Instruments to Mitigate Financial Risk in Indian Renewable Energy

Stanford Precourt Institute for Energy | Clean Energy Finance

Instruments to Mitigate Financial Risk in Indian Renewable

Energy Investments

Gireesh Shrimali,

Research-Fellow, Steyer-Taylor Center for Energy Policy and Finance, Stanford University

Dan Reicher, Executive Director, Steyer-Taylor Center for Energy Policy and Finance, Stanford University

Introduction

AS A KEY component of its Nationally Determined Contributions (NDC) under the Paris climate

agreement, India has committed to ambitious renewable energy targets, of 175 GW by 2022. This includes

100 GW of solar, 60GW of wind, and 15 GW of other sources such as biomass. The 100 GW of solar target

is further divided among 60 GW of utility scale solar and 40 GW of rooop solar.

Based on these targets, and assuming that these

targets will be met in a linear fashion (i.e., equal

capacity installation per year), using forecasted

costs of renewable technologies, this would require

approximately $189 billion of additional investment,

including $132 billion of debt and $57 billion of equity.

Among technologies, solar energy would require

approximately $131 billion, wind energy would require

approximately $51 billion and other technologies

the rest.

Although there are some rosy “best case” scenarios

for access to capital, in the expected scenario, the

debt shortfall would be 27% and the equity shortfall

would be 41%. This requires investigation of alternative

sources that may help fulfill this gap.

We find that institutional investors will be key to

reaching India’s ambitious renewable energy targets.

Institutional investors – insurance companies,

sovereign wealth and pension funds, and university

and foundation endowments – are a potential source

of capital that can help fulfill approximately 50%

and 100% of the expected debt and equity gaps

respectively. Preliminary investigation reveals that

the basic requirements of these investors – long-term

steady returns – match those provided by renewable

projects.

However, given the current policy and institutional

environment in India, these institutional investors –

both domestic and foreign – are currently unlikely to

meet the requirement due to multiple risks, including:

foreign exchange, o-taker credit, regulatory/policy,

etc. Further, these investors face an uncertain business

environment and lack of trusted intermediaries.

Addressing these risks and barriers would go a long

way towards ensuring India’s renewable energy goals

receive the required level of investments.

In Section 1 of this paper, we examine these investment

barriers to get a sense of relative priorities and help

inform appropriate targeting of risk. In sections 2 and

3 we then dig a little deeper into potential solutions for

the top two risks – currency (Section 2) and o-taker

(Section 3). We recognize that both of these risks will

OCTOBER 2017

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need longer-term solutions, however given that India’s

renewable energy targets extend only over the next five

years; our focus in this paper is on short-to-mid-term

solutions. Section 4 concludes with policy implications

and suggestions for future research.

1. BARRIERS TO RENEWABLE ENERGY

INVESTMENT

There are many barriers to clean energy investment

in India. We classify the barriers under the following

categories: financing, completion, operational, and

others (Sen et al., 2016). These can be further sub-

classified as below in Table 1.

We find that currency and o-take risks are the biggest

risks based on discussions with 9 foreign investors in

late-2015/early-2016,

where we asked the investors to

assign scores out of 10 regarding risk. Table 2 indicates

that currency and o-take risks are at least twice as

highly rated as other risks. A similar discussion with

domestic investors reveals that o-taker risk is the top-

rated risk. Therefore, we focus mainly on these two

risks in this paper.

BARRIER BRIEF DESCRIPTION

Financing

Foreign exchange risk Currency risk due to uncertain currency movements and high cost involved with market based currency hedging

solutions.

Oaker credit risk The risk that the buyer/o-taker will not fulfill its contractual obligations. It is a key contributor to the overall

credit risk of a power project.

Quality of renewable energy

Projects

The credit rating of the operational renewable energy assets may be low overall, leading to operational assets not

meeting investment criteria.

Lack of instruments for

investment

Lack of financial instruments (or pathways) – illiquid or liquid – to invest in renewable energy.

Low returns compared to

expectations

Renewable energy projects not being able to meet the risk-return expectations of investors.

Limited availability of debt

capital

Limited availability of debt capital due to capital market conditions, either domestically or internationally.

Completion

Construction risk Risks related to increase in overall financing cost due to construction related issues – esp. due to delays in

construction due to permitting.

Land acquisition issues Issues faced in land acquisition, esp. if there is no single window clearance in place, or if the time taken to obtain

clearances is high.

