A conservative path to get to a fully working Linux computer

by Ajay Shah.

Linux has long been a great operating system, but there is a bottleneck on getting it properly installed and working. It is hard to get it to work with all the hardware such as the wifi, USB devices, audio, suspend/hibernate, etc. This is because this hardware tends to evolve rapidly. The device vendors frequently do not release source code, or even binaries for Linux. The Linux community solves this through large applications of brainpower. As a consequence, Linux support for the devices comes through with a lag. If you get a state of the art computer, and try to install Linux on it, this will often prove to be challenging.

How can we avoid these risks and complexities? There are three conservative pathways to get to a fully working Linux machine.

 

Method 1: Use a chromebook

 

Chromebooks are wonderful machines where Google takes responsibility for your Linux install, and for over-the-air updates (exactly as they do with Android). There are a wealth of good Chromebooks out there, and one that is noteworthy is the Acer Chromebook Spin 513. The basics all work on a Chromebook, and then you get "the Linux development environment" which gives a familiar apt-get interface to installing packages. I have installed emacs, svn, R, latex, etc. and it all just-worked. On many Sundays, my morning ritual of writing a column for the Business Standard is done using emacs on a chromebook.

Method 2: Buy linux pre-installed

 

Firms like Dell or Lenovo offer Linux pre-installed on some computers [example]. Here, again, you're up and running with zero friction. You are guaranteed that all the devices are supported. But there is a downside: You are stuck with the distribution that was chosen by the vendor. This may or may not be to your taste.

 

It's good to have the complete knowledge, so as to deal with future situations of systems administration or full reinstall. As an example, it's nice to have your servers on the identical distribution as your laptop. So I feel incomplete if someone gives me a perfectly working machine that I did not install. This is indeed schizophrenic: with a chromebook or an android device, I do not expect to ever require systems administration or reinstall, but with a Linux machine, I do.

Method 3: A conservative path to choosing hardware and OS

 

As a long-time Linux user, I have found that it's good to understand and get used to one Linux distribution, and then stick with it across the years on all my systems. For me, this distribution of choice is Debian stable.

Debian stable will often not work well on a state of the art laptop. The moniker `stable' implies something that has stabilised after years of testing, and it will not know recent developments in the hardware. What is the way out?

 

Two factors that should be kept in mind. The laptops where Linux is available pre-installed from the vendor are those where device support is superior. And, the laptops that have high production volume are more likely to go out into the expert community that makes Linux work. As an example, Xiaomi's Mi laptops are a high volume part (so the second factor is in favour) but where Linux pre-installed is not a choice (so the first factor is not).

The key idea of this article is to look at the gap between the date of a laptop release and the date of the Linux kernel. Based on your ability to deal with glitches, you must establish a minimum delay that makes you comfortable. For me, this minimum delay is 1 year: once the linux kernel is atleast a year younger than the laptop, I'm in good shape, based on my ability to deal with difficulties and my risk tolerance. Each person should choose this one number.

With this in hand, we have a recipe for screening a laptop before purchase :

1. For a laptop of interest, find out its release date. As an example, when I liked the Mi Notebook Ultra, I found this the release was in August 2021. Similarly the release date for the Xiaomi Notebook Pro 120G was August 2022.
2. Look carefully at the Debian release of interest. The Debian stable of today, which is called `bookworm' has the kernel version 6.1. This has a release date of December 2022. 
3. Restrict yourself to machines which are atleast a year older than this kernel.
   

Example: Mi Notebook Ultra. There is a decent delay between the release date of the Mi Notebook Ultra (August 2021) and the 6.1 kernel release date (December 2022). Hence, this is likely to work well.

Example: Xiaomi Notebook Pro 120G. This has a release date of August 2022. As an example of how these problems play out, this laptop has the sweet Intel work in the 12th generation "Alder Lake" CPU, with performance cores and efficiency cores. Harnessing these properly in the Linux kernel is non-trivial, and got done for kernel 5.18 in August 2022. Going by our recipe, we should wait a year after the laptop release, and thus ask for kernel 6.4. We don't yet know when it will show up in future Debian releases. What is Debian testing today ("trixie") uses kernel 6.3 that was released in April 2023, which does not satisfy the one-year test when compared with the release date of August 2022.

A long-run strategy that harnesses this recipe, to stay on contemporary hardware and software, consists of buying a new machine every time Debian testing reaches "release candidate 1" ("RC1"):

1. Watch the current Debian testing. (At present, this is `trixie').
2. Wait for it to achieve its Release Candidate 1 ("RC1"). For Debian 12 this was 3 April 2023.
   
3. Identify the kernel version that they have in it and the release date of this kernel (using the URLs placed above).
   
4. Limit yourself to examining equipment which has a release date of more than a year prior to this kernel release date. Buy this, and it's likely to work well.
   
5. At this point, you are on a fully working Debian testing RC1, but this will rapidly mature into Debian stable, and then you have a few years of stability. For Debian 12, the stable release was 10 June 2023, which was about two months after RC1.
   

Under this strategy, every few years, when Debian testing reaches RC1, it is time to buy a new laptop. You will regularly buy a laptop that is at least one year older than the kernel version in Debian testing. Modern computers are fast enough that this is not an important constraint, and older laptops are cost-efficient.

Jumping into a testing RC1 is a bit risky. This level of risk seems fine for a personal laptop but for production systems it is better to do this differently: instead of going in roughly 3 months before the release date, it's good to wait 6 months after the release date.

I thank Chirag Anand, Ayush Patnaik and Megha Patnaik for useful conversations.

Announcement

TrustBridge is an organisation that works on improving Rule of Law for better economic outcomes. We focus on understanding the gaps in the existing legal and regulatory framework, evaluating how they impact economic growth, and studying the various ways that these could be improved upon. We aim to undertake legal, quantitative and policy oriented research and dissemination that will inform principles and evidence-based policy making. We believe that implementing ideas that emerge from our research will help bring us closer to our objective of improving the Rule of Law. Our work is in the areas of Energy Transition, Financial Markets, Contract Performance in government and private contracts, and Governance in the start-up ecosystem.

TrustBridge is looking for two full time associates to work on its projects.

Position 1: Quantitative Research Associate

As a quantitative research associate you will deploy quantitative techniques to create and analyse data sets and to generate insights about the problems we are working on.

The requirements for the role are:

• Prior demonstrable experience of working with R, Python, Julia and other open source tools for generating statistical/economic analysis.
• A degree or a professional qualification in Mathematics, Statistics, Economics or Computer Science will be desirable.
• You must be curious and passionate about research and be comfortable working in an interdisciplinary environment. You must be ready to work on independent outputs as well as function in teams.

Position 2: Policy Research Associate

As a policy research associate you will be required to work on projects that seek to engage with governments and with the private sector to generate sustainable reforms in the areas of our interest.

The requirements for the role are:

• A Master's degree or a professional qualification in economics/management/public policy, strong written and oral communication skills.
• Prior work experience in the the areas of interest to TrustBridge.
• A quantitative/computational orientation will be a plus.
• You must be curious and passionate about research and be comfortable working in an interdisciplinary environment. You must be ready to work on independent outputs as well as function in teams.

The remuneration offered will be commensurate with your skill and experience.

Please send an email with your CV to careers@trustbridge.in if you are interested.

Helping litigants make informed choices in resolving debt disputes

by Pavithra Manivannan, Susan Thomas, and Bhargavi Zaveri-Shah.

