Executive Summary

Retail Electricity Pricing is a Delicate Balancing Act for Regulators

Electricity is one of the most important forms of energy in India, and is growing in share of total energy, especially as India strives to decarbonise. Until the late 1990s, integrated State Electricity Boards (SEBs) ran the entire electricity value chain. Over about 15 years, these were corporatised and mostly unbundled, creating separate public companies down the supply chain of electricity generation, transmission, and distribution (including consumer retailing). Almost all Distribution Companies (DisComs) remain State-owned, except for the few regions or cities that were historically private, or two States that privatised their State DisComs. Unfortunately, most DisComs, especially public ones, perennially suffer heavy losses, both of energy and of money. As DisComs are the last leg in the chain of electricity supply, their viability impacts the viability of the entire chain, and struggling DisComs are also a risk for India’s climate change ambitions.

Distribution of electricity to consumers in India is a regulated service, with DisComs being offered a geographic monopoly over a region with regulated rate of return.[1] State Electricity Regulatory Commissions (SERCs) set consumer prices (aka tariffs) with two criteria in mind—to cover DisCom costs and to offer social welfare redistribution to protect the poor. The latter is through a system of cross-subsidies, where some consumer groups pay less and others overpay. This is distinct from any subsidies a State government may wish to offer, but such subsidies are meant to be outside the purview of regulators.

In this paper, we examine the processes and outcomes of regulatory tariff-setting, to see how well the criteria are met. In theory, as long as DisComs perform as per the operational targets set by SERCs, they should not be loss-making.

The SERCs are solely responsible for the process of retail tariffs, guided by the National Tariff Policy (which is enshrined in the Electricity Act 2003). The National Tariff Policy limits the cross-subsidy
price variation for almost all consumer categories like households, industrial, commercial, etc. to ±20% of the Average Cost of Supply (ACoS). However, many regulator-set tariffs do not comply with the policy. In this paper, we quantify the non-compliance and examine possible causes and implications of the violations.

The process of setting tariffs spans several years and is broadly divided into two parts—ex-ante and ex-post. When setting initial tariffs ex-ante through the initial Tariff Order, the regulator must make a range of assumptions on power procurement costs, consumer mix, volumes of sale, etc. Ex-post, there are inevitably deviations from plans, which are meant to be reconciled through a subsequent tariff True-Up process[2] that reconciles and compensates the Discom for legitimate gaps. We show that this is an important element of DisComs’ financial performance.

Bottom-up Cash-basis Analysis of Revenues and Costs Shows a Worse Picture than Conventional Wisdom

This paper studies the entire chain and focuses on cash-basis accounting, which is distinct from the typical accrual-basis accounting followed in most official power sector documents and mandatory for corporate audited reports. Accrual accounting is based on booked values, which reflects the money that is promised or due, but the actual cash received is often much lower. Thus, our analysis shows a graver picture of DisCom finances.

We compare compiled governmental data sources with 60 DisCom Tariff Orders across India to quantify the costs and consumer-wise segment revenues. We calculate the cross-subsidies per segment after factoring in revenues from State government tariff subsidies. We also compare the ex-ante costs and revenues with ex-post, and apportion the changes across the respective stakeholders (DisComs, State governments, consumers, and regulators). We extensively use financial year 2019 (FY19) data as it was the latest available year for which audited annual reports data were available in the public domain at the time of analysis. This is also the last period not impacted by COVID-19, which has since, not only impacted sales but also consumer collection.[3]

Examining the regulatory process and finances, we find Tariff Orders (ex-ante) have virtually no losses, i.e., the expected revenues match the costs, but ex-post, there are significant changes, ones that are mostly one-sided and lead to a financial loss.

Our analysis is per DisCom, which is important given the wide heterogeneity across India.

Even before considering changes in revenues and costs ex-post, the ex-ante Tariff Orders for FY19
set by regulators have more than 50% of electricity units with tariffs exceeding the ±20% crosssubsidy limit. To bring tariffs within compliance of the ±20% limit, a combination approach would be needed—lowering tariffs for some overpayers, and raising tariffs for some underpayers. For those paying below 80% of the ACoS, tariffs would need to rise by an average of Rs 1.17/kWh, which corresponds to a 30% increase from the prevalent tariffs. Such a rise is not easy when compared to the historical average tariff rise trend, which had a 5% compound annual growth rate (CAGR) over the prior five years (FY14-19), roughly in the range of inflation.

Ex-post, costs rise across most DisComs compared to ex-ante projections, by 19% on average. This rise in costs is paired with a fall in average billing rate (ABR, or revenues)—varying by DisCom. Put together, these change the finances from no losses ex-ante (actually, an average 0.5% profit, or 0.04 Rs/kWh) to a 22% gross financial gap for FY19 ex-post, or Rs 1.64/kWh financial loss. This gap is only partially offset by unplanned income and government grants (including Ujwal DisCom Assurance Yojana [UDAY] grants) of Rs 0.63/ kWh, which lowered the net financial gap to 14%, or Rs 1.01/kWh. This shift in costs and revenues means the true cross-subsidy is even higher than as per Tariff Orders.

The ex-ante to ex-post change is substantial. There are multiple factors at play and stakeholders who are respectively accountable. These are broken down in Figure ES 1.

On the cost side, the largest change in absolute terms comes from an increase in power purchase costs, followed by a rise in “other costs” that are primarily financial and operational. Higher distribution network losses than the normative level as per Tariff Orders, also raise costs. Because of such distribution losses, which are a subset of the aggregate technical and commercial losses (AT&C), the DisCom needs to procure more power than planned to supply a given load. In aggregate, costs rose by Rs. 1.19/kWh.

On the revenue side, a substantial fall in cash revenues comes from DisCom failures to collect money from consumers, combined with non-payment of promised subsidies by State governments. Both of these are also components of AT&C losses. Some money is also not realised because regulators don’t set a sufficient tariff, postponing a tariff rise by creating a “Regulatory Asset” instead where the utility doesn’t get money in the current year’s tariff. In addition, on average DisComs earned less than projected from the sale of power and other network charges (such as wheeling charges, open access charges, etc.). A significant part of this is due to a change in how many units of electricity are sold to which type of consumer. Put together, the average revenues on a cash-basis fell ex-post by Rs 0.51/kWh.

If we attempt to apportion responsibility for the changes, some factors could be considered random, such as changes in consumption patterns, but a counter view is DisComs should do a better job planning and projecting demand. Without proper projections, they are also likely to get power procurement wrong, another cost ultimately borne by consumers.

Conventional wisdom holds the poor performance of DisComs as the cause of their financial losses, specifically high AT&C losses. However, only two components of AT&C losses—excess distribution network losses and consumer non-collection—are directly in the purview of DisComs. These losses were only 25% of the ex-post financial gap in FY19. Non-payment of subsidies—officially part of AT&C losses—was due to the State government and was 8% of the financial gap. Even put together, addressing such causes of the gap will not close the overall financial gap that DisComs face.

Most other components that shifted should, in theory, be reconciled through the True-Up process. Even if such ex-post financial gaps were to be recovered, these would take several years to materialise. More importantly, we found that True-Ups only capture a small fraction of exante to ex-post differentials even focusing just on “allowed” differentials that aren’t based on the fault of the DisCom or other stakeholders like the State government (in case they don’t pay promised subsidies in full). In FY19, Tariff Orders embedded just 0.07 Rs/kWh of historical True-Ups as part of the cost structure, or close to only 1% of costs. A complementary paper by Devaguptapu and Tongia (2023) examines such issues over a 15-year time series.

Fixing the Gap And Cross-subsidy Limits Will Ultimately Require a Tariff Rise

Improved operations (e.g., lower AT&C losses) are welcome and important, but will only address a small portion of the financial gap. Closing the gap will require wide a range of steps, including better planning and a streamlined True-Up process. However, the ultimate need will be for higher tariffs than the present ex-ante tariffs, but higher tariffs are unwelcome across the spectrum of consumers and State governments.

Higher tariffs will also be required to keep cross-subsidies within statutory limits. This is a pressing issue not just to comply with the law but also because a system with excessively high prices for so-called “paying customers”—primarily commercial and industrial users—creates several challenges. First, this hampers economic growth and global competitiveness. Second, the growth of such consumers is lower than the growth in sales volume we see from lower-end consumers, putting pressure on the redistribution equilibrium. Lastly, thanks to both technological and regulatory changes, such paying customers are the ones most likely to exit or at least diminish their offtake from DisComs through a combination of self-generation, such as rooftop solar and third-party sales like under Open Access norms.

Fixing the financial gap through improved tariffs is also critical because cash strapped DisComs are forced to rely on a range of coping mechanisms that include delaying payments to their own suppliers, including generators. This propagates upwards all the way to delayed payments for coal, railways, and, ultimately, the banking sector.

If we dig deeper, true cross-subsidies are likely higher than most calculations show. Present norms and our base analysis calculate crosssubsidies based on the ACoS, but the true crosssubsidies are likely even higher if we properly account for differences in cost to serve. Bulk consumers (“high tension” or HT consumers) are cheaper to serve, and so if we re-calculate cross-subsidies with such data (available for a few states), we find an even higher cross-subsidy. We can also estimate differences in costs to serve by using retail electricity pricing data from the United States (US), across consumer categories, where industry has the lowest tariffs, followed by commercial, and with households paying the most. Recalculating cross-subsidies based on such differential costs to serve, would raise the levels of cross-subsidies by tens of percent.

There are a range of steps that should be taken to help the tariff process, distinct from setting more cost-reflective tariffs. DisComs clearly need to lower AT&C losses, but we also need far better operational and financial data, especially on the revenue side. We need more standardisation of consumer categories, slabs, etc., and more granular breakdowns within AT&C losses. This is important because different components of AT&C can only be fixed by different instruments—better management versus investments in the physical network. Even billing today isn’t as scientific as one would expect. It is well known that many irrigation pumpsets are not metered, instead relying on assumptions for measuring agricultural supply. This creates the space for fudging data (and hiding losses) and simultaneously asking for more subsidy, given agricultural supply is often subsidised by the State. What is less understood is how many other consumers don’t have proper monthly billing—many residential consumers only get estimated bills, that too inconsistently. The planned rollout of smart meters should help this process.

Regulators have the ultimate responsibility for setting tariffs right, but DisComs also have a strong role to play. Improved planning would not just help to set prices right (where plans should more closely match actual realisations) but also lower costs by optimising generation procurement and network investments. Proper pricing, which may require increasing tariffs, needs crossstakeholder support, especially from the State government. There is a limit to how much State governments can subsidise consumers, and the interplay between subsidies and cross-subsidies is a hidden barrier to rationalised tariffs. Artificially low regulator-set tariffs for subsidised consumers (like agriculture) may reduce the subsidy burden on the State, but this just means either someone else is paying, or that the DisCom bears the brunt of any leftover gap, more so in the ex-post financial realisation. The present equilibrium of both cross-subsidies and high ex-post losses cannot be sustained and needs prompt rectification.

The post Getting India’s Electricity Prices “Right”: It’s More Than Just Violations of the 20% Cross-Subsidy Limit first appeared on CSEP.

Executive Summary

1.1. DisComs are Regulated Entities who Shouldn’t be Loss-making, if they Perform

Electricity distribution companies (DisComs) are the last leg in the vertically integrated chain of electricity sector that starts with generation. In India, they are also responsible for retailing power to consumers. Independent State Electricity Regulatory Commissions (SERCs) set retail tariffs (prices) meant to balance DisCom viability with consumer interest. Unfortunately, DisComs have sustained substantial financial and electricity losses for many years.

Barring Mumbai, which has retail competition, electricity distribution in India is a regulated, geographic monopoly; and DisComs operate on a costs-plus regulation model that is based on performance norms. If they perform, in theory, they should make the specified statutory rate of return. So, are their financial losses thus just a failure of performance? (Tyagi & Tongia, 2023) (in press)

In this paper, we comprehensively analyse DisCom finances using a long time series that aims to examine and answer the following questions using disaggregated and bottom-up numbers:
1. What are the operational losses of DisComs and what are their causes?
2. How much of the gap between costs and revenues is apportionable to different stakeholders (DisCom, regulator, and state government) or not apportionable?
3. How do the operational (annual) losses link to the DisCom balance sheets?
4. What are the steps needed to fix the financial health of the DisComs, especially for a turnaround (on the basis of operational basis viability)?

This paper builds on a complementary analysis by Tyagi and Tongia (2023) (in press) that compares the planned costs and revenues as per ex-ante tariff orders versus the actual realisations ex-post. They found that ex-ante retail tariffs (consumer prices) are set with virtually no gap between costs and revenues. However, in practice (after the year goes by when the tariffs are in force), an enormous gap appears, of around Rs 1.64 per kWh for FY2018-19 (prior to the provisioning of any grants or other income not planned by regulators).

We extend this analysis across 15 years, covering virtually all of India’s public DisComs, integrated utilities, and power departments.[1] By examining financial details over time, we automatically capture true-up adjustments, which are the formal process for reconciling allowed changes from tariff order plans through subsequent tariff revisions. Failure to perform, such as lower-than-notified operating efficiency, is not meant to be adjusted in trueup tariff orders.

1.2. Despite Relative Improvements, Large Financial Gap Remains

Over a 15-year period, with few exceptions, all DisComs have had revenues lower than costs. Consumers don’t pay all the costs directly, and state governments routinely offer tariff subsidies on top of the regulator-set prices (tariffs). Outside these combined revenues, DisComs also rely on significant Other Income and Grants, but this still left a cash-basis gap of Rs 1,04,091 crore in FY2020-21, or Rs 1.14 per kWh sold (Figure ES 1).[2]

Our focus is on understanding the breakdown of this financial gap. Explanatory factors include DisCom performance lapses, non-payment of subsidies, and regulators explicitly not setting a high enough tariff (instead, creating an IOU called a ‘Regulatory Asset’).

Conventional wisdom is that losses are overwhelmingly due to DisCom non-performance. We find this to be incorrect. While they have failed to meet performance targets, both in terms of billing and collection efficiencies, this amounts to only about 30% of the cumulative gap over 15 years. Unfortunately, DisCom non-performance has grown in recent years. Even within noncollection from consumers, a substantial fraction (estimated at over a third and perhaps closer to one-half) is from governmental entities/consumers. We segregate non-payment of subsidies from the widely cited measure AT&C (aggregate technical and commercial) losses since this is not the fault of the DisCom. Subsidy nonpayment and the creation of regulatory assets together explain 13% of the cumulative gap, but this still leaves a “residual gap” of about 59% which is not attributable to any of these causes. Figure ES 2 shows the split of the financial gap’s components over time.

This residual gap effectively means that we have a tariff that is too low to cover costs even after accounting for the factors above, but why this happens is not conclusive. Questions that need to be considered include: Is it because DisComs are not asking for the right tariffs, including in the true-up (reconciliation) process? Are they being denied by the regulator? Or are there deeper issues in the process? We identify additional partial causes, such as the two-year delay for true-ups, which creates a pipeline problem and carrying costs for the DisComs. However, it would be wrong to place primary responsibility on the DisComs for this residual gap.

1.3. Operating Financial Gaps Accumulate in the Balance Sheet

Not only are direct DisCom failures only a fraction of the operating gap, a much larger share of the lapse comes from consumer non-collection, which, unfortunately, is growing (even after the leeway given for FY 2020-21 due to the effects of COVID-19). The “good” news is such a gap isn’t lost forever; consumer non-collection is theoretically recoverable and remains on the balance sheet as a trade receivable. Balance sheets also show “regulatory assets,” but, surprisingly, don’t visibly separate subsidy non-payment!

As we break down the numbers, the true financial picture is better seen in cash flow accounting, since accrual-based accounting, like what the Power Finance Corporation (PFC) compiles annually, (PFC FY21 report indicates a few cash based statements for recent years) understates the problem. These show revenues as-booked, but much of the cash doesn’t come into DisCom coffers, showing up as an asset like a receivable instead.

Because DisComs are cash-strapped, they are forced to resort to various coping mechanisms. First, they delay payments to suppliers, both generators (Rs 2,52,736 crore on the balance sheet[3]) and other short-term dues to vendors (Rs 2,53,040 crore), some of which entail penalties. They also are forced to take on more debt, and we find that States have pumped in significant equity. Unfortunately, much of this isn’t for asset creation, but simply as a fill-up. Regulators have routinely disallowed returns on the full equity base, and the booked return on equity (RoE) has fallen to 3.28%.[4] Even worse, in a few cases, DisComs are waiving RoE, ostensibly to keep tariffs low. This is a poor and non-scalable means of lowering consumer tariffs. This is nowhere near the hurdle rate of 10% notified by the Ministry of Finance for calculating financial internal rate of return in respect of projects which have identifiable stream of financial returns. Accumulated deficits are enormous, in lakhs of crores of rupees, and visible on the balance sheet as a part of the total equity. These have, by far, eroded the (book) equity. These deficits closely track the annual “residual” operating gap we identified plus the unpaid subsidy—other components of the operating gap[5] show up elsewhere on the balance sheet (as trade receivables and regulatory assets of Rs 2,34,072 crore and Rs 45,907 crore, respectively, for the public DisComs covered). Billing efficiency losses were worse than targets, by 3.53% in FY2020-21, and are a permanent loss that doesn’t remain in the books.[6]

1.4. Fixing the Problem: Without an Operational Turnaround, a Balance Sheet Clean-up won’t Last

There has been a range of instruments used to bail out or prop up DisComs over the decades. While some have focused on fixing the balance sheet, many were conditional on achieving lower losses, requiring a reduction in the AT&C losses or even eliminating the ACS-ARR gap (‘average cost of supply’ minus ‘aggregate revenue realised’). However, as Tyagi and Tongia (2023) (in press) first showed, the ACS-ARR gap at the time of tariff order setting is virtually non-existent. Much of
the problem happens ex-post, and the subsequent true-up processes are not effective.

Fixing operating problems is the first step, and seven utilities are already operationally cash positive (based on FY2019-20 data). We find that 18 out of the 43 public distribution utilities studied for clean-up[7] can resolve the gap by “merely” addressing the known components of the gap (excess billing losses aka excess distribution losses, consumer non-collection, subsidy non-payment, and creation of regulatory assets). We recognise that this is easier said than done. The harder challenge is figuring out how to fix the remaining 18 DisComs that have a residual gap and need more fundamental changes. Addressing regulatory assets requires a tariff rise, while other known components require increased compliance. However, addressing the residual gap will also require a tariff increase. For most DisComs, this should be manageable, but in a few cases, the required rise will be unreasonably high (when benchmarked to average annual tariff rises, which are typically
up to 5% or near about inflation).

Operational improvements can improve the balance sheet (or at least prevent further deterioration). The central government has already initiated a range of steps to reduce operational losses and improve cash flows, many of them after COVID struck, ranging from liquidity support, schemes for paying off generators, installation of smart meters, and oversight of timeliness for statutory regulatory and discom filings of tariff petitions, orders, and accounts. However, these do not address the issue of the residual gap in tariffs.

This study also investigates the other direction, i.e., the balance sheet clean-ups that can help fix the operational gap. We focus on unpaid subsidies and regulatory assets since addressing trade receivables from lakhs or perhaps millions of consumers is a diffuse problem that cannot be fixed by policy (except dues from governmental consumers, both state and local). These components are also ostensibly not the fault of the DisCom. With this cash in hand, it could be used to repay generating companies (GenCos) or other liabilities, which would lower carrying costs and improve operations. Unfortunately, adding this step doesn’t help too many more DisComs cross over into profitability as the residual losses are too high.

We conclude with an analysis of both high level and specific suggestions in order to move the needle towards closing the gap componentwise. The first step is to improve accounting and nomenclature, and introduce greater standardisation in processes (including the segregation of AT&C losses into its components). This applies not just to annual statements but also to balance sheets. We also need to revamp the tariff-setting process, especially the true-up process, to close the residual gap. Lastly, we examine a range of additional issues outside the direct issues of tariffs and tariff setting that need to be addressed to achieve operational viability. These include improvements in planning (especially for power procurement but also in terms of expected consumer mix over time), and in DisCom management. Planning will be especially important in a future with increasing decarbonisation and market-structure redesign. For example, consumer-owned solar (rooftop solar) not only changes the net demand pattern seen by the utility (with an additional time-of-day implication), but it also changes their ability to rely on cross-subsidies from premium customers.

Ultimately, several improvements will rely not only on managerial efficiency but also on addressing issues of political economy and politics. This isn’t just for raising tariffs, but even for enforcing existing norms and regulations. The good news is that the problems aren’t universal or equal. By focusing on relevant components of the gap more intensely, the problem can be addressed in about half the DisComs, more so without significant tariff rises. However, for several DisComs, we may need external support and new or more innovative instruments. The residual gap identified and quantified in this paper is a serious challenge, not merely because of its vast scale, but also because fixing the known causes of the financial gap is “not enough”. The sector needs—and deserves—new kinds of regulatory principles and processes.

The post Breaking Down the Gap in DisCom Finances: Explaining the Causes of Missing Money first appeared on CSEP.

Executive Summary:

“There is a middle ground in things” – Horace

The last decade has been a tumultuous one for Civil Society Organisations (CSOs) in India. Their funding context has gone through a sea change. For reasons both global and local, foreign funding for Indian CSOs has declined sharply during these years. Also, a slew of amendments in the Foreign Contribution (Regulation) Act 2010, have made it increasingly difficult for CSOs to access these funds. Given that foreign funds used to be a very important funding option for CSOs, it has meant that they have had to look elsewhere.

At the same time, the Companies Act, 2013 made Corporate Social Responsibility (CSR) mandatory for all companies that met a certain threshold criteria. Since then, an average of Rs 16,000 crore have been spent by these companies annually on social responsibility projects, either directly or in partnership with civil society organisations. While several companies were already involved in community initiatives, the scale and consistency of these efforts changed enormously. Companies had to set up CSR departments, appoint staff to carry out the mandate, and engage with organisations and issues they hadn’t engaged with earlier. These have been years of rapid learning on multiple frontiers for several large and mid-sized companies in the country.

The past decade has not just seen the emergence of CSR initiatives and funds in a significant way, but has also seen the emergence of individual private philanthropy in a major way. While this has been driven mostly by the rapid increase in the numbers of billionaires and the ultra-rich in India, the increase in private philanthropy is also due to smaller donations made by larger numbers of individuals than before. The growth in small donations (also called retail giving) has in part been due to the ease of giving created by tech-enabled platforms, and possibly also because giving has become more public than before. The combination of these changes has meant that CSOs have had to quickly adapt to the working ethos and approaches of these different kinds of entities in the funding/support ecosystem.

In this situation of flux, in which both corporates and CSOs have been trying to understand and influence one another, we undertook this enquiry to comprehend the actual shifts, and to assess their overall experience of working together. We also wanted to understand how the theory and practice around governance and impact in the social sector have changed in this decade. Finally, we attempt to offer some suggestions for the way forward, so that CSOs can work with CSR funding in a mutually respectful and beneficial manner.

Methodology:

The entire study was carried out during the COVID-19 pandemic, which affected the methodology. Field visits, part of the original plan, had to be done away with. Given the nature of the study, and after consulting others in the field, we decided to use long, in-depth interviews as the principal mode of investigation. These were supported by questionnaire-based surveys and secondary literature review. The initial findings were presented at a round table attended by almost all of the interviewees, after which this report was finalised.

