Enjeux du financement des infrastructures urbaines

NOTE

a croissance urbaine dans l’ensemble des régions du monde a pour conséquence une augmentation vertigineuse des besoins en infrastructures. D’après une récente étude de McKinsey, les investissements en infrastructures (transport, énergie, réseaux de communication, etc.) devront augmenter de 60% d’ici 2030 pour s’adapter aux projections de croissance économique.

A l’échelle mondiale, 57 000 Mds $ devront ainsi être consacrés au renouvellement ou à la maintenance des grandes infrastructures urbaines. Parmi celles-ci, on peut citer en particulier les réseaux routiers et ferroviaires (21 500 Mds $), les infrastructures de production et de distribution énergétique (12 200 Mds $) et les réseaux de télécommunication (9 500 Mds $).

La Fabrique de la Cité / 1

PETIT-DÉJEUNER DÉBAT #3 16 OCTOBRE 2013

La Fabrique de la Cité a pour objectif de valoriser les initiatives pionnières en suscitant l’échange entre ceux qui réfléchissent à l’avenir de la ville.La Fabrique de la Cité organise ses travaux autour de trois axes de recherche : ◗ l’adaptation de la ville existante ; ◗ la mobilité durable ; ◗ l’économie urbaine.

La Fabrique de la Cité promeut notamment la publication d’études et de travaux de recherche, en s’appuyant sur des partenariats avec de grandes écoles et des universités.

La Fabrique de la Cité est un fonds de dotation créé à l’initiative de VINCI depuis le 25 décembre 2010.

La Fabrique de la Cité

Tous les continents sont concernés par cet enjeu de la fourniture d’infrastructures de qualité permettant d’accompagner la croissance démographique et le développement économique des zones urbaines. Mais il faut tout de même noter que les plus forts besoins d’investissement se situent en Asie et en Inde. Ainsi, en 2009, l’Asian Development Bank notait que la croissance économique dans

les pays asiatiques et en Inde requérait des investissements en infrastructures d’un montant cumulé de 8 000 Mds $ sur la seule période 2010-2020. Pour les 2/3, ces investissements devraient aller à de nouvelles infrastructures, l’autre tiers étant dédié à l’entretien de celles qui existent déjà. La moitié de cette somme est censée aller à des projets de production et de distribution d’électricité et un tiers aux infrastructures routières.

Road

16.6

Rail

4.5

Ports

0.7

Airports

2.0

Power

12.2

Water

11.7

Telecom

9.5

Total

57.3 Based on projections of demand by infrastructure segment, about $57 trillion, or 3.5% of global GDP, is needed through 2030 Global investment, 2010-30 / $ trillion, constant 2010 dollars Source : McKinsey Global Institute (2013), Infrastructure productivity : How to save $1 trillion a year.

Enjeux du financement des infrastructures urbaines

Sources: [1] Siemens Financial Services (2011), “The Affordable Metropolis. How are the world’s expanding towns and cities going to afford the infrastructure investments neces-sary to achieve economically sustainable growth ?,“ Research Study.[2] Asian Development Bank (2009), “Infrastructure for a seamless Asia“.Note : Pour l’Europe, les données agrègent les montants estimés pour l’Allemagne, la France, le Royaume-Uni et l’Espagne.

La Fabrique de la Cité / Auteur : Guillaume Malochet - Responsable des études de La Fabrique de la CitéCrédits : La Fabrique de la Cité,/ Adresse : 1 cours Ferdinand de Lesseps, 92500 Rueil-Malmaison Cedex, FranceTél. : 00 33 1 47 16 38 72 / Site Internet : www.lafabriquedelacite.com / Twitter@fabriquelacite

Les enjeux sont considérables :

Estimation des besoins de financement en infrastructures urbaines à l’horizon 2020 (Mds €)

Asie (dont Inde)

8000

Etats-unis Europe Russie

2684

1304398

Nos précédents rendez-vous sur le thème du financement des infrastructures urbaines :Confrontés à la croissance des besoins d’infrastructures (logement, transport, production d’énergie, loisirs…) et à la difficulté de boucler les plans de financement, les acteurs publics et privés doivent trouver de nouvelles façons d’avancer. En impliquant d’autres partenaires, en cernant mieux la création de valeur attendue des infrastructures et en testant des outils originaux de financement sur cette base.

[#1] 4 octobre 2012 : Quels outils innovants pour financer la croissance verte des villes ? Restitution d’une étude menée par l’OCDE pour La Fabrique de la CitéAvec les interventions d’Olaf MERK, Senior Policy Analyst à l’OCDE, et Erwin Van Der KRABBEN, Professeur d’économie à l’Université Radboud de Nijmegen (Pays-Bas).Cette étude portait sur les leviers financiers de la croissance verte et se concentrait sur les outils mobilisés actuellement dans les grandes villes mondiales : les partenariats public-privé, la vente de droits à construire sur le foncier non-bâti et la recherche de solutions fiscales innovantes, comme le “tax increment financing“.

[#2] 12 mars 2013 : Les mécanismes de financement des gares : une comparaison internationale Restitution d’une étude menée par PwC pour La Fabrique de la CitéRichard ABADIE, Global Infrastructure Leader pour PwC, a présenté les conclusions de cette comparaison internationale inédite portant sur 9 gares (nord-américaines, européennes et asiatique). Trois axes de financement ont été présentés :- Le développement commercial, qui permet d’asseoir le financement sur la capacité de la gare à générer des revenus de commerces et de services (Prague, Milan) ;- Le développement conjoint (joint property development), dans le cas où le développeur de la gare dispose d’une emprise immobilière autour ou au-dessus de la gare et en accorde la jouissance à un développeur privé, qui assure en contrepartie la construction ou le financement de l’infrastructure (Canary Wharf, Vienne, MTRC à Hong Kong) ;- Des mécanismes d’anticipation de la valeur foncière (tax increment financing) qui visent à affecter les revenus futurs générés par l’infrastructure à son financement ex ante, par le biais d’impôts spécifiques ou d’émissions obligataires ciblées (Hudson Yards à New York, Potomac Yard à Washington, VNEB et Canary Wharf à Londres).

entretenir les infrastructures existantes, construites il y a plusieurs dizaines d’années (elles doivent faire l’objet de révisions et d’adaptations pour continuer à fournir des services de qualité aux citadins) ;

permettre l’accès de plus grand nombre aux ressources en eau et en électricité nécessaires au développement économique (le besoin en infrastructures de base est rendu d’autant plus impérieux que les centres urbains explosent, dans de nombreux pays émergents) ;

construire un maillage d’infrastructures de transport (métros, routes, gares et voies ferrées) avec pour objectif de décongestionner les centres et de réduire l’emprise du véhicule individuel ;

miser sur la production d’énergies renouvelables, moins polluantes, pour répondre au défi posé par la transition climatique ;

anticiper l’explosion de l’utilisation des données numériques en ville en misant sur des infrastructures « soft » (technologies de l’information et de la communication, réseaux très haut débit).

L’existence d’infrastructures urbaines de qualité constitue un élément de cohésion sociale, voire un gage de démocratisation. Mais elle est également un vecteur de compétitivité dans un contexte où les villes mondiales cherchent à se distinguer les unes des autres et à attirer les investisseurs.