The Indian legal system faces numerous difficulties, and the discourse on legal system reforms has emphasised the workings of the courts from the perspective of judges and registries. Such a focus is not so useful for litigants who are also participants in the legal system. The decisions that they make and the incentives that they face add up to create the case load at the courts.

Consider a supplier of spare parts to a certain manufacturer, who has not been paid her dues. Her lawyer advises her of multiple legal remedies that she can use to recover her dues, from filing a money suit before a civil court to pursuing arbitration proceedings outside a court to initiating insolvency proceedings against the manufacturing company. How would she decide which legal remedy to pursue? More generally, litigants make four classes of decisions: Should one sue? Should one appeal? When faced with a certain proffer, should one settle? When alternative forums are available, which one to prefer? Flaws in a litigant's decision making when faced with such decisions reshape the case flow of courts. In the Indian legal system reform discussion, it is important to think about the incentives and the decision-making of litigants.

At present, litigants make these decisions based on their own, generally limited, prior experience. They are advised by lawyers who specialise in a certain forum. However, lawyers tend to be specialists in one forum or another, and often know impressions rather than systematic evidence. Further, lawyers have an interest in the litigant's decision. Under these conditions, the decisions of litigants might sometimes be sub-optimal.

First steps in measurement

All the four types of litigant decisions - to sue, to appeal, to settle and to choose a forum - involve forecasting the time taken in the legal process, and associated expenses. In an ideal world, litigant decision making would be supported by statistical systems that forecast these two numbers.

In this article, we develop a legal system measurement that can produce such insights for litigants, who are litigating on a narrow class of problems. We do this for three Bombay courts, as a proof of concept of a simple analysis that can help litigants.

The narrow class of problems that we focus on are debt dispute resolutions. Several laws in India allow the enforcement of debt contracts in different forms, which provides us a unique opportunity to compare their relative performance in providing redress for debt default. There are also multiple courts and tribunals that adjudicate disputes on debt contracts in different ways. We choose three in Bombay to study:

1. The Bombay High Court which has original jurisdiction to adjudicate high value contractual matters.

2. The Mumbai bench of the Debt Recovery Tribunal (or DRT), which is a specialised tribunal that has been adjudicating recovery of debts due to banks and financial institutions since 1993.

3. The Mumbai bench of the National Companies Law Tribunal (or NCLT), which is a specialised tribunal adjudicating insolvency petitions against companies.

We build on earlier work that points out that litigants are found to care about the access, efficiency, effectiveness, independence, and predictability of judgements (Manivannan et al, 2023). It is known that secondary data (such as those from court websites) have constraints: (a) it can be used to measure only a subset of these aspects; and (b) even this subset cannot be necessarily computed for all the comparable courts. Assuming that access is not a constraint, Manivannan et al (2023) suggest that the litigant can get an estimate of what she can expect of the amount of time in the court, for each of these courts. They point out that it is possible to get an estimate of what she can expect of costs she will incur, through the expected number of hearings at a given court, where each hearing induces a certain unit cost.

In this article, we move towards three new questions in the field of litigant decision making:

1. How likely is it to get a first hearing in the first year from filing the case in the court?
2. How likely is it that the matter will get disposed in the first year from the filing of the case?
3. How many hearings are most likely to take place in the first year from the filing of the case?

While the first two questions help to address the efficiency in terms of time expected in a court, the third can be used as a proxy for the kind of costs that a litigant can expect from a given court, since every hearing requires the time of (and fees charged by) legal counsel.

Data description

We collect and analyse sample data of cases involving debt disputes, which were listed and heard at three courts in Bombay for the period from September 2021 to December 2022 ('sample period'). The websites of these fora record cases filed across different timelines and do not archive case life cycles of historical cases. This sample period allows us to compare cases that have been filed at the same time and therefore have comparable life cycles.

• In the case of the Bombay HC, the selected matters include suits, summary suits, commercial suits and commercial summary suits, filed under its original jurisdiction.

• For the DRT, we extract cases arising under the Recovery of Debts Due to Banks and Financial Institutions (RDDBFI) Act, 1993, and the Securitization & Reconstruction of Financial Assets & Enforcement of Security Interest (SARFAESI) Act, 2002.

• For the NCLT, we extract all cases listed under the Insolvency and Bankruptcy Code (IBC). We understand that cases involving debt enforcement will be covered under these case-types at the relevant court.

Table 1 shows the number of cases in the data set for all the three courts. We additionally include the status of these cases as pending or disposed. A case is categorised as disposed of by the courts where the disposal is by way of a decree passed by the court, or if it is settled, or it is has been withdrawn for any reason.

Table 1: Distribution of cases

Court	Total	Disposed	Pending
Bombay HC	1243	159	1084
DRT	843	125	718
NCLT	2645	897	1748

Thus, for the same period of time, there have been a different number of applications in the matter of debt dispute resolution in these three courts.

While, this can be used to calculate the 'disposal rate' of matters in each court, these measures suffer from two limitations. It does not take into consideration the duration of the pending cases. Further, it does not take into account that the amounts involved and the complexity are different in the cases handled at different courts. An approach that takes these aspects into account is the survival analysis modelling approach.

Statistical analysis

'Survival analysis' is a method for modelling the time to an event of interest. If the event of interest is the time to disposal, the model will yield the estimated probability of a case being completed between any two timepoints t1 and t2.

Survival analysis models have been previously employed to study judicial delays including at the Income Tax Tribunals (Datta et al, 2017) and at the NCLTs (Shah and Thomas 2018, Bhatia et al, 2019). In this article, we draw on the intuition of survival analysis and offer simple estimates of two quantities (for each of the three courts):

• What is the probability of a case being being heard atleast once within one year? The first hearing is generally an important milestone for a litigant to know the possibility of getting interim relief. How likely it is that this will happen within the very first year?
• What is the probability that the case is disposed of in the first year?

These probabilities are estimated for each of the three chosen courts separately on matters of debt dispute resolution. Much of the earlier research have computed and presented sample means of completed cases only, without taking into account cases that have not been completed. The standard techniques of survival analysis fare well on harnessing information using observations of cases that have not completed as well.

Q1: Chances of getting a first hearing in the first year from filing of a case

Figure 1 presents a graph of the survivor function for a matter getting a first hearing across the Bombay HC, the DRT and the NCLT. Here, time to first hearing is on the x-axis. We pull up the probability of getting to the first hearing within a year from these curves for the three courts and present this in Table 2.

Table 2: Chance of first hearing within the first year at Bombay HC, DRT, NCLT

	(in %)
Bombay HC	36.6
DRT	94.0
NCLT	99.8

A case at the NCLT has the highest chance (of nearly 100%) of being heard with the first year from its filing. There is nearly a similar probability of a first hearing at the DRT within the first year, with a 94% chance. At the Bombay HC, on the other hand, there is a less than 40% chance that a similar matter will get a first hearing within a year of being filed.

Using this approach, we could similarly estimate the probability of a case being heard atleast once within say, the first three months of filing. Our analysis finds that for a litigant at the NCLT, there is an 86% chance of getting atleast one hearing within the first three months of filing a case. The corresponding probabilities for the DRT and the Bom HC are 74% and 5% respectively.

