeastern states. Sikkim and Tripura are entirely covered by the no-fly zone. The no-fly zone covers 86% of the land area in Mizoram, more than 60% in Manipur, Arunachal Pradesh and Meghalaya, and more than 50% in Nagaland. These are all small states, which one would expect to have high coverage, but some of the larger states are also heavily affected. The no-fly zone covers nearly 44% of the total area of West Bengal, nearly 39% of Bihar, and nearly 33% of Punjab.

While a large chunk of the population affected by the no-fly zone will be from rural areas and small towns, some large cities will be affected as well. Table 2 gives an overview of the infrastructure and urban areas located inside the 50 km no-fly zone.

Table.2: Urban areas and infrastructure inside the 50 km zone no-fly zone

Item	Quantity
State Capitals	4
	Agartala, Gangtok, Shillong, Srinagar
Cities (other than state capitals)	9
Towns	325
Canals	3127 km
Roads	70829 km
Railway stations	550
Bridges	3349

As Table 2 shows, a total of 13 cities fall in the no-fly zone. Of these, four are state capitals. Amritsar and Jammu are among the other major cities that fall inside the no-fly zone. A significant amount of infrastructure also lies in it.

With such large areas affected by the proposed ban, it becomes necessary to ponder the costs and benefits of such a blanket ban.

Drawbacks of blanket bans

These draft regulations will exclude a substantial part of India's population from the benefits of drone technology. An example of a similar blanket ban, based solely on geography, is the Ministry of Defence's map restriction policy of 1967 (revised in 2017). It restricts the sale of high-resolution topographical maps of all border areas to civilians. The restricted zone covers all areas within approximately 80 km of the border, which is nearly 40% of India's total land area. This ban, like the drone ban, was also enacted due to national security considerations. However, with the advent of satellite imaging technology, the same maps are easily available from international vendors. This means the ban is not only redundant, but has also resulted in lost revenue for the Government of India. It also means that foreign nationals have easier access to high-resolution topographical maps of restricted areas in India than agricultural cooperatives, gram panchayats, municipal bodies, companies and Indian citizens residing in these areas.

For the government, a blanket ban seems attractive because it (apparently) requires the least amount of state capacity to enforce. In the case of the no-fly zone, all the government has to do is penalise any person flying drones in the no-fly zone. It does not have to determine whether the drone use was legitimate or not. The government also does not have to invest in setting up offices and systems to license and monitor use. However, blanket bans are also the most expensive form of regulatory intervention. They do not distinguish between legitimate and illegitimate activity, and treat both the same way. In doing so blanket bans impose huge costs on those they regulate.

India's economic history is peppered with instances where blanket bans were imposed, only to later realise they were hampering economic development. Banning entry of foreign investors, financial derivatives, and private participation in banking and insurance are a few notable examples. Thankfully, the country has begun to undo them gradually, but the damage has already been done.

In some cases, India has not taken the ban approach. India did not ban mobile phones and internet near the border. Instead, in many border areas, the government has worked harder to provide last-mile internet and mobile connectivity. While mobile phones and internet also pose national security concerns, the country did not choose to go down the banning route for them.

Similarly, for drones, we might need a more nuanced approach to regulation that tries to balance national security with the legitimate needs of residents in the no-fly zone. For example, even today, farmers in Punjab are allowed to grow crops in no-mans-land, beyond the border fence with Pakistan. The security concerns there are addressed by security checks rather than a complete ban on farming. Farmers in 10 districts of Punjab (situated well away from the same border) will be unable to use drones for agriculture. In Punjab, a state which already suffers from overuse of pesticides, drones can decrease their use by only spraying affected crops. The security concerns, like in the case of farming in no-mans land, can be met with monitored use.

The blanket ban also ignores India's border policy. 33 districts (in Uttarakhand, U.P, Bihar and Sikkim), which lie in the no-fly zone, are on or near the border with Nepal (but not China). Similarly, 12 districts in Assam which are in the no-fly zone are on or near the border with Bhutan (but not China or Bangladesh). India has good relations and an open border policy with both these are nations. Using the same standard (i.e. blanket ban) as the one used for districts on "sensitive borders" is a disproportionate response. It demonstrates a lack of risk-based regulatory approach.