The CSO terrain:

A. Who and how many

When we speak of Civil Society Organisations in this paper, we are broadly referring to development organisations working on social issues. These could include the whole gamut of organisations involved in direct action, research, advocacy, rights-based work, capacity-building, community groups, etc. However, there is no comprehensive database of such organisations and efforts at counting CSOs rely on counting organisations registered under the Societies Registration Act, 1860, the Indian Trusts Act, 1882, and Section 8 (earlier Section 25) of the Companies Act, 2013. However, as this dataset is based on legal form rather than purpose, it includes a very wide range of entities—all the way from mohalla puja samitis that come into action only once or twice a year, to some very large institutions such as museums, sports clubs, and media clubs. While all of these no doubt constitute disparate elements of what sociologists call civil society, in operational terms it is hard to consider, say, the Board of Control for Cricket in India (BCCI) or the Gymkhana Club as CSOs.

In 2012, the Central Statistics Office (Ministry of Statistics and Programme Implementation, Government of India) counted all Registered Societies, Trusts, and Section 8 companies in the country since the time these laws were enacted – regardless of whether the entities were currently active – and came up with a number of 31 lakh NGOs/CSOs in India. Of these 31 lakh registered organisations, the Central Statistics Office physically visited 22 lakh organisations, but could actually trace only 6.94 lakh organisations. Given that about 31% of the visited organisations were actually traced, extrapolating to the full set of 31 lakh would produce a figure of 9.6 lakh NGOs/CSOs in the country, which would include not just development CSOs but all the various kinds of organisations referred to in the preceding paragraph.

Apart from inclusion errors, there are also possible exclusion errors, from the perspective of understanding the true size of the civil society organisations space in India. Cooperative societies, trade unions, temples, wakfs, gurudwaras, churches, etc – all of which have legal registration forms different from the three cited above – all adding to the rich tapestry of a nation’s civil society, found no place in the above exercise.

Others have also tried to do this size estimation, including the Society for Participatory Research in Asia (PRIA) which, following an assessment in 2000, concluded that the number of CSOs in the country was likely to be about 12 lakh. In recent years, the NITI Aayog’s NGO listing site, DARPAN, has become a good estimate of active developmental CSOs in the country. It currently lists only 1.25 lakh CSOs – and while listing on DARPAN is not mandatory, it is key for seeking funding or collaboration with government agencies. Thus, it would not be wrong to say that almost all active CSOs are listed on DARPAN.

Hence, while the “31 lakh” CSOs/NGOs number has often been used in media, the actual number may be well below 10 lakh, of which only about 11%-12% may be active. Given India’s population, this means roughly one active CSO for every 11,000-12,000 persons. Since the density of CSOs is lower in most of the poorest (“aspirational”) districts, chances are there could be one active CSO there for perhaps 25,000-50,000 persons. Thus, by no means is the CSO sector as numerous as it should be, given India’s wide and deep triad of problems of economic deprivation, social exclusion, and environmental degradation.

B. Spatial distribution

The paper also looks at the spread of CSOs across the country, and the correlations if any, among the spread, the need (as indicated by the human development indicator for the state), and the availability of funds (as reflected in CSR and FCRA funding) for CSOs. The density index that we have built is based on providing greater weights for CSOs with better procedural accountability systems.

There is a major caveat, though—almost all major datasets list CSOs by states in which they are registered, not where they are working. This is important because most large and mid-size CSOs are active in multiple states. Given the limitations of data availability, our density index, as also the correlations we have made, are based on the CSO’s place of registration, not its area of operation. Even so, the results are still interesting. Further, as and when more correct data is available on the actual work areas of CSOs, this same methodology can be used to arrive at an improved picture.

How has the sector changed?

Almost everyone we spoke with talked about the deep and wide shifts taking place in the social sector. While many of these shifts have been exacerbated over the previous decade, most respondents agreed that the trends had been evident for several years. Some highlights from our interviews:

1) The nature of changes

• The scepticism, suspicion, and regulations amidst which CSOs today work is much higher than ever before. There is a growing perception that CSOs are anti-development, anti-industries, anti-urbanisation, and so on. A narrative has been created, which paints CSOs as inefficient and poorly governed. This perception and narrative lend a justification for tightening the flow of funds to the sector, and for adding to the regulatory requirements. As one respondent quoted their founder: “The freedom of CSOs is a single good indicator of the health of democracy”.The flip side of these changes is that CSOs today devote disproportionately large amounts of energy and effort on reporting and compliances. The internal culture of CSOs has consequently become more ‘corporate’, focused on deliverables and, at times, more top-down. There is a lot of interest in measuring outcomes within short time-frames, leading to a dilution of process and innovation. In addition, since most funding is now ‘projectised’, institution-building in the CSO space has suffered setbacks.

• A rapid loss of ‘biodiversity’ in the sector was flagged by most respondents. CSOs are far more focused on ‘delivering development’ than on strengthening the fundamentals of a more just society. Scale and impact have become extremely important, leading in part to the emergence of specialist CSOs focused on a single problem or theme. While there is no denying the value of sector-focused CSOs, organisations that took a more integrated approach to development now seem to be on the wane. The ‘biodiversity’ loss is also reflected in the larger number of small CSOs that have shut down or come under stress over the past decade.
• A certain kind of “anglophilic” CSO is increasingly becoming the norm, with small vernacular groups finding it much harder to continue. The earlier narrative of small and diverse being more effective is now lost, with scale and similarity becoming the preferred attributes.The rise in private and corporate philanthropy has been accompanied by the birth of a new kind of CSO, in which the donor is the doer. In contrast with traditional philanthropies, many of the new philanthropies have their own implementing arms. Earlier, philanthropies most often pursued their larger objectives through partnering with others in the CSO space. These partnerships were usually long-term, trust-based, and institutional as opposed to just project-based, and took a more comprehensive ecosystem view of development.The last decade has also been marked by the emergence of intermediaries—for incubation, acceleration, capacity-building, funding, and so on. There is now a whole ecosystem of intermediaries, both not-for-profit and for-profit. While intermediaries or aggregators do serve a purpose, most of our respondents expressed disquiet over this strengthening trend. The emergence of social enterprises and other hybrid organisational forms, which combine elements of both for-profit and not-for-profit organisations, are another new and interesting space to watch.
• Another question raised was whether CSOs of the more formal and organised kind would remain the vanguard of large-scale social change in the future. To quote one respondent—“epochal changes are happening outside of structured institutions”. The farmers’ movement of 2020-21, and the anti-CAA/NRC protests of 2019-20 were cited as examples of more non-institutionalised initiatives seeking change. Several people said the youth are approaching things differently, and doing remarkable things outside of formal organisational spaces; there is a need to understand these shifts.

2) Internal Reasons

• We found significant agreement among respondents on the need for greater self-reflection within the CSO space. There were leaders who felt the sector has not truly shared the transformative potential of its work, boxing it into artificial divides of service-delivery and rights. There were others who felt that CSOs have often overprojected their successes and underplayed challenges. All of these have contributed to building a shallow development discourse.
• Some respondents were of the view that the work on rights especially in the last decade has not been as strong, not just because of the changed funding and political context, but also because of the changed community context, in which aspirations are being increasingly influenced by social media.
• The CSO sector comprises a wide variety of organisations, but is often spoken of as an unsegmented universe. There is a pressing need for a more nuanced classification system, and for building good-quality data on the sector, by the sector.
• Many spoke of the need for CSOs to embrace changes such as increased collaboration and use of technology, and for greater emphasis on ‘mutual self-regulation and mutual self-governance’. Mutual self-regulation refers to not just holding oneself accountable, but also to being held accountable by one’s peers.
• Embracing the young, and actively making space for them, was another desirable change that respondents hoped for.

3) External Reasons

• Most respondents felt that the larger societal context today is less open, with a narrowing of spaces for questioning and dissent. This has affected the nature and form of civil society action.
• Notions around charity and philanthropy have shifted, with most new philanthropies not satisfied with just providing support, but wanting to be part of, or influencing the action.
• CSOs have long prided themselves on being self-governed entities, with core value systems that drive them towards good-governance principles such as transparency and honesty. Over the last decade however, the ideas of self-governance have increasingly come under challenge.
• While the shift towards greater quantifiable measurement precedes the entry of CSR, it remains true that CSR funds came in with a very pronounced bias towards measurable outcomes, almost to the exclusion of any other understanding of impact. Further, given the emphasis on implementation and delivery, CSR funds have led to the birth and growth of ‘vendor’ CSOs that are efficient at delivery.
• Finally, our respondents felt that despite everything, certain geographies, especially the North-eastern and Central regions, remained neglected. While the old locational disadvantages persist, new forms of inequality (technology, education access) have emerged. The social sector was about working in areas where no one else would be interested; but in the absence of funding with freedom (which would let CSOs determine their priorities), this has become harder.

Funding shifts

For fiscal year 2019–20, the Central government spending on social sector programmes was Rs 3.2 lakh crore, and State governments spent another Rs 15 lakh crore (Bain & Company, Dasra, 2021). However, support for CSOs and their work mostly came from private sources, whether foundations (foreign or Indian) or individuals.

Over the past few years, corporate giving under CSR has risen rapidly and garnered a lot of visibility. Interestingly, during this same period, Indian private philanthropy by small and large donors has grown even more, even though it has not been discussed as much as CSR. The biggest funding shift to have affected Indian CSOs has been the steady and sharp decline in funds from foreign foundations. The total private sector funding for the social sector for FY20 was Rs 64,000 crore, compared to Rs 52,000 crore in FY19 (Bain & Company, Dasra, 2021).

However, the volume of money flowing into the CSO space does not tell us anything about the health and autonomy of the sector. It is far more important to understand the nature of the money; nature refers to the conditions surrounding the money. These conditions could be about how the expenditure would be monitored and reported, but they could also be about how and where the money would be spent. The tighter the latter set of conditions, the lesser is the agency and autonomy of CSOs to innovate or respond to ground-level variations.

According to the Bain India Philanthropy Report 2021, international non-profit contributions to India have declined by 30% over the last five years. Over the last decade or so, foreign funds coming to CSOs have declined sharply and CSR funds have risen sharply. While they may have substituted each other dollar for dollar, they are different as chalk and cheese. Foreign funds often came with greater autonomy; CSR funds by nature tend to be extremely defined. This is why we often heard concerns among CSOs over becoming merely implementing agencies or ‘vendors’.

New-age private philanthropies and high net-worth individuals are another rapidly emerging source of funds coming into the social sector. These are different from the older philanthropies in that they either set up their own implementing arms, or pick a specific focus/ problem and then look for partners around it.

The small individual donors probably leave the CSO with the greatest agency. They were also the kind of donors that CSOs depended on traditionally. However, in our research, we found very few instances of CSOs for whom this was a significant part of total fund inflows, even though many seemed to be re-appreciating the value of this source of funding.

There was a time when CSOs generated their own funds, through sales of products (CRY’s greeting cards are the most well-known effort) or services (training and capacity-building programmes). Many spoke of the ways in which these channels were an important path to core autonomy, if not full self-sustenance. However, regulatory changes made about a decade ago put a cap of 20% on CSO revenue that could be earned income, setting back these fledgling efforts at self-reliance.

Implications

Respondents across the spectrum spoke of the implications of the shifts in the funding ecosystem. Some of the themes that came up repeatedly during conversations were:

• A pronounced funding skew towards tangible, ‘hardware’ kind of programmes. There is also a marked skew in thematic areas, with health, education, and skilling being clear favourites.
• There is also a geographical skew, at least as far as CSR funds are concerned. An interesting consequence of the focus on select geographies has been that whereas in the past money used to go where CSOs were located, now CSOs are expected to go where the money is located.
• Increasing projectisation and templatisation of development. There is a push towards standardising approaches, solutions, costing within the social sector reality of regions and communities differing from one another. This is accompanied by shorter time horizons, with agreements often being only for a year.
• We repeatedly heard from respondents that “donors are willing to fund programmes, but not the cost of delivering programmes”. This underfunding, coupled with development work being equated with project delivery, has meant there is hardly any support available towards institution-building. The current set of well-regarded CSOs benefitted from institution-building investments made by an earlier set of philanthropies. Respondents said they feared investments in institution-building for the future are no longer happening.
• The implications of the changing funding portfolio have also been strongly felt in the impact and measurement space. CSR funds in particular, have not only influenced the way impact is defined, but have also led to a culture of constant measurement and reporting, in which CSOs are now investing significant time and resources.
• Social sector funding now involves very little risk-taking. The donor is most often looking for established models, and the spirit of search for solutions irrespective of guaranteed success, now seems absent. This is leading to reduced emphasis on innovation or on areas of work that have lower chances of ‘success’.
• Funding has become specialised, requiring a multiplicity of compliances, most of which have to be filed online. While this may improve filing convenience in the long run, in the transitional period, CSOs have struggled with software glitches, non-responsiveness to queries, and lack of staff with IT expertise. As a result, the last decade or so has seen a rapid rise in the number and salience of intermediaries and aggregators. While there were mixed views on this trend, several respondents felt it was putting greater distance between the actual work on the ground, and those who supported that work.

The Unfolding world of Corporate Social Responsibility

The history of corporate philanthropy in India goes back to pre-Independence times, with the most well-known example being of the Tata Group (the Sir Ratan Tata Trust was founded in 1919, although philanthropy by the Tatas is older than that). Many corporate houses stepped forward to support the independence struggle. M.K. Gandhi’s formulation of ‘trusteeship’ spoke of the responsibility of business towards the larger social good. Gandhi’s influence was crucial in the role that Indian companies came to play in nation-building and socio-economic development in the country (Sharma, 2009, p. 1519) between the 1880s and 1950s.

Approaches

Almost every corporate we interviewed spoke of the need for CSR to be in sync with business priorities, whether in terms of the chosen themes or geographies. Even though this was not the intent of the Act, there is clear expectation of some kind of return to business—whether as goodwill of local communities or strengthening the social licence, or at least through greater media visibility. Rare were examples of corporates giving without expectation of some returns accruing to business. The most commonly articulated reasoning behind seeking an overlap with corporate priorities was that ‘business is not charity’. Some said it was a shift from philanthropic CSR to strategic CSR.

Using CSR to create possibilities of employee volunteering is central to many corporates—informed by the idea of giving not just money, but also expertise; driven by the need to be ‘more than just a funding partner’. While this provides additional skilled human resources for CSOs, the availability of volunteers when needed, and their depth of understanding of issues to be addressed, is less than required.

Most corporates seem to use mixed models for implementation—both directly and in partnership with CSOs. The choice is driven most often by convenience or confidence. We had respondents who had made a deliberate choice to implement only through their own trusts since that offered greater governance assurance and control. However, even corporates who worked exclusively with CSOs did not do so from the perspective of building a larger civil society. We heard no corporate mention the strengthening of civil society as a greater objective.

Most corporates we spoke with felt good about their experience with CSOs, with very few instances of disappointment. Yet, corporates were more likely than any other donor category to speak of ‘the need to build CSO capacities’. Their disappointments were mostly to do with the (slow) pace at which CSOs work, or their openness to adopt new practices.

Having heard from CSOs about the impact corporates were having on their world, we wanted to understand from corporates whether—and in what ways—this coming together with non-profits had impacted them. However, the only thing we heard was about the positive impact that volunteering opportunities have had on their staff, in terms of morale and retention.

While corporates recognise that finding a suitable partner is more than just a due diligence process, most of them still use elaborate legal/audit filters. Most corporates spoke of the difference between a vendor and a partner relationship, the desirability of the latter, and their belief that the trend would gradually move in that direction.

We spoke with our corporate respondents about the shift towards tangible and short-term measures of impact. While expressing commitment for the idea of tangible metrics, several of them felt that there was need to find a balance between the long-term, somewhat intangible idea of impact and the extremely short-term perspective. In fact, the CSR professionals seemed to chafe under the constant pressure to show results as much as their counterparts in the CSO space. As one corporate respondent said in exasperation, “almost every few weeks, I get asked about what’s new in CSR?”

However, we also came across interesting instances of corporates going out of their way to create enabling conditions to help CSOs do better—such as facilitating knowledge exchange among CSOs, providing assurance of long-term and adequate funding support, etc.

A lot of the challenges of this coming together are to do with trust and expectations. For-profit and not-for-profit organisations have traditionally been suspicious of each other, with very little common ground. The Companies Act, 2013 and the mandatory CSR changed that, bringing them together, each for their own reasons. The CSOs came to the table because they needed the money; the corporates came to the table because they needed people/organisations who could deliver development.

The corporates are a completely new kind of donor, one that doesn’t even like to be identified as a ‘donor’, one that has the self-image of a doer. They are also more comfortable in vendor-vendee relationships, supported by backend systems for dealing with vendors. Corporates take a lot of pride in their ‘efficiency’ paradigm, honed over centuries of working in the marketplace. On the other hand, CSOs often come to this partnership expecting the kind of donor they have usually worked with in the past. So the starting points are very dissimilar, but most people we spoke with conveyed optimism that over time, CSR as a coming-together space will evolve.

Impact

The research team attempted to understand how the conversations and practice around ‘impact’ have changed in the last decade. We also asked people about variables that influenced impact. While there were differences in articulation and practice, we found much common ground on both sides in terms of a deeper understanding of impact. However, the practices around impact seemed to leave much to be desired.

The meaning of impact

In terms of what people mean by impact, we heard the following:

• While many respondents felt that most CSR funding does not look at impact but only tracks inputs and outputs, some said that impact is insufficiently conceptualised even within CSOs, and often taken for granted. There is need for a clearer articulation of their theory of change so that people can appreciate what they are attempting.
• Most CSOs look at impact in generational terms; as a process of social change and transformation, which is often measured in terms of intangibles such as the strength of community institutions, improved solidarity, sense of self-worth, etc. However, many felt that the pendulum has now swung to the other extreme where the idea of impact has been reduced to merely providing infrastructure, asset-building, and other tangible targets that are achievable in the short run.
• Along with looking at what is happening within communities, people also pointed to the importance of seeing how the organisation itself, its values and work culture, are getting impacted in the course of work. Organisations may also be missing out on the community’s own perception of impact.
• Finally, given the great emphasis on measurement and ‘doing what can be measured’, several respondents spoke of reports missing out some other interesting aspects of the work, since those were not asked for. Likewise, the adverse or unintended impacts of interventions also need to be looked at.

What drives impact

According to our respondents, these are some key drivers of impact in social interventions:

• A contextualised perspective and approach: Formulating ‘contextualised theories of change’ and moving away from silo approaches to systems approaches appeared as a strong determinant of impact. As one respondent said, “organisations have begun seeing development as a decontextualised service; instead any kind of development intervention needs to be strongly rooted in culture and community.”
• Process view: An understanding of social change as a function of sound processes (the means) and not merely as something that is pursued only at the level of ends. This also requires the ability to adapt as things unfold on the ground.
• Good monitoring processes: Impact needs a comprehensive and nuanced understanding of the problem, a good sense of the intervention to address it, and processes of assessing intermediary outcomes, i.e., a process-oriented measurement system, among other things.
• Investing in people: Impact in the development space has an extremely high correlation with the values and commitment of the people engaged in the work. Investments in field personnel/teams give the best returns in terms of outcomes. This includes conveying a sense of stability, agency, and care to the frontline workers.
• Community participation and involvement: Expectedly, the extent of community involvement emerged as a key factor in strong impact. Assessment of community participation must go beyond just the optics and the mechanics.
• An alignment with organisational vision, passion, and expertise: This point was emphasised by several respondents, especially those from civil society backgrounds. Congruence of the initiative with the implementing organisation’s vision and passion was considered vital. Interestingly, this was not emphasised as strongly by corporates.
• Organisational stability and stamina: Having a strong and stable implementing partner is crucial. People spoke of organisations with strong roots and the self-confidence to give honest feedback even when things are not going well—ones that have strong self-accountability, and those with the stamina for the long term and the tenacity to keep going deeper.
• Long term funding commitments: The implementation period must be long enough; long-term projects generally deliver better impact. Long-term work requires long-term funding. Funding organisations, instead of projects, was mentioned as a better approach from the impact point of view.
• Regulation and enablement: Many respondents mentioned an enabling environment of greater trust. The government contributes hugely to the enabling (or otherwise) environment but equally, donors/corporates can help build conducive conditions at least within their micro-contexts.

Governance

• An analysis of the Edelman Trust survey over the decades has shown that CSOs have been displaced by businesses as the most trusted institutions globally. The rising trust in business has also been accompanied by an increased expectation from business leaders to fill the void left by government, as opposed to CSOs or civil society leaders. In India, since the beginning of the survey (a decade ago), businesses have enjoyed more trust than CSOs. This decade has also been marked by a tightening of the regulatory environment within which CSOs function.

The perception of the poorly governed CSO

The burden on CSOs to demonstrate accountability and transparency has increased over time. In 2013, the Delhi High Court branded 99% of CSOs as “fraud, money-making devices” (Nair, 2013). However, the narrative of the ‘untrustworthy CSO’ does not appear grounded in reality. There are hardly any statistics or evidence to back the impression of CSOs as untrustworthy or poorly governed.

Even during our conversations, with both CSOs and corporates, no one had evidence to bear out the prevailing perception. Many CSO leaders strongly protested this formulation of a weakly governed sector. In a survey conducted by Ernst and Young among 100 corporations engaged in CSR, only 8% of respondents were aware that they had received complaints regarding fictitious expenditure incurred during the execution of CSR projects.

The everyday discourse around CSOs has come to be laced with questions of accountability and transparency, without much evidence of wrongdoing. During discussions, most CSO respondents felt strongly that while there is always scope for improvement, the current negative narrative is both unfair and deliberate.

Relooking at the premises

The goal of ‘good’ governance is to ensure that the organisation stays on track in terms of its vision and values. All ideas of ‘good’ governance that came through in the interviews were rooted in democratic ideals of decision-making, and the necessity of devolving the understanding of good governance away from being board-centric. Self-regulation is one of the most important ways for CSOs to improve accountability while retaining their autonomy and core characteristics. Hence, strengthening the idea of ‘mutual self-regulation’ in CSOs ought to be the starting point for strengthening ‘good’ governance.

People spoke strongly of the inaccurate data on the true size of the sector and the lack of segmentation as being major contributors to the misperceptions about the sector. As mentioned earlier, the list of registered societies, trusts, charities, etc. includes a wide range of organisations such as prayer committees, festival committees, resident welfare associations, or sports clubs, only a handful of which are engaged in the actual work of social transformation, but which get clubbed together in the framing of public perception.

Most CSO respondents who protested the label of ‘inadequately governed sector’ argued that governance frameworks cannot be replicated across sectors. There is a need to appreciate the CSO context and understand how they govern themselves, and to root any new ideas on governance within these realities. Most CSOs in the country are medium- to small-sized, and an insistence on setting up elaborate governance systems further strains their scarce resources. In the words of one of our respondents, “most CSOs are MSME-sized, and their governance should be compared to MSMEs, and not the top 1,000 corporates”.