C’est ce qui rend le “ funding gap “ actuel d’autant plus problématique. En effet, les besoins considérables en matière d’investissements apparaissent largement déconnectés, à l’échelle mondiale, des possibilités de financement offertes par les autorités publiques et les investisseurs privés. Cette séance animée par Frédéric Blanc-Brude, professeur à l’EDHEC et directeur de recherche au Risk Institute – Asia, s’intéresse précisément à la difficile adéquation entre les ressources existant sur les marchés financiers et le financement des projets d’infrastructures.

Les interrogations portent à la fois sur les attentes des investisseurs et sur les caractéristiques spécifiques des infrastructures. Quelles sont ainsi les exigences des investisseurs privés (fonds de pension, institutionnels) en matière de risque, de rentabilité et de liquidité ? À quelles conditions les infrastructures urbaines peuvent-elles être considérées comme des classes d’actifs ? Y a-t-il des éléments propres aux infrastructures (au-delà des éventuels risques pays et de l’instabilité législative) qui empêchent le financement par les marchés financiers ? Telles sont les thèmes auxquels ce petit-déjeuner entend aborder.

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A roadmap to develop institutionalinvestment in infrastructureDe nition, benchmarking & investmentsolutions

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This version, September 23, 2013

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Frédéric Blanc-Brude, PhDResearch Director, EDHEC-Risk Institutefrederic.blanc-brude@edhec-risk.com

Omneia R.H. IsmailSenior Research Engineer, EDHEC Risk Institute-Asia

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Contents

1 Introduction 3

2 Why benchmark infrastructure investments? 42.1 The primacy of asset allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.2 The infrastructure investment narrative . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3 Recent evidence of the performance of infrastructure investments 83.1 Listed infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3.2 Infrastructure private equity funds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

3.3 Direct investments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4 De ning relevant infrastructure investments 154.1 Project nance as the underlying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.2 The uniqueness of project nance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.3 A project nance beta? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

5 The roadmap: from benchmarking to regulation and investment solutions 205.1 Benchmarking unlisted project nance instruments . . . . . . . . . . . . . . . . . . . . 21

5.2 Investment solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

5.3 Regulatory developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

5.4 Public policy and procurement implications . . . . . . . . . . . . . . . . . . . . . . . . 25

Bibliography 26

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1 Introduction

The current public and policy discourse about infrastructure investment is mostly about investment

demand: how much new investment is needed and how large is the funding gap to meet the nancing

needs of the infrastructure sector. This paper proposes to take the view of the supply side of capital

investment, with a focus on institutional investors' potential role in providing nancing to the infras-

tructure sector. It aims to sketch a "roadmap" of the necessary efforts and developments required before

pension funds, insurers and sovereign wealth funds may become the alternative providers of long-term

nance for the real economy that they are often described to be.

We argue that for infrastructure investment to become a signi cant component of institutional investment

policies, a clear and robust investment benchmark must be developed, demonstrating the ability of infras-

tructure investment to improve the outcome of the asset allocation process.

Reviewing recent empirical evidence of the behaviour of existing "infrastructure" investment products

suggests that this is not straightforward. Academic research tends to conclude that the different forms of

infrastructure investments available to institutional players have mostly failed to distinguish themselves

from either stock markets, private equity or corporate bonds.

Asset allocation hinges around choosing a combination of exposures to well-identi ed risk factors. Hence,

the de nition of what constitute infrastructure investment plays an important role in establishing its

potential added value for an investor. We argue that the recent research and track record of investments

made in "infrastructure" incorrectly focuses on tangible or industrial categories and fails to isolate any

new or unique risk factor exposure.

Instead, we propose a slightly restrictive but crystal-clear de nition of the relevant instruments as "project

nance" and argue that the characteristics of project nancing are better in line with the motives of

investors who consider investing in "infrastructure".

Thus, we reduce the seemingly intractable question of benchmarking infrastructure investmentfrom an asset allocation perspective to that of benchmarking project nance debt and equity.

The development of this investment benchmark requires risk measurement and valuation methodologies

tailored to project nancing structures, as well as the standardisation of data collection and reporting.

Once investment performance has been benchmarked at the underlying level, investment solutions can

be designed using funds, co-investments or direct investment structures, to meet speci c investment

objectives, and taking into account existing and future market capacity.

Such benchmarking should also allow the development of the prudential regulatory framework to accom-

modate their speci c risk pro le. In particular, we expect that the Solvency-2 framework could lower the

capital requirements that currently apply to project nance debt and equity.

Finally, the development of investment strategies relying on a recognised benchmark opens the question

of market capacity and the role of the public procurement programs to ensure that new investment

opportunities are designed to meet the supply of long-term capital. The standardisation of public-private

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partnerships contracts and the commitment of the public sector to large scale procurement programs to

create enough investable assets are instrumental in this regard.

The rest of the paper is organised thus: in section 2, we examine the motives and expectations that may

lead institutional investors to invest speci cally in infrastructure, including the necessary conditions for

infrastructure investment to be a relevant category at the strategic asset allocation level.

Section 3 reviews known empirical evidence of the performance of listed, unlisted and direct infrastructure

investments. It concludes that identifying nancial instruments which give access to the expected behaviour

of infrastructure assets described in section 2 is not straightforward and that most current investment

products labelled "infrastructure" fail to do so.

Section 4 proposes to restrict the de nition of infrastructure investment to limited recourse project

nance structures, because they are the most relevant form of investment vehicles in underlying infras-

tructure assets by volume and number of transaction, and because they are designed to create the kind

of instruments that attracted institutional investors to infrastructure in the rst place.

Finally, section 5 describes the different steps and developments needed for infrastructure project nance

and debt and equity to become a mainstream element of investors' asset allocation decisions.

2 Why benchmark infrastructure investments?

2.1 The primacy of asset allocation

Providing long-term nance to the real economy is not a part of the mandate or mission statement of

institutional investors. In effect, such investors cannot be expected to have much interest in nancing

infrastructure per se. They are nevertheless increasingly attracted to such investments because of their

potential in helping them achieve their own long-term investment objectives.

There are two main reasons why institutional investors may wish to increase their exposure to new types

of instruments, be they infrastructure or other alternative investments:

l Improving their ability to deliver the dual long-term objective of generating suf cient investment

performance, while maximising the likelihood of meeting their liabilities at the relevant horizon, and

l Respecting short-term volatility constraints, that is, improving diversi cation and controlling downside

risk.

This is a complex constrained optimisation problem requiring the formation of robust expectations about

the relative performance of different nancial instruments, including how their performance may co-vary

in different states of the world, sometimes far into the future.

These expectations about the behaviour of different types of investments are the foundation of any

investment policy. It is often described as "passive" investment insofar as it relies primarily on the systematicdeterminants of asset prices to formulate expected returns and, ultimately, to arrive at the decision to

allocate funds to each category of instruments available to investors.

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Thus asset allocation choices are driven by the investor's expectations of the behaviour of distinct groups

of nancial instruments. Traditionally, such grouping are labelled asset classes, but more recent state-of-

the-art approaches prefer focusing on the role of remunerated risk factors or betas.

Indeed, the academic and industry literature have long shown the decision to allocate (and rebalance) a

certain proportion of assets to different categories or subcategories of nancial instruments explains a

substantial part of investment outcomes: asset allocation is an investor's rst-order problem.