The ban, as it stands is inequitable. It disproportionately affects states sharing a land border with other countries, especially the north-eastern states. If drone technology starts impacting quality of life, persons in the no-fly zone may be deprived of economic opportunities. Such a deprivation is worse when it is done through regulation. Since a regulation is issued by an un-elected government agency; it denies Indians in the no-fly zone their right to participate in the legislative process.

Conclusion

India needs a regulatory framework for drones. The advent of any new, disruptive technology creates tension between the freedom of people (to use to it, to improve their lives) and national-security concerns. Building state capacity is hard, and building it close to borders is harder. However, bans cannot be a substitute for it. In the case of civilian drones in border areas, closer monitoring, cooperation with border forces, involvement of local authorities, and higher security clearances are some alternative approaches that could better balance the tension. Our drone regulations need to create this balance.

References

Cost of compliance for clinical establishments, by Manya Nayar and Shubho Roy, Ajay Shah's Blog (September 2017)

India needs drones by Shefali Malhotra and Shubho Roy, Ajay Shah's Blog (June 2016).

A cost-benefit analysis of Aadhaar, National Institute of Public Finance and Policy (November 2012).


The authors are researchers at the National Institute of Public Finance and Policy, New Delhi. We thank Shekhar Harikumar for valuable inputs.

How well is India's land record digitisation programme doing: Findings from Rajasthan

by Anirudh Burman and Devendra Damle.

Good titles in land improve the security of land tenure, and also enable land holders to capitalise land, either by mortgaging it, or making productive use of it. Conversely, the lack of clear titles in land reduce the security of land tenure since titles are prone to challenge, and inhibit productive use of land since it is difficult to signal title over land (here). It is therefore essential for a well functioning land market to have a well developed land titling system.

The Government of India has been running a program for improving land titles called the Digital India Land Record Modernisation Program (DILRMP, titled the National Land Record Modernisation Program until 2015) since 2008. The DI-LRMP was initiated to improve land titles in India, with the ultimate objective of creating a system of conclusive titling. The title recorded with the state is considered conclusive proof of the title to land in a conclusive titling system.

To be conclusive, a titling system requires that (a) all land transactions be recorded by the government, (b) the applications for registering land titles be verified scrupulously before they are registered, (c) the status of a title once registered is final and not open to dispute (curtain principle - or drawing a curtain over past defects/ disputes), and (d) the registry be completely updated in relation to the status of titles as they are present on the ground (mirror principle). The DI-LRMP aims to create this system all over India through the following activities (see NLRMP Guidelines):

1. Digitisation of textual revenue records (contained in Record of Rights, revenue records are updated through "mutation", and are presumptive proof of the title recorded in the RoR) and registration records (records with the registration department - all agreements pertaining to transfers of land have to be registered, save specified exceptions), including maps.

2. Integration of the processes of mutation (RoR updation), registration and map generation/ creation.

3. Creation of modern record rooms, capacity building within the administrative machinery.

4. Allowing for processes of land registration to be initiated online in addition to physical processes.

5. Fresh land surveys and mapping in areas where required.

The completion of these activities is envisaged to take India close to a conclusive titling system. Our team was one among three coordinating research institutions to conduct the first assessment of the progress of the DI-LRMP. The NIPFP team chose the state of Rajasthan to conduct this study. Rajasthan is the largest state in India constituting 10.4 percent of the total area and contains 5.67 percent of the total population of India.

Our study was able to highlight:

1. Issues with the implementation of the DI-LRMP, at different stages of implementation; and

2. The issues faced by the local administration in the maintenance of land records and in implementing the DI-LRMP.

The removal of systemic and administrative issues highlighted in this report may make the implementation of the DI-LRMP more effective. The report based on the study is available here.