CSOs seem to be stuck in an awkward situation where on the one hand, their systems are being questioned for not being robust enough and on the other, the resources for building new, more elaborate systems are either depleting or not forthcoming. Most CSO respondents felt that solutions to the challenges of the social sector do not have to originate from the business world, rather, they must be located within their context. Imposing business models on CSOs has led to a new set of problems, including procedural and reporting overload.

Finally, almost everyone acknowledged the importance and indispensability of trust in these relationships. Many felt that the emergence of intermediary organisations can also be traced in large measure to the absence of trust.

We have also looked into the processes followed by corporates/donors to look for well-governed CSOs, and found little difference, in terms of outcome, between those having elaborate due diligence and assessments in place, and those using a more personalised and qualitative approach.

Disruptors

The long spell of COVID-19 and changes made to the FCRA in September 2020 impacted all our conversations—more importantly, they severely affected organisations in real time. Hence, while these were not part of our original research, we did spend time discussing their fallout with all our respondents.

The coming together

Few had anticipated the significance of the introduction of Corporate Social Responsibility as a mandate in 2013. For better or for worse, this has created a churn. It has thrown together people and organisations who had hardly known each other before. It has changed the language. It has changed practices. It has changed perceptions. While challenges abound, it is indeed too early to say much apart from the fact that this dynamic needs to be watched and understood, and hopefully influenced towards a better equilibrium.

Approaches:

We share here some of the salient aspects of this coming together.

1) As experienced by the CSOs

• Short-term, target-focused: This is something we heard repeatedly—of development (or at least funding) perspectives having become target-driven and short-term, shifting focus away from process issues, from harder and longer-term issues. We heard about the loss of flexibility leading to loss of innovation, and of the “projectification of development”. We heard about horizon mismatch—one respondent spoke of tree-planting projects with just a nine-month timeline. Also, most reporting now is on outputs, very little on impact: “overall a much shallower approach”.
• Rising ‘hyper-professionalism’ and ‘specialisation’: The ‘professionalisation’ of the sector that began in the 1980s has gone to the extreme of “hyper-professionalism”, often sidelining other ways of working. There is an increasing emphasis on focused thematic projects, as opposed to integrated approaches.
• Shifts in geographies and themes: CSOs spoke of experiencing both these shifts and regretted that neglected geographies have remained neglected under CSR as well. Also regretted was the overemphasis on certain themes (education, health) and the sidelining of others (forestry, community institutions, rights-based work).
• Reporting and compliance overload: These now take up a very large part of the CSO mindspace, effort-space and time-space, without clearly evidenced value-add. One CSO mentioned submitting 80 reports to different donors over a period of six months. Micro-supervision of CSO staff is becoming more common, especially post-COVID. Donors insist on their own reporting systems, without respecting existing organisational systems.
• Rapid loss of institutional biodiversity: Almost everyone we spoke to was worried about the rapidly diminishing biodiversity of the CSO sector—the smaller, the provincial NGOs fading out, leaving behind a similar type of Westernized organisations.
• CSOs as appendages: CSOs worried about the sector being driven by donors or corporates, and of losing their autonomy and the ability to ‘speak truth to power’. Some said that CSOs themselves have ceased to ask fundamental questions, and become more of service delivery agents. Others felt this was part of a larger shift towards top-down control. Another sentiment was that corporates tend to project CSO work as their own just because they give the money.
• The rise of the intermediaries: While intermediaries and aggregators serve a function, many respondents from both non-profits and for-profits flagged this as a worrying shift, with one respondent calling them ‘extraordinary middlemen’.
• Changing internal cultures: People who can speak the corporate lingo are now valued more even within CSOs. Staff members are becoming more silo-ised into their ‘projects’. One respondent mentioned having to let go, in the face of pressure to meet targets, of conversations dealing with gender-based violence in the communities. Another spoke of the neglect of ‘community-centred approach to development’.

2) As experienced by the corporates

• Vendors or partners: Most corporates are used to working with vendors, with no category of ‘partners’. The systems and processes lead towards reducing CSOs to vendors.
• Why the increased emphasis on compliances and monitoring: Some corporates felt that given the very high demands for accountability from company boards (including for CSR), it was to be expected that companies would pass those expectations onto the CSOs, and take a more cautious approach.
• Corporate value-add: Several corporate respondents were of the view that they actually help CSOs with systems/processes, leading to better governance and impact assessment.
• The CSO value-add: Many corporate respondents spoke of the value of volunteering opportunities for employees created through CSR. One respondent said her staff had become more patient as a result. Some spoke about a gradual recognition in corporate offices of the real pace of development work.
• CSOs lack flexibility, don’t collaborate with each other: Some corporates find that CSOs are rigid and set in their ways, unwilling to learn and change. Several wondered why CSOs have not come together to create an industry-based platform or body like FICCI/CII.
• The horizon question: Almost all corporates acknowledge the need for a longer-term horizon, while recognising that much of CSR is short-term. Many try in their own ways to make these engagements longer-term.
• Navigating the power imbalances: Some respondents were forthright in saying that the power imbalance is a reality, but CSOs needed to find ways to deal with that.
• CSO overpromise: Some respondents felt that CSOs also need to be transparent and not overpromise.
• CSO exposure to business risks: An interesting comment from one of the respondents was that ‘in a way, the CSOs are also now not insulated from market risks’. CSOs’ budgetary ups and downs are now linked to fluctuations in the market. Another respondent advised CSOs to not think of CSR as a ‘permanent’ source of funding.
• Nature of CSR: while some corporates said CSR was gradually moving from being ‘spend driven’ to ‘value driven’, others felt it had become much more transactional. CSR prior to the coming of the Act was driven more by a philosophy; the primary driver now is compliance.

On balance: Suggestions and conclusion

• Overall, a win-win: The CSR Act proved almost providential for Indian CSOs, coming just as funding from other sources began to fall sharply. Likewise, the existence of strong CSOs in India helped corporates to rapidly meet the 2% spend target and show quick outcomes.
• Alignment: The expectation that CSR must add in some way to the company’s credibility, goodwill, and social licence is mostly the norm. CSR departments function between “business interests and societal purpose”, with the tilt often towards the former.
• Trust and respect: Despite seven years of working together, the underlying trust deficit remains strong. Issues of insufficient mutual respect and recognition too came up repeatedly. But there were also many cases of deep friendships and alliances being formed across these borders.
• The nature of relationship: Most corporates (and philanthropists) are driven by their own worldview or corporate priorities. They tend to specify the thematic area, geography, sometimes even the outcome, and then look for partners who will deliver on those. With notable exceptions, the degree of specificity with corporates tends to be much higher than with other kinds of donors.
• Nature of development outcomes: The jury seems to be still out on whether we are witnessing better development outcomes due to the coming together, but many felt there was a loss of depth and complexity in the discourse. The formulations have become rather ‘simplistic’.
• Culture-understanding osmosis: More CSOs spoke of corporate influence on discourse and practice than the other way round. The score on improved understanding of the other—not an inconsequential outcome—seems somewhat low at this point. However, several CSOs spoke of the need to invest in dialogue, and to build platforms to facilitate this.
• Bridging the gaps: One important area of disconnect seems to be around the metrics. As one respondent said, “The answer may not be to move away from metrics, but to create another set of metrics, even if those are intangible”. Improved conversation is also needed around the degree to which reporting, audit, bureaucratic processes are reasonable. Currently, CSR seems to be heading towards a procedural overload.
• Changing profile of the sector: Apart from intermediaries and aggregators that have come up or grown in response to the corporate need to de-risk and delegate, there is the emergence of corporate (and UHNI) foundations as a new kind of CSO, with often high visibility.

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Evidence from existing literature indicates that children, including adolescents, from disadvantaged sections of the society demonstrate adverse health outcomes, ceteris paribus. This, in turn, prevents them from achieving their full economic potential as adults, essentially creating an inter-generational vicious cycle between poor health outcomes and poor access to resources. Using a novel, nationally representative dataset (the Teen Age Girls [TAG] survey) that collected information from adolescent girls (aged 13-19 years) in India, this first-of-its-kind study attempts to explore the link between property rights and health outcomes. We capture information on property rights through one proxy indicator – housing type; health outcomes are captured using age-standardised height and BMI measures. In India, where the right to property and housing are not recognised as fundamental rights, the poor incrementally gain security of tenure, moving from a continuum of insecure housing to full titles. Research from India and other parts of the world shows that a movement towards greater tenure security has been associated with home improvements, and thus type of housing is a strong indicator of security of tenure and therefore property rights, as viewed within a continuum of rights gained incrementally. Our study finds that adolescent girls from households with lower quality houses and fewer household goods fare poorly on health outcome indicators. This creates a space and need for designing and implementing sustainable policy measures that would eventually uplift the overall quality of life of India’s 80 million adolescent girls.

The Property Rights Research Consortium (PRRC), supported by Omidyar Network India, brings together top research institutions undertaking research on various aspects of property rights, land governance and housing issues in India. It aims to develop a multidimensional understanding of property rights through assessing and testing the broad agreement that property rights are vital to development. The larger purpose is to enable evidence- based solutions for securing land, housing and property rights for all Indians. As part of the PRRC, the Centre for Social and Economic Progress examines health as one of the four themes it analyses,[1] focusing on property rights as a pathway to social mobility. The initiative has contributed to the research on property rights, by examining the multidimensional impacts of property rights in India on mobility, health, real estate markets, gender, etc.[2]

Our work focuses on property rights and health in India. There is substantial research on health disparities amongst poor households, and those belonging to the disadvantaged, vulnerable and marginalised sections of the society, in terms of socio-economic profile. The first part reviews literature on the state of property rights in India and presents an analysis of issues pertaining to security of tenure in India. It also examines literature that links tenure security and property rights with type of housing and home improvements both in India and globally. Drawing from this research, this paper examines available data on type of housing as a strong indicator of security of tenure and property rights. We also study literature on the relations between indicators of socio- economic status and health outcomes, among children in particular. The third part uses data from Project Nanhi Kali, a nationally representative dataset that collected information from adolescent girls (13-19 years) in 2016-17 in India, to examine the link between property rights and health outcomes. The fourth and concluding part of this research examines the findings and proposes new areas of research that can inform us better about how property rights influence health outcomes of adolescent girls.

I. Property rights in India

Though the Indian constitution affirmed the right to property as a fundamental right, it was later removed in 1978 through an amendment.[3] India does not recognise the right to housing, despite having ratified the International Covenant on Economic, Social and Cultural Rights in 1979 (Housing and Land Rights Network (HLRN), 2016, p. 1).[4] The Indian state, therefore, possesses enormous power to acquire land, even of those who possess full legal titles. The poor who cannot afford land/ housing and occupy public or private land that they do not possess titles to, are therefore more vulnerable to lose their homes through forced evictions. Government urban policies and programmes that focus on ‘slum free cities’, further increase this risk, as poor habitations are not only viewed as eyesores, but are also considered threats to public health and morality. Evictions that are normalised as essential to development have deep impacts on the urban poor who are vulnerable to eviction and live life with a high sense of insecurity and impermanence (Bhan, 2009; Bhan, Goswami, and Revi, 2013; Ghertner, 2008; Ramanathan, 1996, 2005, 2006).

There is no official data on forced evictions in India. The Housing and Land Rights Network (HLRN), a Delhi based NGO has been collecting some data on forced evictions since 2017 through the National Eviction and Displacement Observatory (NEDO), a network of partner organisations in India. This data is not exhaustive and is based on the limited number of organisations within the NEDO and their access to information. Based on this data, the HLRN reported 213 evictions in 2017, with 53,700 homes destroyed and affecting 2,60,000 people (Chaudhry et al., 2018).[5] In 2018, it reported 218 evictions, with 41,700 homes destroyed and rendering 2,02,000 people homeless (Chaudhry et al., 2019).[6] During both these years, the majority of those evicted were for beautification and development projects — 77 percent in 2017 and 73 percent in 2018; beautification alone accounted for the largest share of evictions — 47 percent of homes destroyed in 2017 and 47 percent of affected persons in 2018 were due to this reason. In its 2018 report, HLRN’s data also revealed that 11.3 million Indians are vulnerable to eviction and potential displacement. Again, this is not an exhaustive figure and is limited by access to data.

Uncertainty about land and property rights forces the poor to postpone their plans in perpetuity (Thara, forthcoming). They refrain from planning for their future and do not make investments to improve their quality of housing and productivity of land, in the fear that an eviction would wipe out their investments. Lack of security propels people to spend time protecting their land/housing (Feyertag et al., 2020) and also in political activities to gain the support of local politicians, thus taking away time from productive work (Thara, forthcoming), or from other essential activities such as childcare (Feyertag et al., 2020). People are also physically vulnerable to violence and injury, as can be seen in India in the many ‘slum fires’ that are often suspected to have been initiated to evict the poor (Chaudhary et al., 2019, pp. 30-31),[7] especially if the groups concerned have little political support (Feyertag et al., 2020; Thara, forthcoming).

The Indian state does provide some housing for the poor and economically weaker sections, but this is largely inadequate and does not address to the massive demand for affordable housing. The Report of the Technical Group on Urban Housing Shortage (TG-12) (2012-2017) estimated the urban housing shortage in India at 18.78 million houses, with 99 percent of the demand from economically weaker sections (EWS) and lower-income groups (LIG).[8] The Working Group on Rural Housing for the 12th Five-year plan estimated rural housing shortage at 43.13 million units.[9] While there is state-wise data on the housing provided under various programs, there is no national-level data on the total housing provided in India each year to the EWS and LIG sections.[10] A good part of the housing provided by the state is often used to displace the poor, offering ‘rehabilitation housing’ in exchange for vacating land within cities for development or beautification projects (Thara, forthcoming). This housing is provided not as a right but as a welfare measure, under the Directive Principles of State Policy (Part IV of the Constitution) which provides for a set of non-enforceable state responsibilities.^[11]

II. Tenure security in India

While the poor often live on land they do not own, and do not possess full titles to property, they enjoy varying levels of tenure security.

Tenure security has been defined via multiple modes over the years. Payne (1996, p. 3) defines land tenure as ‘the mode by which land is held or owned, or the set of relationships among people concerning the use of land and its products’, within these frameworks, land tenure relies on the social recognition of use rights vis-à-vis property rights which are state or legally-recognised interests in land or property. (Payne and Durrand-Lasserve, 2012) Fischer (1995) also viewed land tenure as ‘a social relation involving a complex set of rules that governs land use and land ownership’, noting that there is heterogeneity in the access to the ‘bundle of rights’.

Tenure security is not solely determined by law, and therefore, notions of legal or illegal, formal or informal status, do not apply. It is ‘a relative concept and a matter of perception as well as law’ (Payne, Durrand- Lasserve, & Rakodi, 2009). The poor transition through different stages of tenure security from insecure tenure (with no rights whatsoever and a very high risk of forced eviction) to de-facto rights – i.e., rights in fact (with a perception of security) and finally, progress to achieve de-jure rights – i.e., legal rights of various types, including right to reside, possession certificates, allotment of homes and property titles. Slums and settlements are classified into notified or non-notified slums. Those living in non-notified slums live with insecure tenure, while notified slums enjoy a quasi-legal status, as they are recognised by the state and are also often supplied with public services. Those living in non-notified slums may begin with insecure tenure, but can transition to obtaining de-facto rights through long residence; bigger size of settlement which allows them to gain political support through vote banking; through access to welfare benefits (access to BPL/APL cards); access to public services and infrastructure from the state and/or access to voter identity cards or payment of property tax. Apart from the duration of residence and size of the settlement, the strength of de-facto tenure security also depends on how many people possess such documents in a given slum (Mahadevia, 2010). Access to services such as water, electricity, sanitation and toilets is perceived as an indication of the state’s acceptance of the continued existence of settlements, thus providing de-facto tenure (Paul Strassmann, 1984; Strassmann, 1980).

As Nakamura points out, the strength of political support or lack of it can also determine whether or not a settlement enjoys a weak or strong de-facto tenure (Nakamura, 2014). De-facto tenure is obtained through many factors rather than a single act of the state, and thus results in improved quality of life and social protection. Those having de-facto tenure have a greater perception of secure tenure in comparison with those who possess insecure tenure. Slums that are new, small in size, and/or located on land reserved for public purposes, may not be able to obtain de-facto rights. Those living in de-facto tenure security may enjoy either weak or strong de-facto tenure, depending on the type of land they inhabit and the form of de-facto tenure security they have obtained. (Paul Strassmann, 1984; Strassmann, 1980).

De-facto rights are not only socially recognised, but also recognised by the state. Possession or occupation of land is often considered by the state as providing certain rights to the occupier, based on the duration of possession. In governing land within cities, the Indian state has tended to recognise these rights, often incorporating occupation as a consideration in land planning. Urban sociologists call this “occupancy urbanism” (Benjamin, 2008). Slums and settlements with de-facto rights are recognised by the state as possessing certain rights, especially if they have existed for long periods of time, as this is also legally recognised under the law of adverse possession. The first schedule to the Indian Limitation Act, 1963, provides for a period of 12 years for property owners to approach a court of law to reclaim property taken over through illegal possession against the will of the owner. When the land in question belongs to the state, the prescribed period is 30 years.[12] This law is subject to interpretation by courts, which demand proof of possession and weigh evidence to establish whether the possession was ‘adverse’ to the owner, i.e., with the knowledge and without the consent of the owner. However, the fact that possession is recognised as creating legal rights perforates into everyday law and governance. This can be observed not only in the manner in which the state deals with slums and settlements, but also in its policies on legalising illegal occupation of land that aim to ‘regularise’ illegal constructions and occupations of land (Benjamin & Raman, 2011). This facile conversion of illegal to legal (albeit subject to certain rules and regulations) facilitated by the exchange of money for a change in papers, forces us to think of property law and rights in a far more fluid sense in the Indian context, and not in a rigid sense of either having or not having rights to property. Furthermore, the success of poor groups in asserting claims to land/property is dependent on political configurations at different levels (local, state and national). Therefore, de-facto rights that provide different levels of tenure security are just as important in the Indian context as de-jure or legal rights to property.

De-jure rights are gained when the state confers legal recognition of such housing through slum declaration, certificates of rights/possession certificates, the provision of rehabilitation housing, etc. Just as there are varying grades of de-facto security (weak and strong), de-jure status can be further broken down into quasi-legal status of various types, beginning with slum notification, allotment of slum rehabilitation housing/sites and finally transfer of full property titles. Legalisation of land titles involves amending land laws pertaining to ownership, use and transfer (Mahadevia, 2010). Payne et al. observe that people who benefit from titling programs often seem to have enjoyed ‘a certain level of de-facto tenure security’ in the past (Payne et al., 2009). He suggests that “a starting point maybe to regard every step along the continuum from complete illegality to formal tenure and property rights as a move in the right direction, to be made on an incremental basis.” He also notes that the sharp distinction between formal and informal may be misleading. The notion that all formal or legal land property holders conform to all laws, rules and regulations, is erroneous as the degree of conformity may vary (Payne, 1996).

This progression from one level of tenure to another, normally takes place due to the struggles of the poor who incrementally obtain rights that are manifested through their access to basic services such as water, sanitation and electricity (Das, 2011). Therefore, tenure security is intricately interwoven with access to services, with progressively higher tenure security meaning better access to services. Sociologists have been advocating for policies to provide tenure security to poor households, in this incremental manner, claiming that it would help the poor retain their housing, while an outright provision of property rights may result in them losing their homes to those who can afford to buy them out (Payne et al., 2009). “Secure tenure is the right of individuals and groups to effective protection by the State against forced evictions”, while insecure tenure contains the risk of forced eviction (Durrand-Lasserve & Selod, 2007).[13] Mahadevia (2010) argues that it is important to distinguish between use rights and property. She argues that “the latter is, therefore, a market paradigm of land holding, whereas the former is a welfare approach wherein the right to shelter is extended”. Secure tenure guaranteed by legal rights can therefore accomplish welfare objectives (ibid.).

Varley (1987) points out that while providing legal tenure can benefit urban poor settlements, legalisation alone is not sufficient to enable improvement in the lives of the poor. Providing titles without providing access to infrastructure and services, and other upgrading measures, would not serve the purpose that tenure security is meant to achieve.

III. Tenure security and quality of housing

Providing security of tenure results intangible consequences in the lives of the poor. With stronger tenure, the poor enjoy better access to basic services, a better standard of life and improved economic status (Mahadevia, 2010). Secure tenure alone (Gelder, 2009; Payne 2001) and tenure with income (Payne, 1996) can motivate the poor to invest in improving their homes, which, in turn, can have a range of other positive outcomes, making titling unnecessary. Perceptions of tenure security are important as they influence behaviour and the decisions people make, which have social, economic, and environmental consequences. The Prindex, a research group, has come out with a global assessment of perceived tenure surety for 140 countries. This comparative report collects perceptions data across diverse land governance systems, with differing levels of security tied to legal titles and different sources of property rights, including traditional systems. As per the report, 21 percent of Indians feel insecure about their main property, while 66 percent feel secure. The report further reveals that 22 percent feel insecure about all their properties, while 64 percent feel secure.

In India, the poor live in homes that can be broadly categorised into three types: kutcha housing, pucca housing and semi-pucca housing. Kutcha housing is makeshift housing constructed with materials that last temporarily, for example, mud walls, thatched roofs, or plastic-covered roofs, etc. Pucca housing is built with materials that last, brick and mortar housing with concrete roof. Semi-pucca housing are structures that are built with both permanent and temporary materials. For example, brick and mortar structures with thatched, asbestos, or plastic sheet roofs or with unfinished floors.[14] According to the National Family Health Survey 4 conducted in 2015-16, 0.9 percent of the urban population and 8.1 percent of the rural population live in kutcha housing. Around 13 percent of the urban population and 46.9 percent of the rural population live in semi-pucca housing. Almost 85 percent of the urban population and only 41.2 percent of the rural population lives in pucca housing. The following section of the paper examines evidence both from India and as well as from other parts of the world, which establishes that tenure security (de-facto and de-jure including property titles) motivates poor households to improve their homes.

In Ahmedabad, the Slum Networking Programme (SNP) covered 60 slums and 13,000 households and provided physical infrastructure such as water, electricity and toilets, roads, street lighting and solid waste management; a ‘no demolition guarantee’ of ten years and community-based programmes (including community health centres). Physical infrastructure was provided on an 80-20 basis, with households required to bear 20 percent of the cost. To understand the effects of varying levels of tenure security, a study of six slums under the SNP was conducted in Vasna ward in the south-west part of Ahmedabad, Gujarat, with a sample of 553 households of a total 3,514 households. The six slums were segregated on the basis of tenure into three categories: ‘strong de-facto tenure, weak de-facto tenure and insecure tenure’. This research revealed that settlements with higher tenure security have higher numbers of pucca homes. While 54 percent of households in the insecure tenure category lived in kutcha, or temporary houses, it fell to 39 percent in settlements with weak de-facto tenure and 32 percent in settlements with strong de-facto tenure. While 42 percent of households with strong de-facto tenure lived in pucca housing, it fell to 39 percent in weak de-facto tenure, and only 24 percent in insecure tenure situations (Mahadevia, 2010b). These findings are significant to our study as they reveal that pucca homes have a higher probability of more secure tenure, while kutcha homes have a greater probability of less secure tenure. This is despite the fact that all these settlements had benefitted under the SNP program (Mahadevia, 2010b).