Transmission evacuation

The lack of availability of transmission evacuation infrastructure, and time taken to get the clearances and

permitting.

Operational

Curtailment issues Wind developers may face this issue during high wind seasons when higher than expected generation creates

oversupply situations as well as congestion.

Contract enforceability risk Drastic reduction in cost of solar power generation may result in poor contract enforceability in the long-term.

Others

Lack of trusted intermediaries Lack of trusted financial intermediaries may result in new and/or smaller investors staying away from the sector.

Limited understanding of

sector

Many investors are not aware of renewable energy sector and, therefore, prefer to make investments in

mainstream asset classes.

Regulatory/policy risk The risks related to uncertainty in availability of incentive schemes, poor implementation of policies and non-

uniform policies across states.

Net metering policies The net metering policies across states may lack coherency as well as poor implementation.

TABLE 1: Risks faced by investors in renewable energy projects in India

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We had follow-up discussions with 5 foreign investors

in mid-2017 to verify these findings.

These follow-up

discussions confirmed the earlier findings related to

the high importance of currency and o-take risks.

2. THE CURRENCY (OR FOREIGN

EXCHANGE) RISK

We find that, to achieve India’s renewable energy

targets cost-eectively, more debt is required at

attractive terms – i.e., with reduced costs and extended

tenors (Shrimali et al., 2013). High costs (more than

12%), short tenors (less than 10 years), and variable

rates (as opposed to fixed), end up increasing the cost

of renewable energy in India by 24-32% compared to

renewable energy projects elsewhere (Shrimali et al.,

2013).

Foreign loans (e.g., in USD) appear attractive for Indian

policymakers, given that seemingly cheaper (e.g., 5-7%

USD), longer-term (15 years or more), fixed-rate foreign

loans have the potential to not only reduce the cost

of renewable energy significantly but also reduce the

cost of government support by making renewable

energy more competitive with fossil based-electricity

(Shrimali et al., 2013; Shrimali et al., 2017). This raises

the question as to why developers just don’t borrow in

USD, and the answer is foreign exchange rate risk, as

described below.

The reason that foreign exchange risk is an issue is that

renewable projects earn revenues in local currency

(e.g., in INR), when financing a renewable energy

project by a foreign loan (e.g., in USD), the mismatch

in the currency of debt obligations (i.e., USD) and

currency of revenue (i.e., INR) exposes the project to

the risk of devaluation in INR over time. This can result

in reduced investments in the country due to currency

risk,

necessitating the use of a currency “hedge” (or

currency “swap”)

with a third-party provider to protect

against these devaluations.

Market-based currency hedging solutions are not only

limited in availability (e.g., beyond 5-years) but also are

expensive in India, increasing the final cost of debt, and

almost entirely eliminating the benefit of seemingly

cheaper foreign loans. For example, the typical cost

of currency hedging in India is around 7% per year

(Bloomberg Terminal, 2017), making completely

hedged foreign loans as expensive as domestic loans –

i.e., at 12-13% (Shrimali et al., 2013).

Further, depending on the credit risk of the borrower,

additional credit-risk premium may increase the cost of

currency hedging by another 100bps.

Credit risk is the

risk that a party to the swap agreement will default on

its obligations. Currency swaps have high exposure to

credit risk as they involve the exchange of money (e.g.,

USD and INR) over an extended period of time. Since

a premium is charged for default risk, currency swaps

lead to a double counting of credit risk as the borrower

already pays a credit risk premium for the underlying

debt to the creditor.

Governments need to recognize the role that cheaper

currency hedging mechanisms could play in expanding

renewable energy capacity. Further, there is an

argument that governments should bear currency risk

in some strategic situations. One main reason is that

macroeconomic conditions are key drivers of currency

TABLE 2: Scoring of risks faced by investors in

renewable energy projects in India

RISK/BARRIER SCORE (OUT OF 10)

Currency 8.33

O-taker 7.11

Regulatory/policy 3.89

Unfavorable returns 3.0

Transmission and evacuation 2.78

Land acquisition 1.78

Cost of capital 0.89

Availability of debt 0.78

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movements and related foreign exchange rates, and

government policy, in turn, influences macroeconomic

conditions.