Land records in Rajasthan

Work on computerisation of Records of Rights started in 1999-2000, well before the NLRMP was conceived. These activities got subsumed by the Land Records Computerisation project which was later subsumed by NLRMP.

Rajasthan's history presents some interesting challenges to this exercise. The state was originally composed of five main Riyasats (princely states), and several smaller ones. Each of these five Riyasats used different units to measure land. For example, a bigha in one Riyasat was the equivalent of 3000 sq.ft., while in another it was close to 1600 sq.ft. These differences still persist today. Not only are the units of measurement different, but some of the official terms used in relation to land records also vary across districts. The state government tried to introduce the metric system in 1976, but as per discussions with local officials and villagers, it was rarely used in practice by the local populace who were more comfortable with the old measurement systems. With the DI-LRMP there is a renewed effort to standardise units of measurement across the state.

1976 was also the year the state government last undertook re-survey operations across the state. The re-survey operations which will be undertaken under DI-LRMP will be the first since then. All maps currently in use were made using traditional techniques. They will be replaced by maps made using High Resolution Satellite Imagery.

In spite of early movements towards improvements in land records, the level of implementation of DILRMP in Rajasthan remains low. This is highlighted in the findings from our study.

Scope of the study

Our study evaluated the implementation of DI-LRMP through four activities:

1. Collecting state-level data from government websites of the Department of Land Resources, Government of India, as well as the websites of the Departments in charge of Revenue and Registration, Government of Rajasthan;

2. Interviews with senior officials in the Departments of Revenue and Registration in the Government of Rajasthan;

3. Performing test-checks on the land record websites on the government of Rajasthan, and

4. Studying the implementation of DI-LRMP in two tehsils in Rajasthan.

The research team undertook the tehsil level study with the help of local retired revenue officials. This facilitated interactions with local officials in the revenue and registration offices in the two tehsils. In addition, the study involved a visit to five villages each in the two selected tehsils, interactions with villagers, and collection and verification of information relating to a sample of ten parcels in each village (a total of 50 parcels in each tehsil).

Findings

State-level findings

We first collected state-level data from websites of the Rajasthan Government, and verified it in conversations with government officials. The state-level data reveals the following:

1. Most RoRs (revenue records) have been digitised, but maps have not been updated through modern survey methods and the maps available online at present are digitised copies of cadastral maps.

2. Our test-checks revealed that while most records of rights are available online, there was a significant volume of cases where the records were not available/accesible. There is a uniform problem of the absence of legacy records online.

3. The RoR is available only in paper form locally in a total of 1603 villages out of 47,918 villages.

4. Only a small proportion of the RoRs are available with digital signature of the designated official (3,632 villages out of 47,918), and RoRs of most villages are not available in a legally usable form (42,683 villages).

5. Most tehsils in Rajasthan have functional and usable maps, albeit in paper form. 88 tehsils out 242 have some proportion of damaged or mutilated maps. In all other tehsils, 90 percent or more of maps are in a usable condition.

6. While there has been some provisioning for online registration, most of the processes are still manual. Out of 527 Sub-Registrar Offices (SROs), 117 SROs have online systems for verifying documents and paying stamp fee duty.

7. The state of Rajasthan has made very little progress on integration of all three processes - mutation, registration and map generation. The process of registration alerts the revenue records database by noting the fact of registration in some form in 15 SROs, but this does not work the other way round, i.e. the process of changes in revenue records does not alert the registration database.

An analysis of the findings from the state highlights significant steps required to be taken for the implementation of the DILRMP. This was also confirmed by our study of DILRMP implementation in the two tehsils selected for the study.

Tehsil-level findings

Tehsil selection: The two tehsils selected for the study were Girwa and Uniara. Both tehsils are at different stages of implementing DI-LRMP:

1. Girwa: Girwa is part of the sub-humid southern plains agro-climatic zone. It is situated on and around the rocky hills of the Aravalli Range, at an average elevation of 540 meters. The climate is moderate year-round with moderate seasonal variation in temperature and humidity. Rainfall is scanty with little to moderate year-on-year variation. The main reason for selecting Girwa as one of the sample tehsils is that it is a good representative of the typical tehsil. It represents the typology of about 184 tehsils, out of 314 tehsils in Rajasthan in terms of the status of land records computerisation.