While the six slums with varying tenure security status studied by Mahadevia benefitted from this program, differences in access to both infrastructure and services offered under the SNP persisted on the lines of tenure security. The most pronounced differences were noted in terms of access to water. In slums with strong de-facto tenure, 90 percent of households had individual water supply and only four percent depended on common public taps; in settlements with weak de-facto tenure, 29 percent of households had access to individual water connections and 18 percent depended on public water taps; and with insecure tenure, only 19 percent had individual water taps and 52 percent depended on common public taps. In strong de-facto tenure settlements, all households had access to toilets and 94 percent had access to an individual toilet in their household; in weak de-facto tenure settlements, 86 percent had access to individual toilets, one percent depended on community toilets and five percent did not have access to toilets; and in insecure tenure situations, 69 percent had access to individual toilets, 18 percent used community toilets and 2 percent had no access to toilet (Mahadevia, 2010b). As this data reveals, a greater number of poor households with insecure tenure and weak de-facto tenure did not opt to invest 20 percent in physical infrastructure, despite the government’s 10-year no eviction guarantee. Tenure security, which includes access to basic services, is thus crucial to motivate poor households to invest in their homes and improve from kutcha to pucca structures.

Quality of housing improves when settlements obtain de- jure status even if this is a quasi-legal status. Nakamura, for instance, in his research in Pune, shows that slum residents improve their homes, especially once their stay has exceeded 10 years. This study shows that slum declaration increases the chances of households’ using better materials in constructing their homes by 47 percent and adding a second floor by 78 percent (Nakamura, 2014). It is therefore clear that type of housing is a strong indicator of property rights in the broader sense of the term, including security of tenure as discussed here.

Studies from other parts of the globe also confirm the link between secure tenure and home improvements. In a study of 296 households in squatter settlements in Cartagena, Colombia, Strassman examined home improvements across different population groups. He found that both tenure and access to water encourage owner-occupants to expand and improve their homes (Strassmann, 1980). Thus tenure security or property titles cannot be considered in isolation from access to basic services. In another study conducted in Lima, Peru, Strassman studied 506 households in two impoverished urban neighbourhoods – Popular Urbanisation and Pueblos Jovenes – to compare home improvements by owner- occupants. He suggests that home improvements were motivated more by access to services than any other factor (Strassmann, 1984).

These studies show that providing property rights alone without access to services, cannot motivate home improvements, confirming our definition of property rights as including access to services and basic infrastructure.

Field, in her study of a nation-wide titling program in Peru, found a 68 percent increase in home renovation within four years of titling. (Field, 2005).

Jimenez (1983), in a study of a squatter legalisation program in Tondo, Manila (between 1975 and 1981), also confirmed a similar effect of property rights on home improvement. This legalisation program affected 27,500 households (180,000 individuals) living in 16,500 homes located on 137 hectares of urban government-owned land in Manila’s port area. The project included the provision of individual water connections, road access, sewerage systems, and support for community and health facilities. It rationalised the land tenure system in the area allowing residents the right to buy a lot in the area at a highly subsidised price. Homes were re-blocked minimising dislocation while rearranging homes to conform to regularised lot lines so each home would have access to a communal roadway or footpath and to the main water and sewer lines. Within three months of re-blocking, overall housing quality in Tondo increased by 30 percent to 44 percent. The monetary value of the absolute difference in housing quality before and after re-blocking ranged from about 4,200 pesos to over 6,200 pesos in 1978 (approximately, U.S. $600 to $886 at the time of the study). In comparison to other estimates of changes in the average values of housing in both developing and developed countries, Jimenez concluded that a significant portion of the changes measured in Tondo must be project-induced. Even in the absence of a formal and effective mortgage market, the habitants were able to generate enough resources to make substantial investments in their homes, with the author concluding that the riskiness of investments in homes was lowered by the provision of tenure.

Porio & Crisol (2004) found that residents with tenure security or a promise of titles invested more in improving their homes. Regularised (with de jure rights) homes invested substantially both in home and land while the un-regularised (with de facto rights) improved their homes. Improvement in homes included using more durable building materials such as cement, iron and wood to strengthen homes; while land improvement included fencing of plots with iron grills and planting ornamental plants and fruit-bearing trees.

Examining the impacts of land titling programs such as the World Bank’s Land Administration Program on tenure security and housing consolidation, Reerink and Gelder surveyed 340 households in seven kampongs in Bandung, Indonesia.[15] Housing consolidation was measured on the basis of a composite score representing quality of the floor, the walls, and roof. The sample consisted of 100 titled households; 95 semi-formal tenure households (with traditional ownership rights under adat) and 145 households with informal tenure (squatters on public/ private land). Data was collected from 50 low-income households across seven kampongs. The study found that those ‘with formal tenure live in significantly more consolidated dwellings than informal dwellers’, but found no difference between formal and semi-formal dwellers. Though titling contributed to housing consolidation’, its impact was found marginal. (Reerink & van Gelder, 2010).

Durrand-Lasserve and Selod (2007) argue that “improvements in home environment can have indirect beneficial effects on health of household members.” There are a few studies on the impacts of property rights on health. In Mahadevia (2010b), health outcomes were recorded in one of the six slums chosen for the study. Apart from an improvement in living conditions, improvements in health, education, income, employment status and asset ownership, were also observed. (Mahadevia 2010b).[16] Providing tenure along with infrastructure and services clearly resulted in improved health outcomes, as evident from this study.

Galiani and Schargrodsky (2004) in their study in Buenos Aires, Argentina, have examined the impacts of legal property titles on child health and education. Their study shows, that children living in titled property had better Weight- for-Height scores, lower teenage pregnancy rates, and lower school repetition grades than children living on land without titles. Field (2003), in a study of a Peruvian urban titling programme, finds that providing legal titles resulted in a 22 percent decrease in fertility. She attributes this to improved “bargaining power of women in fertility decisions” due to titling, in addition to “a decrease in the ‘value’ of children since they are no longer needed to secure informal ownership rights or claims to community resources”, and are less “needed for their parents’ old age subsistence”. In the next section, we discuss the link between socio-economic factors and health outcomes.

IV. Socio-economic status and health outcomes

Literature in social sciences has demonstrated a continued interest in SES, especially in demography- related studies. However, there has not been any conclusive evidence on what it definitively represents (Bradley and Corwyn, 2002). It is  considered to include a comprehensive list of demographic and economic variables, including but not limited to, caste, religion, occupation, education, income, family size and household composition, parental involvement and education, ownership of a set of assets, and access to facilities or services; some studies also extend the scope of the definition to include parameters like neighborhood and school influences. Further, globally, SES is found to have strong links to developmental outcomes such as health, education and cognitive outcomes. In this research, we refer to SES as a combined measure to represent demographic, economic and social status for a household. The variables considered are discussed in the following sections of this paper.

A number of studies have documented how asset ownership affects health outcomes among children. Simandan (2018) points out that the “subjective experience of social class mediates widely differentiated outcomes for the mental and physical health of upper- class individuals”. Those belonging to the lower classes have fewer resources and thus experience uncertainty and worse outcomes, whereas, the upper-class has greater financial, social and intellectual resources at their disposal, allowing them to have control over their lives (Simandan, 2018). Asset ownership of households determines the household’s SES and, in some sense, can be understood as a measure of wealth. A review of studies were undertaken to determine the relationship between household asset ownership and developmental outcomes of children—undernutrition, access to healthcare services, educational outcomes, schooling and child labour— concluded that asset-building initiatives are a catalyst to enhancing household well-being in developing countries (Chowa et al., 2010).

Boyle et al. (2009) suggest that people’s lack of ability to move upward in the social class system amplifies health inequalities for a household over time and for all subsequent generations. They claim that “healthy are more likely to experience upward social mobility, and those who are less healthy tend to move down the social hierarchy, widening the health gap between higher and lower social classes” (Boyle et al. 2009 pp??). Therefore, children born in disadvantaged households inherit this inequality. Consequently, large inequities in health and health services persist across states, rural and urban areas, and within communities in India (Baru et al., 2010). A community randomised control trial from Zimbabwe has also shown the positive influence of household asset ownership on the well-being of orphaned and vulnerable children (Crea et al., 2012).

In Tanzania, Kafle and Joliffe (2015) use three waves of the National Panel Survey to establish a causal relationship between asset ownership on child health and educational performance. They find that the effect on educational outcomes is asset-specific. Ownership of agricultural assets was found to have an adverse effect on educational outcomes of children.

Another study from Tanzania (Mwageni et al., 2014) looked at SES and health inequalities in rural Tanzania using the Rufiji Demographic Surveillance System (DSS) to find significant gradients in access to assets and health inequalities—infant mortality, under-five mortality, mosquito net ownership—across all wealth quintiles. In studying socioeconomic inequities in health in Tanzania, Schellenberg et al. (2003) found that care-seeking behaviour for children, indicated by child’s illness episode, is worse in poorer families—based on source of income, household assets and the household head’s educational status—than among rich families. Wu et al. (2018) concluded that young adults with more assets and positive net worth have a higher probability of achieving better health outcomes.

Social class health inequalities data of the Office for National Statistics’ Longitudinal Study for England and Wales suggested that social mobility constraints health inequalities (Boyle et al., 2009). Case and Paxson (2006) demonstrate how income inequality is associated with poor child health indicators at birth and this disparity tends to grow more pronounced as children grow older. They show that children from low-income families are more likely to have serious health problems, and these health issues limit children’s economic potential as young adults. While on the one hand, children from the economically weaker section suffer from serious health problems compared to those better off, on the other hand, poorer children fare worse than wealthier children who have the same health concerns. Poor children have access to less and low-quality medical care since their families are ill-equipped to manage their problems, thus worsening their condition. They concluded that improving the physical conditions of children in poor health would lead to their improved economic circumstances later in their lives.

Using the NFHS (1, 2 and 3), Chalasani (2012) provide evidence of wealth-based inequalities in the Indian context. Wealth was determined based on ownership of 13 household assets, including dwelling characteristics. The results indicated that with India’s overall economic growth between 1990 and late 2000s, mortality inequality decreased only in urban areas, although malnutrition increased in rural as well as urban areas.

To understand how household wealth affects health outcomes among children, Bhandari et al. (2002) also observed that children from the affluent section of the society – residing in south Delhi and having socioeconomic characteristics similar to those living in developed countries – had anthropometric indicators closer to the WHO reference range, or are ‘better off’. In the local context, these residents can be considered an outlier towards the higher end of the spectrum.

In India, the literature on caste and wealth status has helped identify and document the disparities that exist across various sections of the society. Coffey et al. (2019) studied the disparity in height of infants across four population groups — Scheduled Caste (SC), Scheduled Tribe (ST), Other Backward Caste (OBC) and General — in rural India. Using decomposition analysis, their paper suggests that differences in children’s height — a crucial indicator of health and future success — can be attributed to differences in the SES of these four groups of the population. They find that socio-economic differences—based on household floor type, mother’s education, household electricity, type of toilet and ownership of phone, radio, TV, refrigerator, bicycle, motorcycle, car and land—can explain the gap in height (lower) among ST children, but not among SC and OBC children. The findings of their study are a departure from research of other population groups where population segregation or the practice of apartheid have been found to be negatively associated with health. In another study of three waves of India’s NFHS (1, 2 and 3), researchers attempted to determine how caste influences delivery of health services based on under-5 mortality and health consumption expenditure (Baru et al., 2010). It concluded that the socially marginalised in India get the least access to preventive and curative health services; they face financial and cultural barriers to utilisation of health services. Their analysis revealed that NFHS-3 (2005-06) shows glaring regional and socio-economic divides in health outcomes — “the lower castes, the poor and the less developed states (bear) the burden of mortality disproportionately” (Baru et al., 2010).

With substantial literature on correlations between SES and health discussed above, we used NFHS-4 data to provide for: (a) caste-wise information on different types of housing, and (b) asset ownership in households based on type of housing.[17] We found that half of the population resides in pucca housing, more permanent structures. Of the remaining, around 43 percent are housed in semi- pucca housing, whereas 7 percent of the population lives in kutcha housing, which are temporary shelter arrangements. As we see in Table 4 in the Appendix, a fewer proportion of people from SC, ST and OBC backgrounds reside in pucca housing (45 percent, 28 percent and 55 percent) compared to 67 percent from the ‘General’ category.[18] Similarly, a smaller section of the remaining population lives in kutcha housing, whereas more people from SC, ST and OBC background live in temporary housing structures. Table 5 in the Appendix suggests that among households that does not possess any household assets, 34 percent are in kutcha structures (59 percent are semi-pucca).[19] As expected, more than 90 percent households that own more than 15 items (maximum being 24) are in pucca houses.

Some literature on homeownership exists from outside India. For instance, Haurin et al. (2002) used four waves of the United States’ National Longitudinal Survey of Youth augmented with Child Data to study the effect of homeownership status on child’s cognitive outcomes and behaviour. Their research design controlled for social, demographic and economic variables that have been traditionally found to influence child outcomes. The study found that in comparison to renting a home, owning a home—an indicator of higher wealth stature—led to higher (a 13 to 23 percent increase) and improved quality of home environment, greater cognitive ability and fewer behavioural issues among children (Huarin et al., 2002).

Ample evidence exists that has established the effect of early-life health on adult circumstances, including an individual’s earning potential and achievement. Lundborg et al. (2014) established that taller people earn more- a “substantial height premium” exists when all other factors are accounted for (also, Currie and Vogl, 2013; Avgeropoulou, 2014). Height has found to be positively associated with cognitive ability, which holds greater value in the labour market (Case and Paxson, 2008). A study from the United States and the United Kingdom shows that taller children have higher cognitive test scores, which in turn determine the height premium in earning in later life (Case and Paxson, 2008).

In addition to the socio-economic status of the adolescent girls, the social determinants of health (SDH) also explain their health outcomes. These determinants are the conditions in an individual’s environment where they are “born, live, learn, work, play, worship, and age” that affects their overall health outcomes (Office of Disease Prevention and Health Promotion [ODPHP, 2020]). An increasing body of evidence has argued in favour of a strong link between these factors and health outcomes in different geographical settings (de Andrade et al., 2015; Adler et al., 2016; Cowling et al., 2014; Kulkarni, 2013) and for various age groups (Ahnquist et al., 2012; Baheiraei et al., 2015; Wilensky & Satcher, 2009), including those of adolescents (Viner et al., 2012). In addition, developing policies that take into consideration various elements of SDH is known to reduce health inequalities (Adler et al., 2016; Penman-Aguilar et al., 2016).

I. The Teen Age Girls (TAG) Survey [20]

To test our research hypotheses, we used a nationally representative novel data set obtained through a primary survey – the Teen Age Girls (TAG) Survey. This survey was conducted during 2016 and 2017, under Project Nanhi Kali, which is jointly managed by Naandi Foundation and K. C. Mahindra Education Trust. The uniqueness of this nationally representative survey lies in the fact that it focused only on various aspects of India’s teenage girls such as their health, education, and most notably, their dreams and aspirations. The survey collected information from 74,000 adolescent girls, aged 13 through 19 years during the survey period, from across 30 states and seven Indian cities, which had a population of more than four million according to the 2011 Census. These cities were Ahmedabad, Bengaluru, Chennai, Hyderabad, Kolkata, Mumbai, and New Delhi. Sample from each state is allocated to its urban and rural areas in a way that it is proportional to its population in these areas, with a minimum of 500 samples from urban areas across all the states. The Ethics Committee of the Institutional Review Board at the L. V. Prasad Eye Institute, Hyderabad, granted approval to Naandi Foundation to carry out the TAG Survey.

The sampling design and sample size allows for producing national- and state-level estimates by various socio-economic groupings, separately for rural and urban areas, as well as city-level estimates. The survey adopted a multi-stage sampling strategy to identify respondents, separately from rural and urban areas. Selection of respondents involved three and four stages, respectively, in rural and urban areas, including seven cities. In rural areas, the first stage involved selecting villages, which were the primary sampling units (PSUs). The second stage comprised of selecting households from within the PSUs that had at least one girl aged 13-19 years. If there were two or more 13-19-year-old girls from the selected households, then in the third stage one girl was randomly selected from such households to be the survey respondent.

All the villages within a state constituted a sampling frame, except for those villages with less than five households, which were excluded. All included villages were first stratified in various regions such that each stratum comprised of villages from neighbouring districts. Further stratification was conducted within each region by village size, based on number of households. The cut-off number applied for stratifying villages within a region by size varied across state and region. Within each village type stratum (based on size), further stratification was applied using a cut-off number that was obtained based on the proportion of SC/ST population. Finally, an implicit stratification was applied within these villages based on ascending order of female literacy. In case a large village (more than 300 households) is selected, an adequate segmentation is carried out first by dividing the village into two or more smaller segments comprising of 100-200 households. Finally, only two segments were selected, which formed the primary sampling unit. Households with at least a respondent within all selected villages or village segments comprised of a sampling frame. From within this frame, a total of 22 households, including two households to account for any non-response, was selected using systematic random sampling.

As mentioned earlier, respondents from urban areas and towns were selected through a four-stage process. First stage comprised of selecting a required number of urban wards, followed by selecting one Census Enumeration Block (CEB) from each ward in the second stage. In the third stage, a required number of households within selected CEBs that had at least one 13-19-year-old girl was selected. In case a selected household had more than one respondent, one such respondent was selected randomly.

A similar step-wise stratification technique, like in the rural areas, was adopted in the urban areas. All the wards across all cities and towns in a state formed a sampling frame. These wards were first stratified into various regions of contagious districts, with implicit stratification carried out based on female literacy. Probability proportional to size (PPS) technique was used to select a required number of wards from each stratum. Only one CEB from among all the CEBs within the selected ward was randomly selected. Further, from all the potential households, with at least one adolescent girl, in the selected CEB, 22 households were selected using systematic random sampling.

Respondents from seven cities were also selected using a four-stage process. In the first stage, a required number of urban wards were selected from all the wards applying PPS technique and implicit stratification based on female literacy. Second stage comprised of selecting two CEBs from the selected urban wards. The next two stages, as well as selection of households, followed exactly the same pattern as in urban areas.

The TAG data set obtained by the study team comprised of approximately 61,600 observations. However, due to missing data and biologically impossible values (discussed later) of the dependent variables, the final sample size of our analysis is about 56,200 observations. In the following section we describe the variables that we have used in our analysis.

II. Variables

Dependent variables: We studied the impact of housing type and other SES related variables on health outcomes using two dependent variables, height-for-age z-scores (HAZ) and BMI-for-age z-scores (BAZ). These variables were computed using standard conversion techniques developed by the World Health Organization’s (WHOs)

AnthroPlus tool, which allows for “assessing growth of the world’s children and adolescents” (WHO, 2009). We discuss this step subsequently.

The TAG survey collected weight, height and hemoglobin data on-site from respondents using a digital weighing scale (in kilograms), the Prestige Stadiometer (in centimeters) and HemoCue Hb 301 analyser, respectively. For the purposes of this study, we have only used weight and height data. In order to reduce error originating either from the surveyor or the measuring instrument, girls’ height and weight were measured three times and recorded under three variables each. We created two new variables, one each for weight and height, by taking the average of the original three variables. For approximately 200 respondents, where weight and height data for one variable was entered as zero, we computed the average using the remaining two non-zero values for weight and height.

We applied the WHO Stata-based macro available to users (WHO, 2009) on input data comprising of girls’ height, weight and age to obtain standardised scores or z-scores for height-for-age and BMI-for-age for adolescent female population aged 13-19 years. The WHO macro does not produce weight-for-age for children beyond 10 years as this indicator “cannot distinguish between height and body mass in an age period where many children are experiencing the pubertal growth spurt and may appear as having excess weight (by weight-for-age) when, in fact, they are just tall” (WHO, 2009, p. 2). These z-scores provide us the distance and direction of a respondent’s measurement from the population mean in units of the standard deviation. These measures are obtained by comparing individual respondent’s growth indicators against growth data from a reference population, using LMS technique (see de Onis et al., 2007; Cole 1990). The standardised measures are used to explore growth and nutritional status (e.g., stunting, overweight) among infants through adolescents. The use of z-scores is recommended as (a) they allow us to compare with a reference population, (b) being a dimensionless quantity, allow for comparisons across age and sex, and (c) are able to compute extreme values. The WHO macro also flags biologically implausible or extreme z-scores for height-for-age (less than -6 or greater than 6) and BMI-for-age (less than -5 or greater than 5), which we dropped from our analysis to reduce outlier influence on estimated coefficients.

Independent variables: The TAG survey did not ask any direct questions related to property ownership or rights. Therefore, we looked for other ways (variables) to capture the idea of ownership. Based on our review of the extant literature, we believe the type of house is such a candidate variable. In our dataset, house type is a categorical variable comprising of three categories – pucca, semi-pucca and kutcha house. Households with more ownership rights and tenure security are likely to reside in better quality houses (through formal ownership or formal rent agreements etc.). However, the type of house indicates the economic condition of the household as well. Richer families are expected to live in pucca houses, while poorer ones are expected to occupy semi pucca, and kutcha houses. Thus, the effect of house type on health outcomes can be due to the ownership as captured through the quality of the house or the economic condition of the family. If the dimension of economic well-being and wealth is controlled for through some other variable(s), then the residual effect of the type of house on health outcomes can be interpreted to be the effect of the house type and, by proxy, of tenure security and property rights. A well-constructed permanent house not only provides shelter from elements but also provides a sense of security. Therefore, we expect the quality of house and health outcomes to be positively related. The variables through which we attempt to capture the economic condition of the household are a set of variables recording the ownership of around 25 household items and the availability of a toilet within the house premises.

The heterogeneity in material possessions among the households is recorded in a set of binary variables. The survey asked and recorded the ownership of a total of 25 separate items. These items range from smaller value items like chair, fan, watch, to high-cost items like cars. Moreover, there are items like threshers and tractors which are of the nature of capital goods. Considering various aspects of the items (i.e., cost, capital good), we have created five variables to demonstrate item ownership. They include ownership of low-cost items (count), slightly costlier household durables (count), thresher and/or tractor (category), animal cart and car (last two are binary). Sometimes in the literature, a categorical wealth quintile variable is created from this type of item ownership variables. However, we decided against following that path as ownership of a car and ownership of a table fan should not be treated similarly – which is done in the creation of such wealth indices. Another variable that captures economic condition of household is the availability of toilet facilities within the house. This variable captures both the economic condition and health awareness level of the family.

Apart from these, we have included source of lighting in the house, source of drinking water, and other demographic indicators as control variables. Source of lighting can be either electricity, kerosene, solar panels, bio-gas, etc. Given that most (over 95 percent) of the sampled households either used electricity or kerosene to light up their houses, we coded the sources into three categories – electricity, kerosene, and everything else. The survey collected information about the source of drinking water within the household as well. The source of drinking water has two aspects that can affect the health and well-being of the girls. First, if the water is not treated then it could expose the girls to water-borne diseases. Second, if the source of the water is too far away from home, then fetching the water can expose the girls to both physically demanding work and to safety-related issues. However, the survey did not collect any information on the distance of the source or whether the water source is treated or not. Therefore, we decided to capture the heterogeneity in the sources of drinking water through a binary variable – piped water vs everything else. We think that piped water can be considered to be a treated source of drinking water while there are question marks over the other sources (open well, covered well, river, pond, etc.).

