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Wednesday, March 30, 2022

Energy transition investment in India and in the world

by Akshay Jaitly and Ajay Shah.

At a time when the 20th century has returned, in terms of geopolitical conflicts, we should not take our eyes off the climate change problem. CO2 is a global pollutant, and it will be harder than ever to get the world economy to safety, so we will need to make more of an effort.

Measuring energy transition investment in 2021

BloombergNEF builds an important annual statistical picture in the `Energy Transition Investment Trends' report. The 2022 report measures global investments into the carbon transition. They break this down into two groups: the direct energy transition investments, and the investments in R&D for improved technology.

The headline numbers for 2021 are that there was \$755 billion of energy transition investment and \$165 billion in technology development, adding up to \$920 billion. Under `energy transition investment', the sub-components that are tracked by BloombergNEF are (a) Renewable energy; (b) Energy storage; (c) Electrified transport; (d) Electrified heat; (e) Nuclear; (f) Hydrogen; (g) CCS and (h) Sustainable materials.

For the Indian economy, it is largely a story of learning, purchasing and implementing the technology developed elsewhere in the world. As an example, many people all over the world invested in, and took the steps on the journey to, cheap solar photovoltaics. We in India are the beneficiaries by being able to buy solar panels or the machines that make solar panels, without needing to invest risk capital in developing the technology. We also can do M&A, like Reliance Industries’ buyout of solar cell and panel manufacturer REC Solar Holdings for \$771 million in late 2021. Hence, for the remainder of this article we focus on the \$755 billion of energy transition investments (worldwide) in 2021.

The big facts

Of the \$755 billion, there are two large components -- \$366 billion into renewable energy and \$273 billion into electrified transport. But there are also many other things going on (energy storage, electrified heat, nuclear, hydrogen, CCS, sustainable materials), adding up to the remaining \$116 billion.

Investment into the energy transition has grown well. A decade ago, this was at \$264 billion, thus giving an average compound growth of 11% per year in USD.

The report estimates that to get to net zero, these numbers need to triple to 2025 and then double to 2030. Overall, a six-fold rise is required from 2021 to 2030.

The values seen in India

Energy transition investment in 2021 in China was at \$266 billion (out of the total of \$755 billion), and in India it was \$14 billion. The Chinese GDP is about five times larger than India, but their investment in the energy transition last year was 19 times larger than India's.

If we apply the Indian share in world GDP of 3%, the value of Indian energy transition investments should be at \$23 billion. If we relate this to the Indian share in world CO2 emissions of 7%, this should be at \$53 billion. By these two normative yardsticks, then, energy transition investment in India needs to be 1.6 or 3.8 times bigger than it is.

What impedes the energy transition in India?

If we multiply the present value of \$14 billion a year by 6 x 1.6 or 6 x 3.8, we get to the estimated required investment in India for 2030 of \$134 billion or \$319 billion. Such values cannot be obtained from the fiscally stressed Indian exchequer. They can only be obtained from the private sector. But the private sector is still skeptical about energy investment in India (as is evidenced by the relatively low value of \$14 billion in 2021).

The present policy frameworks for the sectors that receive energy transition investments have been in place for decades. Intensification of these frameworks, or better implementation of the present policy paradigm, is unlikely to shift the needle sufficiently. For instance, persisting along this path will mean that electricity in India will continue to be unreliable, expensive and carbon-intensive.

When we look at the landscape of \$755 billion of investment in 2021, it is not, China apart, taking place in a world of central planning; it is in a world in which the government sets up the foundations through which the price system operates, and then the precise decisions about technology and business model are made locally by private persons. This is the key transformation that is required in India. The decision to put up a solar plant or build an electrolyser should be made by an individual looking at the prospective profit, not a government official who puts out a tender. The decision to put up a storage facility should be made by a private person who sees opportunities in a large gap between the highest price of the day and the lowest price of the day.

As we argue in a recent paper, the problems of the Indian climate transition are now beyond the calibrated control of officials. The government controlled system is experiencing substantial stress, owing to the contradictions inherent in it. A centrally planned system is ill equipped to think about technical and business model problems in each square kilometre of India. Government control will tend to push simplistic solutions that will drive up the cost imposed upon society for the energy transition.

Tuesday, March 29, 2022

How competitive is bidding in infrastructure public procurement? A study of road and water projects in five Indian states

by Charmi Mehta and Diya Uday.

Introduction

Competition is central to the functioning of a market economy. Market power is a market failure, and governments around the world work hard to fight anti-competitive behaviour and market capture by firms. When competitive pressure is lacking, firms fail to achieve efficiency in production.

An efficient system for government procurement is one where the government obtains purchases for the lowest possible price. In the international literature, studies have shown the linkage between higher competition and lower procurement prices (Estache et al. 2008; Hanak and Muvchova 2015), greater efficiency (Adam et al. 2021) and a lower rate of corruption and kickbacks (Knack et al. 2017).