Recent development in academic research have also highlighted the importance of "fund separation"

or how investors should design speci c portfolios to address individual objectives. These portfolios are

typically described as the "building blocks" of the asset allocation process. For instance, investors may have

a performance-seeking portfolio (PSP) designed to maximise risk-return pro le, and a liability-hedging

portfolio (LHP) designed to maximise the protect against the risk in the investors' liabilities.

The primacy of asset allocation in determining the outcome of the investment process means that the

decision to invest speci cally in "infrastructure" is only relevant from an institutional investor's point of

view, if it can be expressed in terms of its impact on the outcome of the asset allocation decision.

For example, if infrastructure investment can, on average, provide exposure to remunerated risk factors

that are reasonably uncorrelated with other investments in the PSP, it can improve the diversi cation

bene ts (the risk/reward trade-off) of this portfolio.

Investments with a signi cant and well-de ned duration, and yielding predictable cash ows are also

instrumental to build liability management portfolios, and long-term instruments like infrastructure debt

are one of the few alternatives to the bondmarket for such purposes. Likewise, if infrastructure investment

is found to systematically provide at least partial in ation-linked income, it can improve the in ation

hedging property of the LHP.

As well as meeting long-term objectives (performance-seeking and liabilities-management), institutional

investors are also typically required to maintain a short-term solvency or funding ratio above a certain

threshold, while applying market valuation principles to their assets. By investing a larger share of their

long-term assets in unlisted instruments such as infrastructure debt or equity, they can minimise the

impact of sharp market downturns, as they have experienced in recent years on multiple occasions. Hence,

infrastructure investment could also help investors respect short-term constraints.

To arrive at such conclusions however, investors need to be able to take a view on the expected behaviour

of a set of instruments called "infrastructure", to which they can then decide to make an allocation in

the expectation that it will make a systematic and unique contribution to their investment policy. The

uniqueness of the behaviour of a new investment category is a matter of correlations with other types

of investments and determines, amongst other things, its portfolio diversi cation potential.

This is why "benchmarking" infrastructure investments is pivotal to the involvement of institutional

investors in the infrastructure sector. Benchmarks are necessary to design large institutional portfolios

that are run mostly on a passive basis. As long as infrastructure investments are considered to be a sub-

category of another "asset class" or other investment "bucket", there is no reason for investors to choose

to invest speci cally in infrastructure. Of course, they may still invest in infrastructure assets but only

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because of the expected behaviour of the broader category to which they are considered to belong i.e. in

this case whether or not they invest in infrastructure is irrelevant from their point of view; what matters

is the expected performance of the category to which a strategic allocation has been made.

In fact, the question of benchmarking infrastructure assets on the investment supply side (investors) goes

at the heart of the investment demand debate: if pension funds and insurers are to channel signi cant

amounts towards the long-term nancing of infrastructure projects, infrastructure must become a signif-

icant element of the asset allocation puzzle.

In other words, if we cannot expect to see three, ve or even ten percent of institutional assets under

management allocated to investments that are ultimately funding infrastructure projects, then there

is little point in the current debate about how institutional money can play a role in narrowing the

infrastructure nancing gap.

Conversely, in order for pension funds and insurers to invest such a proportion of their assets in infras-

tructure, clear and robust evidence of the systematic contribution of these investments to the outcome

of the asset allocation process has to be developed.

Again, generating this evidence requires an investment benchmark, documenting the systematicbehaviour of infrastructure assets (we return below to the question of what these asset might be).

Next, in section 2.2, we brie y discuss what expectations have drawn investors to the infrastructure sector

in recent years. In the absence of a clear investment benchmark these expectations are mostly derived

from theoretical economics, in particular, the theory of the rm and industrial organisation.

However, these ideas only provide limited insights into the investment characteristics of infrastructure

assets, let alone a clear de nition of what infrastructure investment might be. We address these two other

points in sections 3 and 4.

2.2 The infrastructure investment narrative

In a recent paper, we described the set of expectations that investors are supposed to have about infras-

tructure assets as the "infrastructure investment narrative" (Blanc-Brude, 2013).

It can be summarised thus: Infrastructure development is associated with large upfront investments in

businesses providing "essential services", hence a low price-elasticity of demand and limited a correlation

between revenues and the business cycle. Operating tangible infrastructure assets also suggests elements

of monopoly power, hence pricing power and ultimately a higher correlation of revenue growth with

in ation. Next, because infrastructure assets have high sunk or xed costs, their operating or variable

costs are relatively low and the free cash ow of the rm is expected to be very stable. The combination

of the rm's pricing power with the low volatility of its operating and free cash ows suggest an attractive

risk-adjusted cash yield.

1 - This would correspond to USD1-6Tr using 2012 gures. The OECD has identi ed a global infrastructure funding gap of USD57Tr (OECD, 2006)

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This stylised presentation of the nancial economics of businesses running a country's infrastructure is

in itself a "benchmark" insofar as it is an ideal-type or model of what the average utility or concession

contract may be expected to be.

From this narrative, investors have to imply what investment characteristics may be of use to them. As

suggested above, attractive risk-adjusted returns and low business cycle correlations suggest a contri-

bution to the performance-seeking portfolio, while long-term cash ows and correlation with in ation

are appealing characteristics to build a liability-hedging portfolio.

Paraphrasing aWarren Buffet quip, one investmentmanager brochure describes infrastructure investment

as "an in ation-linked bond with a rising coupon."

However, the above "narrative" is also largely derived from the real or tangible character of infrastructure

assets, which confers them their natural monopoly status, from which springs most of the argument. This

focus on tangible assets typically leads to an investment categorisation by industrial sectors e.g. trans-

portation (road, rail, ports &c.), environmental services (water treatment, municipal waste, &c), energy

(from coal and gas- red power plants to wind energy), &c.

In effect, the division of infrastructure assets into (industrial) sectors is to infrastructure investment

what dividing the investment universe into traditional asset classes (stocks, bonds, property, &c) is to

risk management: not very informative and possibly very misleading. Indeed, focusing on infrastructure

as a real asset can be misleading insofar as the tangible or industrial characteristics of such investments

are not necessarily the main drivers of their nancial performance or asset value.

We have argued elsewhere (see Blanc-Brude, 2013, for a detailed discussion) that infrastructure cash

ows are explained by the contractual and regulatory context in which such investments take place,

rather than their tendency to create natural monopolies. Economics has long showed that the outcome

of long-term investments involving large sunk costs is a function of the ability of two or more parties to

write and enforce a contract that shares risks and the surplus generated by the investment over multiple

periods (Hart, 1995). The outcome of this long-term contract is determined by information asymmetries,

contract incompleteness, and the bargaining power of the parties involved, which may lead to contract

renegotiations, hold-ups and sometimes termination or even expropriation. Hence, the contracts allowing

long-term investments in infrastructure projects to take place are an essential determinant of investment

performance.

Moreover, natural monopolies tend to be regulated by the public sector, especially when they are a matter

of essential services, and the regulatory framework is often a more signi cant driver of the nancial

performance of the rm than its monopoly status warrants.

Finally, in the majority of cases, investable infrastructure assets can be strictly considered to be purenancial assets: the project investment vehicle that raises equity or debt for a new project does not own

the tangible assets that it has been mandated to nance, build and operate. When it does (e.g. privatised

utilities), this asset is so "relationship-speci c" (single use) that it's value can only be a function of the

contractual and regulatory framework de ning its ability to generate free cash ow in the future.