Q2: Chances of getting a case disposed in the first year from filing of a case

Figure 2: the survivor function for disposal for three courts

Figure 2 shows the litigant the chances of a debt dispute resolution matter getting disposed, within one year of it being filed in each of these three courts. This presents a very different picture than for the survivor function for the chances of getting a first hearing that we see in Figure 1. The chances of disposal are (logically) much lower at any given point in time. Table 3 presents the chances of disposal of case within the first year of being filed. The NCLT has the highest chance of disposal at nearly 40%. Between the Bombay HC and the DRT, the DRT has a higher chance at 17.3%. But the Bombay HC has a similar chance at 16.3% of the case being disposed within the first year.

Table 3: Chance of disposal within the first year at Bombay HC, DRT, NCLT

	(in %)
Bombay HC	16.1
DRT	17.0
NCLT	39.3

Q3: Expected number of hearings in the first year from the filing

So far, we have focused on the time to completion, which matters greatly through its impact upon the net present value of the moneys recovered. We now turn to the question of the costs of ligitation. We compute the expected number of hearings within the year and present these in Table 4. We recognise that there is a sharp distinction between substantial hearings and infructuous hearings, but in the present state of the research, we treat both alike.

Table 4: Expected number of hearings within the first year at Bombay HC, DRT, NCLT

	Number
Bombay HC	0.4
DRT	2.7
NCLT	4.0

The NCLT has the highest expected number of hearings within the first year of filing at 4 hearings, while the Bombay HC has the least (not even one hearing may happen within the first year of filing).

Using these estimates, a litigant can estimate her legal costs for the first year. For example, we now know that a litigant will face 4 hearings, on average, in the first year after filing at the NCLT. If the legal fees that she is charged by her legal team are Rs.100,000 per hearing, on average, this implies that she can expect to pay Rs.400,000 in the first year from filing.

Discussion

Better decisions by litigants are not only valuable for the litigants, but will also improve the working of the Indian legal system. We have shown simple statistical results about delay and costs at three alternate venues for one narrow class of matters. These results point out the differences that exist among three courts, in terms of the kinds of legal remedies they offer, their administrative processes and their capacity. Litigants would have to weigh those considerations also in their thinking.

These results have many interesting implications. For instance, if a bank strategically prefers an early first hearing, it might be better off instituting proceedings at the NCLT compared to the DRT, even if the latter is a forum dedicated to banks and financial institutions. On the other hand, if a bank prefers disposal within fewer hearings compared to an earlier first hearing, the analysis indicates that it is better to approach the DRT.

We recognize that there may be other considerations that weigh with the litigant in making her decisions. For example, Mannivannan et al, 2021 find that litigants also care about the fairness of a judge and the effectiveness of the remedy. But our analysis in this article focuses on metrics that can be evaluated with secondary data from courts. Another consideration is that the analysis does not consider the nature of the legal remedies offered by the three courts. While litigants may approach the Bom HC and the DRT for debt recovery, the NCLT offers a remedy of insolvency resolution. But creditors in India find it optimal to use both recovery and resolution processes to recover their dues. Finally, it is not that the litigant prefers one forum over another, but that important metrics such as the probability of disposal within a given time frame allows the litigant to choose one among multiple choices of forum.

We believe that the comparative approach in this article can be extended in, at least, three ways. First, these measures can be calculated for locations other than Bombay. A comparative exercise of this kind can potentially help understand benches with bottlenecks and potential areas of improvement. Second, within this class of matters, statistical modelling can permit these estimates to vary with case characteristics. Finally, these measures needs to be calculated beyond this narrow class of matters. For example, such an approach could offer more clarity to litigants involved in involuntary litigation, such as criminal litigation.

The data used for this analysis can be found here. The dataset can be cited as Manivannan, Pavithra and Thomas, Susan and Zaveri-Shah, Bhargavi (2023), "Helping litigants make informed choices in resolving debt disputes".

If you're interested in seeing other WIP applications of this framework, XKDR Forum is organizing a roundtable in Mumbai on the 17th of June (Saturday).

References:

Bhatia, S., Singh, M., & Zaveri, B. (2019). Time to resolve insolvencies in India. The Leap Blog, March 11, 2019.

Datta, Pratik & Surya Prakash B. S. & Sane, Renuka, (2017), Understanding Judicial Delay at the Income Tax Appellate Tribunal in India, Working Papers 17/208, National Institute of Public Finance and Policy.

Manivannan, Pavithra and Thomas, Susan and Zaveri, Bhargavi, Evaluating Contract Enforcement by Courts in India: A Litigant's Lens (November 26, 2022). Also available at SSRN: https://ssrn.com/abstract=4286562.

Shah, A., & Thomas, S. (2018). The Indian bankruptcy reform: The state of the art, 2018. The Leap Blog, December 22, 2018.

Pavithra Manivannan and Susan Thomas are researchers at XKDR Forum. Bhargavi Zaveri-Shah is a doctoral candidate at the National University of Singapore. We thank Ajay Shah for inputs on the survival analysis, Geetika Palta for research and data support, Tushar Anand for helping out with corrections to the data, and participants of the internal seminar series at XKDR Forum for their comments and feedback.

Who is litigating cheque bounce cases?

by Siddarth Raman.

Cheque bounce cases under Section 138 of the Negotiable Instruments Act are an important source of case load at the Indian judiciary. This has inspired many attempts at modifying laws and court procedures so as to reduce the burden. In this journey, empirical evidence about the nature of the litigants is required. In this article, we establish a dataset about these matters, and measure the shares of financial firms, non-financial firms and individuals. We find that in Mumbai, financial firms filed 52% of cases, and that 83% of cases were against individuals. Cases filed by financial firms are likely to be disposed quicker than those filed by individuals. We explore how the cheque is used as a means of credit, and why financial firms accept them as collateral / security. It appears that financial firms are using cheques and Section 138 as a coping mechanism for poor civil remedies. While there is a need for legal system reform in the context of S.138 of the N.I. Act, it would also be useful to find solutions in banking regulation and personal bankruptcy law. We conclude with a recommendation of caution. Just as the amendment in 1988 has led to certain behaviours and industry practices, new solutions will alter the equilibrium, creating new incentives and new behaviours. The patterns seen in Mumbai are not present in regions of lower economic activity like Jhabua-Nimar. We need to be aware of the wide differences across different districts and states of India, and be mindful of complexity, as we proceed on the path to legal system reform.

Introduction

Section 138 of the Negotiable Instruments Act, which was introduced in 1988, creates the possibility of imprisonment for upto two years, a fine upto twice the amount of the cheque, or both, in response to cheque bouncing. The Act prescribes a six month time horizon for disposing these cases. This 1988 amendment is widely used as an example of the need for judicial impact assessment: The legislative action substantially enhanced the load upon the judicial branch, but there was a lack of commensurate operational planning and resourcing to deal with the enhanced case load.

What fraction of the pending cases or the flow of new cases emanates from this? A precise answer to this is not feasible under the present state of legal system data in India, but it is likely to be about 15 per cent (Chapter 3, Law Commission of India, 2014 ^[1] ; Supreme Court in Makwana Mangaldas Tulsidas vs The State Of Gujarat, 2018 ^[2] ; Mahadik D, 2018 ^[3] ). An important paper in this literature, Damle and Gulati, 2022 ^[4] examines 363,720 cases across 8 States and 2 Union Territories and estimates that cheque dishonour cases represent 13.2% of the courts' workload and take 395 days for disposal.