It is difficult to make normative claims about what is the adequate level of competition. Economists have emphasised contestability of a market as the underlying source of efficiency; simple proxies like concentration ratios do not correctly evoke the level of competition. Researchers in the field of competition levels in government contracting have used the number of bids received for a tender as an empirical measure.

There is some international evidence from developing countries about the desirable numbers of bidders in infrastructure public procurement. There are thumb rules, such as desiring eight-or-more bidders for a roads contract (Gupta 2002, Estache et al. 2008) or seven-or-more for water projects (Estache et al. 2008). These normative numerical values would of course, not readily carry forward across locales, but we use them cautiously in the present work.

In the field of government contracting in India, there is anecdotal evidence of anti-competitive behaviour in the market with reports of bid-rigging and collusion. In this article, we aim to step up from this to some statistical evidence. We ask: How much competition do we see in Indian infrastructure procurement? How does this vary across states and sub-sectors?

Methodology

We hand-construct a novel data-set with a sample of tenders from five states: Tamil Nadu, Odisha, Maharashtra, Uttar Pradesh and Kerala. This choice of states was shaped by the levels of spending on infrastructure, geographical heterogeneity, and data availability. We extracted data from 1000 randomly sampled, awarded e-tenders published by state governments on the Central Public Procurement Portal (CPPP) in the water and roads sector for 2018 and 2019.

CPPP is a centralised repository of tender data at the union and state level. Procuring entities across union and state tiers are obliged to publish their tenders on the portal. We use data solely from this portal to ensure consistency in variables and recording. The data-set includes:

  1. States in the sample: Kerala, Maharashtra, Odisha, Tamil Nadu, Uttar Pradesh
  2. Sectors covered: roads, water
  3. Years covered: 2018, 2019
  4. Total sample size for each sector: 500 tenders
  5. Key words used while searching through the CPPP to select tenders: "road", "water".

We extract the number of bids received for each tender in order to examine the level of competition.

In the research literature, it is argued that three factors shape competition in public procurement:

The value of the contract
Larger contract sizes require greater capital and expertise, which act as an entry barrier for small/mid-size players in the market (Estache et al. 2009; McEvoy 2020).
Structure of the tender
Bundled tenders, where multiple works of different types are bundled into a single tender document, restrict competition to only those firms that can undertake the varied components of bundled tender (Estache et al. 2009). Dividing contracts into smaller lots bolsters MSME participation and thus competition (Hoekman et al. 2022).
Time taken to award contracts
Lengthy award schedules require participating firms to lock-in capital and resources for the bid amidst the uncertainty of winning the bid; this adversely impacts private sector enthusiasm towards bidding (World Bank 2020).

We will examine the extent to which the number of bids per tender correlates with these features.

Results

Table 1 summarises the statistics on the number of bids received across the five sample states for the years 2018 and 2019.

Table 1: Number of bids received in the infrastructure sector

In the Roads sector

2018 2019

Min Max Median Average Min Max Median Average
Maharashtra 1 4 3 3.26 1 11 3 3.94
Uttar Pradesh 1 11 3 4 2 9 3 3
Tamil Nadu 1 3 2 2 1 3 2 2.08
Kerala 1 8 2 2.08 1 7 2 1.80
Odisha 1 27 5 7 1 55 6 9.96

In the Water sector

2018 2019

Min Max Median Average Min Max Median Average
Maharashtra 1 34 3 5.56 1 17 3 4.17
Uttar Pradesh 1 8 3 3.04 1 16 3 4.05
Tamil Nadu 1 4 2 1 1 12 3 2
Kerala 1 5 2 2.08 1 5 3 2.28
Odisha 1 52 2 2.45 1 27 3 4
Source: Authors' compilation and calculation from CPPP data

 

Q.1. How competitive is infrastructure procurement?

We find that, with the exception of the road sector in Odisha, the level of competition in terms of the average number of firms bidding for the projects is lower than the normative thumb-rules from the literature. This holds across all states, sectors and years. Further, two features about the lack of competition in this data-set merits discussion:

  1. Tenders where bids satisfy the thumb-rules of the literature

    We examine the fraction of tenders in our sample that satisfy these thumb rules, and count the tenders that got more than seven bids in the water sector and eight bids in the roads sector. Table 2 summarises these results. Here, we see that the roads sector fares worse than the water sector.

    Table 2: Fraction of tenders that receive bids meeting normative thumb rules (share in per cent of tenders)

    Maharashtra Uttar Pradesh Tamil Nadu Odisha Kerala
    Roads 5 5 0 34 1
    Water 14 7 1 8 0
     
  2. Tenders that received only one bid and were awarded

    We find several awarded tenders that attracted only single bids. This is true even in states with relatively higher levels of competition such as Uttar Pradesh, Maharashtra and Odisha. But there are more tenders with single bid awards in the states with the lowest levels of competition, namely, Tamil Nadu and Kerala. We find that single bid awards are more prevalent in the water sector.