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In other words, at the underlying level, investable infrastructure debt or equity are simply claims on

streams of expected cash ows without any terminal or collateral value.

Benchmarking infrastructure investments at the underlying level thus requires identifying anddocumenting the systematic risk factors that explain the volatility of expected cash ows andhow unique these risk factor exposures are, compared to other investments.

We return to the characteristics of underlying infrastructure investments in section 4. In the next section,

we review existing evidence of the performance of infrastructure investments.

3 Recent evidence of the performance of infrastructure investments

Empirical evidence about the nancial performance of underlying infrastructure investments currently

remains very limited and anecdotal. In sections 4 and 5, we detail a new approach to de ne and benchmark

underlying infrastructure investments on both debt and equity sides of transactions. In what follows, we

rst review existing evidence with regards to "listed infrastructure" equity investments, unlisted infras-

tructure equity funds and direct equity investments by a handful of large Canadian pension funds.

3.1 Listed infrastructure

A number of infrastructure indices have been created to proxy the performance of listed infrastructure

assets. However, what quali es as "listed infrastructure" is highly debatable. A number of indices, more

akin to an infrastructure equity theme, include rms that are likely to bene t from the expected growth

of the infrastructure sector worldwide because they provide essential technology or know how e.g. energy

recovery devices for water desalination, wind power turbines, facility management services &c. Whether

or not infrastructure is a valid equity theme, such indices are only indirectly related to the infrastructure

investment narrative.

Still, a number of indices are exclusively focused on listed utilities, transportation, telecoms and energy

rms as well as listed infrastructure funds, and aim to provide a market-cap weighted proxy of the sector’s

performance. In what follows, unless otherwise stated, the terminology "listed infrastructure" includes

utilities.

Utilities, telecoms and transport rms in the US, Europe and Australia dominate the listed infrastructure

space. Indeed, since the 1970s, IPOs have been the default method to fully or partly privatise existing state-

owned utilities and transportation infrastructure and the most important privatisation programmes have

occurred in these jurisdictions. Thus, listed infrastructure market capitalisation has grown considerably.

Rothballer and Kaserer estimate that the number of listed infrastructure companies that own or have a

concession for physical infrastructure assets and generate more than 50% of their revenues from these

assets increased from 216 to 1,458 between 1980 and 2010, excluding American depositary receipts, funds

and trusts (Rothballer and Kaserer, 2012).

Several papers examine the performance of listed infrastructure. Looking at a sample of 32 hand-picked

infrastructure entities listed in Australia, Newell and Peng (2007) nd that for the period between 1995

and 2006, listed infrastructure exhibits higher returns, but also higher volatility than equity markets. Still,

they show that listed Australian infrastructure has a better Sharpe ratio than the market and that the

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correlation between Australian listed infrastructure returns and themarket is not signi cant over their full

sample period (1995-2006). However, they also document that the correlation of returns is not constant

and tends to increase over time (after 2001). In a follow up study, Newell and Peng (2008) nd that in

the US, infrastructure (ex-utilities) underperforms stocks and bonds over the period from 2000 to 2006,

while utilities outperform the market.

Using a multifactor model of excess returns adjusting for Fama-French style factors, Bird et al. (2012)

nd that listed infrastructure and utilities proxied by the UBS indices for Australia and the US generates

excess returns from 1995 to 2009. They nd that listed infrastructure exhibits much higher volatility than

listed utilities and have a higher market beta. They nd a high and signi cant equity beta of 1.35 for US

infrastructure and of 1.00 for Australian infrastructure, while listed utilities in their sample have more

defensive equity betas between 0.47 and 0.57.

Using a sample 1,458 listed rms in the transport, telecoms and utilities sectors, Rothballer and Kaserer

(2012) nd that infrastructure stocks have lower market risk than equities in general but not lower

total risk i.e. they nd high idiosyncratic volatility. They also report signi cant heterogeneity in the risk

pro les of different infrastructure sectors. The authors argue that construction risk, operating leverage,

the exposure to regulatory changes and the lack of product diversi cation explains this volatility. Looking

at the 35 Hong Kong-listed infrastructure entities, Newell et al. (2009) report similar ndings of relatively

low market correlation but signi cant volatility.

Examining three major listed infrastructure indices between 2002 and 2009, Sawant (2010) also nds

that return distributions show negative skew and high kurtosis and high volatility and concludes that

infrastructure equity indices do not provide a good proxy to be exposed to underlying infrastructure.

Rothballer and Kaserer (2012) also nd that listed infrastructure entities exhibit leptokurtic returns.

Thus, listed infrastructure ts the infrastructure investment narrative insofar as it is shown to improve

portfolio diversi cation (Sharpe ratio) but this is mainly a feature of utilities and one has to question

whether investing in listed utilities represent anything new for institutional investors.

Further stylised facts emerging from studies of the listed infrastructure space include:

l Non-persistence of excess returns: listed infrastructure and utilities are not found to signi cantly

outperform the market in the long-run in (Idzorek and Armstrong, 2009; Dimovski, 2011; Bird et al.,

2012)

l A strong correlation with the credit cycle in the case of listed infrastructure funds because of their use

of nancial leverage (Bird et al., 2012)

l Higher cash yield than market benchmarks but with higher yield volatility and not obvious difference

with the higher-than-average cash yield of other growth stocks (Blanc-Brude, 2013)

l Absence of superior in ation-hedging properties than the stick market as a whole (Bird et al., 2012;

Rödel and Rothballer, 2012; Newell and Peng, 2007; Van Antwerpen, 2010)

l Absence of drawdown protection in bad times (Blanc-Brude, 2013)

Table 1 summarises some of these ndings and splits the return data of major infrastructure indices into

two 5-year periods preceding and following 2008: between 2008 and 2013, all infrastructure indices

consistently underperform major market indices and exhibit lower Sharpe ratios.

..

9

Table 1: Pre- and post-GFC investment characteristics of listed infrastructure indices

42 An EDHEC-Risk Institute Publication

Towards Efficient Benchmarks for Infrastructure Equity Investments - January 2013

3.2.2.1 Stable cash yieldIn the case of listed infrastructure, industry studies argue that dividend yields are systematically higher with infrastructure stocks (Colonial First State Asset Management, 2010a). We are not

aware of any academic research on this topic but it should not come as a surprise that low growth stocks should offer higher income on average than stocks associated with expectations of higher capital gains. Figure 1 suggests that the average

3. Investing in Infrastructure: The Investment Narrative and Existing Evidence

24 - An investment company that chooses investments according to a particular issue or theme. For example, a fund built on an agricultural theme might invest in the equities of farm equipment manufacturers, chemical companies, and other firms that sell agricultural products. Likewise, an investment company might choose to invest in equities that would reflect an ecological or baby-boomer theme.