2. Uniara: Uniara is a tehsil in Tonk, Rajasthan and is situated approximately a three-hour drive away from Jaipur, the state capital. The tehsil is primarily agricultural, with little or no industrial activity. The tehsil is largely rural, with no large cities in its close vicinity. Uniara is part of the semi-arid eastern plains agro-climatic zone. The terrain is flat barring a few areas to the northwest. The climate is predominantly dry and there are large seasonal variations in temperature. Rainfall is scanty with large year-on-year variation. Uniara is cited as an example of a model tehsil in Rajasthan with respect to land records modernisation. It was also featured in the Success Stories of NLRMP report published by the Department of Land Records, Government of India.

Findings from Girwa and Uniara

Vacancies: We found significant vacancies in the local administrative units in both tehsils. Tables 1 and 2 provide details of the sanctioned and vacant positions in Girwa and Uniara respectively.

Table 1: Revenue Department Vacancies in Girwa

Post	Sanctioned	Vacant
Patwari	52	20
Land Revenue Inspector	13	0
Naib-Tehsildar	3	1
Tehsildar	1	0

Table 2: Revenue Department Vacancies in Uniara

Post	Sanctioned	Vacant
Patwari	54	35
Land Revenue Inspector	13	4
Naib-Tehsildar	3	1
Tehsildar	1	0

Accuracy of recorded land area: We measured a total of 99 parcels across the two tehsils (Figure 1). In 30 percent of the cases the area is within 5 percent of the area on record. In 25 percent of the parcels, the difference between the area on record as compared to the area as measured, is 10-20 percent. In 24 percent of the sample parcels, the difference between the area on record as compared to the measured area is more than 20 percent. It must be noted that digitised cadastral maps were not available for either tehsil for the purpose of our study. The deviation recorded here is the deviation from the area recorded in the RoR.

Figure 1: Difference Between Area on Record vs Measured

Causes for deviation from recorded area: Encroachment onto neighbouring land is the most frequently observed cause for deviation from the recorded area. We observed two types of encroachments:

1. Encroachment onto adjoining fields i.e. onto private property, and

2. Encroachment onto public property. This can be further subdivided into two types: (a) encroachment onto roads, nallahs and farm roads, and (b) encroachment onto pasture land, forest land and other government-owned land.

Figure 2 provides details on the causes for differences between recorded area and measured area.

Figure 2: Causes of Difference Between Area on Record vs MeasuredNote: Only shows parcels where the difference is 10 percent or larger.

Information recorded in Record of Rights: We noted that a number of transactions and kinds of titles are not recorded in the RoRs at the tehsil level. For example, construction on agricultural land is not recorded if less than 500 square metres. Possession, independent of ownership is also not recorded. Encumbrances other than mortgages are also not recorded. This is an impediment in providing conclusive titles, as a number of rights over land are not recorded at all.

Administrative issues: We found local administration under-staffed, lacking basic infrastructure (at the patwar-mandal levels) including electricity in some places, and without network connectivity. Most of the administrative processes are manual. In addition, revenue administration is burdened with a number of tasks at best incidental to land revenue and record management. Some officials pointed out that land revenue collection, a core activity for the revenue department, does not seem like a feasible activity any longer as the costs of collecting revenue far exceed the revenue collection. Building administrative capacity is therefore an important challenge for the state.

Conclusion

Our report makes the case for legal and administrative changes based on the results of our study. It is important to realise that the process of digitisation must be accompanied by complementary legal changes and administrative capacity building. Rajasthan has an advantage in the fact that its digitisation program is not yet at an advanced stage and some of these issues can be fixed right now rather than later. Additionally, while digitisation may remove some dependency on human interaction with revenue officials, land record management will continue to require sufficient human capital.

 

Anirudh Burman and Devendra Damle are reasearchers at National Institute of Public Finance an Policy.