Table 3: Fraction of awarded tenders that received only one bid (% of tenders in the sample)

Maharashtra Uttar Pradesh Tamil Nadu Odisha Kerala
Roads 6 2 4 6 40
Water 8 6 52 8 21

Q.2. How do the findings vary across states and sectors?

The results are fairly consistent results across sectors and years. For instance, three states -- Uttar Pradesh, Maharashtra, and Odisha -- have higher levels of competition across both sectors when compared to the other observed states. Kerala and Tamil Nadu have lower levels of competition across both years for both sectors.

Q.3. What features of tenders correlate with a low number of bids?

In the literature, there has been interest in three features that may shape the level of competition: the value of the contract, the structure of the tender and the time taken to award contracts. In our data-set, however, these three factors do not correlate with the number of bidders.

Discussion

This evidence suggests there is a low level of competition in public procurement, in two sectors and five states. There are some systematic patterns, where some states and sectors fare worse in getting competitive bidding than others.

Competitive conditions seem to be the feature of a given state. This suggests that there are some features in states like Kerala or Tamil Nadu, which are inhibiting competition, and can be addressed in a way that would impact on government purchases across sectors.

A large number of tenders with a single bid that get awarded are a curious phenomenon and merit further research. These tenders are awarded under the previous Central Vigilance Commission (CVC) guidelines, which require that state Public Works Departments (PWD) cancel tenders that receive single bids at the first instance. Single bids could be accepted only if the procuring entity received only one bid, even after re-tendering. However, the recent General Instructions on Procurement and Project Management, allows the acceptance of single bids under certain conditions. These include: (i) the procurement was satisfactorily advertised and sufficient time was given for bid submission; (ii) the qualification criteria was not unduly restrictive; and (iii) the price in the bid is reasonable in comparison to market values.

Further research is required in extending this kind of work to other sectors and locales, to assess the extent to which the lack of competition is a more general phenomenon in public procurement in India. The source of this lack of competition also merit exploration.

There are limitations in how state organisations do procurement (Mehta and Thomas 2021), including potential gaps in the capacity of implementing rules (Roy and Uday 2020), inefficiencies of processes and timelines (Roy and Sharma 2020), and delayed payment of invoices (Mannivanan and Zaveri 2021). Such problems could create an inhospitable environment for bidding firms, and deter many good firms from taking interest in state purchases. Well incentivised state actors should solve these problems. This raises questions about the feedback loops that impinge upon state actors.

References

Antonio Estache and Atsushi Iimi, (Un)bundling Infrastructure Procurement: Evidence from Water Supply and Sewage Projects, Policy Research Working Paper No. 4854, World Bank, March 2009.

Antonio Estache and Atsushi Iimi, Procurement Efficiency for Infrastructure Development and Financial Needs Reassessed, Policy Research Working Paper No. 4662, World Bank, March 2008.

Bernard Hoekman and Bedri Taş, Policy and SME participation in public procurement, Vox EU - CEPR, 23 March 2022. 

Charmi Mehta and Susan Thomas, Lessons from the COVID-19 vaccine procurement of 2021, The LEAP Blog, 15 November 2021. 

Emma McEvoy, Small and Medium-Sized Enterprises (SME) Participation in Public Procurement, Maynooth University, 2020. 

Isabelle Adam , Alfredo Hernandez Sanchez and Mihály Fazekas, Global Public Procurement Open Competition Index, Government Transparency Institute, Working Paper Series: GTI-WP/2021:02, April 2021. 

Pavithra Mannivanan and Bhargavi Zaveri, How large is the payment delays problem in Indian public procurement?, The LEAP Blog, 22 March 2021. 

P. Manoj, Govt lifts the ‘fear’ on accepting single bids during public procurement tenders, The Hindu, 2 November 2021. 

Srabana Gupta, Competition and collusion in a government procurement auction market, Atlantic Economic Journal 30, 13–25, 2002. 

Shubho Roy and Anjali Sharma, What ails public procurement: an analysis of tender modifications in the pre-award process, The LEAP Blog, 26 November 2020. 

Shubho Roy and Diya Uday, Does India need a public procurement law?, The LEAP Blog, 19 August 2020. 

Stephen Knack, Nataliya Biletska and Kanishka Kacker, Deterring Kickbacks and Encouraging Entry in Public Procurement Markets : Evidence from Firm Surveys in 88 Developing Countries, World Bank Working Paper, May 2017. 

Tomáš Hanák and Petra Muchová, Impact of Competition on Prices in Public Sector Procurement, Procedia Computer Science, Volume 64, Pages 729-735, 2009. 