One pathway to legal system reform lies in an 80:20 analysis, in a vertical approach of finding solutions that are specific to certain classes of matters. Many thinkers have proposed making progress on S.138 of the N.I. Act as a component of legal system reform (Law Commission of India, 2008 ^[5] ; Law Commission of India, 2009 ^[6] ). Alongside this is the proposal for decriminalisation of cheque bouncing, broadly drawing on the concept that debtors prisons are not how modern economies operate. All these discussions require more knowledge about the nature of litigants in these matters, which is presently lacking.

This article seeks to fill this gap. In their paper, Damle and Gulati, 2022 ^[4] establish that the impact of Section 138 cases on caseload, pendency and time to disposal varies by State. We ask the questions: Who are the litigants in Section 138 cases? Does the nature of cases vary based on who the participants are? Do these characteristics vary based on location?

Methodology

The e-courts database for district courts was used to build a dataset about pending and disposed cases relating to Section 138 of the Negotiable Instruments Act. This was done for India's most advanced region (Bombay). For a comparison, this was also done for the group of districts (termed "homogeneous region" by CMIE) with the highest share of households in agriculture. This is the "Jhabua-Nimar" homogeneous region, which comprises six districts in Madhya Pradesh - Alirajpur, Barwani, Burhanpur, Dhar, East Nimar (Khandwa), Jhabua, West Nimar (Khargone). These two datasets thus show the full range from the old India to the new India.

Litigants were classified into three groups:

• Financial Firms
• Non-Financial Firms
• Individuals

This was done through a process of looking for keywords in the name:

1. Financial Firms typically have the terms bank, finance, invest, loan, and related keywords and variations.
2. Non Financial Firms have terms like ltd, pvt, corporation.
3. Non Financial Firms may contain common nouns from the English Language.
4. Litigants with the term proprietor in the name were categorised as individuals.
5. Those that did not fit these criteria were categorised as individuals.

This classification heuristic requires a standard corpus of English words. We used the NLTK Wordnet corpus and identified all words in the names of litigants that overlapped. A manual cleanup was required as the corpus contained some proper nouns. We assessed the words which made up 95% of the instances of overlap with the corpus and eliminated names and common nouns that could be Indian names ("Rout", "Harsh", "Baby", etc.). In Mumbai, we found 8133 unique words appearing 763,593 times. The 95% filter resulted in 1,165 unique words in Mumbai. For Jhabua-Nimar, we found 1,006 unique words appearing 19,974 times. The 95% filter resulted in 345 unique words.

These heuristics will of course engage in a small rate of misclassification. Some names like Banku and Chitra containing the terms Bank and Chit could be classified incorrectly. We do not account for firms that have common nouns in their name from languages other than English. In many cases, an individual proprietorship may have the term company or finance in their name. The methodology does not take into account spelling errors.

In order to assess the accuracy of the work, it is important to estimate the defect rates associated with these heuristics. We manually analysed a random sample of 100 cases (and 200 litigants) in each district, in order to measure the error rate. We found two errors in our Mumbai analysis. They are:

1. Ms M. D. Vora Co. is a non-financial firm categorized as an individual.
2. Alexander Xavier Dsouza is an individual categorized as a non-financial firm. Alexander is present in the wordnet corpus, and appears 16 time in the dataset which puts it in the bottom 3% of words by frequency, which is why it was excluded in the manual cleanup.

Similarly, we found seven errors in our Jhabua-Nimar analysis. They are:

    Two cases where non-financial firms with names in Hindi were misclassified as individuals:

1. Shri Krishna Prajapati Sakh Sahkari Sanstha Maryadit.
2. Shubhalakshmi Sakh Sahkari Sastha Mrya. Dhamnod By Nitesh Bhawsar.

    Two cases where financial firms with typos were misclassified as individuals:

3. EEASVAM KREDIT KO DVARA VIJAY.
4. BHARATEEY STET BAIANK MUKHY SHANABAG BURAHANAPUR.

    One case of an individual misclassified as a financial firm:

5. Kashish Finance H.U.F Propriter Vijay Rathore.

    Two cases where the State was a party. The State was misclassified as a non-financial firm.

This suggests a defect rate of 1% for Mumbai and 3.5% for Jhabua-Nimar. This gives us a sense of the extent to which the estimates presented ahead should be treated with caution.

Results

In Mumbai, we have a dataset of 417,437 cases. Of these, 317,225 are disposed, and 99,712 cases are pending.

Table 1: Section 138, NI Act cases in Mumbai district courts classified by Type of Litigant

Respondents → Petitioners ↓	Financial firm	Non-financial firm	Individual	Total
Financial firm	0.2%	6.5%	46.2%	52.8%
Non-financial firm	0.1%	7.0%	21.3%	28.4%
Individual	0.2%	4.8%	13.8%	18.8%
Grand Total	0.5%	18.3%	81.2%	100.0%

This yields the facts:

• Finance firms filed 53% of cases, non-financial firms 28%, and individuals 19%.
• 81% of cases were filed against individuals, 18% against non-financial firms and less than 0.5% against financial firms.
• The biggest chunk of cases are financial firms vs individuals - 46%, followed by non-financial vs individuals - 21%.

In Jhabua-Nimar, we have a dataset of 22,564 cases. Of these, 14,130 are disposed, and 8,434 cases are pending.

Table 2: Section 138, NI Act cases in Jhabua-Nimar district courts classified by Type of Litigant

Respondents → Petitioners ↓	Financial firm	Non-financial firm	Individual	Total
Financial firm	0.0%	0.2%	12.3%	12.5%
Non-financial firm	0.0%	0.6%	5.2%	5.8%
Individual	0.1%	2.1%	79.5%	81.2%
Grand Total	0.1%	2.9%	97.0%	100.0%

• Individuals filed 82% of cases, finance firms 12%, and non-financial firms 6%.
• 97% of cases were filed against individuals, 3% against non-financial firms.
• The biggest chunk of cases are individuals vs individuals - 80%, followed by finance firms vs individuals - 12%.

At an overall level, disposal rates in Mumbai are close to 90%+ for years before 2015, from where we see a steady decline in share of cases disposed. Thus today's pending cases are largely those that began after 2015.

Figure 1: Total Cases by Year and % of Cases disposed as of April 2023

In Figure 1 above, the blue bars on the chart are the total number of cases filed. The orange line depicts the % of the cases filed in that year which stand disposed as of April 2023 when the data was analysed.

In Mumbai, we see an interesting pattern when we compare the disposal rates of cases filed by financial firms, non-financial firms and cases filed by individuals.

Table 3: Share of cases filed in a specific year that stand disposed as of 2023

Year	Financial Firms	Non-Financial Firms	Individuals
2015	74.0%	65.9%	66.9%
2016	61.1%	60.7%	66.4%
2017	77.8%	50.8%	51.1%
2018	75.9%	47.9%	41.1%
2019	48.8%	42.8%	28.9%
2020	75.3%	35.0%	27.6%
2021	42.2%	25.5%	19.6%

This table shows the share of cases that were filed in Mumbai in a certain year that are now disposed. An important finding here is that cases filed by financial firms have a much higher likelihood of getting disposed in 2-3 years compared with cases filed by individuals.

Figure 2: Cases filed between 2015-2021 by Status and Type of Litigant

In Figure 2 above, we see that Financial Firms account for 60% of the total cases filed, but constitute ~70% of the cases that have been disposed, and account for only 50% of the pending cases.

We see no such patterns in Jhabua-Nimar with disposal rates not being dependent on the nature litigant filing the case.