MSCI World Infra

(sector capped)

MSCI World Infra

S&P Global Infra

FTSE Macquarie

Global Infra

UBS World Infra

UBS World Infra & Utilities

UBS Global 50-50 Infra & Utilities

S&P 500 Comp

FTSE All Share

Performance†

3 year 14% 13% 16% 13% 15% 13% 14% 16% 15%

5 year -4% -7% -6% -6% -4% -6% -5% -2% -1%

7 year 2% 1% 2% 2% 5% 2% 2% 2% 2%

10 year 5% 4% 8% 7% 11% 7% 8% 4% 4%

Risk*

3 year 14% 13% 16% 13% 15% 13% 14% 16% 15%

5 year 18% 17% 23% 18% 22% 18% 20% 22% 19%

7 year 16% 15% 20% 16% 20% 16% 18% 19% 17%

10 year 14% 14% 18% 15% 18% 15% 16% 17% 15%

Sharpe ratio#

3 year 0.2 -0.1 0.1 -0.1 0.4 -0.04 0.2 0.5 0.3

5 year -0.3 -0.4 -0.3 -0.4 -0.2 -0.4 -0.3 -0.1 -0.1

7 year 0.0 -0.1 0.0 0.0 0.2 0.05 0.01 0.0 0.0

10 year 0.2 0.2 0.4 0.4 0.5 0.4 0.4 0.2 0.2

Table 1: Risk return characteristics of major infrastructure indices in December 2012

Table 2: Characteristics of major infrastructure indices before and after 2008

† annualised monthly returns* annualised standard deviation of monthly returns# ratio of annualised excess monthly returns over 3-months risk-free rate to annualised standard deviation of monthly returns

* January 2003 to January 2008† January 2008 to January 2013

MSCI World Infra

(sector capped)

MSCI World Infra

S&P Global Infra

FTSE Macquarie

Global Infra

UBS World Infra

UBS World Infra & Utilities

UBS Global 50-50 Infra & Utilities

S&P 500 Composite

FTSE All Share

Performance (annualised)

Pre-dislocation* 16% 16% 25% 24% 28% 24% 25% 9% 10%

Post- dislocation† -5% -7% -6% -7% -4% -7% -6% -1% -1%

Risk (annualised)

Pre-dislocation 8% 10% 10% 10% 12% 10% 10% 9% 10%

Post dislocation 18% 17% 23% 18% 22% 18% 20% 22% 19%

Sharpe ratio

Pre-dislocation 1.55 1.33 2.22 2.12 2.09 2.08 2.10 0.71 0.75

Post dislocation - 0.30 - 0.44 -0.30 - 0.42 - 0.20 - 0.41 - 0.32 - 0.05 - 0.07

Source: Blanc-Brude (2013)

The studies reviewed above suffer from a number of limitations: authors use ad hoc datasets suffering

from historical and country biases in the case of Australia (Newell and Peng, 2007) or industry-provided

infrastructure indices which suffer from a fundamental drawback: market-cap weighting leads to poor

diversi cation and even concentration in a few very large stocks. Indeed, existing research has shown

that market-cap weighted indices are so inef cient that they are dominated by equal-weight indices,

which are themselves suboptimal (Amenc, Martellini, Goltz, & Milhau, 2010). In the case of infrastructure

and utilities, this concentration can be extreme (see Blanc-Brude, 2013, for a detailed analysis). Each

infrastructure index also introduces some heterogeneity in the type of underlying investments that are

made and varying degrees of geographic concentration.

Clearly, the infrastructure indices fail to replicate some of the expected characteristics of infrastructure

investment. As we have argued above, bundling together a number of rms because they operate priva-

tised utilities or invest in toll roads, without taking the impact of regulatory (rate of return or price cap)

and contractual (real tolls, shadow tolls or availability payments) frameworks into account leads to a very

unclear picture.

Next, we review existing empirical studies and available data for unlisted infrastructure funds.

3.2 Infrastructure private equity funds

Unlisted infrastructure equity funds are a relatively recent invention. PPP funds started in the UK in the

1990s and wider infrastructure funds in Australia in the same decade. Unlisted funds can pursue several

strategies. Most funds are either primary funds aiming to win deals, manage them through construction

and to make a capital gain upon exit with a target net IRR of 20%, or secondary funds aiming to acquire

and enhance the long-term income streams generated by operational projects.

Fund duration is partly a function of their preferred investment strategy: the 7-10 year classic private

equity (PE) structures are by far the most common but hybrid funds (investing in projects with short and

longer maturities) and evergreen funds are possible. In what follows the term ‘infrastructure PE funds’

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10

refers to closed-ended seven to ten-year private equity structures using the now classic partnership model

(GP/LPs).

As opposed to listed infrastructure, data paucity is a signi cant challenge to develop an unbiased view of

unlisted infrastructure funds' investment performance. A rare case of such research is Bitsch et al. (2010),

who look at the investment characteristics of individual investments made by unlisted infrastructure PE

funds, using a global sample of cash ows from the CEPRES database for 363 individual infrastructure

investments made by unlisted funds within a universe of eleven thousand private equity investments

between 1971 and 2009.

They nd that investments made by unlisted infrastructure PE funds are ve times larger than other PE

deals but do not have longer durations.

They also test the variability of cash ows around the average s-shaped cash ow structure of individual

investments in their database and nd that individual investment cash ows in infrastructure PE fund are

not less volatile than in other types of PE fund. However, they observe fewer zero (bankruptcy) or below

unity (loss) multiples in infrastructure funds compared with other PE funds, as well as higher average and

median IRRs.

The authors conclude that infrastructure PE funds have a better Sharpe ratio than their private equity

control group, but are not less risky. They argue that unlisted infrastructure deals are highly levered, and

that returns are largely driven by higher market and political risk.

Also using the CEPRES database, (Weber and Alfen, 2010) shows that the average risk/return character-

istics of infrastructure PE compared with European and US Buyout PE is slightly better pro le than other

PE funds.

The main dif culty with interpreting the analysis of underlying infrastructure fund transactions is sample

bias: their data is drawn from private equity databases and includes only transactions conducted according

to the private equity model. While these are the majority of existing infrastructure funds to date, other

fund models could be used to invest in infrastructure. Moreover, the de nition used to select ‘infras-

tructure’ deals in Bitsch et al. (2010) leads to a signi cant share telecoms deals in the US, while most

deals in the dataset were conducted before 2001, a watershed year for global markets.

Observing a biased sample of underlying PE transactions may not be representative of the investment

pro le of unlisted infrastructure equity.

Several papers also examine the returns that investors might expect at the infrastructure fund level, netof fees. Using Mercer net-of-fees return data series on ve major funds, Newell and Peng (2007) nd

that for the period 1995-2006, Australian unlisted infrastructure delivers excess returns and has a Sharpe

ratio of 1.47, second only to direct property and that unlisted returns are more stable than that of listed

infrastructure during the period.

Bird et al. (2012) also use Mercer data for ten Australian unlisted infrastructure managers, representing

105 underlying assets worth A$11.1bn, 59% of which are utilities and a similar proportion is invested in

domestic Australian assets, with the balance evenly split between the UK, the US and the rest of the world.

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11

They nd that, like listed infrastructure, unlisted Australian infrastructure funds exhibit excess returns with

the best Sharpe ratio and lowest beta, positive skew and very high kurtosis. DeFrancesco et al also report

evidence of excess returns in unlisted Australian infrastructure but with a small sample (De Francesco,

Newell, & Peng, 2011).

However, the use of Australian equity funds to illustrate the characteristics of infrastructure funds is

problematic. Bird et al. (2012) and others report that the Newell and Peng (2007) results about Australian

infrastructure are biased because they include a period during which assets were acquired at signi cant

discounts from local governments in distress (e.g. the Victorian government in the early 90s) and a benign

regulatory environment allowed tariff increases consistently above real GDP growth. Australian unlisted

infrastructure funds can also be open-ended (Bird et al., 2012), which is exceptional in other jurisdictions

and may thus have a different return pro le than the global population of close-ended infrastructure PE

funds.