World Bank, Contracting with the government, World Bank Doing Business, 2020

 

 

Charmi Mehta and Diya Uday are CMI-XKDR Forum researchers. The authors thank Shailesh Phatak, Susan Thomas and Ajay Shah for their valuable inputs on this work; and Abhinav M from the Indian Institute of Human Settlements for his valuable research support.

Sunday, March 27, 2022

How did courts respond to the pandemic lockdowns: evidence from the NCLT

by Pavithra Manivannan, Susan Thomas and Bhargavi Zaveri-Shah

Introduction

An important problem of the Indian state is the working of the judiciary, which is hampered by procedural frictions and delays. Several research papers measure the output of the judiciary in terms of number of cases disposed and the elapsed time from start to finish (DAKSH (2016), NALSAR (2016), Regy and Roy (2016), Datta et. al (2017), Tata Trust (2019), Vidhi Centre for Legal Policy (2021)). While recognising that the end objective of a sound judiciary is to decide cases correctly, these practical measures of the output of the judiciary are interesting in capturing what the judicial performance is at any point in time, as well as how it changes from one point to the next.

An example of such an episode is the COVID-19 pandemic. This event disrupted all economic and social processes in India, including the working of courts. Service organisations all over the world responded by building an all-digital workflow. With digital adaptations, many service organisations have matched upon pre-pandemic levels of output and productivity. We analyse the quarterly results of listed non-finance services firms for 2019, 2020 and 2021, for the April-May-June quarter. The total net sales of the firms was Rs.2.87 trillion, Rs.2.2 trillion and Rs.3 trillion. These firms had output in 2021 that was similar to that seen in 2019.

In case of the judiciary, the response included selecting urgent matters for hearing, as well as adopting e-filing and virtual hearings as the norm. How did the judiciary in India fare during the lockdowns that were put in place during the peak of the pandemic, once in 2020 and another in 2021?

Sharma and Zaveri (2020) examined the response of the Indian judiciary during the pandemic. They introduced an important innovation in the literature on court performance, by constructing a data-set of outputs based on cause-lists of the NCLT. They used this data-set to examine the relative output of the NCLT during the first pandemic lockdown (25 March 2020 to 30 June 2020) to the output in the pre-lockdown period in 2020 (1 February 2020 to 24 March 2020).

In this study, we carry this research agenda forward. We argue that a useful quantitative measure of output is the number of cases scheduled per day and cases disposed per day. We use this to examine the extent to which the output of the NCLT changed during their repeated exposure to pandemic triggered lockdown conditions. We examine these for three comparable periods in 2019, 2020 and 2021. In this, we recognise that the NCLT added courtrooms during the pandemic period of 2020, which can influence the NCLT output. We also recognise that the NCLT scheduled hearings only for urgent matters, and that the complexity of the matters scheduled can impact the number of disposals. We introduce a classification scheme of complexity of cases, and examine the extent to which the number of cases disposed responds to metrics of case complexity.

Methodology

As with Sharma and Zaveri (2020), our data-set is constructed from the cause-lists of the NCLT. In this article, we measure the months of March, April and May for 2019, 2020 and 2021. We focus on the same three months in each year for two reasons: One, it controls for any variation that may arise due to seasonal factors, such as court vacations and festivals. Second, India saw the peak of the pandemic in these three months in both 2020 and 2021.

The daily cause-lists for each of these periods are available for 11 out of 15 benches of the NCLT. Our analysis is focused on those benches which consistently published cause-lists during each of these three periods. These were the benches of Cuttack, Jaipur, Kolkota, Mumbai and New Delhi (including the Principal bench). This data-set makes it possible to observe the number of cases scheduled on each day and the number of cases disposed. If the NCLT is viewed as a black box, its performance can be measured by the number of cases disposed. (As stated before, there is a quality dimension, which is not addressed in this quantitative research).

When the systems of the NCLT are augmented, whether by introducing additional courtrooms or technology and technology led processes, we expect a scaling up of the number of cases disposed per courtroom per day. In addition to the per day averages, we focus on hearings scheduled and disposals per courtroom per day to understand the extent to which this took place.

When the pandemic began and only urgent matters were scheduled, there could be a selection bias on the part of both plaintiffs and judges to emphasise important and urgent cases. This could generate an increase or decrease in the complexity of cases which, in turn, could impact the measured output of the court. In order to explore this problem, we construct a measure of complexity of cases. For this, we categorise each hearing under five heads: Insolvency and Bankruptcy Code (IBC), Oppression and Mismanagement (O & M) under the Companies Act (CA), Schemes, Strike off Appeals and Miscellaneous. We classify IBC and O & M matters as Complex and all the others as Simple. This allows us to examine the extent to which the observed changes in output have been influenced by a change in complexity.