Discussion

We now have new facts about litigation associated with the S.138 of the NI Act. What have we learned? How does this change our mind? What are the downstream implications of this new knowledge?

Most attempts at reforming Section 138 have focused on on improving the processing speed within courts. Little has been done towards preventing cases emerging in the first place. Our data shows that financial firms are the main petitioners in Mumbai, with a higher disposal rate than individual litigants or non-financial firms. This may reflect greater organisational capability in financial firms. Cases filed by individuals or non-financial firms vary based on the nature of contract entered into by the two parties. We speculate that cases filed by financial firms are mostly related to loans.

Financial firms often use cheques as an alternative form of collateral. This can help individuals with poor credit ratings to access loans. Should there be a loan default, there is the choice of filing a criminal case. This process is expedited by Section 138 that requires petitioners to file a case within 45 days of the cheque bounce. Banking regulations may also be a contributor. In December 2016, the Supreme Court ruled that officers of private banks are to be treated as public servants under the Prevention of Corruption Act. Financial firms have practices to ensure that a debt is indeed irrecoverable before they can classify it as bad debt. The large volume of cases from banks may be a mechanism to check against petty corruption from branch officials and comply with regulatory requirements.

Filing a Section 138, NI Act case not only allows a bank official to demonstrate effort and intent, it also allows the lender access to the coercive power of the State. The police arriving with a non-bailable warrant at your doorstep is a persuasive means of negotiating with a borrower. Petitioners in a Section 138 case are using this to recover dues. Are there better civil alternatives to debt recovery? How does their efficiency in terms of time to disposal compare with those in Section 138 cases? As we think of improving processes, we should consider the possibility that making Section 138 cases more efficient may prevent litigants from considering civil recourse. The combination of slow civil courts and under-developed credit markets make Section 138 cases an attractive proposition for financial firms. Accepting cheques as security may have developed as an industry practice because it allows financial firms to be less diligent when making loans as they can now rely on the criminal justice system to coerce settlement. In addition to court processes and legislative changes, remedies to the burden of Section 138 on the Indian courts may also lie in the realm of banking regulation, credit practices, and personal bankruptcy law.

The introduction of Section 138 has resulted in some discernable behaviors from financial firms. Future changes to the status quo will invariably alter incentives resulting in different behavioral patterns among litigants. The variation in litigant composition between different regions illustrates that litigation patterns are shaped by local context. The patterns observed in a metro like Mumbai, largely influenced by financial firms, don't find a parallel in areas such as Jhabua-Nimar. Attempts at legal system reform must account for the disparities across the various states and districts of India. We caution against one-size-fits-all solutions and suggest that solutions be crafted keeping in mind the local context.

References

[1] 245th Report On Arrears And Backlog - Law Commission of India, 2014 . Retrieved from 20th Law Commission of India.

[2] Makwana Mangaldas Tulsidas vs The State Of Gujarat , Order dated 5 March, 2020. Retrieved from Supreme Court of India.

[3] Mahadik D, 2018. Analyses of Causes for Pendency in High Courts and Subordinate Courts in Maharashtra. Retrieved from Department of Justice.

[4] Damle D, Gulati K et al. 2022. Characterizing Cheque Dishonor Cases in India: Causes for Delays and Policy Implications. SSRN.

[5] 213th Report on Fast Track Magisterial Courts for Dishonoured Cheque Cases, 2008. Retrieved from 18th Law Commission of India.

[6] 230th Report on Reforms in the Indian Judiciary - Some Suggestions, 2009. Retrieved from 18th Law Commission of India.

Siddarth Raman is a researcher at XKDR Forum.

Announcements

Joint Field Workshop on Public Procurement

Workshop Date: 25^th August 2023
Submission Deadline: 28^th July 2023

We cordially invite you to submit your research papers to be presented at the Joint Field Workshop on Public Procurement, 2023. This workshop, jointly organized by the Chennai Mathematical Institute and XKDR Forum, aims to bring together academics, practitioners and policymakers to share their research findings and discuss the current and challenging issues which surround public procurement in India. The conference will be organized in-person in Mumbai on 25^th August 2023. The workshop will feature the presentation of research papers along with panel discussions.

Topics

We invite you to submit quantitative or qualitative research papers from any discipline which broadly cover any of the following topics:

• design and structure of government contracts;
• legal frameworks and institutions that play a role in the planning-to-payment stages of procurement;
• monitoring and enforcement of government contracts (this includes dispute resolution);
• impacts of inefficient procurement on: public expenditure, the financial health of firms, and the economy in general; and
• issues in sectors where public procurement is undertaken at a large scale (e.g. health, defence, water and sanitation etc.)

Paper submission

We invite your submissions as PDF files, no later than 28^th July 2023, via email to outreach@xkdr.org. Preliminary versions of the paper may be considered provided that the research question is clearly outlined along with preliminary results.

Submitted manuscripts will be peer-reviewed. No submission fee is required. Costs of accommodation in Mumbai and travel within India will be reimbursed. General inquiries regarding the call for papers should be directed to outreach@xkdr.org

Important dates

• Submission deadline: 28^th July 2023
• Notification of review results: 8^th August 2023
• Workshop event: 25^th August 2023

Lost in Translation: Legislative Drafting and Judicial Discretion

by Madhav Goel and Renuka Sane.

Precisely drafted legislation that reflects its objective and boundaries, and judicial discretion that confines itself to legislative intent are critical pillars of a rule of law economy. There are concerns that both are broken in India. In a new paper, Lost in Translation: Legislative Drafting and Judicial Discretion we discuss these issues in the context of the decision of the Supreme Court in Vidarbha Industries Power Ltd. v. Axis Bank Ltd. (Vidarbha) pertaining to the Insolvency and Bankruptcy Code, 2016 (IBC, or Code).

The IBC sought to introduce an objective test for initiating insolvency, providing that as long as a financial creditor files for insolvency and the objective criteria of "debt" and "default" are established, the National Company Law Tribunal (NCLT) is expected to initiate the corporate insolvency resolution process (CIRP). Until 2022, this intent had been respected. However, Vidarbha conferred discretion on the NCLT to not accept an insolvency petition by relying on the use of the word may in the phrase, may admit the petition, in Section 7. This has opened the gates to increased discretion in the admission of IBC petitions, potentially derailing the entire reform process. In fact, in a majority (56%) of the reported cases the NCLT has chosen to not admit the application for initiation of CIRP. These range from instances where the corporate debtor is owed money, to where the Court suspects the intention of the creditor to file for insolvency. Furthermore, there are two instances where the NCLT/NCLAT has exercised the discretion conferred by Vidarbha in respect of applications by operational creditors under Section 9 of the Code. This is despite the fact that the statutory language of Section 9 as well as the decision in Vidarbha nowhere confers such discretionary powers upon the NCLT/NCLAT. By doing so, the NCLT/NCLAT have potentially opened the door to further expansion of the scope of discretion conferred by Vidarbha to extend to applications under Section 9 as well, an outcome fraught with its own issues.