Using a global sample from Prequin, Blanc-Brude (2013) shows that the dispersion of returns for mature

funds (10 years old or more) is signi cant and suggests only top quartile funds perform to their investors’

expectations with IRRs in the 18-22% range.

As was the case for listed infrastructure, most authors suggest that leverage is the main source of return

in unlisted infrastructure PE. Unlike traditional buyout deals, there is only a limited scope for managers to

‘turn around’ infrastructure projects and regulated utilities all of which operate within the tight constraints

of, respectively, their nancial plan as agreed with lenders at nancial close, and the requirements of

regulators. Utilities can show potential for extra leverage at the enterprise level, which PE managers have

been keen to exploit (see Helm, 2009), and PE funds themselves tend to add another layer of leverage to

increase returns.

Still, beyond the casual observation of industry practices, the sources of equity returns in infrastructure

funds are badly documented, especially those of hybrid and evergreen funds that may have longer-term

investment strategies. Existing studies do not, to our knowledge, attempt multifactor estimations of the

different drivers of returns in unlisted infrastructure funds: illiquidity, political risk, leverage &c.

Existing studies (Bitsch et al., 2010; Newell and Peng, 2007) also nd that

l Return correlations with other investments tends to be high or increasing with time;

l There is no evidence of in ation protection from such investments either at the underlying or the fund

level.

Hence, in the case unlisted infrastructure equity invested through classic PE structures, deal sourcing and

exit timing are the main sources of added value.

3.3 Direct investments

Direct investment in utilities and projects has gained momentum in recent years amongst pension and

sovereign wealth funds that have reportedly grown increasingly dissatis ed with the infrastructure PE

fund model described above.

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12

Figure 1: Net investment income by "asset class" at the Ontario Municipal Employee Retirement System

-8,000

-6,000

-4,000

-2,000

0

2,000

4,000

6,000

8,000

2003 2004 2005 2006 2007 2008 2009 2010 2011 C$

m

capital markst

provate equity

real estate

infrastructure

Source: Blanc-Brude (2013)

Since 2005, a number of large Canadian pension funds have moved out of infrastructure funds and into

direct infrastructure investments. These portfolios are still young, not completely formed and their long-

run performance untested. Blanc-Brude (2013) highlights several salient facts:

l Portfolios are sizeable at CND10bn but nevertheless concentrated. In one case, ve assets make up 77%

of the allocation at one of the largest Canadian pension funds.

l Despite their size, and as a consequence of their concentration, each infrastructure portfolio is unique

and performs differently, with Sharpe ratio varying from 0.3 to 1.8

l Building signi cant investment positions takes years.

Of course, each one of these pension funds has different investment needs and objectives and their

infrastructure investment strategies may not be compared directly. In their annual reports, the also report

being exposed to foreign exchange risk since signi cant proportions of their infrastructure portfolio is

invested internationally, and being exposed to a varying degree of demand risk: for example the Canadian

Pension Plan Investment Board (CPPIB) invests in airports that have returns correlated with economic

growth.

Figure 1 suggests that the choice of direct investment can deliver aspects of the infrastructure investment

narrative, de-correlation and stability in particular. But direct investment in underlying infrastructure

assets creates a number of portfolio construction issues, including the dif culty to create a well-diversi ed

portfolio of a reasonable size. The issues found in infrastructure portfolio construction echo those expressed

in the literature about real estate assets (King & Young, 1994). Individual infrastructure assets tend to be

large and this makes building portfolio of infrastructure assets a lengthy process for direct investors.

With very large assets, satisfactory diversi cation is unlikely to be possible. For example, with normally

distributed returns and equal weights, listed equities can achieve 95 per cent diversi cation of speci c

risk with 44 stocks (Brown and Matysiak, 2000). While infrastructure return distributions are not well-

documented, real estate assets can give us some perspective: if returns are skewed and leptokurtic, we

know that with assets as bulky as real estate assets, a portfolio of at least 1,700 properties is needed to

reduce risk ten-fold (Young et al., 2006). The problem of non-normal returns is compounded by the indivis-

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13

ibility of assets, which prevents equal weighting. If equal weighting is not an option, larger portfolios of

value-weighed assets are required to obtain the same level of diversi cation.

Hence, the route followed by large Canadian pension funds in order to gain exposure to a series of risk

factors found in infrastructure projects can seem rather unorthodox. It is, for the most part, an active

strategy of individual asset selection executed in-house. It is thus not focused on capturing the equivalent

of the "asset class" since idiosyncratic risk will remain dominant.

This approach is expensive and unavailable to smaller investors. However, it suggests better results at

capturing certain aspects of the infrastructure investment narrative than "listed infrastructure" or "unlisted

infrastructure PE".

3.3.1 Conclusion

In conclusion, existing academic research on the relative performance of "infrastructure" equity invest-

ments concludes the following:

Listed infrastructure

l Listed infrastructure has historically been dominated by utilities and has exhibited lowmarket covariance

but not low variance compared with other stocks.

l Listed utilities may have better in ation hedging properties compared to other infrastructure sectors,

but there is no statistically signi cant evidence of improved in ation hedging of listed infrastructure

or even listed utilities over the stock market in general.

l Listed infrastructure cash yields, while they tend to be higher, are also more volatile than the market

l A-cyclicality is also hard to demonstrate in existing studies and looking at listed data. In particular

infrastructure indices have changed pro le since 2008 and the reversal of the credit cycle.

Unlisted infrastructure PE

l Unlisted infrastructure funds are found, in research conducted to date, to have typically emulated the

private equity buy-out format, to have used leverage on top of the already signi cant leverage of most

underlying assets and to have charged signi cant fees. As such, they often fail to be a transparent risk

pooling mechanism by which nal investors could address the portfolio construction issues (the lot

size problem) that characterise direct infrastructure investment.

l Unlisted infrastructure PE funds as currently researched do not show evidence of offering returns that

are in ation linked.

l These results are constrained by the limited access to investment data, in particular, all papers rely

on data from PE funds, which are invested according to an ill-de ned specialisation, and thus nd,

unsurprisingly, PE-like results.

Direct infrastructure investment

l Direct infrastructure investment remains a very active approach limited to very large investors. The

young age of their portfolios and the diversity of their investment objectives limit the evaluation and

comparison of direct investing by pension funds.

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14

l Even if infrastructure equity returns were normally distributed and a portfolio of equally sized assets

could be built, a single well-diversi ed infrastructure portfolio would have to be extremely large.

l This highlights the need for continued need for intermediation ] in all likelihood, infrastructure portfolios

are not fully diversi ed, active investment approach is necessary, and project and manager selection

matters. Indeed, existing infrastructure PE has not provided a systematic answer to generating infras-

tructure betas. When beta (normal/systematic performance) investing is not reliable, it becomes crucial

to pick projects and managers, both internal and external, that deliver top quartile total performance.

We must conclude that creating exposures to the risk factors described in section 2.2 has not so far been

obvious for investors. If these instruments do not create well-de ned and unique exposures compared

to other instruments (stock markets, private equity, corporate bonds) it is dif cult to argue that they are

relevant from an asset allocation or from a regulatory perspective.