Results

Table 1: Average daily NCLT output

Period Hearings Disposals
Mar - May 2019 399 65
Mar - May 2020 149 30
Mar - May 2021 255 48

In 2019, NCLT scheduled 399 hearings per day and disposed 65 cases per day. Table 1 shows us that, in 2020, in the aftermath of the first extreme lockdown, the output of NCLT dropped both in terms of scheduled hearings (149) and disposed cases (30). It then partially increased in 2021 (255 hearings per day and 48 disposed cases per day). This demonstrates resilience in the NCLT capacity during the second wave, in 2021.

Some benches of the NCLT had a higher number of courtrooms in 2020 and 2021. For example, the number of courtrooms in New Delhi went from 4 in 2019 to 6 in 2020 and 2021. Similarly, in Mumbai, it increased from 3 in 2019 to 5 in 2020 and 2021. On the other hand, the courtrooms for the Kolkata, Cuttack and Jaipur benches remained constant during all three periods. Some of the increased outcomes in 2021 may be owed to the increased number of courtrooms.

In order to control for this feature, we focus on the average disposals per courtroom per day. Table 2 shows that there was a 66% decline from 2019 to 2020, and then a 50% rise in 2021. The final level – 3 disposals per courtroom per day – was half than seen before the pandemic, but better than during the first wave in 2020. This suggests that the addition of courtrooms alone did not significantly alter the output of the NCLT. Wide-scale adoption of technology such as video-conferencing facilities that enabled the NCLT to operate without exposing the members to the virus is likely to have contributed to these improvements in outcome.

Table 2: NCLT output, measured as the average per courtroom per day

Period Hearings Disposals
Mar - May 2019 36 6
Mar - May 2020 10 2
Mar - May 2021 17 3

NCLT hears matters of varying complexity. Time taken to dispose off a complex matter might be higher due to the procedures, technicalities and stages involved. The increased outcome in 2021 could have been achieved by NCLT by merely altering the scheduling proportion of complex v. simple cases. We examine whether such a selection bias contributed to higher disposals in 2021.

Table 3: The role of case complexity

Period Complex Complex Simple Simple

Hearings Disposal Hearings Disposal
Mar - May 2019 263 35 126 29
Mar - May 2020 102 13 44 16
Mar - May 2021 199 33 50 14

Table 3 shows that the proportion of complex vs. simple cases scheduled for a day, is greater in 2021 than in the pre-pandemic period 2019. In terms of disposal, in 2019, complex and simple cases disposed were of a similar order of magnitude (35 complex cases a day vs. 29 simple cases per day). In 2021, there is evidence of a greater proportion of complex cases being disposed off: 33 complex cases a day vs. 14 simple cases per day. This shift in the case load, in favour of more complex cases, would mean that the increased output of NCLT in 2021 is not out of scheduling larger fraction of simple cases. But this shift would ordinarily go with a reduction in output per courtroom per day, holding productivity constant.

Discussion

The working of the judiciary has deep ramifications on the working of the economy which depends upon timely and just decisions on disputes. While the ultimate objective is that cases should be decided correctly, there is an emerging literature which emphasises quantitative measures of the output of courts. This is an interesting and important line of questioning, even without bringing in the analysis of the quality of court judgements, because it helps to identify and understand the response of the court to disruptions such as the COVID-19 pandemic.

The evidence here shows that NCLT was disposing 65 cases per day under pre-pandemic conditions. In the worst pandemic conditions in 2020, this output dropped to 30 cases disposed per day. Under similar conditions in 2021, output was higher at 48 cases disposed per day.

Did additional courtrooms that were added in 2020 help explain this rise? When output is measured per courtroom per day, there was a decline in 2020 to 2 cases per courtroom per day from a disposal of 6 cases per courtroom per day in 2019. The output went up to 3 cases disposed per courtroom per day in 2021. This is an improvement in the NCLT output, even if it is still at a level which is half of that seen under pre-pandemic conditions, and resulting productivity gain.

Was the output higher because the case mix emphasised more simple cases? This was not the case. On the contrary, there was a shift in favour of more complex cases. In our evidence, complex cases went up from 55% of disposals in 2019 to 70% in 2021. As these cases would be expected to require more time, this constitutes a partial explanation for the reduced output per courtroom seen in 2021 when compared with 2019.

A third factor is the technology and the digital processes adopted and refined by the NCLT after the strict lockdown imposed in 2020 was lifted. The evidence in our study shows that these new processes yielded the NCLT gains in 2021 when compared with 2020.

The Indian law fraternity is debating whether it would be beneficial to revert to physical functioning of courts as opposed to going further into the video environment (Press Trust of India, 2021). In our data, we see that, NCLT productivity was at 3 disposals per courtroom per day in pandemic environment of 2021, as compared with 6 disposals per courtroom per day in the pre-pandemic environment of 2019. These facts can help shape judgement about future possibilities.