The Vidarbha judgement raises three questions:

1. Quality of drafting: The Bankruptcy Legislative Reform Commission's recommendation on lack of discretion was clear. The legislation, however, provided no rationale for why it chose to ignore the BLRC report and allow for the possibility of discretion by using the word may in Section 7. If it was an inadvertent change in the language of the provision, then that highlights the need to make the drafting process more robust. If the change was deliberate, then the lack of publicly available reasoning is harmful as it not only goes against the fundamental tenet of rule of law that material decisions ought to be accompanied with reasons, but also because the lack of reasoning has led to uncertainty in the law. Interestingly, the Government itself is pushing for a review of the decision in Vidarbha, a situation that could have been avoided if the drafting processes were more robust, transparent, and accompanied with reasons.
2. Legislative intent: The jurisprudence on the treatment of the words "may" and "shall" has been fairly fluid. The rule of thumb is that the former implies conferral of discretion, while the latter implies a mandatory obligation. However, the rule can be dispensed in certain cases, and the courts can interpret "may" as "shall" and "shall" as "may". These are cases where an analysis of the real intention of the legislature points to dispensing with the rule of thumb. In these instances, the Courts have gone beyond the statutory language and treated the legislative intent as its north star in interpreting the words "may" and "shall". That approach was missing in Vidarbha, and it is unclear why.
3. Tests for applying discretion: The Court did not provide guidelines for exercise of this discretion or for determining insolvency. Unchecked discretion eventually leads to abuse of power. In Vidarbha, the Court failed to provide tests for exercise of discretion to admit/not admit an insolvency petition, thus creating a situation that will lead to greater uncertainty of law. Consequent to Vidarbha, NCLTs will devise their own methods to assess whether a corporate debtor is financially healthy and solvent, thus leading to greater uncertainty and lesser consistency of law. This can already be seen from the fact that the NCLT/NCLAT has exercised discretion in 13 cases to dismiss the CIRP initiation applications for myriad reasons, whereas there are at least 10 other cases where the NCLT/NCLAT has expressly declined to exercise the discretion.

The economic effect of unguided discretion and lack of certainty in the law will be that prolonged litigation and delayed timelines will result in erosion of the economic value of the corporate debtor's assets, reducing the chances of it being brought back to life. As a consequence, the Ministry of Corporate Affairs has proposed a series of amendments to the IBC, one of which seeks to clarify the law that it is mandatory for the NCLT to admit petitions under Section 7 once "debt" and "default" are established. While it fixes the obvious mistake in the initial drafting, it does not guarantee that the judiciary will take cognizance of legislative intent. There is therefore a need for deeper reform, both of legislative drafting, and of the way the judiciary interprets economic and commercial laws.

The authors are researchers at TrustBridge.

Author: Karthik Suresh

Karthik Suresh is a researcher at XKDR Forum, Mumbai.

On this blog:

• Are startups engaging in innovation in India?, 25 April 2023.
• Revising the Information Technology Act, 2000, 4 April 2023.
• History of disinvestment in India, 21 March 2022.
• Grievance Redress in the Financial Sector in India: Lessons from the field, 26 February 2021.
• Applicability of the IBC to public sector enterprises: The case of Hindustan Antibiotics Ltd, 18 February 2020.

Author: Rishab Bailey

Rishab Bailey is a Lawyer, Technology Policy Researcher and Visiting Fellow, XKDR Forum, Mumbai.

On this blog:

• Revising the Information Technology Act, 2000, 4 April 2023.
• Backdoors to Encryption: Analysing an Intermediary's Duty to Provide 'Technical Assistance', 10 May 2021.
• Analysing India's KYC Framework: Can We Do Things Better?, 13 April 2021.
• Response to the Consultation Whitepaper on 'Strategy for National Open Digital Ecosystems (NODEs)', 12 July 2020.
• Comments on the draft Personal Data Protection Bill, 2019: Part II, 10 April 2020.
• Comments on the draft Personal Data Protection Bill, 2019, 3 April 2020.
• Fiduciary relationships as a means to protect privacy: Examining the use of the fiduciary concept in the draft Personal Data Protection Bill, 2019, 13 January 2020.
• Data localisation in India: Questioning the means and ends, 22 February 2019.
• Disclosures in privacy policies: Does 'notice and consent' work?, 19 February 2019.
• Response to the Draft Personal Data Protection Bill, 2018, 20 October 2018.
• Placing surveillance reforms in the data protection debate, 6 August 2018.

Announcements

We in XKDR Forum are recruiting in both policy & quantitative-research roles.

Quantitative research: we integrate multiple datasets (household survey data, firm data, macroeconomic and financial time-series, satellite imagery, legal systems data, other custom datasets) to obtain insights into the world aiming for academic research and real world applications. Along the way, we innovate on methods. Here are some examples: self reported health, informational efficiency of credit ratings, the working of financial markets, improved methods for nighttime lights radiance satellite imagery. We build open source packages in Julia and R, partly to do better computation around existing methods, and partly to express our innovations in statistical and computational methods.

The right persons for quantitative research at XKDR Forum are those who have knowledge of mathematics, statistics, computer science and economics, and take interest in the world, in applying quantitative tools to obtaining insights into the world. Existing capabilities with contributions to open source projects are a plus. Of great importance is collaboration with the policy oriented researchers in XKDR Forum.

Policy oriented research: we build knowledge on the working of government and how improvements can be made, and carry the knowledge through into connections into the real world reform process. We stand on the modern understanding of the Indian state and the difficulties of the Indian development journey, that fuses public economics, law and public administration, as seen in the ISOTR book. The X in XKDR Forum stands for Inter-disciplinary: we integrate diverse strands of knowledge into innovating on the question at hand. Of particular importance are the fields of government contracting, legal system reform, household finance, and climate change. Our thinking in each of these fields takes from and feeds into the big picture of Indian development strategy.

The right persons for policy research at XKDR Forum are those who take interest in the world, and bring social science and humanities insights into the world. Of great importance is collaboration with the quantitative researchers in XKDR Forum. 

In both categories, we care more about knowledge and passion, and less about the credentialism. High levels of intrinsic motivation are essential. Please look us up at: website, youtube channel, open source releases, annual conference, newsletter on substack.

The remuneration offered will be commensurate with your skill and experience and will be comparable with what is found in the Indian research ecosystem.

Interested candidates must email their resume with the subject line: Application for "Research Associate" at XKDR Forum, to Ms. Jyoti Manke at careers@xkdr.org by 31st May, 2023.

Are startups engaging in innovation in India?

by Aneesha Chitgupi, Karthik Suresh and Diya Uday.

Introduction

What is a startup? The academic literature takes a broad view --- startups:

• have a high growth rate (Moogk 2012),
• have a lower number of employees (Beck et al. 2008),
• are at the early stage of the life cycle of a firm (Eisenmann 2013, Stevenson and Jarillo 1990), and
• are drivers of innovation (Cohen and Klepper, 1996).

However, governments across the world focus on the link between startups and innovation. In the Netherlands, a startup is defined as "a business that translates an innovative idea into a scalable and generic product or service, using new technology." In the United States, a startup is one that "has never been an SEC reporting company, uses invested capital, often from venture capital investors, to build an innovative growth focused, scalable business." The Israeli "innovation model" is "largely based on the creation of technological value, mainly in start-up companies and multinational corporations R&D centres".

This is true of the Indian government as well. The stated objective of the Startup India Action Plan of 2016 is to promote innovation. The idea that startups are innovative is also reflected in the draft Science, Technology and Innovation Policy of 2020) as well as foreign policy initiatives like the Engagement Group on startups at the ongoing G-20 Summit.