In case of India, another strong argument for

government-sponsored currency hedging solutions

is that bearing the currency risk for renewable energy

today osets the currency risk the economy would

have borne in future on purchasing imported fossil

fuels that the renewable energy would displace. This

is particularly relevant for imported coal, which is the

marginal fossil fuel that additional renewable energy is

likely to replace (Shrimali et al., 2016).

Given that currency depreciation is a direct consequence

of macroeconomic conditions, such as inflation, the

long-term solution to control currency risk is to reduce

inflation via sound macroeconomic policy that, for

example, targets disciplined government spending

and borrowing. However, controlling inflation may not

always be possible in a fast growing economy such as

India and, therefore, short-term fixes may be required.

Multiple solutions may be possible in the near term.

One potential solution is to use a structure where

public money is used to provide a buer against the

risk of unexpected currency movements (Section 2.1).

2.1 Foreign exchange hedging facility:

Using a risk buer

In providing currency hedging solutions for renewable

projects, we need to consider the following questions:

first, what are the expected costs of providing such

hedging solutions? Second, how can the risks related

to unexpected and extreme movements in foreign

exchange rates be managed? Third, what is the market

risk premium for taking these risks? We provide insights

into these questions by examining a government-

sponsored foreign exchange rate hedging facility

(“FXHF”).

Under an FXHF, the government would provide project

developers or o-takers a currency hedging solution

through a standalone fund that covers debt payments

for underlying USD loans. In this case the government

is not providing a sovereign guarantee,

but rather is

pre-committing public money for creating a standalone

fund that can be used to provide cheaper currency

hedging solutions. As we will see below, the FXHF

provides an indirect way to subsidize currency hedging

without providing an explicit (or direct) subsidy.

We explain the working of the FXHF for a local currency

power purchase agreement (PPA). Under a local

currency power purchase agreement, the project

developer borrows in foreign currency (i.e., USD) and

therefore, the foreign exchange risk exposure is borne

by the project developer. In this case, the FXHF can

enter into a swap – via a “contract for dierences (CFD)”

– with the project developer.

Under a contract for dierences, the two counterparties

– FXHF and developers – would sign a contract at a fixed/

initial foreign exchange rate and, over time, exchange

payments for the dierences between the actual and

the contracted foreign exchange rates (see Figure 1).

The frequency of this payment would be similar to debt

payment obligations of the project developer.

FIGURE 1: Cash flows in a local currency PPA

[Source: Farooquee and Shrimali (2016)]

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For example, when the fixed/initial rate is 1 USD = 63

INR, then, at fixed periods when debt payments are

due, if the foreign exchange rate is higher than 1 USD

= 63 INR, the FXHF would make a net payment to the

project developer. This net payment is equal to the

dierence of a variable payment (USD debt payments

at the actual/current foreign exchange rate on the day)

from the FXHF to the developer and the fixed payment

from the developer to the FXHF (USD debt payments at

the contracted foreign exchange rate of 1 USD = 63 INR).

In the reverse situation, if the foreign exchange rate is

lower than 1 USD = 63 INR, the project developer would

make a net payment to the FXHF.

The final design of the FXHF would depend on the

underlying mix of loans. Here we provide an indicative

analysis based on assumptions from primary and

secondary research. We assume that the underlying

USD loan is at 5.5% and for 10-years. We also assume

that the market cost of providing a 10-year USD to INR

currency swap would be 7 percentage points.

We start with the first question: what are the expected

costs of providing such hedging solutions? Our analysis

reveals that the expected cost

– or the average cost

across all potential outcomes represented by our

probabilistic model – to provide a 10 year currency

hedge via the FXHF is approximately 3.5 percentage

points per year, 50% below market rates. This is what

the FXHF would charge the developer.

However, governments should be aware of the risk

exposure of the FXHF. That is, they should be aware of

what would happen to the FXHF if the Indian currency

depreciates more than the expected value and that

also in extreme ways. The FXHF would need to manage

this risk; a risk that is typically managed by market.

We therefore examine the second question: how can the

risks related to unexpected and extreme movements in

foreign exchange rates be managed? One way to protect

against this risk, and to ensure that the FXHF does not

default, is to use a capital buer. Based on our analysis,

for the FXHF to achieve India’s current sovereign rating

of BBB-,

the cumulative capital buer requirement for

10 years would be almost 30% of the underlying loan

amount; that is, with a leverage of approximately 3.