Demographic control variables include indicator variables on caste (ST, SC, OBC, and General), religion groups (Hindus, Muslims, Christians, Sikhs, Others), parental education (six ordered categories for both mothers and fathers), number of household members, whether the girl is currently going to school or college and the age of the girl.

Ideally, we would have liked to have a variable that captured the relative position of the girls within the household. The sex of the head of the household, relative number of males and females in the household could have been such variables. But we do not have any such variable in the dataset. Therefore, we decided that the educational qualification of the parents and whether the girls are currently enrolled in a school or college will have to do. There could be many reasons for girls to not be currently enrolled in school or college (not being able to cope with the classes, family does not think education is important for girls). But if the girl is currently enrolled, then that means that not only the girl is able to cope, but the family values their education. This last part, in turn, implies that we can think that such families value the girls as well. In addition, we also believe that a girl’s relationship with the head of the household could determine how a girl is treated within the household. Our analysis included this through a six-category relationship variable.

III. Empirical Strategy

Multiple regression allows us to control for factors which are expected to affect the health outcomes along with the house type and goods ownership variables. Thus, we employ this empirical method for deciphering the association between the health outcomes and the explanatory variables of interest. Our general empirical model is of the following form:

where the index i stands for each adolescent girl and the index j stands for each PSU. The dependent variable is either the standardised height-for-age or BMI-for-age. Vectors of variables and vectors of coefficients are written in bold in the above equation. Thus, H is a vector of (binary) variables that denote the house type (kutcha, semi-pucca, and pucca, with pucca being the reference or base group); SES is a vector of socio-economic status variables (source of lighting, availability of toilet and piped water in the house, and number of household items owned/possessed by the family); Caste is a vector of (binary) variables that denote caste of the household (SC, ST, OBC, and general, with general being the reference group); and X is a vector of other demographic controls (whether the surveyed girl is currently studying, mother’s and father’s education, relation of the surveyed girl to the head of the household, age of the girl, number of household members, and religion of the head of the household). All models’ parameters are estimated allowing for PSU unobserved heterogeneity through PSU fixed effects.

We estimate several regressions of this form. First, we estimate average differences in adolescent girl’s height (and BMI) by house type by running a regression with the house type as the only indicators. Next, we include controls for caste to see whether the differences in the averages are because people belonging to ST or SC category are more likely to live in poorer quality houses vis-a-vis OBC and General category (the association between caste and house type is shown in the Appendix). Then, as discussed earlier, we include controls for parental education, religion, relationship of the girl to the head of the household, number of household members, current educational enrollment status of and age of the surveyed girl (and its square). Next, a set of indicator and count variables about the household’s SES is included. The indicator variables used to account for household-level SES are ownership of car, and ownership of animal cart. The count variables used are the number of items owned in a set of fourteen relatively low-cost household items,[21] the number of items owned in a set of seven slightly more costly household durables,[22] and ownership of two agricultural equipment (a thresher and a tractor). We use cluster robust standard error estimates where the clustering is done at the PSU level. We use probability weights supplied by the survey dataset in all the estimations. In the next section, we present the findings from our analysis.

I. Descriptive Statistics

Table 1 presents the overall characteristics of our sample. The top portion of this table presents the descriptive statistics for our dependent variables (and the variables from which they are derived), and the bottom portion presents the same for explanatory variables used throughout the study. The average height-for-age z-score is -1.54. This means that, on an average, an adolescent girl in India is almost one and a half standard deviation shorter than their counterparts in the WHO reference group. This shorter average height can be an indicator of the differences in nutrition, genetics, and general living condition. The BMI-for-age difference between Indian adolescent girls and their international counterparts is not as much as that in the height variable. But still, in terms of BMI-for-age, Indian girls underachieve by more than half a standard deviation. Although, height-for-age z-score and BMI-for-age z-score are our main dependent variables, we carried out some additional analysis in terms of height (measured in cms.), weight (measured in kgs.), and BMI of the girls surveyed. The average height of the adolescent girls in India is computed to be just above 151 cms. and the average weight is approximately 44 kgs. The weight of the girls has a relatively large standard deviation of approximately eight kgs. (the coefficient of variation is much larger for weight compared to height – 18 percent and 4.25 percent, respectively). The average BMI is 19.23, which can be considered to be within the normal BMI range of 18.5-24.9, albeit on the lower side. However, a standard deviation of close to three indicates that on the lower side, many girls actually slide into the underweight group.

The rest of Table 1 reflects the information available regarding living condition, ownership of household stuff, and demographic characteristics of our sample. Kutcha and pucca house dwellers constitute roughly equal proportion (38 percent each) of the entire sample with the rest living in semi-pucca houses. The caste composition of our sample is 11 percent ST, 21 percent SC, 45 percent OBC, and 23 percent General category. The representation of General caste in our sample is a bit smaller than their share in the national population, according to NSSO data. Recent NSSO surveys estimate this percentage to be close to 30 percent.[23] This gap is filled in by slight over-representation of other three castes, with OBCs accounting for the most of it (around a four-percentage point over-representation). Although caste composition of TAG sample is slightly different from the national averages, religious composition is quite on the mark. Hindus, Muslims, Christians, and Sikhs constitute 80 percent, 14 percent, 4 percent, and 1 percent of the sample, respectively. The rest is constituted by other religions.

Close to 80 percent of the households use electricity as source of energy for household lighting, while 16 percent use kerosene lamps. Around 63 percent of the houses have toilet facilities, whereas 45 percent have piped water facilities at home. On an average, households own around eight relatively low-cost household items, and around one and half of the slightly more costlier household durables and appliances.[24] Animal carts are owned by around 9 percent of the houses and an equal percentage owns cars. Tractors and threshers are owned by households involved in agriculture. Around 3 percent of the sample own only one of these two items, while double of that owns both items. Approximately two-thirds of the sampled girls (77 percent) were currently studying. Around 40 percent of the girls have mothers without any education and the same percentage for the fathers stand at 21 percent. Finally, most (91 percent) of the surveyed girls were daughters of the head of the household. Next, we discuss the results of our estimations.

II. OLS Regression Results

In Tables 2 and 3 we present our main regression results. In column 1 of both tables, we only estimate the expected difference in height-for-age z-score and BMI-for-age z-score for the surveyed girls based on their housing conditions. Those who live in pucca houses are the reference (or base) group. Thus, the intercepts are the estimated height-for-age z-score (Table 2) and estimated BMI-for-age z-score (Table 3) of those girls who live in pucca houses. The estimated coefficients of kutcha and pucca (both are statistically significant in both the tables) show by how much adolescent girls living in these two types of houses underachieve in terms of these two health outcomes relative to the pucca house dwellers. For example, the baseline point estimates (Table 2) tell us that compared to an adolescent girl living in a pucca house, a girl living in a kutcha house is expected to have 0.124 standard deviation lower height-for-age z-score and a girl living in a semi-pucca house is expected to have 0.122 standard deviation lower height-for-age z-score. Similarly, on an average, compared to the reference group, a girl living in a kutcha house and semi-pucca house has 0.073 and 0.054 standard deviation lower BMI-for-age z-score, respectively. As we include other factors which are expected to affect height-for-age z-score, these point estimates keep becoming smaller – signifying that part of the differences are being explained by those other factors.

In column 2 of both the tables, we introduce the caste variables to account for this underachievement through caste discrimination. Health and material underachievement due to caste is a well-documented fact of Indian society. The General category is the reference group here. As expected, the coefficient on all the three lower castes – ST, SC, and OBC – are negative. But while all the three coefficients are statistically significant in Table 2, that is not the case in Table 3. Thus, on an average, girls from these castes underachieve in terms of height-for-age z-score relative to the General category girls. This result persists in all our models. However, although the girls belonging to the SC category statistically significantly underachieve relative to the General category in terms of BMI-for-age z-score, the ST and OBC girls’ underachievement is not statistically significant.

In columns 3, 4, 5, and 6, we progressively include demographic controls and different types of ownership variables. Source of lighting (kerosene lamp, electricity, or other types) and access to piped drinking water at home does not seem to affect either height-for-age or BMI-for- age z-scores – both in the models where we do not include any indicator of wealth (through item ownership) and models where we do. Girls who reported that they are currently studying have a positive and negative effect, respectively, on their height-for-age and BMI-for-age z-scores. However, availability of toilet affects health outcomes positively. When we include detailed controls for item ownership, this positive effect vanishes for BMI- for-age z-scores. Thus, to some extent, the availability of toilet is a proxy for wealth and economic condition of the household, which, when captured through other direct variables, loses its explanatory power at least for BMI-for- age z-scores. For both the dependent variables, ownership of household items has a positive effect on health outcomes. Ownership of these items indicates economic well-being and hence affects the health outcomes positively. The difference between columns 5 and 6 are in how we treat different types of household items vis-à-vis each other.

In column 5, we have a naïve count of all the items – treating all items similarly. The item variable in column 5 thus does not make a distinction between a car and a chair, allocating equal weight to these items. To make this distinction, we group household items into different types based on a rough estimate of their prices and usage. This gives us five variables capturing economic well-being rather than just one. Ownership of threshers and tractors does not seem to affect height-for-age z-scores (although the coefficient is negative, it is not statistically significant), but negatively affects BMI-for-age z-scores. There is a greater probability that these items are owned by relatively well-to-do agricultural households. One way to explain this result is to appeal to the possibility of discrimination against girls within these households. Thus, girls may be deprived of nutrition and care in such households, which results in lower achievement on relevant health outcomes. Ownership of animal cart also negatively affects health outcomes. This may be through poverty pathway (in addition to whatever inter-household discrimination is present). Some households that own animal carts probably earn a living through plying those carts. With widespread mechanisation in all aspects of transportation and agriculture, such livelihood may not be very profitable resulting in an economic disadvantage for the families. And girls from poorer families suffer setbacks in health outcomes. One of the interesting results is the non-existence of any effect of car ownership on health outcomes. This is interesting because car ownership is expected to indicate economic well-being and hence should affect health outcomes positively. One possibility for not finding any significant effect of this variable could be that the ownership of other items captures this dimension already and hence there is no additional effect of car ownership on our variables of interest. Although we have not presented the results here, we have estimated the coefficients of similar models using height measured in centimeters (cms.), weight measured in kilograms (kgs.), sample z-score of height, weight, and BMI as well (Tables 2A and 3A in the Appendix). All the results discussed above (from Tables 2 and 3) hold for these variables as well.

Interestingly, the adolescent girl being a daughter, wife, grand-daughter, etc. vis-à-vis being the head of the household has a positive effect on the BMI-for-age z-score but not for height-for-age z-score.[25] Both these indicators are necessarily linked to the nutrition content of food intake. If an adolescent girl is the head of the household, it is probably because such a household does not have earning male or female adults in the family – at least not locally (the earning male or female members may have migrated to somewhere else in search of work). Such households are likely to be poorer and hence lack access to a nutritious diet. This result reflects this reality.

As a robustness check, we also estimated the baseline (column 1 in regression Tables 2 and 3) and the full model (column 6 in Tables 2 and 3) for the rural, urban (excluding the seven major cities included in the survey) and the seven major city sub-samples separately (Tables 2B and 3B in the Appendix). For the dependent variable height-for-age z-score, the results for the rural and urban subsamples are almost similar to what we have presented here, although the coefficients of the house type variables remain no longer statistically significant in the urban sub-sample. In the city sub-sample, only a few variables seem to explain any part of the variation in the dependent variable. The coefficient of constant from city sub-sample is the lowest among the three sub-samples. This coefficient, which is the estimated average height-for-age z-score for a girl with zero values on all the explanatory variables, is a whopping 2.5 standard deviation lower. This sub-sample needs further exploration.

For the dependent variable BMI-for-age z-score, result from the urban sub-sample is similar to what we have found here. In the rural sub-sample, coefficients on the house type variables are not only statistically significant, the sign on semi-pucca is positive. However, the ownership of household items seems to have similar effect as the results presented here. The results from the city sub-sample are contrary to our expectations. Neither the house type nor the caste variable seems to explain the variation in the BMI-for-age z-score in this sub-sample. The two variables that are found to be important (with positive and statistically significant coefficients) for both height-for-age z-score and BMI-for-age z-score are whether the mother had higher education and the ownership of household durables. The effect of mother’s educational achievement on the welfare of the family and the children is a well-documented fact. The ownership of household durables implies better economic condition and hence has a positive effect on the health outcomes. These results are consistent across all our models.

Our main results tell us a generally consistent story. Girls from households that live in poorer quality houses (kutcha or semi-pucca) tend to have adverse achievement on the health outcomes even after controlling for economic condition of the family and caste differences. Thus, even after accounting for those differences, the quality of houses still seems to be a strong predictor of health outcomes for the adolescent girls in India.

We believe that this is a first-of-its-kind study from India that has attempted to address a major evidence gap in terms of linking property rights with health outcomes of adolescent girls, a group that roughly comprises seven percent of the total population (Office of the Registrar General & Census Commissioner, India [ORGI], 2020). Though the TAG survey does not provide us information on the property rights enjoyed by these households, literature that we have discussed earlier establishes a relationship between type of housing  and property rights, and between property rights and home improvements. This, therefore, allows us to safely assume that those living in pucca houses in this study have a greater probability of enjoying secure tenure in the least and property rights in the best-case scenario. Similarly, we can safely assume that kuccha houses have a greater probability of having insecure tenure. Our findings on type of housing as influencing health outcomes are significant in that they underline the importance of decent housing to health outcomes. Our research can therefore be interpreted as making a case in the least for the underlying importance of decent housing with adequate access to basic services such as water and toilets. Secure tenure can motivate poor households to improve their homes, and thereby result in positive health outcomes.

In the absence of straightforward data on property rights from India, we have attempted to use a proxy measure – type of house – that strongly indicates property rights, including tenure security (Mahadevia, 2010), to study its impact on adolescent girls’ physical growth measures. As discussed earlier, such growth measures are known to not only have life-long impacts but can also be intergenerational (Mulugeta et al., 2009; Murrin et al., 2012). Adolescence is generally considered as the last window period to take necessary steps to control any intergenerational impact of poor health outcomes (Gebregyorgis et al., 2016; Melaku et al., 2015). We believe this study has produced critical evidence, significantly linking house type with health outcomes, thereby justifying the need for implementing sustainable policy measures today, in order to have a more equitable future.

A significant proportion of existing research from India that has attempted to predict adolescent girls’ growth measures has focused on nutritional and household SES factors (some of which are included in this study). Most of such studies are either based on small sample (Macwana et al., 2017; Rohilla et al., 2014; Goel et al., 2013) or in a specific type of residence such as in rural areas (Coffey et al., 2019). Such study designs limit the generalisability of findings. Our study is a departure from the existing empirical findings; it uses a nationally representative data set, the TAG survey, to test the research hypotheses. Upon comparing simple bivariate cross-tabulations (e.g., caste and house type) from TAG and NFHS-4 data sets, we find some similarity. This provides additional validation regarding the quality of TAG survey data.

Based on the most robust model, which includes full set of controls as well as village-level fixed effects (column 6 in Tables 2 and 3), our analysis indicates that overall, an adolescent girl residing in a kutcha and semi-pucca house compared to a pucca house experience lower height-for-age, almost by 0.05 SD (p < 0.01). Similarly, girls residing in a kutcha house have significantly lower BMI-for-age; 0.04 SD lower BAZ compared to reference group (p < 0.10). Adolescent girls from rural areas demonstrate significantly lower HAZ scores for house type. Those residing in a kutcha and semi-pucca house in rural areas have 0.07 SD lower HAZ score compared to the reference group (p < 0.01). BMI-for-age score is lower for a kutcha house resident from rural area, albeit insignificantly. To our knowledge, we found only one study from India (Pal et al., 2017) that linked stunting (HAZ < -2SD) and thinness (BAZ < -2SD) with house type in a multivariate setup using a rural sample of 839 adolescents aged 10-17 years. Our findings for the adjusted model, based on rural sub-sample of TAG data on HAZ (used to define stunting) significantly diverges, whereas on BAZ (used to define thinness), it is insignificant when compared with Pal et al. (2017).

Lower attainment in growth measures among girls residing in poor quality housing are known to have life- long and intergenerational impact (Aurino et al., 2019; Murrin et al., 2012). For example, height is an established predictor of academic achievement (Magnusson et al., 2006; Spears, 2012), which in turn determines economic well-being (Agerström, 2014; Lundborg et al., 2014), leading to better quality health (Lê-Scherban et al., 2014), all of which are known to have intergenerational impact. Stulp et al. (2015), based on observations collected through three natural settings, “conclude that human height is positively related to interpersonal dominance” (p. 1) and that it may also explain the social status that a ‘tall’ individual enjoys in a society. Height is also a good predictor of self-esteem in an individual, which significantly explains earnings (Drago, 2008). Thus, there are multiple ways through which an individual’s height could explain overall well-being and satisfaction in life (Salahodjaev & Ibragimova, 2020; Coste et al., 2012).

While we have not included nutrition, personal eating preference, physical activity and a host of other explanatory variables in our analysis, they nonetheless significantly determine growth measures from across various settings. Wassie et al. (2015), based on a community-centered cross-sectional study of adolescent girls from Ethiopia, concluded that increasing the variety in dietary intake and participating in a community-based nutrition programme decrease the odds of poor HAZ and BAZ scores. Unhealthy food consumption pattern and sedentary lifestyle are strong predictors of overweight and obesity, a finding that is common across various countries (Costa et al., 2019; Dixit et al., 2014; Goel et al., 2013; Rohilla et al., 2014; Adesina et al., 2012)

Ownership of household items generally speaks volumes about the economic well-being of a family, thereby affecting health outcomes positively. Findings from our study significantly confirm gains in HAZ and BAZ scores among the owners of low-cost items and household durables. This finding resonates with similar findings on predicting nutritional status among children and adolescents from Bangladesh (Rousham & Khandakar, 2016), Gambia (Juwara et al., 2016), Gaza Strip (Abudayya et al., 2011), and Macedonia (Stojanoska et al., 2014). On the other hand, respondents from the household that owned an animal cart compared to those that did not, report lower height-for-age (-0.05 SD, p < 0.10) and BMI- for-age z-scores (-0.11SD, p < 0.01). Threshers and tractor ownership also significantly predicted lower BAZ score (p < 0.01). Lower growth measures among adolescent girls across these groups, be it rich or poor (reflected by ownership of threshers and tractors, or animal cart), point to another dimension in our society. It is likely that girls, in general from any households are treated differentially, compared to boys. This has been highlighted in studies from Tanzania (Kafle & Joliffe, 2015) and the Unite States (Roberts & Warren, 2017). Differential treatment could include poor dietary provision, which, when sustained for a long time period is known to reduce growth measures.

Access to a toilet facility within household positively impacts adolescent girl’s height-for-age z-scores, with higher upward movement among urban respondents. Pal et al. (2017) study from India and Mulugeta et al. (2009) study from Ethiopia demonstrates the importance of access to a toilet facility. Both these studies illustrate that lack of a toilet facility is significantly associated with thinness and stunting. Evidently, girls who do not have household access to toilets are travelling outside of their homes to defecate in the open, which is known to negatively impact anthropometric indicators (Chakrabarti et al., 2020; Chattopadhyay et al., 2019; Ahmadi et al., 2018). While controlling open defecation remains a priority for the central government, even though the campaign formally ceased on October 2, 2019, evidence indicates that we are far from reality (Yadavar, 2019). Gupta et al. (2019), based on a 2018 survey of four North Indian states, concluded that even though the construction of toilets had increased under the Swachh Bharat Mission, open defecation still continues to be a concern. This problem can only be successfully addressed if there is a nationwide Information, Education and Communication (IEC)-based campaign that promotes use of latrine (Coffey et al., 2014).

Caste continues to explain adolescent girl’s height. Girls from the lower castes – SC, ST, and OBC – suffer from reduced height-for-age z-scores, demanding corrective measures. Girls from Scheduled Caste suffer disproportionately, as has also been established by Venkaiah et al. (2002). Previous studies have explored several pathways through which height of lower caste girls can further explain change in learning outcomes (Aurino et al., 2019) to dietary intake pattern (Seshadri et al., 2016). Most existing evidence indicates that caste is a significant predictor of adolescents’ nutritional status (Degarege et al., 2015; Madjdian et al., 2018; Singh & Bansal, 2017).

As discussed earlier, parental education, either one of the parents or combined, plays a critical role in determining their child’s physical growth measures. Compared to no education, HAZ scores progressively increased with both mother’s and father’s level of education from primary to higher education, Mother’s level of education registered greater gain on HAZ scores. Similarly, mother’s education level also significantly improved BMI-for-age z-scores from secondary level onwards. Educated parents are in a better position to decide on various factors that impact physical growth, from dietary pattern and its nutritional content, to involvement in physical activities.

Limitations

Limitations to our study mostly emanated from the use of the TAG survey dataset. Thus far, only one round of the TAG survey has been conducted during 2016 and 2017. The cross-sectional nature of the dataset does not allow us to observe trends over time. Perhaps, with further rounds conducted we will be able to conduct a robust analysis of how evolution in housing type and property rights impact adolescent girls’ health outcomes. The sample represents female adolescents aged 13-19 years. We, therefore, cannot extend our findings for the male cohort in the same age- group in India.

In addition, no variables in the dataset capture direct or distinct information that would allow us to determine the status of a household’s property rights or security of tenure. Thus, we have resorted to establishing the relationship between tenure security (as a proxy for property rights) and housing type using globally available literature. Further, information on whether the dwelling is owned or rented by the household is not available; this would have been a more refined indicator of property rights. Other existing datasets, such as the Prindex data, which has better information on property rights and ownership, does not include any health indicators.

The TAG survey captures height, weight and haemoglobin levels as the only indicators of health. Thus, height-for- age and BMI-for-age are the most suitable variables for analysis in this context. Weight-for-age is not applicable for this particular age group. Furthermore, data on genetic factors, such as parental BMI and health conditions, which could impact girls’ health is not available.

Data on additional aspects of household demographics such as, gender composition of siblings, social status of girls within a household and primary occupation or type of employment in a household are not available. Including these variables in the regression model would have made our analysis even more robust. In the future, additional waves of TAG survey could include some of these missing variables, including retrospectively, provided conducting survey among the first wave of sample households (as in the India Human Development Survey, various rounds).

Conclusion

The central findings of our analysis are that health outcomes (age-adjusted standardised height and BMI) of adolescent girls in India are systematically lower for those living in poorer quality houses and systematically higher for those in families with ownership of more household goods. Based on the existing literature, we interpret that the type of house is a satisfactory indicator of property rights and tenure security. Thus, we conjecture that girls from households with tenure security fair better in terms of the standard health outcomes relative to girls from households without such security. Adolescent health outcomes strongly predict an individual’s future health conditions. A healthy labour force is not only more productive but also aids in spending a lot less on healthcare. Resources thus generated could be invested in the general well-being of the society. In addition, adolescent girls of today are also the prospective mothers of tomorrow. A healthy mother has a much higher likelihood of bearing a healthy child. Thus, these outcomes are not only contemporaneously important, but have strong intergenerational implications as well. Unfortunately, within the policy arena, the adolescent age group is one of the neglected subsets of the population. Therefore, on the one hand, we need to do more research on the pathways through which property rights and tenure security affects the adolescent girl’s health outcomes and, on the other hand, we need to pay more attention to these linkages within the policy discourse.