The Startup India Policy offers a suite of regulatory exemptions and incentives linked to innovation by startups. Two key components of this policy are: (i) reduced fees and priority in processing patent and design applications for startups, and (ii) full exemptions on income tax to the startup following approval from an Inter-ministerial Board (IMB). The Startup India Policy has been amended several times. Key changes relating to the definition of a startup have been:

1. February 2016: a startup is (i) not older than five years from the date of its incorporation/registration, (ii) turnover in any of the previous five financial years has not exceeded INR 250 million, and (iii) it is working towards innovation, development, deployment or commercialisation of new products, processes or services driven by technology or intellectual property. The startup should develop and commercialise "a new or a significantly improved product or service or process that will create or add value for customers or workflow".
   To be registered with the DPIIT, as well as to qualify for the tax exemption, a startup needs to be recommended by a registered incubator, or an angel/private equity/ accelerator fund with at least 20 per cent funding, or by the Union or state government as part of a scheme to promote innovation, or it should have filed a patent.
2. May 2017: the age of an eligible firm and the period for calculation of turnover was increased from five to seven years from the date of its incorporation/registration (ten for firms in the biotechnology sector).
   In addition to the definition, a startup may now also have scalable business models with a high potential of employment generation or wealth creation to gain benefits.
   To register as a startup and avail of the tax exemption from the IMB, a firm now only has to make an online application by providing the details of (i) certificate of incorporation/ registration and "other relevant details as may be sought", and (ii) a write-up about the nature of business highlighting how it meets the criteria in the definition. The DPIIT would consider "innovativeness" from a domestic standpoint. DPIIT may grant or reject recognition after review.
3. February 2019: age requirement of an eligible startup was relaxed to ten years for firms across all sectors. The turnover limit was increased to INR 1 billion.

Given the emphasis on "innovation", we consider it important to examine whether India's policies are incentivising innovation by startups by asking the following questions:

1. Are startups in India engaging in innovation?
2. How innovative are Indian startups compared to non-startup firms?

To answer this, we require some well-accepted measure for studying startup innovation. We adopt the most popular method i.e. using patent fillings and grants as proxies to measure innovation (Wang 2018; de Rassenfosse 2019; Katila 2000). We chose this over other proxies like expenditure on R&D (Rothwell and Ziegler, 1981; Geroski, 1989). We examine our questions using patent filings and grants to startups. We also use a novel measure i.e. the benchmarks for innovation as defined under the Startup India policy. We found that startups are not driving "innovation" in the conventional sense of the term in India.

We lend new insights into the conventional wisdom on startups and innovation in India and highlight the need for a re-look at the current policy on startups in India.

Methodology

We use two methods to determine whether startups are engaging in innovation:

(i) Measuring innovation using patent applications and grants: We hand-collected data on patent filings and grants from the Indian Patent Office across different categories of entities for the years 2016-17 to 2020-21. We substantiate this data using the annual reports of the Department of Promotion of Industry and Internal Trade (DPIIT). We examined the fraction of patents filed and granted by startups over the years compared to other entities.

(ii) Measuring innovation using startup registration and granted Income Tax (IT) exemptions under the Startup India Policy: The Startup India Policy 2015 requires startups to be innovative to (i) register as a startup and (ii) be granted IT exemptions under the Startup India Policy read with section 80-IAC of the Income Tax Act. We collected data on the number of startups that have successfully received tax benefits (after being classified as innovative). We then calculated the fraction of startups that were granted exemptions versus total startup registrations. For this, we collected data on startup registrations, applications for IT exemptions and approvals to applications of IT applications for all states and UTs in India between 2016-2022. We aim to gain insights into how many startups are "innovative" according to the policy definitions of "innovation".

We also collect currently available data on the total number of startups in India with the number of startups that are registered with the DPIIT. However, this is only available for the current year. We aim to examine how many startups in India qualify under the policy definition of a recognised startup to examine the stringency of the definition of a startup.

We conducted a detailed analysis of startup policies in India to give us further insight into our results from (i) and (ii) above.

Results

Impressive growth rate in patent filings by startups but their overall share remains small: We examined patents filed and granted by Indian startups versus other Indian entities which include small firms, private and public firms, and natural persons. We did not include foreign firms and institutions filing for patents in India or Indian entities filing for patents abroad. We found, across the years, that the number of patents filed by startups has increased possibly on account of the fee waiver and fast-tracking of applications. We also see specific increases in the years in which these interventions were made (May 2017, February 2019) when patent filings doubled (see Figure 1). The CAGR for patents filed by startups and other entities show a disproportionate growth rate for startups at 54 per cent for the period between 2016-17 to 2020-21 which was nearly 12 per cent for other entities for the same period. We found that startups constitute a small proportion of the total patents filed in India when compared to other entities. Patent filings were largely driven by large firms and universities.

Figure 1: Fraction of patents filed by startups over non-startups (2016-17 to 2020-21)

Disproportionately fewer startups were granted patents: The share of patents granted to startups peaked at 8.8 per cent during 2017-18, remained the same the following year and has declined since then. One reason for this could be that startups were obliged to file for a patent to receive registration under DPIIT as well as for applying for IT exemption. The reason for the drop in shares of both patents filed and granted during 2020-21 could be the removal of patents as a condition for registration of a startup and for IT exemption (in May 2017). We also believe that there could be an overall decline in the quality of patents filed. It appears that while the current policy has incentivised firms to file patents, their applications do not pass the more stringent test of proving innovation and hence they fail. The threshold required to grant a patent is strict and requires a firm to prove novelty, which is not the case at the application stage where anyone may file for a patent.

Figure 2: Fraction of patents granted to startups over non-startups (2016-17 to 2020-21)

Source: Annual reports of Indian Patents Office

Figure 1 showed that the share of patents filed by startups in total patents filed was rising during the period 2016-17 to 2019-20. This is not the case for the share of patents granted (Figure 2).

Less than two-fifths of startups registered with DPIIT qualify for benefits: We find that since 2016, the number of companies registered as startups under the Startup India Policy with the DPIIT has increased in absolute terms. However, the growth rate over time has reduced. We further find that out of all the startups that exist in India, only a percentage of them qualify as "startups" under the Startup India Policy and have been registered as such. For instance, there are 2,49,107 startups in India (as on February 2023) out of which only 90,939 (36.5 per cent) are registered by the DPIIT as startups. It is possible that the unregistered startups have either not applied to be registered or have not qualified as startups as per the definitions. This raises the question: is our current definition of a startup under the Startup India Policy the right one? Should we rethink the definition to extend the benefits of the policy to more startups on the ground?

Low grant percentage of IT exemptions for startups: We found that out of the total number of registered startups, less than 2 per cent of startups have been granted the IT exemption, signifying that few startups have been certified as innovative as described in the Startup Policy on external scrutiny by the IMB. We validated this with data on the number of applications for the IT exemption for the year in which this data is available (2017) and found that 90 per cent of registered startups applied for the IT exemption in that year. This indicates that the low fraction of startups receiving IT exemptions is not for the lack of application on the part of registered startups. This has even prompted questions in Parliament.

To be registered as a startup under DPIIT, a startup has to only declare that they are working towards innovation, whereas to obtain an IT exemption, the fact of innovation is scrutinised by the IMB based on specific criteria because of which a startup may not qualify. It is possible that, at registration under the policy a startup need not demonstrate innovation but only declare it, however, for the IT exemption it must now demonstrate and prove innovation in the manner specified in the policy. It appears that few startups are actually being innovative according to the Startup India Policy. Table 1 summarises our findings.