Recent research and most existing nancial instruments labelled "infrastructure" suffer from a funda-

mental design aw: they aggregate nancial instruments based on industrial categories and without

attempting to isolate methodically the contractual and regulatory characteristics that explain risks and

returns or taking into account what might distort the investment characteristics of the underlying, such

as leverage PE fund structures. The expectation is to capture a kind of average ‘infrastructure effect’ just

because a series of businesses describe themselves as being part of the "infrastructure sector", but without

explicating the mechanisms at play. It clearly fails.

An index should clearly state an investment objective. Second, index design should articulate the rules

for asset selection and asset weighting. Understanding the mechanisms driving risk factor exposures

at the underlying level should be instrumental in de ning rules for asset selection. hence, designing

infrastructure investment products and benchmarks requires a risk factor heuristic relying on a clear

de nition of what is being invested in. In the next section, we propose to return to reconsider the de nition

of what consists an infrastructure investment and to what extent a clearer, albeit narrower, focus may

still create new systematic exposures for investors.

4 De ning relevant infrastructure investments

The investments described above amounted to instruments labelled "infrastructure" but that essentially

failed to be very different from other, existing instruments. From an asset allocation perspective, such

investments make a focus on infrastructure investment look rather unwarranted.

This opens the question of what is de ned as "infrastructure" from an investment perspective. Utilities or

other infrastructure investment companies may well bene t from natural monopolies in certain aspect

of their business, provide essential services and have stable revenue streams, but their stock price remains

driven in large part by what subsegment of the stock market they belong to (e.g. "low beta, large cap"), the

bonds they issue are not fundamentally different from other corporate bonds with similar credit rating,

and their potential return for a private equity raider belong in the same category of investment than

other large scale LBOs. Despite their being related to the infrastructure sector, the characteristics of these

investments are predominantly determined by broader systematic risk factors.

From that perspective, one may invest in infrastructure without creating a different type of risk exposure

than an investment strategy that would ignore the notion of "infrastructure".

..

15

Instead, we propose to focus on a type of underlying that neither a listed stock or a corporate bond, a

privately held company or a real asset or any other type of alternative investment that already exists in a

standard asset allocation framework: project nance.

4.1 Project nance as the underlying

We propose to equate infrastructure investment with project nance i.e. the nancing of a special purpose

entity (SPE) dedicated to the construction and operation of a new infrastructure project over a given

period, typically 25-30 years.

Indeed, most infrastructure investment and the immense majority of new or `green eld' projects are

nanced using such structures.

Crucially, while limiting our analysis to project nancing may exclude a limited number of investment

opportunities that may reasonably be labelled as "infrastructure", Project Finance bene ts from a clear

and universally recognised de nition since the Basel-2 Capital Accord.

"Project nance (PF) is a method of funding in which investors look primarily to the revenues

generated by a single project, both as the source of repayment and as security for the

exposure. In such transactions, investors are usually paid solely or almost exclusively out

of the money generated by the contracts for the facility's output, such as the electricity sold

by a power plant. The borrower is usually a Special Purpose Entity (SPE) that is not permitted

to perform any function other than developing, owning, and operating the installation. The

consequence is that repayment depends primarily on the project's cash ow and on the

collateral value of the project's assets." (BIS, 2005)

Hence, by focusing on project nance, we capture the bulk of private infrastructure nancing and gain a

clear de nition of what may be invested in.

Project nance creates the opportunity to invest in a single-project rm with a pre-de ned lifespan.

Before the nancing decision can been taken, the SPE has to demonstrate its nancial viability with a

high degree of probability. In the process, two inter-related types of nancial claims are created, splitting

the free cash ow of the rm between a senior claim and one or more subordinated claims.

l The senior claim or "tranche" is a debt instrument, which has priority over more junior claims over the

project's free cash ow, in a structure sometimes known as a cash ow "waterfall". This tranche is built

to absorb the most predictable part of a project's free cash ow.

l Junior tranches include debt instruments (e.g. mezzanine) and a residual claim tranche known as project

"equity", despite the fact that is has a xed term.

Taken as a whole, the claims that constitute an instance of project nancing can be interpreted as a

portfolio of inter-linked bonds, with different maturities and grace periods, some paying a xed rate of

interest and some paying a variable rate of interest.

2 - We estimate that more than USD3Tr of project nancing was closed worldwide between 1995 and 2012 (Blanc-Brude and Ismail, 2013c).

..

16

This comparison with a bond portfolio is all the more relevant that as we argued above, in the majority

of cases, the SPE does not own any tangible assets, or owns assets that are so `relationship-speci c' that

they have little or no value outside of the contractual framework that justi es the SPE's existence. In

Project nance, contracts must suf ce to explain the existence of enforceable and valuable claims. (see

Blanc-Brude, 2013; Blanc-Brude and Ismail, 2013c, for a detailed discussion of the governance function

of project nancing).

Finally, an unique feature of project nancing is the role of initial nancial leverage (at nancial close). In

a recent paper, we nd that senior project debt in infrastructure project nance between 1994 and 2012

averages 75% and can be as high as 90% (Blanc-Brude and Ismail, 2013c).

Previous research has typically concluded that the high leverage observed in project nance is a sign of

low asset risk (Esty, 2003) i.e. lenders agree to provide most of the necessary funds because the probability

of repayment is very high. In other words, the `split' of the project's cash ows between senior (low risk)

and junior (riskier) instruments allows a larger senior tranche if cash ows are more predictable.

4.2 The uniqueness of project nance

Project nancing is themarket (evolutionary) response to the hurdles inherent in the nancing of investment

projects that can only be repaid over extended periods of time: individual long-term investment are

likely to fail because the long-term is risky, information asymmetrically distributed between investors

and managers, and long-term contracts too incomplete to avoid opportunistic behaviour. In effect, the

classic theory of the rm predicts that long-term investment (investments with a delayed pay-off) are

very unlikely to take place.

Project nance emerged from the need to create credible long-term commitment mechanisms so that

long-term investments could take place. A combination of contractual and governance mechanisms allow

the long-term commitment of project developers, their subcontractors, equity investors and lenders. These

commitment mechanisms are credible enough to allow the nancing of a new rm: a dedicated vehicle

to be funded with both equity and debt and carry out a single investment project.

This single-project rm is fundamentally different from other types of rm. It only has one very well-

de ned mission and no freedom to anything else. It is created to execute a set list of tasks with the

means created by its initial nancing: say to commission the construction, maintenance and operations

of a large structure while collecting a more or less risky income stream from a third party (public or private

clients).

Project nance, the art and science of manufacturing long-term commitment, is however very expensive

i.e. the transaction costs involved in resolving the information asymmetries inherent in the investment

and lending process, of securing the credible commitment of numerous parties to share risks and execute

a set of tasks according to a schedule pre-agreed long in advance are high (see Dudkin and Välilä, Timo,

2005, for a review of empirical evidence).

It follows that project nancing can only applied to very large investment projects with the scale to

shoulder signi cant xed transactions costs: these are infrastructure projects for the most part, even

though project nance can in principle be applied to any business with suf ciently predictable cash ows.

..

17

Hence, we are now looking at infrastructure investment from a completely different angle: insteadof considering investing in a bridge project which may or may not have predictable long-term cash ows,

we are looking at an investment in a dedicated nancial structure, which can only exist if it has made

the demonstration of its ability to generate long-term cash ows.