A potential solution to avoid such large public

commitments is to use a structure where public

money is used to provide protection against currency

devaluation in particular range, via a market based

instruments such as currency options (Farooquee et

al., 2016a). This approach shows that much higher

leverages (up to 10) for public money can be achieved.

The government should also be aware that the expected

cost of the FXHF of 3.5 percentage points doesn’t take

into account the market cost of a capital buer – i.e.,

the risk-premium that the market would place on

taking the risk of unexpected and extreme movements

in foreign exchange rates, and maintaining this capital

buer.

We therefore examine the third question: what is the

market risk premium for taking currency risks? Using

foreign exchange option pricing theory, we explicitly

calculate the risk-premium as 2.76 percentage points,

which largely accounts for the dierence between

the cost of currency hedging in the market and the

expected cost of the FXHF. That is, the government is

indirectly subsidizing the FXHF by keeping the capital

buer but not charging for the risk it mitigates.

3. THE COUNTERPARTY RISK

The counterparty risk is related to the risk of non (or

delayed) payment by the power purchaser (also known

as the o-taker) to the power producer. From a lender’s

perspective, this results in the power producer missing

the debt payments. The typical power purchasers in

India are the public-sector, state-level distribution

companies, also known as DISCOMs.

Figure 2 shows the main components, with arrows

depicting the flow of energy and money flowing in the

reverse direction. In this structure the main problem

lies with the DISCOMs who, due to their poor financial

health, regularly delay payments.

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FIGURE 2: Flow of electricity

For example, during 2014-15, the DISCOMs had booked

cumulative losses on the order of INR

633 billion (Power

Finance Corporation, 2016), for two reasons. The first

is economic – the DISCOMs do not even recover costs

due to power taris being kept artificially low because

of political pressures: in the same year, the average cost

of purchase of power for the DISCOMs was INR 5.20/

KWh whereas the average consumer tari was INR 4.62/

KWh. The second is operational – in the same year, the

aggregate transmission and commercial (AT&C) losses

stood at 24.62% (Power Finance Corporation, 2016).

This poor performance results in a combined negative

net worth of DISCOMs at INR 1,164 billion as on March

31, 2015, with loans outstanding at INR 6,730 billion,

receivables outstanding against banks at 92 days, and

receivables outstanding against Independent Power

Producers at 121 days. The receivables outstanding

Tamil Nadu FIT was

INR 7 / kWh

FIGURE 3: Auction prices in recent auctions

gap clearly indicates that power producers are exposed

to the risk of the poor financial health of the DISCOMs

and the consequent risk of delays and/or defaults in

payment.

In fact, state DISCOMs have a history of delaying

payments to independent power producers (IPPs) by

up to as much as 24 months. This poses a direct risk to

the ability of IPPs to meet their credit obligations and

exposes debt investors to default scenarios. This causes

banks and other debt providers to limit their investment

to the renewable energy sector or otherwise raise the

cost of debt provided.

The higher cost of capital available to the IPPs may

ultimately result in higher power taris (Figure 3). This

has been evidenced in recent solar auctions, wherein

the PPA prices are always lower when the well-rated

National Thermal Power Corporation (NTPC) is the o-

taker. For example, a state auction held in Karnataka

resulted in an average price of INR 5.07 per kWh while

a NTPC auction - also held in Karnataka - achieved a

price of INR 4.78 per kWh, equivalent to a saving of INR

0.29 per kWh (Bridge to India, 2017).

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The long-term solution to o-taker risk lies in proper

management of the DISCOMs, where states assume

full responsibility of running the utilities on sound

commercial principles (Ministry of Power, 2012). A

comprehensive set of measures is required to do so,

including financial restructuring, tari setting, revenue

realization, subsidies management, metering, and audit

and monitoring. In the past, the central government has

introduced many schemes for financial restructuring

of DISCOMs, but none of them have produced the

intended outcomes.

The most recent example is a financial restructuring

scheme called UDAY (Indian Express, 2015). The

scheme involves four initiatives: improving operational

eiciencies of DISCOMs; reducing the cost of power;

reducing the interest cost of DISCOMs; and enforcing

financial discipline on DISCOMs through alignment

with state finances. UDAY allows state governments,

which own the DISCOMs, to take over 75 percent of

their debt and pay back lenders by selling bonds.

DISCOMs are expected to issue bonds for the remaining

25 percent of their debt. The scheme aims to achieve

a reduction of average transmission and commercial

(AT&C) loss to 15% by 2018-19 as well as a reduction in

gap between average cost of supply (ACS) and average

revenue realized (ARR) to zero by 2018-19.