References

DAKSH, Access to Justice Survey, Technical report 2016.

Pratik Datta, Surya Prakash B. S. and Renuka Sane, Understanding judicial delay at the Income Tax Appellate Tribunal in India, NIPFP Working Paper No. 208, October 2017

NALSAR University of Law, A study of court management techniques for improving the efficiency of subordinate courts, Technical report 2016.

Prasanth V. Regy and Shubho Roy, Understanding judicial delays in debt tribunals, NIPFP Working Paper No. 195, April 2017.

Tata Trust 2019, India Justice Report: Ranking states on police, judiciary, prison and legal aid, Technical report 2019.

Vidhi Centre for Legal Policy, The Delhi High Court Roster review: A step towards judicial performance evaluation, Technical report 2021.

Anjali Sharma and Bhargavi Zaveri (2020), Measuring court output in the pandemic: evidence from India’s largest commercial tribunal The LEAP blog, 11 September 2020.

Press Trust of India (2021), Continuance of courts virtually will be a problem’: SC on resuming physical hearing, Business Standard, 8 November 2021 at 

Acknowledgements

Pavithra Manivannan is a Research Associate and Susan Thomas is a Senior Research Fellow, both at XKDR Forum in Mumbai. Bhargavi Zaveri-Shah is a doctoral candidate at the National University of Singapore. We thank Pramod Rao, M. S. Sahoo, Ajay Shah, Anjali Sharma and Diya Uday for comments and suggestions.

Monday, March 21, 2022

History of disinvestment in India

by Sudipto Banerjee, Renuka Sane, Srishti Sharma and Karthik Suresh.

Disinvestment of public sector enterprises has been an important part of Indian economic policy since the 1990s. Research in this field has been constrained by a lack of foundations of facts. There is limited information on policy positions, policy actions, as well controversies around policy actions. For example, Baijal (2008) provides a history of early disinvestment decisions in India; Banerjee Sane and Sharma (2020) provide information on the more recent methods adopted for disinvestment; Banerjee, Moharir and Sane (2020) document disinvestments undertaken to meet the minimum public shareholding rule in India.

In a new working paper, History of disinvestment in India: 1991-2020, we contribute to the literature by documenting the history of disinvestment of Central Public Sector Enterprises (CPSEs) in India between March 1991 to December 2020. The paper is a collection of facts on:

  1. The policy position of governments across the years
  2. The policy processes adopted by governments on selection of enterprises for disinvestment
  3. The difficulties encountered in various transactions on (i) methods of valuation, (ii) legal disputes challenging the transactions, (iii) adverse audit remarks of the CAG, and (iv) labour unrest.
  4. Targets for disinvestment and amounts raised
  5. The different methods of disinvestment, especially those used in recent years such as compulsory buybacks, Offer for sale through the stock exchange (OFS-SE), CPSE to CPSE sales, Exchange Traded Funds (ETFs), and public offers.

We found it difficult to achieve this level of clarity on the facts, and hope that this helps many others approach the field with better foundations on facts.

References

Baijal, P. (2008), Disinvestment In India: I Lose and You Gain, Pearson; 1st edition.

Banerjee S., Moharir, S., and Sane R. (2020), The problem of minimum public shareholding in public sector enterprises , The Leap Blog, 18 November 2020.

Banerjee S., Sane R. and Sharma, S. (2020), The five paths of disinvestment in India , The Leap Blog, 7 July 2020.

Sunday, March 20, 2022

Economic stress in Russia

by Ajay Shah.

The Russian economy has faced a series of adverse shocks after the invasion of Ukraine:

  • Many de facto restrictions have emerged upon international trade,
  • Many foreign companies have chosen to pull out or restrict activities in Russia, spanning non-financial and financial firms,
  • Many individuals living in Russia have chosen to emigrate; these are likely to be high skill people.

We may think it is not hard for Russia to absorb these shocks. After all until 1991 it was the USSR, a land of central planning and autarky. We think they will just go back to those ways. However, the recent events are likely to impose substantial costs for the Russian economy.

Russia is no longer a centrally planned economy

It sounds funny, in today's world, to think of officials owning a target for exports, to think of officials making calculations about how much steel will be required in the light of what the five-year plan has envisaged for building railway lines. But that non-market mechanism for thinking and allocating resources did exist in the USSR (as it did in India).

That institutional capacity has been lost after 1991, and it cannot be quickly recreated. Now, Russia is a capitalist economy. The shocks will be dealt with by the price system in its usual ways.

Disruptions in the price system

Within the domain of the price system, trade and FDI have a deep influence upon the structure of production. Every modern economy involves millions of decisions about what to produce and how to produce. These decisions are made in a decentralised way, and millions of contracts are in place that govern the purchases and sales of each firm.