Table 1: Total startups registered and granted IT exemptions based on whether they are "innovative" (2015-2016 to 2020-21).

Year	Number of startups registered	Growth rate (%)	No of startups granted 80-IAC	Fraction of total (%)
2015-16	471	--	7	1.5
2016-17	5233	1011	69	1.3
2017-18	8775	68	18	0.2
2018-19	11417	30	162	1.4
2019-20	14596	28	83	0.6
2020-21	20160	38	70	0.3

Source: Authors' calculations from DPIIT data

Limitations: (i) We do not have access to consistent yearly data on the number of total startups v. those which are registered. (ii) We do not have data on the pre-policy period. (iii) Our present study is not focused on industry-level features. We intend to pursue this in the next leg of our study.

Discussion

Our findings indicate that both measures --- IT exemption grants based on innovation and patents filings and grants --- suggest that innovation in India does not consistently emerge from startups. Instead, our findings are in line with studies in other jurisdictions which suggest that large firms undertake most innovation on account of their risk appetite and R&D capacity (Cohen and Klepper 1996, Symeonidis 1996). Our findings are also aligned with reports that indicate large firms and universities engage most in innovation if measured by patent filings in India. Is this, however, a true picture of innovation on-ground? And what are the implications of our findings for current innovation policies for startups?

The literature makes the case for government intervention on startup innovation citing the disparity in the ability to compete as a market failure (Wang 2018, Symeonidis 1996). The argument is that startups require a boost to even out the playing field as they are unable to compete with larger firms with more resources. Our findings lend some support to this by demonstrating that (i) startups in India are not innovating as much as large firms, and (ii) patent filings by startups have increased since the Startup India policy came into effect. We also, find that patent grants to startups have not increased. Therefore, despite government intervention in India, startups are not driving innovation. Some explanations for this are as follows:

• The current set of incentives may not be sufficient to drive startups to innovate more. We find some support for this in the literature that finds that supply-side policies alone (e.g. subsidies) are not sufficient to stimulate innovation (Geroski 1989). Focusing on additional demand-side measures such as public procurement of innovation from startups may trigger greater innovation as it reduces the market risk for innovators (Rothwell et al. 1981; Tiwari 2017).
• Conventional notions of innovation are linked to "novelty" through patenting which is a very high standard for measuring innovation. In reality, startups in India may be engaging in innovation which is not eligible for conventional patents such as technological improvements or modifications suited to the domestic context. Reports suggest that startups in India adopt rather than innovate in the conventional sense. For instance, India is using the technology adoption route for developing Web3.
  Another reason could be that Indian firms are innovating but are not registering patents in India. Reasons for this range from poor enforcement in India to sector-specific commercial preferences. An example of the latter is the semiconductor sector --- India has a large chip design industry but this work is done on a contract basis for US semiconductor firms which file their patents in the US.
  Therefore, patents may not be the best way to measure innovation in India. Current startup policies in India should re-think the definition of "innovation" and make it more suited for the Indian context.

We gain some insights from the innovation-linked incentives that are offered by other countries. In South Korea, which has the highest per-capita granting of patents in the world, all startups irrespective of how innovative they are qualify for reduced fees in patent filings and certain tax exemptions available to SMEs. South Korean policy appears to focus more on promoting linkage between large and small firms to promote networking and market access. In the Netherlands, which ranks ninth in the world in patent filings, vouchers are given to SMEs for patent filing that cover up to 75% of costs. The Dutch Tax Office evaluates and grants specific tax incentives for "technical-scientific research" and "development projects". Both these countries, considered to be highly innovative, have tax schemes that are targeted at specific outcomes and there are some general exemptions for patent filings. India could perhaps learn from these policies.

Conclusion

We set out to answer two questions in this article: Are startups engaging in innovation? How innovative are startups compared to non-startup firms? Our findings using both measures indicate that startups are not driving "innovation" in the conventional sense of the term in India. However, many Indian startups have scaled up by engaging technology towards creative solutions in many industries such as payments (Paytm), e-commerce (Meesho), credit cards (CRED) and healthcare delivery (PharmEasy). While these firms may not do well on the conventional measures of "innovation", they have played a role in encouraging entrepreneurship to solve everyday challenges, all while benefiting their shareholders.[1] Policy in India must, therefore, be suitably modified to recognise such contributions towards innovation. This is an emerging idea that Indian policymakers are increasingly acknowledging. For instance, the Economic Advisory Council to the Prime Minister of India noted the importance of FDI from tech transfers as a key source of promoting innovation in India. We need to think harder about what "innovation" means in India and what role should the government play in encouraging innovation.

In further research, we will analyse the pattern of patents filed and granted across various industries to understand which sectors are more innovative in the traditional sense. We will also examine the firms that have received the IMB's certification of being "innovative" to (i) study the characteristics of these firms and the industries to which they belong, and (ii) study the trends in the grant of certification by the IMB for innovation to startups. This will help us gain a more nuanced understanding of what drives innovation among startup firms in India.

Footnotes

[1] According to its Red Herring Prospectus filed at the time of its IPO (November 2021), Paytm does not own any patents.

References

1. Tom Eisenmann, Entrepreneurship: A Working Definition. Harvard Business Review, January 10, 2013.
2. Stevenson, H. H., and Jarillo, J. C., A Paradigm of Entrepreneurship: Entrepreneurial Management. Strategic Management Journal, 11 (1990), 17-27.
3. Dobrila Rancic Moogk, Minimum Viable Product and the Importance of Experimentation in Technology Startups, Technology Innovation Management Review, March 2012.
4. Beck, Thorsten and Demirguc-Kunt, Asli and Maksimovic, Vojislav, Financing patterns around the world: Are small firms different?, Journal of Financial Economics, Volume 89, Issue 3, September 2008, Pages 467-487.
5. Jue Wang. Innovation and government intervention: A comparison of Singapore and Hong Kong. In: Research Policy 47.2 (Mar. 2018), 399-412.
6. Wesley M Cohen and Steven Klepper, A Reprise of Size and R&D. In: Economic Journal (1996), 106 (437), pp. 925-51.
7. Gaetan de Rassenfosse, Adam Jaffe, and Emilio Raiteri. The procurement of innovation by the U.S. government. In: PLOS ONE 14 (Aug. 2019), pp. 1-11.
8. Katila, R. Measuring innovation performance. In: International Journal of Business Performance Measurement (2000), 2: 180-193.
9. P. A. Geroski. Entry, Innovation and Productivity Growth. In: The Review of Economics and Statistics 71.4 (1989), 572-578.
10. R Rothwell and W Zegweld. Industrial Innovation and Public Policy: Preparing for the 1980s and the 1990s. In: London: Francis Pinter Publications (1981).
11. G. Symeonidis, Innovation, Firm Size and Market Structure: Schumpeterian Hypotheses and Some New Themes, OECD Economics Department Working Papers, 161 (1996).
12. S.A. Low and M.A. Isserman. Where Are the Innovative Entrepreneurs? Identifying Innovative Industries and Measuring Innovative Entrepreneurship. In: International Regional Science Review 38.2 (2015), 171-201.

Aneesha Chitgupi, Karthik Suresh and Diya Uday are researchers at XKDR Forum. We thank Devendra Damle, Josh Felman, Dr. R. A. Mashelkar, Amey Mashelkar, Megha Patnaik, Arjun Rajagopal, Anjali Sharma and the anonymous referees for their feedback and comments.