The issue of property rights and tenure security of poor households has been approached in the policy space, using a rights-based approach of the right to housing and shelter, or as enabling the accrual of capital through housing that can be used to raise loans and improve the economic opportunities of the poor. Both these approaches miss the health dimensions of decent housing, even if the rights-based approach is broader, and focuses on the human experience of homelessness and the indignity and life-threatening potential of inadequate housing.[26] Our research emphasises the health dimensions of housing, and therefore the potential for affordable housing to provide benefits that are not just economic but also improve human capabilities and, in turn, human achievements.

Our research also points to the provision of tenure security as a solution to the problem of poor housing, within a context of inadequate state resources and the meagre supply of affordable housing. However, this requires a paradigm shift from the current approach of viewing slums and settlements as eyesores and obstacles to development. Poor housing, unsanitary conditions of living and the environmental consequences of slums and settlements such as garbage and open defecation, have been perceived as threats to public health and mortality (Gilbert, 2007). Urban programs that offer affordable housing have been used to remove the poor from within cities and displace them in the peripheries, in ghettoes of sorts, with even poorer access to basic services. Such programs often recreate slums, albeit vertically, in apartment buildings, far away from the city and therefore from sources of lucrative employment. This reveals a myopic view of housing as the mere provision of shelter, which can then be arranged in any part of the city, ignoring both the tremendous upheaval of displacement and the effects of relocation in spaces that provide fewer services and fewer economic prospects (Thara, forthcoming). Mahadevia, for instance, reveals the poor quality of rehabilitation housing provided by the state and the lack of services in such housing (Mahadevia et al., 2013). Kamath reveals how slum dwellers provided with rehabilitation housing have to again negotiate with local political representatives to obtain access to services, which takes place incrementally over years (Kamath, 2012). Thara, in her research in the biggest rehabilitation housing area in Bangalore, reveals how residents, despite their political negotiations, do not have access to piped water and sanitation more than two decades after rehabilitation (Thara, forthcoming). Even during the implementation of the Pradhan Mantri Awas Yojana (launched in 2015), which emphasises the provision of housing in situ (on the spot where slums are originally located), evictions for city beautification have persisted unabated as reported by the HLRN in 2017 and 2018 (Chaudhry et al. 2018, 2019). This is bound to have tangible consequences on the evicted poor, much beyond the mere loss of housing, to a deterioration in conditions of life, lack of access to basic services such as water and sanitation, fall in wages/income, increased travel time, etc. all of which are bound to impact their health. As Mahadevia argues, housing is not the mere provision of shelter but also includes access to services such as water, electricity and sanitation (Mahadevia, 2010). Providing housing, without access to services, as has been evidenced in several slum rehabilitation programs, will therefore not enable people to achieve better health outcomes.

Over the years, a formidable mechanism of slum rehabilitations has been established to address the problem of slums and settlements in India. However, available research on tenure security shows that the poor need nothing more than tenure security to invest in home improvements. We are not the first to point this out, urban sociologists have proposed tenure security as a simple and effective solution to affordable housing requiring low investment by the state and fewer resources (Banerjee, 2002; Kundu, 2009; Mahadevia, 2010; Mahadevia, Joshi, and Sharma 2009). This is specifically in the context of evidence that reveals that a majority of forced evictions in India are for city beautification projects (see discussion on the HLRN reports mentioned in part one). The trade- off between beautifying cities and providing urban poor housing should be, therefore, one that is easier to make, as it is not only in the interests of the larger good, but also results in multiplier effects enabling effective poverty reduction, enabling economic empowerment, and most importantly, improving the capabilities of people through positive outcomes on health.

However, addressing the need for planned housing and ownership requires a paradigm shift in the ways in which the urban poor are perceived both by the state and other actors. It also requires confronting the fear of an apocalypse, of overgrowth and proliferation that is out of control (Gilbert, 2009). This calls for a strong political resolve that can ensure inclusive growth and equitable distribution of resources while withstanding the onslaught of the real estate sector, bureaucrats and political representatives who have a stake in freeing expensive land of its poor inhabitants. Most importantly, allowing for greater upward social mobility of the disadvantaged sections of the society merits a commitment to property rights as integral to enabling equal citizenship.

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The post Do property rights explain health outcomes of adolescent girls in India? first appeared on CSEP.

As part of the “stimulus” packages announced by the central government due to COVID-19, Rs. 90,000 crore was initially earmarked for electricity Distribution Companies (DisComs).[1] This “stimulus” (cash flow relief) was meant to address DisComs’ financial difficulties, and the government subsequently announced that it could be extended to a limit of Rs. 1.25 lakh crore. This was widely reported[2] to be large enough to bridge the gap of dues to upstream generators (who themselves owe significant money to their own suppliers).

Proponents of this relief package acknowledge that it merely amounts to loan-financed liquidity, and is not a grant or write-off. However, we find the true picture of shortfalls, cash requirements, and generator dues to be multiple times worse than the roughly Rs 100,000 crore discussed widely in the press, which might be based on the government’s PRAAPTI portal.[3] The incomplete nature of PRAAPTI fails to reflect that the generator dues alone are about double this amount. The actual total dues and short-term liabilities are multiple times higher. Our calculations are based on earlier data that do not reflect the full extent of COVID-19 implications, which will only show up meaningfully in FY2020-21. This means that while the stimulus may be helpful, and even necessary, it will not be anywhere near sufficient.

Such relief also doesn’t begin to address larger structural distortions, where different stakeholders are treated differently, such as types of consumers, or types of generators (with or without a power purchase agreement, or PPA). Most importantly, there is an enormous focus on non-payment by DisComs to generators, but insufficient focus on non-payment to DisComs by state governments for electricity consumption or promised subsidies.

Most discourse also underplays dues to other suppliers and vendors beyond generators, in addition to other dues or liabilities. DisComs will need support in the coming months, exacerbated by COVID-19 which has hurt their revenues more than simply the reduction in demand (because of the disproportional reduction in demand from high-revenue commercial and industrial consumers). Not only will the high shortfalls need more funding, but we should also look for new instruments beyond just loans. If there is a haircut to be taken, it should be equitably and realistically spread through the ecosystem, and not just by DisComs. The concentration of the challenges in selected states also emphasises the limits to a one-size-fits-all approach.

In the backdrop of COVID-19 and its unprecedented shock to the economy, the Government of India initially announced a relief of Rs 90,000 crore to assist the stressed electricity distribution sector[4] for liquidating their dues to suppliers like generation companies (GenCos) and transmission companies (TransCos) via loans through the Power Finance Corporation Ltd. (PFC) and the Rural Electrification Corporation Ltd. (REC). According to press reports at the time of writing,[5] PFC and REC together received applications for Rs. 87,320 crore from distribution companies/utilities (DisComs)[6] (Figure 7). This number may rise as more states debating the loans take the plunge.

Was this amount appropriate or sufficient? To answer this key question, we must first examine DisCom finances including several sets of dues, not just payables by DisComs, but also receivables to DisComs.

For a mostly monopolistic, regulated (rate-of-return) entity like a DisCom, why should there be financial losses? Why should they have dues (unpaid bills) to generators who supply them power? After all, both sides of DisCom financials are regulated – what they have to pay (expenses, overwhelmingly for power purchase) and what they can earn (revenues). A subtle but very important aspect of this equilibrium involves a range of assumptions that regulators make or impose upon DisComs. It is only based on these that they are able to earn a statutory rate of return.

If one looked at the aggregate income statements for DisComs, like compiled in PFC’s Reports on Utility Performance,[7] these lists all the revenues and expenses of DisComs. Correction, they list the booked values, which assume all incoming cash flows are actually received and all outgoing are actually paid out. The unpaid dues to generators make headlines but there are many other headings of both expenses and revenues which don’t materialise as booked, and merit attention.

Even a cursory glance at the income statement shows a net deficit (annual expenses > revenues), and the balance sheets, which apportion utility assets across liabilities and equity, are also not very healthy. In fact, for FY2018-19, the liabilities were greater than the assets (!), but that is the topic of another paper. However, very little attention is given to cash flow statements since these are not publicly available. Income statements rightfully focus on accrual accounting (book values), which is the norm in India based on an accounting standard that smooth out cash flow ups and downs to better reflect operations instead of delays in cash payments.

However, in the case of DisComs, we really need to see the cash flow statements as well for two reasons. First, like with all businesses, even if the book value appears healthy, cash matters. Lack of cash means either one must take loans (sometimes classified as working capital), or one has to delay payments until receivables come in. The receivables are measured not in days or weeks,[8] but many months, far exceeding the “normal” payment cycle. Second, an implicit assumption in accounting is that the differentials between cash and accrual accounting even out over time – different flows are expected to be late at different times. However, if we examine the books of utilities over time, we find that this isn’t true and there is a steady increase in the gap between cash and accrual accounting. This is seen in Figure 1 showing days of receivables and payables, which have increased between FY2009-10 and FY2018-19.

The upswing in days of payables or receivables hasn’t been monotonic. Why there was a dip (improvement) in days of receivables and even payables is an interesting question – one beyond the scope of this paper – but it could be related to operating discipline, more free cash flow etc. What is interesting is that there has been a crossover in FY2011-12, before which receivables were greater than payables in absolute terms.

Most conversations around the cash flow or even (book-value) income statement deficit revolve around electricity losses, often “commercial losses” which include theft as well as lack of billing and collection. The composite measure is dubbed aggregate technical and commercial (AT&C) losses, the latter spanning theft and non-collection.[9] AT&C losses are officially more than 20% on average in the country; the government’s UDAY portal has more details on such losses. They not only vary widely across states, but they also inherently have uncertainty because of the impossibility of quantifying unmeasured components (theft, technical losses, and unmetered consumption) except through underlying assumptions.

It’s important to note that, up to a point, such losses are normal because of the physics of transmitting electricity over wires, and these losses can never be zero. However, they certainly can be measurably lower than they are today.[10]

Today’s reference number for “acceptable” AT&C losses is 15% – in practice each DisCom is given slightly different targets, but government policy refers to 15% as a national goal. Any shortfall in achieving targeted AT&C loss by a respective DisCom would hit them financially based on aggregate revenue requirement (rate base) calculations. However, even if we assume regulators disallow all losses above the targeted (average 15%) AT&C loss, such a bounding exercise only creates a financial loss of 5% in aggregate, which doesn’t explain the very large unpaid bills. While handling the failure to meet AT&C targets is an important challenge, it isn’t the focus of this paper.

Receivables or dues to DisComs are a much bigger challenge for cash flows than AT&C losses. These are of two types. The first is subsidies from the state governments which may not have been received (Table 1), and the second is unpaid dues from consumers. A critical subset of the latter is dues from state governments for their consumption, which, put together with unpaid subsidies, results in state governments being responsible for the largest fraction of DisCom receivables.

3.1. Subsidies – A large share of revenues but often delayed

Independent regulators (the State Electricity Regulatory Commissions) are meant to set retail prices (tariffs) so that DisCom costs (rather, their allowed costs), are covered, inclusive of any statutory returns. Consumers by category (residential, agricultural, industrial, commercial, etc.) have tariffs that are not exactly equal to the DisCom cost of supply for several reasons. First, many categories have progressive (telescopic) tiers, or slabs, such that the category average includes smaller consumers, who are ostensibly poorer, paying less than the category average, offset by some within the category paying more. Second, categories themselves may differ based on a principle of cross-subsidy where commercial and industrial users typically overpay to offset underpayments by domestic and agricultural consumers. On paper, based on the Electricity Act 2003, the maximum cross-subsidy is meant to be 20%, but many states have far greater cross-subsidies.

Outside of cross-subsidies, state governments are free to provide a separate, explicit subsidy to lower the bills for selected consumers as they see fit. Thus, if the regulator sets an agricultural price of, say, 4.5 Rs./kWh the state can declare zero cost electricity for farmers by promising the tariff difference as a subsidy. As Table 1 shows, promised subsidies can be an enormous fraction of total cost structures, more so when we dig at a state-level (Table 2).

However, these are all mere promises, and the important question is whether subsidy payments are actually given on time. Evidently, there is measurable unpaid subsidy. According to the PFC Report on Utilities Performance for FY 2018-19, the un-realised subsidy was Rs. 11,738 crore. At first glance, in comparison with the annual value of electricity, this appears very modest (1.6%).[11]

However, if we add all the unpaid subsidies over time, these become a considerable amount. From FY 2009-10 through FY 2018-19 we calculate the cumulative unpaid subsidy as Rs. 46,281 crore (Figure 2). We can then put this aggregate into context by comparing it to DisComs’ aggregate cost structure (Table 1). Importantly, this total is without adding any carrying cost of such unpaid subsidy. At a hypothetical 10% rate, the carrying cost of such unpaid subsidy just between FY2009-10 and FY2018-19 exceeds Rs. 30,000 crore. Thus, from a cash flow perspective, this aggregate is now very substantial (in the order of 10% of FY2018-19 total costs). We also haven’t factored in any historical unrealised subsidy prior to FY2009-10 as PFC’s public databases on their website only begin with 2009-10 data. However, that year showed a very large unpaid subsidy, suggesting it might also have been high for prior years.

The amount of subsidy that each state wants to provide is a policy decision that in theory should not affect DisComs. However, Table 1 shows that the fraction of the cost structure meant to be covered by subsidies reached its minimum in FY 2012-13, but has since grown to about 15%. When any translation between the share of received versus booked subsidies becomes a large cash flow issue it creates problems for DisComs, even more so in aggregate over time.

More than the national unpaid subsidy, it is important to understand state-level implications. On a year-by-year basis, some states “overpay” subsidies, which, in effect, pays off prior dues (a few have overpaid in aggregate). But such overpayments don’t help other states, even though the all-India figure improves. Table 2 shows the time series of subsidies at a state level, capturing both share of subsidies booked compared to total cost structure overlaid with a colour schema showing whether that particular year’s subsidy as booked was paid in full or not (or overpaid). We can immediately see that a “modest” all-India average figure includes enormous unpaid subsidies for states like Rajasthan and Andhra Pradesh. The key point to note is these states show a combination of high subsidy share combined with low realisation of booked subsidies. In contrast, say, Haryana has much higher subsidies as share of tariffs, but it received almost all of it. Conversely, Tripura and Puducherry had poor realisation of subsidies booked, but the share of subsidies in cost of electricity was low.

It’s worth emphasising that cumulative share of subsidies booked is over 10 years, so a hypothetical state-specific 3% aggregate subsidy shortfall (product of share of subsidies times the share un-realised) is multiple times more than 3% of annual electricity costs. And when DisComs have little or no cash surplus to pay their suppliers, this can become a critical contributor to their inability to pay generators or other vendors.

3.2. Many consumers don’t pay in full, including state governments

While many diverse consumers may owe money, the single largest non-payer for consumption is the state government(s).[12] Breakdowns of dues from consumers are not declared by DisComs, but during the third quarter of FY 2019-20, press reports[13] observed pending dues from ten states (which include Maharashtra, Chhattisgarh, Kerala, Tamil Nadu, Punjab, Bihar, Haryana, UP, Telangana and Andhra Pradesh) as Rs. 37,211 crore. This figure would clearly increase when we add the all-India numbers beyond these 10 states. We don’t know if states not shown have proportional receivables from state governments for consumption, but assuming they did, extrapolating to all-India could raise the dues shown by several tens of percent.

We further triangulate these numbers based on the official figure given by the Power Minister in Parliament in December, 2019,[14] which stated that the total dues/outstanding against state government departments stood at Rs 41,000 crore. Subsequent informal discussions with various experts in the industry indicate plausible outstanding unpaid consumption dues (unverified and un-authenticated) of government departments could be around Rs. 65,000 crore out of which 13 States together owe Rs. 52,852 crore to their DisComs (Table 3).

Due to these receivables, DisComs may not have any option but to borrow from banks to cover cash needs. This attracts a carrying cost, but much if not all such unplanned loans are disallowed in the tariff calculations by the Regulator. The extent to which DisComs charge interest or penalties on chronic defaulters is also unclear, since the theoretical norm is to simply shut off supply – which they are not doing for government consumers.

A summary of the income statements and sub-set of the balance sheets is given in Table 4. The lower half examines the balance-sheet side of dues (from and to Discoms) but only for short-term obligations, which means these will have cash implications for DisComs soon (technically, within one year). Long-term DisCom debt (not shown), categorised as non-current borrowings and other non-current liabilities, was Rs. 486,673 crore In FY2018-19.[15] However, the annualised implications are already captured in maturities and interest, and this paper is focused on short term cash needs, which are a driver for the “stimulus” loans.

While a measurable gap of Rs. 61,255 crore is found on an annual operating basis, the DisCom balance sheet net short-term liabilities, which are due soon, even after offsetting receivables from payables, were Rs. 3,19,414 crore for FY2018-19. Adding these up shows that they need support, assuming no other restructuring, of
Rs. 3,80,669 crore for FY2018-19. This is after taking in all the receivables. The Appendix visualises these flows in a Sankey diagram, adding more nuance to booked versus realised income flows.

Out of all the liabilities of DisComs, dues to generators (for power purchase and fuel, the latter applicable for integrated utilities like in Tamil Nadu who also generate) are the largest immediate need. On an annual (income statement) basis, procurement of power alone cost utilities Rs. 5,62,026 crore in FY2018-19. This amount exceeds the income from operations (Table 4), and it’s only owing to grants and subsidies (the latter being the largest non-sales income for DisComs) that DisComs are expected to stay afloat.

4.1. PRAAPTI doesn’t capture all GenCos or their dues

The lower right quadrant of Table 4 shows that power purchases (and fuel) have dues in FY2018-19 of Rs. 2,27,018 crore. This is much higher than the 2020 figures discussed in the media in the order of one lakh crore, which appears to be based on PRAAPTI, the government portal meant to ensure transparency in generation billing. However, PRAAPTI only captures portal-reported dues to GenCos (Rs. 116,580 crore at the time of writing), but this understates the problem by far. Although the portal is a great start at aggregating and adding transparency, it has made no claims of being 100% comprehensive as it is primarily based on the collective effort of GenCos which report via the portal. As all GenCos aren’t on the platform (or submit all billing information, consistently), the PRAAPTI dues shown are far short of the real figure.

By examining the monthly trendline on PRAAPTI along with GenCo participation (Figure 3), we can see how PRAAPTI’s aggregate snapshot could be misleading. In April 2017, the portal started with 46 GenCos, and it now[16] has participation from 195 GenCos. This number remains measurably below the true number of generating companies operating in the country (approximately 548 non-RE generators[17] – Central, State and Private sectors together – and a significant number of RE generators). More than the number of participants, the majority of participating GenCos do not provide consistent and timely information. In particular, as Figure 3 shows, State

GenCos joined PRAAPTI relatively recently, and so the time series information on their dues is missing.

The fact that participation of GenCos is below the total number partly explains why the PRAAPTI figure for dues to generators is much below the PFC figure for the same time period. In addition, the information on PRAAPTI is constantly changing as we found a change in reported historical GenCo dues in the range of 3.38% to 31.26% just in the span of a few weeks of examining the data (Table 5). This illustrates the “non-definitive” nature of PRAAPTI data.

Additionally, a closer examination of PRAAPTI data indicates sudden unexplained jumps in billing and payments (Figure 4 for Rajasthan and Figure 5 for Andhra Pradesh as examples, respectively), which do not map one-is-to-one to electricity transactions by DisComs when we dig deeper into the time-series monthly data.

The billing data provided in PRAAPTI also does not indicate the break-up of dues into overdues of past period, versus the dues of current billing month, let alone late payment surcharges or affiliated charges.[18] However, it has a breakdown of payments made, whether they are for current bills or past dues. The data remain silent on occasional one-off jumps in dues, leaving them unexplained. Conversely, there are often sudden jumps in payments made, frequently including those made in March (financial year ends; see three such yearly dips in Figure 3) or UDAY-linked payments. This emphasises the need to look beyond any single month or slice, but rather at the trends.

A comparison of payables towards power purchase and fuel by DisComs for FY 2018-19 (the PFC Report) with their dues to GenCos (as per the PRAAPTI portal) for the same period finds significant discrepancies. Out of fourteen chosen states, except in the case of Rajasthan, the payables under the PFC report are much higher than the payables to GenCos under PRAAPTI; even Rajasthan has a slightly lower amount due shown in PRAAPTI (Figure 6). Although the element of charges on account of fuel can create some differences, this applies more in states with integrated operations, and it certainly does not explain the huge discrepancy between the two comparable parameters. Some part of discrepancies can be attributed to ‘dues’ as per PFC, which might factor in single month billing (shown as a slice for March 2019), combining historical past dues. But even this doesn’t explain the gap – the fundamental issue is a misreading of what PRAAPTI covers.

The latest state-wise dues by the end of FY 2019-20 reported from various press reports vis-à-vis the dues to GenCos as per PRAAPTI portal also indicate large variation. The GenCo dues of States of Jharkhand, Maharashtra and Rajasthan on PRAAPTI are in excess of dues indicated in press reports. But, for Andhra Pradesh, Bihar, Karnataka, Manipur, Meghalaya, Punjab, Tamil Nadu, Telangana, Uttar Pradesh and Uttarakhand the PRAAPTI indicated dues are lower by 21%–85% compared to the information available in press reports (Table 6). While press reports are not official, they can be more up-to-date based on current information. On the other hand, sometimes they show enormous differences, for example, for Rajasthan (Table 6).

The purpose of using press reports is to get a secondary estimate of dues in 2020, for which audited or official data like from PFC’s report, are unavailable. However, the more important takeaway than specific numbers is the range and heterogeneity of dues across states. To summarise, PRAAPTI dues are a subset of generator (power procurement) dues, and generator dues are a subset of short-term liabilities. As discussed before, there are significant other short-term payables, also adding up to over three lakh crore.

4.2. Non-Genco Dues

PRAAPTI only captures dues to generators, and if dues to TransCos (which are modest compared to dues to GenCos) and other working capital requirements are also included, any loan relief calculated just on the basis of electricity procurement dues would require a further upward revision.
To summarise, PRAAPTI dues are a subset of generator (power procurement) dues, and generator dues are a subset of short-term liabilities. As discussed before, there are significant other short-term payables, also adding up to over three lakh crore.

5.1. When are they really due?

A simplified view would be to simply offset the incoming with outgoing (income statement, top of Table 4), and to do the same for dues on both sides, i.e., receivables and payables. Even for FY2018-19, and today’s picture can only be far worse, adding up the top and bottom halves of Table 4 shows a shortfall of Rs. 3,80,669 crore. This assumes that all dues and receivables are liquidated.

Even before COVID-19, it would have been unrealistic to expect dues to be liquidated overnight (or even within the year). The entire point of the government loans is to provide cash, ostensibly to pay off generators. This means the balance sheets of DisComs don’t improve at all – there’s only a formalisation of liabilities into another head, shifting payables into a loan. Depending on the terms of the loan, this provides a liquidity cushion to the DisComs, but it now creates interest obligations on the income statement, plus some portion of dues or maturity segregated in the balance sheet. A missing but useful lens becomes the cash flow statement.