While a financial overhaul of DISCOMs is the necessary

long-term solution to mitigate o-taker risk, there

are also short-term solutions that can help drive

renewable energy investments. Depending on the

creditworthiness of the o-taker, a liquidity facility and/

or a sovereign guarantee could support the o-takers’

obligations (OPIC, 2015). In this paper, we examine

such a short-term solution, called a payment security

mechanism (PSM). A PSM is a standalone fund that is

a form of guarantee that covers the risk of payment

default in a power purchase agreement.

Multiple approaches to a PSM] may be possible in the

near term. One potential approach is to use a structure

where public money is used to provide a buer against

the risk of DISCOM default (Section 3.1).

3.1 Payment security mechanism:

Contingent facility

Payment risk is similar to credit risk: both are legal

obligations, where credit risk is related to the default

risk in debt payments, payment risk is related to the

default risk in accounts payable. For the purpose of

this discussion, we make a simplifying assumption that

defaulting on any legal obligation is equivalent, and

hence the defaulting on debt payments is the same as

defaulting on accounts payable. This allows us to use

well-known techniques for creating contingent facilities

for credit risk management.

The framework for calculating the size of this contingent

facility (i.e., PSM) uses elements of credit guarantees,

specifically the probability of default (i.e. the likelihood

that default would occur), exposure at default (i.e. the

amount not paid due to default), and recovery aer

default (the percentage of exposure at default that is

eventually recovered) (Hsiao, 2001; Marrison, 2001).

We estimated the probability of default using a modified

version of the popular Z-score methodology (Altman,

2000; Crosbie and Bohn, 2003), which uses key financial

characteristics of the firm. Based on typical delays and

power purchase agreement legalities, we estimated

the exposure at default as the payment for one-year

worth of electricity produced at the contracted per unit

price. Finally, given that payments are always made

eventually,

the recovery aer default as 100% of the

guaranteed payment aer delay.

We retrospectively estimated the expected size of an

existing payment security mechanism – equal to the

probability of default and the exposure at default – for

a central solar power aggregator that buys power from

multiple generators and sells power to multiple o-

takers under the Jawaharalal Nehru Solar Mission.

selected a sample of DISCOMs representing the credit

spread of all the DISCOMs (Ministry of Power, 2013).

For the supported capacity (750MW) of the existing

payment security mechanism, and based on the

realistic assumption that the exposure at default is

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12-months, we estimated the size of the payment

security mechanism as less than 10% of capital costs

of the solar power deployed, but almost three times

the size of the existing payment security mechanism

deployed by the government. That is, our results

indicated that the existing provision for a payment

security mechanism may not have been adequate in

covering the risk of delayed payment from DISCOMs.

However, this solution does not assess the impact

such a security mechanism would have on the credit

ratings of the covered projects, or alternatively, the

size of the PSM needed to achieve the desired credit

enhancement (e.g., from BBB to AA). Additionally, the

existing work also misses a crucial piece of analysis

comparing the expected benefits of such a facility with

the cost of maintaining such a pool of capital. A sizing

that takes into account the dierential credit quality of

DISCOMs would ensure a fair and eicient allocation of

capital. Further, the cost of maintaining such a facility

also needs to be determined, and the pros and cons of

such an approach contrasted with other structures. All

this is part of future work.

4. CONCLUSIONS

In this paper we investigated key risks to investing in

clean energy in India. We found currency and o-take

risks to be the top risks – in fact, riskier compared to

other risks by a margin of two. We also discussed some

potential financial instruments to address these issues:

an FXHF to address currency risks and a PSM to address

o-take risk. These instruments have the potential to

reduce the cost of capital and eventually the levelized

cost by up to 20%. These instruments may take dierent

forms, depending on policy priorities.

The policy implications of our work so far are three-fold:

first, Indian policymakers should recognize the relative

importance of currency and o-take risks to renewable

energy investment in India. By focusing on key risks

and developing solutions to alleviate these risks they

can more eectively achieve their ambitious renewable

target of 175GW by 2022.