When 10% or 30% of these relationships are disrupted, it adds up to a storm in the economy. Yes, production can be reconfigured in a self-reliant way (and self-reliance will always induce greater poverty), but that takes time. There is a period of extremely volatile prices, of shortages, where every firm is cautiously waiting for the dust to settle before establishing a new set of self-reliant contracts. Millions of negotiations have to take place, to get a new set of production relationships going. There is a learning process where some contracts fall into place, and then prices change, and then once again some contracts are disrupted or renegotiated, and so on.

When the price system is humming, it is a marvel to behold, and when it is disrupted, getting back to normalcy (even the low level normalcy of self-reliance) is hard.

In the case of Russia, foreign goods and foreign technology are particularly important. They are an economy organised around selling natural resources and importing everything else. Hence, cutting off ties to the rest of the world will be particularly painful. Russia is more like Saudi Arabia and less like India in this regard.

Finance is the brain of the economy

Every real sector decision is shaped by finance. To get to the correct decisions in the real sector, we need finance to be operating correctly.

Russian finance is not operating correctly. The Moscow stock exchange was closed down on 25 February. For a month, the economy has not known stock prices. It is difficult for managers to make real sector decisions without the direction that stock prices provide. Conversely, the lack of observation of stock prices induces private decision makers to wait and see.

The credit market is also disrupted. Foreign banks have a position of about $120 billion (about 8 per cent of GDP) and are downgrading or exiting their role in the economy. Many borrower firms have a cashflow crisis owing to fluctuations in the economy, and would default on banks. A large scale banking crisis is likely. These fears, in turn, would hamper the ability of banks to fund real sector firms in rebuilding for a world of self-reliance.

The mind of the firm

In this thinking, it's important to go into the minds of the key persons of Russian firms. They are debating and thinking to themselves: Will I default on debt? What will happen when there is a default? What will input and output prices be a year from now? How can I put my skills to the best use in this environment, so as to buy locally and sell locally and make a profit? How do I address the departures of some of my employees? Should I leave? How much emotional and financial resource should I commit to overcoming this crisis? Do I just wait this out, and there will be a regime change, and we will go back to globalisation?

Many firms will choose to lie low and wait for the storm to end, as opposed to jumping to action in reconfiguring production for a new world of self-reliance. This inaction will increase the short term pain in the economy and increase the time required to get back to a humming economy.

The threat of emergency central planning

While Russia evolved into a market economy in the post-1991 period, in every society, when faced with a war and an economic crisis, there is a greater danger of central planning by the state. For an analogy, think of the behaviour of Indian officials when faced with Covid-19. In a crisis, there is a greater risk of abandoning the price system, of officials giving orders to firms. The lack of rule of law and constitutionalism in Russia implies that there is more of a free hand for officials to behave like this.

To the extent that central planning resurges in Russia, it will make things worse.

Conclusions

There are three levels of bad economic performance.

Economic performance is bad when there is self reliance.

It gets worse when we layer self reliance with central planning.

It is worst when the self reliance and central planning are brought in suddenly.

In steady state, Yes, it is possible to do self-reliance. We know that self-reliance will induce mis-allocation of resources and a low GDP, but it can be done. A sustained estrangement by Russia will taken them back to conditions reminiscent of the old USSR or the self-reliant India of old.

But getting to that (poor) state is itself a difficult task. In the short term, the Russian economy is in even worse shape than the mere self-reliance scenario.

The fact that the USSR was once the prime exponent of central planning and autarky does not mean that it is easy for today's Russia to readily go back to autarky and central planning. Russia now operates in the price system; the institutional capacity for central planning has atrophied and cannot be readily recreated. The sudden difficulties in trade, FDI, and finance, create a very difficult environment for every private firm. Self-reliant structures of production can indeed be created, and they will achieve a low level performance of the economy, but it will take years to get there, to reconstruct the complexity of the modern economy in a self-reliant way. In the short term, there will be a large scale economic collapse.

I have previously argued that freezing central bank assets is not that important. But the rest of the economic sanctions are an imposing barrier, that will likely induce an economic collapse, even without considering the direct cost of waging war.



I am grateful to Alex Etra and Josh Felman for useful discussions.

Sunday, March 13, 2022

The industry structure of India's large firms: IT is the biggest industry

by Ajay Shah.

When trade liberalisation took place, roughly 1991-2007, there was large turbulence in the structure of production in India. It's interesting to take stock and wonder: What is the present industry structure of the large firms of India?

The overall output of the country is, of course, made up of both large and small firms. Small firms are illegible, so we know much less about what is going out in the vast informal sector. What we do observe with confidence is the large firms. So, while we recognise that the industry structure of the large firms is not the industry structure of the overall economy, we examine this here.