Figure 1 gives us a plausible idea of what should be the “best case” scenario for winding down payables and receivables. Like AT&C losses cannot be zero, neither can days of receivables or payables. There is always an allowed and expected payment period – 45 days is a good target. Electricity consumers should normally pay within a month but let’s assume an upper bound before their supply may be disconnected. For purchasing power from suppliers, 45 days also matches CERC guidelines before which Late Payment Surcharges apply.[19] In comparison, total receivables and payables in FY 2018-19 were 135 days and 150 days, respectively. This translates to a realistic upper bound of winding down these dues by 66.7% and 70%, respectively, with the respective days of dues coming down to 45 days. Even if both sides materialise together at 45 days, that still translates to a net payable of Rs. 37,093 crore, not very different from the total difference of payables over receivables in Table 4, equivalent to zero days, of Rs. 44,289 crore.

While we appear to have an instrument to shift GenCo dues thanks to the “stimulus” loans, it is unclear that there is any similar instrument to speed up or formalise receivables owed to the DisComs. Thus, at one extreme, one could have a very slow wind down of receivables if at all. Official numbers also appear to exclude the cumulative non-payment of subsidies which don’t appear to show up as assets (perhaps because they are outside regulator purview).

It’s worth pointing out another very large segment of payables, that gets very little attention, namely Other Current Payables of Rs. 2,18,441 crore. Not only is this very large, almost as much as for sale of power, but it might also include smaller vendors providing equipment and services, including IT, meters, cabling, and transformers. It’s not clear where those are booked. For instance, BESCOM’s Annual Report 2018-19 indicates that the majority of Other Current Liabilities are for interest on Consumer Security Deposits. For all the focus on GenCo dues (including publicised via PRAAPTI) there is near zero discussion of these liabilities.

As a bounding exercise, if we consider a world where the receivables don’t materialise any time soon, then the upper-bound total loan needed, based only on FY2018-19, and including bringing down payables for power purchase to 45 days and assuming a similar multiplier for Other Current Liabilities (we don’t have the breakdown of days overdue, if at all), would then be Rs. 4,18,806 crore, which is different from Table 4 as all dues are now set at 45 days. This figure assumes that annual (ongoing) operations can’t help as they had a deficit themselves of over 60 thousand crore rupees. What any loan will do is spread out the liabilities into per-year smaller but longer-term obligations. However, in a post-COVID world, it’s unclear whether this will be enough, as annual cash flows have cratered.

In fact, if we examine a few key states, for most of them the loans announced as of the time of writing fall far short of even generator dues for FY2018-19,[20] forget total short-term obligations (Figure 7).

5.2 How much of a tariff hike does this translate to?

How manageable or impactful are these obligations, which include not only generator dues but also other payables? The last two columns of Table 6 converted the dues into Rs./kWh, based on the annual volume of electricity – a one-time equivalent of rupees per unit electricity (rather, paise/kWh). For reference, the 2018-19 all-India average electricity revenue from power sold (i.e., excluding subsidies and grants like UDAY) was 4.23 Rs./kWh.[21] We note that the implications are usually lower, but for a handful of states the one-time equivalent amount is very high.

A one-time tariff hike is impractical and it would be better to convert the dues to an annual impact based on, for example, a loan to cover expected payables. If we use a reference 10-year loan at 9.5% interest, that translates to 15.9% annual costs for ten years, based on an EMI-type annual equal repayment schedule. Thus, a theoretical one-time one rupee per kWh payable becomes a 10-year tariff hike of 16 paise. In reality the denominator will rise as demand grows so the effective impact would be lower. However, it’s evident that for some states, especially Jharkhand, Rajasthan and Meghalaya, the impact of these generator dues is still dramatic (last columns of Table 6), even after multiplying those numbers by 15.9%. This is one reason headline figures with total dues for a state are misleading – large states like UP and Tamil Nadu will always have larger dues, and normalisation is important.

It’s possible to put these figures in the context of DisCom losses, which are on a regulated (book value) basis, and consequently do not factor in dues (or receivables). PFC’s 2018-19 Report shows a gross input energy of 11,87,830 Million Units[22] (MU) of all distribution utilities in aggregate, which means it was purchased from suppliers, in 2018-19. For this power, they officially suffered a loss (with Tariff Subsidy Received but excluding Regulatory Income and UDAY Grant) of Rs. 85,803 crore, which translates into 72 paise losses per unit incoming; official loss numbers are lower as they factor in grants.

In contrast, if we calculate DisCom financial losses on the basis of units sold, which would then add distribution losses, then the denominator would fall to 891,109 Million Units sold, translating to losses of 96 paise/kWh. For the same year, the payables only towards power purchase as per PFC Report alone stood at Rs. 227,018 crore which converts to an equivalent one-time generator dues burden of 2.54 Rs./kWh of sales. Converting this to a 10-year payment (at 15.9% annually) means a tariff hike of 0.41 Rs./kWh overall. Adding other dues beyond those to generators makes this proportionally higher, almost double, even after adjusting the days payable to 45 days, instead of full liquidation (which corresponds to zero days). Thus, paying off the dues means the equivalent of doubling aggregate DisCom losses, unless one has a tariff hike (or external grant, which is difficult in these challenging times).

Importantly, we are not suggesting an across-the-board tariff hike to liquidate the dues as that would burden other (future) consumers for the failures of selected consumers and state governments – we are only indicating the scale of the problem. On the other hand, it is not possible to hold prior customers accountable, who should have borne the subsidy hike but did not.

Clearly, minimising any loan required means taking in all the receivables possible. But herein lie two problems. First, the inability to collect certain receivables pre-COVID, raises a question whether they can be paid down at all, let alone soon, in today’s environment. Perhaps a third of trade receivables are non-payments by government consumers. Second is the unique case of Regulatory Assets. [23] While they are listed as a receivable (see Table 4) and hence an asset, these actually require a tariff hike to be drawn down. This is because Regulatory Assets, by definition, represent a Regulator-ordained deferred increase in tariff. In contrast, when other receivables are taken in, it reduces any tariff increase required to liquidate dues.

Assuming that the Regulatory Assets are similarly liquidated over 10 years, and have a carrying cost of only 9.5% (which is much lower than what Regulators allow today), FY2018-19’s Rs. 50,301 crore Regulatory Assets translate to a 9 paise/kWh hike for these 10 years. Just like with subsidy (non)payments, this all-India average cost of liquidating Regulatory Assets has enormous heterogeneity across states. In fact, for 2018-19, just four states (Delhi, Maharashtra, West Bengal, and Karnataka) had all the Regulatory Assets between them![24] Thus, their deferred tariff hike is many times the 9 paise/kWh all-India average figure.

6.1. “Muddling along” may have worked…until COVID-19

As highlighted before, the near-term cash requirements of DisComs are measured in the multiple lakhs of crore of rupees, and “stimulus” loans only scratch the surface of the problem. The ostensible driver, payments to generators, in itself is about double the figure widely discussed. But before examining possible implications and solutions, it’s important to understand, ‘How did things get so bad?’

This problem didn’t happen overnight and has been in the making for years. The earlier solution, rather, equilibrium, was one of “muddling along”, where all sides delayed payments, and even generators have outstanding dues to their own suppliers. Such a game of musical chairs can’t end well, especially given COVID-19, which means the music has stopped. If FY2019-20 was more of the same (a steady but mild deterioration along historical trends), then FY2020-21, post-COVID-19 will be dramatically worse when it comes to DisCom revenues as well as state finances.

Up until now, rising volumes combined with rising prices were enough to keep a semblance of liquidity coverage, without fixing the solvency problem. Stated another way, we need to break the cycle where growing future revenues are needed to pay off the past. This is a trap similar to one faced by many builders in real-estate, where funds are required from pre-launch sales of new projects to pay off the costs of older projects. While it would take more than a balance-sheet level analysis, a possible analogy is where DisComs receive grants from the central government for projects, but don’t pay their vendors and non-generation suppliers on time.

A separate study (forthcoming) analyses whether another game is being played, where income statement losses are masked through balance sheet deteriorations. If a DisCom was not allowed to lose equity value, then operating losses would be even higher, or the state would have to chip in periodically. As we have seen, DisComs have taken a pseudo-“loan” by racking up large payables. In between FY2009-10 and FY2018-19, the payables for power grew at a CAGR of 18.20%, while total cost structure grew only 12.38% CAGR (and revenues lag the cost structure slightly).

This cannot continue, and regulators must clamp down on this practice that shifts the burden instead of solving the problem. An example of such a hidden loan comes from Other Current Liabilities, which have shown growth from Rs. 1,53,943 crore on March 31, 2017 to Rs. 2,18,441 crore in just two years, resulting in a CAGR of 19.1%. If some of these are vendors, don’t they have any recourse? While terms of contracts aren’t public, and it is unclear which heading these fall under, anecdotal discussions with suppliers indicate payments are perpetually delayed.[25]

In fact, generators are actually better off than many other stakeholders who owed money. For many power purchases, DisComs are liable to pay a late payment surcharge (LPSC) for non-payments to select GenCos (those with a PPA), and must meet their working capital requirements, which sometimes necessitates loans.[26] This is missing from many approved regulatory rate bases. As Footnote 20 pointed out, even after the reduction in LPSC after COVID-19 for tariffs under CERC purview, these charges are higher than loans. In that sense, isn’t formalisation of the dues via loans a good thing? In practice, GenCos are often willing to reach a settlement where they waive some or all the LPSC in return for getting paid sooner. Such adjustments are distinct from possible waivers or bailouts, which further disincentivise good behaviour, and represent moral hazard risk.

A macro-level look at the sectoral chain means dues to GenCos could lead to defaults on bank loans. After the RBI’s 2018 circulars, lenders have less leeway to negotiate around non-payments, with defaults automatically triggering insolvency proceedings after a time period. Compared to DisComs, GenCos, have a higher debt funding, more so for new capacity. Understanding heterogeneity amongst GenCos (public versus private), or state-wise variations is a separate discussion, but one distortion is that legal frameworks apply disproportionately along different segments of the electricity chain.

Even proposed Amendments to the Electricity Act 2003 seek to add in a new regulatory entity, the Electricity Contract Enforcement Authority (ECEA), to ensure payments to GenCos. However, this proposed entity has no mandate or loci to tighten up payments to the DisComs[27] – which creates a squeeze upon them. This asymmetry needs addressing – how to align risk and returns across the electricity value chain. Profitable generation and transmission, in some cases highly so, cannot sustain with increasingly squeezed distribution. The focus on timely payments to generators must be matched with a focus on timely payments to states for government electricity consumption and promised subsidies.

DisComs should not be viewed as wilfully negligent in their payment delays. The dip in ‘GenCos Dues’ in March of each financial year (Figure 3) shows one side of the coin – as states clear accounts and also give guidance, they often comply. On the other side, the obligations are continually rising both by accumulation as well as running (ongoing) obligations. Of course, this is not meant to gloss over their inefficiencies, or poor quality of service provision. On the other hand, they are perpetually cash-strapped, hitting their ability to not just deliver quality supply but also invest in system improvements. This is one reason many improvements have necessitated central government support through various schemes and programs over the years.

Formal accounts are important, but GST is a mixed bag for electricity. While there are many good reasons to bring electricity under GST purview, it’s ironically helpful to DisComs that electricity is presently outside GST purview. This is because under GST, raised bills immediately require tax payments, even if payments aren’t received. Perhaps GST would nudge a reduction in the dues game. GST implications for states would also be highly asymmetric, given the differences in use of coal across states, an input that is eligible for GST credit.

6.2. Recommendations

6.2.1. You’re going to need a bigger bailout (or loan)

The government needs to plan for a much larger loan package than announced, more so if COVID-19 creates prolonged cash flow challenges. This shouldn’t just be limited to a greater loan limit across India, but also new instruments that do not place all burden on the DisCom.

While one may want to equate receivables with short-term payables, they aren’t equivalent as cumulative receivables cannot be liquidated rapidly – they get accumulated over time. On the other hand, vendors and suppliers, including for generation, need payments more quickly. So do DisComs, but managing this is a political and policy challenge, not one DisComs can handle unilaterally. Even regulators, who manage items like Regulatory Assets, have normally not paid them down in a rapid manner, plus, of course, this only applies in a handful of states.

One option worth considering is rolling over short-term obligations into longer-term debt. It’s worth pointing out that the short-term debt (and even long-term) seen on the books dated March 31, 2019, are largely post the UDAY scheme, which offloaded a large fraction of debt to the state, and recast much of the remaining debt to lower interest rates. While interest rate arbitrage should always be considered, just like finding a cheaper home loan, spreading the loan out purely on liquidity grounds is also an important tool. Of course, this assumes a willing lender, at reasonable if not favourable terms. This should only be done in limited circumstances, where we find credible mechanisms to fix the problems of dues and insufficient tariffs.

Post-COVID-19, while basic life support (through the “stimulus” loans, for example) is important, the structural reforms required cannot be ignored. If we simply kick the can down the road, not only are we delaying the inevitable, we also add time, which, instead of diminishing the problem, makes it much worse given the trendlines of both income statements and balance sheets. This increases the risks of a hard landing.

6.2.2. Tariffs will need to rise

If we assume DisComs avail long-duration loans at reasonable terms, this will necessitate a measurable consumer tariff increase, which in the case of some states could exceed one Rs./kWh for 10 years. All discussions of AT&C loss reduction, while important and can reduce the loan required, don’t solve this problem.

Post-COVID19, this becomes tricky in several ways. Not only is the aggregate macroeconomic picture challenging, historically the balance of tariffs was based on overpayments by commercial and industrial consumers. Not only are they disproportionately hit by the lockdowns and economic slump, there is pressure to lower their tariffs for employment and competitiveness reasons. Thus, any aggregate increase in tariffs will have to, finally, include dedicated effort on raising the tariffs for the under-paying categories of consumers.

6.2.3. Real solutions will need structural reforms and aligning risks

While higher tariffs are one solution, they may not be sufficiently achievable given the magnitude of the problem. Even if these were, these are a solution within the existing framework. Instead, or perhaps in addition, we should also improve the frameworks.

Yes, DisComs are inefficient, not just in terms of AT&C but also quality of supply. Muddling along has been one reason that DisCom operations, planning, and investments haven’t been able to focus on areas like urban ones, where there is a willingness to pay more for quality supply.

The current exercise of DisCom ratings, carried out by ICRA and CARE rating agencies through PFC, should be updated to reflect not just assets and liabilities but also credible plans and tariff implications to resolve the challenges of payables (and receivables).

Post-COVID, if policymakers agree that we need to take a financial haircut, how do we share the pain equitably? The past structure disproportionately placed risks (and, simultaneously, low returns!) on DisComs. The lenders, generators, transmission, etc. will all need to be willing to share the pain. Else, returns risk remaining on paper only, as DisComs continue their spiral downwards.

The liquidity solution via “stimulus” loans explicitly makes the entire chain more asymmetric. Discoms bear the brunt of formalizing dues via new debt. But the underlying financial structure was always highly asymmetric. The March 31, 2020 regulated equity value of just NTPC (which probably covers under a quarter of generation in India) is Rs. 61,811 crore.[28] In contrast, the 2018-19 aggregate DisCom equity value inclusive of capital reserves is negative. Now consider both entities enjoying a regulated rate of return on their equity; DisComs have very little equity, and their returns are clearly not aligned with risks.

Ultimately, the solutions needed are more political than managerial or even regulatory, and this paper helps showcases the looming urgency. Most importantly, the sole focus cannot be on payables by DisComs, that too only on generator payments. New regulatory and policy mechanisms are needed to ensure payments to DisComs materialise (both subsidies and for electricity consumption), and the biggest gap remains from state governments.

An upcoming paper will attempt to better quantify the sources of losses for DisComs, as well as their balance sheets. The challenge isn’t just one of “don’t make losses”, we also need policies and regulations that answer the question, ‘If there is a loss, then what?’ At one extreme, like today, there exist circular outstanding dues. On the other extreme, dues can be formalised, such as fresh loans to pay off GenCos. There is a need to look for other equitable and viable instruments as well, ideally ones that incentivise improved performance, instead of a system with asymmetric risk, or, worse, socialisation of losses or inevitable bailouts.

6.2.4. Improving data and transparency is a low hanging fruit

There is an urgent need to increase the transparency and timeliness of accounts and data across the electricity chain, which means audited, regulatory-grade data, besides bringing all GenCo transactions with DisComs on a common platform or database. This is especially vital for the data for suppliers without a power purchase agreement (PPA), where both volumes and prices could have volatility. Said data should also break down more details including interest and late payment surcharges, other charges, etc. One option is to release quarterly data like many public companies do. A useful interim step would be to segregate bills and payments between current versus historical. After all, when payments are made, it would be important to know which are being made for “past sins” as opposed to present operations.

The ‘PRAAPTI’ portal is a great initiative in facilitating transparency of transactions. However, this initiative will achieve its goal only if all GenCo transactions with DisComs are brought on board. This needs to be done before attempting to enhance the data captured in terms of granularity, such as segregation of interest/LPSC, overdues, outstanding, other charges, etc. Ideally, reporting should also capture the status (existence and utilisation) of any Letter of Credit (LC) mechanisms, which were mandated in 2019 as a payment security mechanism for GenCos for power purchases outside the state. One other critical component, i.e., billed energy, is essential to analyse the impact of cash flow per unit —PRAAPTI today only captures rupees.

On the revenue side, greater breakdowns of trade receivables are important, especially segregating dues from state governments versus other consumers. Even for other consumers, a granular break-up across categories of consumers would be helpful given each segment may have to be tackled differently, in practice, especially for agricultural and residential.

The last need is for not merely income statements and balance sheets to be public, but also cash flow statements, which help us understand the picture beyond booked values (accrual accounting). Ideally, each project should have its own book of accounts. Else, funds from one source could be used to prop up gaps elsewhere. This exact issue was successfully tackled under the real-estate reform bill, RERA, which aimed to stem the almost ponzi-scheme flow of cash from advance sales for upcoming projects to cover costs of already paid-in-full (historical) projects.

6.2.5. One-size doesn’t fit all – we need flexible and innovative solutions

While there is a need for national policy consensus, the instruments needed should vary based on the particular circumstances. For extreme cases, we may require formal bailouts, since incremental improvements, refinancing, etc. may not be enough. As the data on dues, Regulatory Assets, and non-realisation of subsidies show, the national aggregate is usually concentrated in a handful of states. Thus, we need different targets (or more leeway) in tackling problem states.

As Table 3 shows, government dues for consumption vary by state and maybe a threshold system could treat egregiously defaulting states differently than others, to the extent that the Central Government may want to intervene using centre-state fiscal control as a backstop. After all, this instrument was harnessed in the past to handle state dues to NTPC. On the flip side, if we consider carrots instead of sticks, support mechanisms should not become a blanket bailout that writes off mismanagement or operational failures; where required, bailouts should be conditional.

Ultimately, fixing the DisComs isn’t an easy task. Just like with weight control, crash diets rarely work, more so when the fat was accumulated over many years. Like diet and exercise work better in tandem, there is a need to use all available tools to tackle this crisis. Not only has COVID-19 disrupted the status quo of muddling along, technology shifts are forcing change upon the entire DisCom equilibrium. So-called “paying customers” will be the first ones to leave the system for renewable energy along with storage and smart systems. If DisComs don’t improve, they would be relegated to the scraps of the future grid. In contrast, they could evolve to play a meaningful role in an equitable and efficient electricity system.

We thank a number of colleagues and domain professionals who have shared ideas and inputs, including some of the data. A number of experts, especially within the government and PFC, are not listed but we thank them for their clarifications to our queries. We have also benefited from comments and suggestions from Rakesh Mohan, Daljit Singh, and Vikram Singh Mehta, as well as the three anonymous reviewers. We also thank Rishabh Trivedi and Aditya Srivastava for their help with data compilation.

Support for this research was generously provided by the MacArthur Foundation. CSEP recognises that the value it provides is in its absolute commitment to quality, independence, and impact. Activities supported by its donors reflect this commitment and the analysis and recommendations found in this report are solely determined by the scholar(s).

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India finds itself in an increasingly dangerous world, one that is fragmenting and slowing down economically. It is a world in transition, one in which India’s adversaries state or non-state, or both as in Pakistan’s case are becoming increasingly powerful. If the external world is becoming more unpredictable and uncertain, so are internal politics and security in most of the powers. These are challenges that traditional institutions and state structures are not well-equipped to handle, mitigate, or solve. In this changing world, what are some of the basic and long-term drivers of India’s foreign policy which determine the overarching goal? What is India’s strategy to achieve those goals? What should India be doing?

Simply put, the task of India’s foreign policy is to protect and secure India’s integrity, citizens, values and assets, and to enable the development and transformation of India into a modern nation in which every Indian can achieve his or her full potential. The task of foreign policy professionals is to enable the transformation of India and to create an environment for that transformation.

At present, India should concentrate its efforts on strengthening itself, consolidating its periphery and external balancing.

India risks missing the bus to becoming a developed country if it continues business and politics as usual, or tries to imitate China’s experience in the last forty years, does not adapt, and does not manage its internal social and political churn better. Avoiding war and attaining one’s goals is the highest form of strategy by any tradition or book whether Kautilya, Sun Tzu or Machiavelli. And if India’s record over seventy years of independence is to be examined, it has not done badly in moving towards its main goal of transforming India.

Ultimately what should guide India is the quest to make itself a great power with a difference, namely, in a way which enables it to achieve Mahatma Gandhi’s dream of ‘wiping the tear from the eye of every Indian.’ That would be in keeping with India’s core values and national interest. That is the right objective for a great country like India.

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The aim of this paper is to provide a more complete picture of Chinese investment in India and to assess the implications of Chinese investment and acquisitions for India’s diplomacy, trade strategy, and security. Rather than attempt to provide a definitive figure, which is beyond this paper’s scope, the broader objective is to examine the growing stakes of Chinese companies in India and assess the implications for the relationship. This paper draws on MOFCOM data, publicly available information sourced from Chinese firms, press reports in China and India, and background information shared by Indian and Chinese officials. It is possible to estimate that the total investment from China exceeds official figures by at least 25%, and this is a very conservative estimate. When announced projects and planned investments are included, the total current and planned investment is three times the current figure, crossing at least US$26 billion. In greenfield investments and capital invested in acquiring or expanding existing facilities in India, Chinese companies have invested at least US$4.4 billion. Chinese companies have also invested in acquiring stakes in Indian companies, mostly in the pharmaceutical and the technology sectors, and participated in numerous funding rounds of Indian startups in the tech space. Another US$15 billion approximately is pledged by Chinese companies in investment plans or in bids for major infrastructure projects that are as yet unapproved.

These figures are likely an underestimation as there are several limitations in the exercise of mapping Chinese investments in India. For one, there is no exhaustive list or record of Chinese companies operating in India or their investments with either the Indian or Chinese governments. One reason is the routing of investments through different countries. A second is the different routes of foreign direct investment (FDI) into India, as a result of which complete FDI statistics are not available with a single government agency. Chinese ministries, on the other hand, may have more accurate country-wise data but tend to be less forthcoming in sharing it. Complicating the picture are investments from funds whose links to Chinese entities are difficult to ascertain. Another limitation is the inability to confirm whether stated investments by Chinese companies have materialised to the fullest extent. Verifying this is beyond this paper’s scope.