Second, Indian policymakers should also recognize that

these risks – currency and o-take – are connected to

higher level issues that potentially aect the economy

as a whole. For example, the currency risk is related to

macroeconomic conditions and the government may

need to think about longer term solutions focusing

on issues such as: stabilizing inflation, reducing

government borrowing, improving balance of payment,

etc. (Farooquee and Shrimali, 2016b). Similarly, o-take

risk is related to the troublesome financial conditions

of the DISCOMS, requiring longer-term fixes to fiscal

prudence and operational eiciencies.

Third, while recognizing the long-term aspects, Indian

policymakers should think about the short-to-mid-

term solutions to still attract foreign investment in

renewable energy in India. These solutions include

not only policy/regulatory solutions but also financial

instruments, such as ones discussed in this paper. By

allocating public money to these instruments, which

are designing to maximized leverage of public money,

they can ensure that India stays on target to achieving

its ambitious renewable energy targets.

We recognize that our work is just the beginning. We

still need to develop the design details of many of

these mechanisms. One of these eorts is currently

underway at the Stanford Steyer-Taylor Center for

Energy Policy and Finance, where we are exploring the

design of a contingent facility for the PSM, based on the

credit enhancement approach. Finally, stemming from

our analytical insights, we still need to design robust

financial mechanisms that would work in the market.

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(ENDNOTES)

1 Gireesh would like to thank the following for providing research support:

Noam Rosenthal, Vivek Sen, Vinit Atal, and Vaibhav Pratap Singh. The authors

would also like to thank Je Brown for this insightful review.

2 This sections relies on Sen et al. (2016)

3 This sections relies on Sen et al. (2016)

4 Transmission evacuation essentially means the infrastructure to connect to

the transmission grid.

5 The investors included: Bank of America, Blackrock, Generation Investment

Management, EIG Partners, Goldman Sachs, Morgan Stanley, Silverlake

Krawerk, TIAA CREF, UC Regents, etc. Some of this information was used to

support the analysis in Sen et al. (2016).

6 These investors included: Bank of America, Barclays Finance, Blackrock,

Citibank, Goldman Sachs, GE Capital, etc. The conversations with Barclays

and GE Capital were more in depth on India.

7 This section relies on Farooquee and Shrimali (2016a)

8 Currency risk is a major barrier to foreign investments in developing

countries. Currency crises, defined as a quick decline of a local currency, have

triggered regional economic crises (Laeven and Valencia, 2013). While all

projects with foreign investments face currency risk, infrastructure projects

are oen exposed to greater risk because of longer terms and diiculty in re-

deployment of assets, making exit diicult for investors.

9 A currency swap is an agreement to make a currency exchange between two

parties. The agreement consists of swapping principal and interest payments

on a loan made in one currency for principal and interest payments of a loan

of equal value in another currency. Borrowers can lock in currency swaps with

a third-party provider that takes currency risk and charges a currency swap

fee.

10 100bps is equal to 1% point.

energy.stanford.edu/clean-energy-finance

11 The price of a market-based currency hedge reflects three components:

cost of managing currency risk itself, cost of managing the credit risk of the

counterparty, and margin for the currency hedge provider. Given that the

debt provider and currency hedge provider can be dierent parties, credit risk

gets priced into not only the debt rate but also the price of currency hedge.

12 Typically governments are averse to providing sovereign guarantees against

their own currencies, since that amounts to taking positions against their own

macroeconomic policies.

13 In the context of a probabilistic model, the expected (or average) cost means

a statistic that is higher than 50% of the potential cost outcomes and lower

than the other 50%.

14 The basic idea is to enable investors to view this investment as good as

investing in the government of India securities. Since government of India is

rated at BBB-, which is also investment grade.

15 This section relies on Farooque and Shrimali (2016b).

16 INR is the Indian currency i.e., Indian Rupee. Currently, the currency exchange

rate stands at 1 USD = (approximately) 60 INR.

17 Average transmission and commercial (AT&C) losses refer to not only

electrical losses due to transmission and distribution but also commercial

losses due to the and non-payment.

18 Another potential approach is to use public money to provide protection

against DISCOM default via using risk management instruments already

provided by multilateral agencies such as MIGA.

19 Since the DISCOMs are public sector entities, though they delay payments,

they do not default due to regular bailouts by the central government.

20 The Jawaharlal Nehru National Solar Mission initially set a target of 20GW of

solar power by 2022. This target was later revised to 100GW of solar power by

2022 under the National Solar Mission. Recognizing that attracting investment

for this target would necessitate a PSM, the government of India did allocate

some funds; however, we show that this amount was not enough.