We look at the 26,040 non-financial firms where data is visible for 2018-19 in the CMIE database. For each firm, we focus on gross value added (GVA) and the wages paid. Our crude estimator of GVA, from the income side, is profit before tax (PBT) + depreciation + wages. All values are nominal.

Industry No. firmsWagesGVAShare inShare in
(Rs. Trn.)(Rs. Trn.)wages (%)GVA (%)
Information technology 1117 3.83 5.56 30.92 22.84
Chemicals 1997 0.95 3.44 7.69 14.12
Mining 175 0.64 1.82 5.16 7.49
Transport equipment 899 0.69 1.78 5.60 7.30
Miscellaneous services 4043 1.08 1.37 8.75 5.62
Metals, metal products 1525 0.48 1.34 3.86 5.51
Wholesale, retail trading 4378 0.61 1.19 4.93 4.90
Food, agro-based products 1645 0.40 1.06 3.27 4.37
Machinery 1591 0.51 0.98 4.08 4.03
Electricity generation 640 0.30 0.88 2.41 3.62
Electricity trans., distn. 120 0.47 0.66 3.77 2.69
Consumer goods 645 0.25 0.58 2.02 2.38
Construction materials 416 0.18 0.58 1.43 2.36
Transport services 783 0.45 0.57 3.67 2.36
Ind., infr. construction 2255 0.39 0.54 3.11 2.21
Communication services 153 0.32 0.50 2.55 2.07
Textiles 1111 0.31 0.50 2.48 2.04
Misc. manufacturing 1005 0.14 0.35 1.15 1.44
Div. non-fin. services 692 0.20 0.31 1.58 1.26
Div. manufacturing 82 0.05 0.13 0.40 0.55
Hotels, tourism 564 0.12 0.13 0.93 0.54
Real estate 204 0.03 0.07 0.26 0.29
All non-fin. firms 26040 12.39 24.35 100.00 100.00

IT was the most important industry: with 30.92% of the wages and 22.84% of the GVA. This category includes computer services and IT-enabled services.

There are six big industries, which have atleast 5\% of either wages or GVA, and they are: IT, Chemicals, Mining, Transport equipment, Misc. (non-financial) services, and metals. The fortunes of the economy are now primarily about the fortunes of these six industries, which add up to about 60 per cent of the total.

It's surprising, how little is going on in some labour-intensive industires like textiles which is at 2.48 or 2.04 per cent.

The mean firm size (overall) is Rs.935 million of GVA or about \$12 million. In the case of IT, the mean firm is bigger, at about Rs.4,978 million or \$65 million.

Some will read read this table and jump to calls for industrial policy that favours these six industries. This would work poorly, as all industrial policy does. But this table should influence our thinking on the prioritisation of the public goods that will serve the six most important industries, and most notably IT.

India is in a position of strength in IT. This is inconsistent with the language of weakness in a lot of policy thinking on IT, where we see an emphasis upon national champions and protectionism [example]. It is in India's best interests to favour an open global order for the IT industry, but the Indian state tends to argue for a world of narrow domestic walls.

Wednesday, March 02, 2022

Announcements

Position for researchers in the field of working of courts

xKDR Forum is looking for a researcher to work on a project, involving studying the working of courts in India.

xKDR Forum is a Mumbai-based inter-disciplinary group of researchers working in the fields of household and firm finance, public finance management, land and courts. In these fields, the group engages in academic and policy oriented research, and advocacy. The new recruits will come into an active research program in the field of working of courts.

Researchers at xKDR Forum have been working on projects on the working of courts and tribunals in India from an empirical perspective. Using data from various public sources, they have worked on projects involving a study of orders passed by the NCLT and estimating the workload and capacity requirements required at the NCLT. Some of the published research using this work is listed below:

  1. Chatterjee, S., Shaikh, G., & Zaveri, B. (2018). An Empirical Analysis of the Early Days of the Insolvency and Bankruptcy Code, 2016. National Law School of India Review, 30, 89-110.
  2. Damle, D., Gulati, K., Sharma, A., & Zaveri, B. (2021, May 26). Litigation in public contracts: some estimates from court data. The Leap Blog.
  3. Sharma, A., & Zaveri, B. (2020, October 14). Judicial triage in the lockdown: evidence from India's largest commercial tribunal. The Leap Blog.

As a research associate at xKDR Forum, you will work on project deliverables under the supervision of a senior researcher. You will be expected to work in person at the office premises in Mumbai.

Eligibility

The requirements for the role of a research associate are: a background in law, inclination to learn and undertake empirical work, atleast one year of work experience preferably in the field of litigation. You must be comfortable working in an inter-disciplinary research environment with people from varying backgrounds such as economics, public policy and data science. You must be curious and passionate about research and must be willing to work on independent outputs as well as in teams.

The remuneration offered will be commensurate with your skill and experience and will be comparable with what is found in other research institutions.

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 March, 2022.