The first section of the paper, “Actors in China’s foreign policy”, looks at how China’s foreign policy is shaped by the growing weight and stakes of new actors, such as the private sector and provincial governments. The second section, “China Inc. and India” traces the changing strategies and interests of Chinese companies, both state-owned and private, in doing business and investing in India. The section on “Making in India” describes and analyses investments in five sectors: infrastructure, energy, automobiles, consumer goods, and real estate. The fourth section, “Buying in India”, looks at acquisitions focusing on the technology sector in particular. The last two sections examine the implications of this on India’s relationship with China and suggest five key recommendations for India’s trade and investment policy.

The paper argues that India needs to proactively engage with new actors in China’s foreign policy, particularly the private sector and the provincial state governments, where many decisions regarding trade or investment deals are made. India needs to reexamine and update its trade and investment strategy and better leverage the growing stakes of Chinese companies in the Indian market, if it wishes to more successfully pursue its trade objectives with China. The flush of investment from China’s private sector poses new challenges for India’s regulators and has underlined the need for a transparent, credible and predictable regulatory framework. In China, the boundaries between the state and private sectors are blurry at best, and some of China’s most prominent private technology companies, including those that are major investors in India, are playing key roles in advancing government initiatives at home, including in running an effective censorship regime.

This blurred separation between state-owned enterprise (SOE) and private enterprise raises the question of whether the Chinese private sector can indeed be considered as an entirely distinct entity from the state. This question becomes even more relevant with Chinese and other foreign firms acquiring controlling stakes in Indian companies, particularly in the technology sector where definitions of security or strategic implications are rapidly evolving. Rising investment from China certainly brings advantages both for the government of India, which is looking to correct a lopsided trading relationship, and for Indian companies in need of capital. This paper argues that while it is in India’s interests to enable this process through creating a friendly, open and predictable investment environment, the government will also need to more proactively safeguard longer-term considerations of security and privacy as it opens the door to new sources of investment.

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The Act East Policy remains the subject of considerable confusion both in India and overseas, for several reasons. First, it is not a doctrine spelled out in an official Indian government document, such as a white paper, although its contours are clearly discernible, including in speeches by senior officials. Second, the Act East Policy represents the rebranding of an earlier Look East Policy, which arose in the early 1990s. The differences between the two have not always been made clear. Third, the Act East Policy has often been lost amid a number of related, but distinct, strategic initiatives and concepts adopted not just by India but by other countries. There is particular confusion over India’s recent adoption of the Indo-Pacific strategic concept, its relationship with the separate “free and open Indo-Pacific” strategies of Japan and the United States, and conflation with the quadrilateral security dialogue (or “quad”) involving Australia, India, Japan, and the United States.

But in fact, the Act East Policy is rather specific about its ends, ways, and means. India’s Act East Policy evolved naturally from the Look East Policy as a direct consequence of the nature of China’s rise; the inadequacies of the regional security order in Asia; and India’s own growing capabilities, profile, and obligations. By “Acting East,” India can play a meaningful role in managing China’s rise, incentivising its evolution into a more transparent, market-driven, status quo-oriented, and norm abiding power. It can also help to shape the regional order in a manner that is advantageous to Indian interests. Act East consequently represents the securitization of India’s eastward engagement, reflects a wider scope that encompasses the Indo-Pacific region, and heralds a greater urgency. It is meant to preserve a favorable balance of power by ensuring a free, open, and inclusive Indo-Pacific. The Act East Policy has antecedents, and India can build upon its earlier history of leadership in Asia between 1947 and 1962.

Looking ahead, India’s Act East Policy will involve at least four elements. One, India will have to secure the Indian Ocean region against greater security competition through better maritime domain awareness, improved naval capabilities and presence, enhanced infrastructural and capacity development, and greater institutional leadership. This is at the core of Prime Minister Narendra Modi’s slogan for the Indian Ocean, SAGAR (“security and growth for all in the region”). Two, India will have to accelerate its diplomatic, economic, and military integration with Southeast Asia in order to preserve a stable balance of power in the region. This would complement attempts to preserve the institutional centrality of the Association of Southeast Asian Nations (ASEAN), but will also require working bilaterally with Southeast Asian countries on security, trade, and connectivity. Three, India will have to deepen its strategic partnerships with other countries that share its concerns about the manner of China’s rise, especially the United States, Japan, and Australia, but also France, Russia, and others. Fourth, India will have to manage relations with China, mitigating differences while seeking avenues for engagement whenever possible. Finally, in addition to continuing with ongoing efforts, India will need to prioritise a number of new areas, including regional trade, naval acquisition, overseas project implementation, defense exports, air connectivity, and foreign investment screening. The following paper provides an overview of historical antecedents for India’s reengagement with the region, outlines the driving factors for India’s Act East Policy, describes the conceptual evolutions of Act East and the Indo-Pacific, details the four elements of India’s Act East Policy to date, and, in conclusion, identifies priority areas for future Indian policy.

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Like every major country, India has a strategic community: a relatively small group of professionals who, in different ways, direct or influence India’s foreign and security policy. This strategic community includes career diplomats, bureaucrats, military commanders, and intelligence officers, as well as political leaders from the ruling party/coalition and the opposition. Additionally, reporters and commentators in the media, scholars at universities and think tanks, and members of the business community also play a role in shaping perceptions and influencing outcomes.

While general attitudes and areas of broad consensus can be discerned in a variety of ways, no systematic survey of India’s strategic community has been accomplished.

In an attempt to fill this gap, a survey of India’s strategic community was fielded in December 2018. Email invitations to participate in a 20-question survey were sent to 290 members of India’s strategic community from 14 December, 2018 onwards. Of those who received the email invitation to answer the SurveyMonkey questionnaire, 127 (44%) responded by 25 December, 2018. The survey was anonymous but linked to individual email addresses to ensure its integrity. The average time spent on the survey was seven minutes. Respondents were required to answer all 20 questions to successfully submit their responses.

The survey reveals some distinct trends concerning India’s biggest domestic and foreign challenges, its major global and regional partners, institutional and policy priorities, and variations across sectors and age profiles.

The survey reveals some distinct trends concerning India’s biggest domestic and foreign challenges, its major global and regional partners, institutional and policy priorities, and variations across sectors and age profiles. Here are some highlights from the survey:

71% of respondents believe that economic issues constitute India’s biggest domestic challenge. These include, specifically, (1) inequality and lack of opportunity and (2) insufficient skills, education, and employment. Addressing these deficiencies, including through sourcing external investment and financing, research collaborations, and the import of technology, are considered high policy priorities by India’s strategic community.

54% see China’s assertiveness as the most significant external challenge India faces. There are particular concerns about the China-Pakistan Economic Corridor and Chinese investment in the Indian Ocean. Only 2% believe that India should collaborate more with China in the event of greater U.S.-China competition. However, Chinese global dominance is not seen as assured and the strategic community considers the odds of a limited conflict between India and China unlikely.

75% perceive the United States to be India’s most important partner on global issues. Additionally, a large minority of respondents (43%) are in favour of closer collaboration with the United States in the event of greater U.S.-China competition. However, trade disputes and U.S.-Pakistan relations are believed to be constraining the India-U.S. partnership.

74% believe the Indo-Pacific is the dominant framework for India’s extended neighbourhood. The Indian Ocean, South Asia, and Southeast Asia are the regions of chief importance for Indian interests and the East Asia Summit is considered by the largest number of respondents to be a very important institution for Indian interests. Regional connectivity with South and Southeast Asia and maritime investments are considered among the top foreign policy priorities for India.

Views are varied concerning engagement with Pakistan and partnerships in West Asia. There are competing clusters of opinions concerning engagement with Pakistan’s military, civilian government, and civil society. Opinion is also divided as to whether Israel, the United Arab Emirates, Iran, or Saudi Arabia is India’s most important regional partner in West Asia.

Certain historically dominant institutions, regions, and issues are now low priorities. These include: the South Asian Association for Regional Cooperation (SAARC), Non-Aligned Movement (NAM), and the Commonwealth; developments in Europe, Africa, and Latin America; and nuclear and missile modernisation, foreign aid, and cultural diplomacy.

Those who believe that India’s most important global partnership is with Russia reflect divergent views on a number of other issues. While only a minority (12%), they are more likely to advocate remaining equidistant between the United States and China in the event of greater competition, believe Iran is India’s most important partner in West Asia, and prioritise the Shanghai Cooperation Organisation and BRICS in India’s institutional engagements.

Minor differences are discernible between the attitudes of decision-makers and influencers. Current and former members of the military, civil services, and political parties exhibit slightly greater wariness about engaging Pakistan than academics, think tank experts, and members of the media. They also deem military interventionism in India’s neighbourhood as more likely and place a marginally higher priority on defence industrialisation and the import of technology over incoming economic investment.

There are some clear differences in attitudes across age cohorts. Those born before 1960 attribute greater importance to the United Nations and do not prioritise an expansion of India’s diplomatic capacity. Those born between 1960 and 1979 generally place a greater priority on the partnership with the United States and on trade issues. Finally, those born after 1980 are more comfortable with the concept of the Indo-Pacific and are less likely to believe that sectarianism and identity politics constitute India’s major domestic challenge.

Strategic elites hold similar views to the Indian public except on Pakistan (and to a lesser extent on China). A comparison with a similar survey of Indian public opinion conducted in March 2017 suggests India’s strategic community shares similar views on international partnerships with the United States, including in the context of U.S.-China competition. However, the public appears to be more critical of Pakistan and slightly less concerned about China than elites, although different methodologies and timings make exact comparisons difficult.

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In 2014, India unilaterally announced plans to quadruple Renewable Energy (RE) to 175 GW by 2022, an ambitious target that required an annual growth (CAGR) of over 25 percent. Since then, growth has exploded, especially for grid-scale solar power, which is meant to be 100 of the 175 GW RE targeted.

Until recently, RE was a limited if not a fringe player even in FY2017 its share of overall generation was only 6.7 percent at a gross level, but the share is rising rapidly. Per targets, this would reach over 19 percent of total demand by 2022.  Despite this growth, and the high targets India has set its sights on, a previous Brookings research report points out that there are significant political and economic contradictions that may hinder these dreams from turning into a reality.  This paper examines grid integration as a subset of challenges for scaling RE, with financing, contracting, regulation, market design, technology risks, etc. as other issues that will impact the growth trajectory.

The challenges of grid integration for higher RE

Rapid growth in renewables poses challenges for grid operations and has various implications on the finances of distribution companies (Discoms), consumer tariffs and incumbent power generating companies, especially traditional thermal power plants. Integrating renewables at this scale with limited impact on tariffs, minimised curtailment rates, and with stable grid operations will require careful technical studies and discussion of tradeoffs, instruments, and risk-allocation.

In this paper, we focus on some of the major knowledge gaps when it comes to planning for and adapting to the rapid expansion of renewable energy power in India. We begin by giving an overview of the power grid in India, and what the broad challenges of RE integration are. We identify major questions that need to be addressed by the government and the energy policy research community in terms of understanding the system-level costs of RE.

Rapid growth in renewables poses challenges for grid operations and has various implications on the finances of distribution companies (Discoms), consumer tariffs and incumbent power generating companies, especially traditional thermal power plants.

There haven’t been sufficient studies on grid integration, especially ones that combine optimisation, economics, and risk. The Greening the Grid (GTG) study was a ground-breaking effort in this direction, with multiple stakeholders providing inputs and experts across the US and India collaborating. We examine that study to tease out what is or isn’t said (or assumed), and what research and planning focus should be next.  We find that integrating high RE into the grid isn’t merely a technical challenge, but one that also faces institutional challenges exacerbated by the fact that RE potential is concentrated in a handful of states in India.

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Studies and planning for higher RE

Future studies should build on the GTG analysis by incorporating more data which need to be publicly available. First, states must collect and integrate RE generation data, including backing down (curtailment) with granularity. Second, there must be a systematic and framework aligned analysis to quantify the “hidden” (rather, systems-level) costs of RE. This must clearly incorporate the economics and contractual issues. Ultimately, optimisation studies would become inputs to the next effort of determining the best instruments for managing these system-level costs, ranging from ancillary services, to storage, to Time of Day pricing, etc. It may even involve payments or compensation mechanisms to states that bear a disproportional burden for RE.

At some point, future studies will have to go beyond 15 minute intervals, not just because of ramping issues in short timeframes but also because of grid concerns on transients and stability. Few models can capture unknown risks and low-probability events, such as fuel supply disruptions or shortages of water for cooling towers, and so these remain unavoidable concerns that strengthen the interpretation of any optimisation model to be “best-case”.

Yes, 175 GW RE can be integrated at a national level without major storage needs, but even this will involve more transmission across longer distances. The real challenge comes after, when RE grows far higher.

Yes, 175 GW RE can be integrated at a national level without major storage needs, but even this will involve more transmission across longer distances. The real challenge comes after, when RE grows far higher. The 175 GW target is mostly one that relies on low-hanging fruit of variable RE.  Further scaling, towards deep decarbonising of India’s electricity system, is a hard task, and one that will require a host of technical, policy, and regulatory improvements spanning storage, time of day pricing, and flexibility of both operations and of power purchase agreements.

Ultimately, the question of integrating RE isn’t going to be “can we?” but rather “how best can we”?

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The post Complexities of integrating Renewable Energy into India’s grid first appeared on CSEP.

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This paper explains the basic concepts of product space analysis and works with the data provided by the Atlas of Economic Complexity that reflect these concepts, i.e. ease of moving into production and export of another “nearby product”, the consecutive chain of domestic capabilities that can be developed by moving into a nearby product and the linkages between products and capabilities that will help sustain export diversification. This paper combines these concepts and data based on product space analysis with several policy objectives to identify sectors or product categories whose exports could be emphasised to achieve the largest impact in terms of the objectives concerned.

These products are identified in terms of improving both exports in general as well as exports to specific major markets. In this context, a simple method is discussed in this paper to identify products whose exports could potentially increase if non-tariff barriers faced by them are addressed in major markets. This effort provides a basis to develop a bilateral dialogue with selected countries to improve the operational conditions faced by Indian export when they seek market access abroad and to develop a basis for regulatory coherence and cooperation.

Trade policy for promoting exports includes both policies at the border (tariffs, quotas and customs procedures) and policies within the border (standards, regulatory regimes, policy procedures for getting approvals, subsidies and other forms of support, skill enhancement).

With an increase in global value chains and trade in services, facilitating rather than restrictive policies have been found to be better for improving cost-efficient quality production and competitiveness.

The policies under both these categories can be broadly identified as either restrictive policies or facilitating policies. With an increase in global value chains and trade in services, facilitating rather than restrictive policies have been found to be better for improving cost-efficient quality production and competitiveness. There may, however, be a need for restrictive policies in certain instances. In that context, it is suggested that the decision be based on transparent and objective analysis of the impact of such policies, and if a restrictive policy is to be implemented then it should be done on a temporary basis, reducing the restrictiveness of the measure over time, with the restrictive policy being removed in a time-bound manner.

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The post Product space analysis and industrial policy: Identifying potential products for India’s export expansion & diversification first appeared on CSEP.

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India’s decision to adopt a new Model Bilateral Investment Treaty (BIT) especially in light of the growing debate on how to reconcile investment protection with host state’s right to regulate should be welcomed. After foreign investors sued India under different BITs, India realised that broad and vague investment protection standards can be interpreted in manners that give precedence to investment protection over the host state’s right to regulate. The fact that India has adopted a new Model BIT that continues to give the right to foreign investors to challenge India’s regulatory measures under BIT shows India’s continuous engagement with the investor-state dispute settlement (ISDS) system unlike countries like South Africa and other Latin American countries. However, India has significantly altered the terms of this engagement.

India has not been quite successful in developing a model that balances investment protection with the state’s right to regulate.

India claims that the change in the terms of this engagement is to strike a balance between investment protections with host state’s right to regulate. However, this paper shows that barring the Model BIT, India has not been able to reconcile the interests of foreign investors with the host state’s right to regulate. The Model BIT contains a narrow definition of investment, an extremely narrow fair and equitable treatment-type provision, excludes Most Favoured Nation clause and taxation measures from the purview of the BIT. Furthermore, it provides for a general exception provision without a chapeau and contains a complicated and sequential ISDS. The presence of these provisions makes the Model BIT pro-state with limited rights to foreign investors.

Furthermore, although the attempt of the Model BIT is to reduce arbitral discretion, as the discussion shows, many provisions still remain undefined and vague; thus, continue to grant significant discretion to ISDS arbitral tribunals.

Therefore, our analysis shows that India has not been quite successful in developing a model that balances investment protection with the state’s right to regulate nor in reducing arbitral discretion. In view of this, this paper suggests how these goals could be achieved by providing alternative formulations.

Indian BIT practice needs to evolve keeping the following in mind: First, India’s desire to increase foreign investment inflows, especially under government initiatives like Make in India. The paper explains there is evidence to show that BIT regime in India has played an important role in attracting foreign investment. Further, even globally, many studies show the positive relationship between BITs and inflow of foreign direct investment (FDI). Second, the significance of BITs for foreign investors in India also assumes importance due to larger goals of good governance and pursuit and strengthening of rule of law. Having a balanced BIT regime would also help in improving the perception of foreign investors that it is easier to do business in India and that in case of undue regulatory interventions, they could rely on promises made under international law to safeguard their investment.

Third, India is not just an importer but also an exporter of capital. India’s overseas FDI has increased from less than $1 billion in 2000-01 to more than $21 billion in 2015-16. A BIT that tilts towards the host state’s regulatory power will reduce protection for Indian companies abroad.

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The post India’s model bilateral investment treaty: Are we too risk averse? first appeared on CSEP.

As a market, India sells only a fraction of electric two-wheelers (E2Ws) and four-wheelers (E4Ws) annually as the aggregate two- and four-wheeler sales daily. In the absence of any significant deployment, it becomes difficult to plan and prioritise on a large-scale based on learnings. This is especially true in case of a transition to EVs, which has several wide-ranging ramifications related to urban infrastructure, manufacturing transitions and learning curves, grid planning and behavioural shifts.

This paper is set in the context of the electricity grid-level impact of EVs and the drivers and fallouts from a large-scale transition to EVs, based on the recent findings of an ongoing study by the authors. Through this paper, we also intend to explore specific aspects related to peak coincidence of EVs’ demand and Time of Day (ToD) aspects, heterogeneities between private and fleet vehicle charging behaviour and requirements, local issues of distribution capacity, carbon and grid utilisation co-benefits, tariff design strategies and fiscal implications of powering mobility.

We find an enormous divergence between energy (kWh) and load capacity (kW) implications of EVs. This is likely to be unmanageable under the conventional approach to capacity expansion, both on a technical level as well as a regulatory/pricing model. Regardless of the exact volume (share) of EVs in 2030, the grid impact can vary–between theoretical worst case scenario of when all EVs are plugged in simultaneously to a best case scenario of charging spread out as much as possible–with a ratio of over 50 times. The reality will be somewhere in between, based on several unknowns as discussed later. Normal grid loads today have an annual aggregate load capacity to effective capacity used factor of nearly five; for EVs this can vary between 80 and 160, based on the sales mix, duty cycle, and charging speeds. ToD pricing, local congestion signalling, and similar measures can play a crucial role in synergising the EVs to the electricity grid.

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The post Electrifying mobility in India first appeared on CSEP.

More recently, there has been another challenge that creates problems for discoms: in some states, large consumers are using OA to switch frequently between the market and the discom’s regulated tariffs. This behaviour creates greater volatility in the load to be served by the discom, which makes power procurement planning difficult for the discom and can also lead to stranded generation capacity. Such behaviour by large consumers is likely to further harden the resistance to OA by discoms.

In order to tackle the problem of frequent switching, this Brookings India Impact Series paper suggests redefining consumer choice. It also notes the mismatch in the perspectives of the Centre and the states about the power sector and recommends that one recognises it. While the Centre is more focused on creating a vibrant power market, the paper notes, the states have more immediate concerns – “ mostly about affordable tariffs, an issue that has electoral and political repercussions.

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The post Newer Challenges for Open Access in Electricity first appeared on CSEP.

This paper examines whether Delhi’s power subsidies are efficient or expensive for the government, and therefore the taxpayer.

Key Points

• The Government of Delhi’s household electricity subsidy is amongst the most generous in India. With eligibility based on how much you consume, the upper bound threshold for availing subsidies is so high that on average about 80 per cent of households qualify for a 50 per cent taxpayer subsidy. In some months, this goes as high as more than 95 per cent of households. This is beyond cross-subsidies approved by the Delhi Electricity Regulatory Commission (DERC) in the tariffs that keep household power prices lower than the cost.
• The subsidies are regressive – mid-level consumers of power, ostensibly the middle classes, enjoy more benefits on a percentage basis than the lowest consumers (the poor). The lowest tier, on average, gets under 33 per cent net billing subsidy, while those using a little under the limit get over 40 per cent net subsidy.
• The average household subsidy varies from a little over INR 1,000/year for those who consume up to 100 units per month to over INR 9,000/year for those whose consumption is 300-400 units per month.
• Altering the subsidy rules only slightly can save significant money, while still offering benefits to targetted segments of the population. For example, lowering the threshold of maximum monthly consumption to be eligible for the subsidy from 400 to 300 units per month results in almost 30 per cent taxpayer savings while reducing coverage by only about 13 per cent. Going to 200 units a month still covers over half the population (compared to 80 per cent today) but can save two-thirds or about INR 1,000 crore per year.

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The post Delhi’s household electricity subsidies: High and inefficient first appeared on CSEP.

One needs a feasible roadmap for installation of required equipment, the authors recommend, in addition to improvements in norms that incentivise if not mandate dispatching cleaner coal first. This requires a multi-stakeholder discussion as soon as possible, bringing together not just power plants and the government but also state utilities and grid operators.

This paper draws from a related discussion on lessons between Brookings India Fellow Rahul Tongia and UC San Diego scholar and environmental policy expert Deborah Seligsohn from China for India’s new power plant pollution norms. The discussion is available online in the form of a video.

The post Challenges, recommendations for meeting 2017 norms for air pollution from thermal power plants in India first appeared on CSEP.

Highlights of Main Findings

• India’s design capacity in the number of patents granted is approximately 3 percent of China and less than 2 percent of the U.S.A.
• India’s industrial design capacity is approximately 1 percent of China and 6 percent of the U.S.A.
• Historically, non-resident entities have been granted the most number of patents within India.
• Since 2012, more patents have been granted to Indian entities abroad than the number of patents granted by the Indian government to either resident or non-residents entities within India.
• While in India and the U.S.A. the most number of patents are annually granted to non-resident entities, in China the most number of patents have been granted to resident Chinese entities since 2008.
• Among the broad economic factors that affect design economy in India, the role of higher education, FDI, digital connectivity, infrastructure and trade have been identified as the most important.

Some specific policy recommendations to boost design economy in India are:

• Curricular reform for research and development in higher education
• Workforce development for R&D sector
• Establishing design labs and special economic zones to focus on R&D
• Developing and enforcing domestic legislation for intellectual property protection
• Promoting greater collaboration between business, government, and academia

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The post Paper | Building a Design Economy in India first appeared on CSEP.