Indeed, project nance acts as a ltering mechanism for investment projects that can demonstrate the

kind of characteristics that attracts institutional investors to the "infrastructure" in the rst place. In a

recent paper (see Blanc-Brude and Ismail, 2013c, for a detailed discussion), we argue that the creation

of separately incorporated and highly leveraged rms or SPEs has two important dimensions: the self-

selection of the equity investor and the signalling of high credit quality.

First, the decision to use a separate incorporation of the project is a choice made by its shareholders. Thus,

while high leverage clearly plays a disciplining role (à la Jensen and Meckling, 1976), it is self-imposed,

it is appealing to interpret this choice of a highly leveraged nancial structure as a form of signalling by

shareholders to lenders, that they are willing to be exposed to potentially high losses (equity wipe-out) if

they do not manage the project very well (see Grossman and Hart, 1982).

Second, in contrast to classic corporate nance, the nal decision to leverage the SPE is effectively taken

by the lenders, not its management. Since the SPE is dedicated to realising a standalone investment the

decision to nance is more binary from the point of view of the lender than in the case of relationship

banking: lenders can opt-out without directly jeopardising existing client relationships.

Project nance should thus be understood as a project selection process: large projects are incorporated

separately and highly leveraged because they are low risk projects that generate suf cient free cash ows

to service large amounts of debt nancing.

It is insuf cient to say that high leverage is justi ed because 'debt is cheaper than equity'. In project

nance, leverage is high because asset risk is low (Esty, 2003).

This is not very different from the manager selection problem in the theory of the rm (Jensen and

Meckling, 1976): increasing the chances of bankruptcy by increasing leverage, because it transfers risk to

managers, should lead to the self-selection of the best managers (adverse section) and the optimal level

of managerial effort (moral hazard). Likewise, using project nancing to nance individual projects should

lead to the selection of the best projects for which the optimal incentive structure has been put in place.

Finally, if the decision to invest equity in highly leveraged SPEs is a form of self-imposed discipline by

shareholders, how can we interpret this behaviour in terms of the debt overhang problem? Under the

standard theory, shareholders should aim to maximise their access to residual free cash ows, not the

lender's (Myers, 1977).

However the debt overhang problem in its simple formulation overlooks two important dimensions of

project nance: the bene ts of controlling a new project-speci c rm for an existing sponsor rm, and

the impact of the continuous de-leveraging of the SPE.

l The SPE is a new rm created by the shareholders of an existing sponsor, hence it is only a mean to

an end. The bene ts of control for the sponsor are speci c in project nance since sponsors typically

..

18

control the ability of the SPE to choose it subcontractors i.e. to contract with themselves. Moreover,

by investing subordinated debt in the SPE, the sponsor can bene t from an improvement of its own

tax shield. Hence, the bene ts of SPE control are also indirect and not only about controlling the SPE's

cash ow. (See Chemmanur and John (1996) for a theoretical discussion of the rationale to incorporate

projects separately from the point of view of the sponsor and the decision to use project nance as a

function of the bene ts of project control and the choice of capital structure.)

l Because the SPE is dedicated to delivering a single project and starts repaying its debt almost immedi-

ately (interest-during-construction or IDC is not a rare feature), the leveraging of its nancial structure

is not constant but decreases over time until it eventually reaches zero. It follows that as the project's

lifecycle develops, the share of cash ows that is expected to accrue to the SPE's shareholders is

expected to increase signi cantly.

Thus, the decision to create and leverage a dedicated rm or SPE should be understood as a joint signalling

and (self-)selection decision by the rm and its lenders in a context where asymmetrical information

normally lead to moral hazard and adverse selection in the decision to nance a long-term project.

It also follows from this selection process that the average infrastructure project nancing is not theaverage infrastructure project.

In a world in which, cost recovery and pro table infrastructure investment are not given, since most

infrastructure investments require considerable public subsidies (Megginson, 2005), the average project

nancing is more likely to be a much better investment prospect than the average infrastructure project.

This conclusion further supports our argument above that investing in infrastructure is about a lot more

than tangible infrastructure.

4.3 A project nance beta?

Theoretical and empirical economics tend to conclude that project nance SPEs constitute a unique type

of rm and that project nance debt and equity have fundamentally different characteristics than other

rms equity or debt instruments.

Infrastructure project nance is the result of speci c choices about the nancing of new investment

projects. It implies a preference for delegating this investment to a third party via a dedicated corporate

structure or SPE. This, in turn requires the selection of the project for dedicated limited-recourse nancing

by lenders, following the self-selection of project sponsors to invest equity in a single-project, highly

leveraged SPE.

Project nance leads to the creation of a speci c form of corporate governance, in which lenders play an

instrumental role at the investment decision stage. In fact, the structuring of project nance debt can be

described as an optimisation exercise in which lenders can set most of the parameters usually controlled

by the management of the rm in classic corporate nance.

If this is the case then infrastructure project nance equity and debt are likely to be good candidate to

contribute signi cantly to the asset allocation process that we discussed earlier. If that is the case, we

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19

may refer to a project nance beta for shorthand, even though we really mean gaining exposure to a

series of risk factors.

Three questions underpin the notion of a project nance beta:

l Does it exist? In other words, can the demonstration be made of the distinctive behaviour of basket of

such assets? Answering this question implies identifying what a well-diversi ed basket of project debt

or equity might be.

l Is it accessible? How large is this basket and how can one become exposed to it?

l Is it relevant? Is there enough investable infrastructure in the world to be relevant at the strategic

asset allocation level i.e. to invest at least a few percentage points of institutional investors' assets

under management, estimated at USD85Tr in 2012.

These questions mostly remain to be formally answered.

In the next section, we detail a roadmap of the different steps that need to be taken for develop insti-

tutional investment in infrastructure project nance, starting with answering whether project nancing

instruments can create a new and unique set of risk factor exposures i.e. benchmarking infrastructure

debt and equity instruments.

5 The roadmap: from benchmarking to regulation and investment solutions

We have argued above that the development of infrastructure investment by institutional investors on

a scale that is congruent with the current policy and regulatory agenda, that is, on a big scale, requires

understanding what infrastructure investment means from an asset allocation perspective.

The empirical evidence that we reviewed above suggests that listed infrastructure portfolios may not

improve or offer different exposures than the rest of listed equities. Likewise, unlisted PE funds using

infrastructure projects and utilities as an underlying may not be very different than other PE funds. Hence,

in both cases, there is little evidence of the a-cyclicality, predictability or in ation-hedging properties that

infrastructure investment is nevertheless expected to exhibit.

While direct investment in infrastructure projects suggests that some of these characteristics may be

captured by large investors, the dif culties encountered in building well-diversi ed positions mean that

the expected (systematic) behaviour of individual infrastructure assets is dominated by a more mundane

aspect of these investments: asset selection.

We argue that gaining exposure to the risk factors that can be expected from underlying infrastructure

investments, following the "infrastructure investment narrative", requires a shift of perspective, from

form of fundamental analysis, which only implies potential nancial characteristics, to the instruments

themselves and how their characteristics may be relevant to investors' asset allocation decisions.

Thus, answering the question of how pension funds and insurers are going to invest signi cant amounts of

capital in the infrastructure sector requires, paradoxically, to stop focusing on investing in infrastructure

projects or utilities, and to understand instead what risk factor exposures may be created for institu-

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20

tional investors using instruments that are in ne -- and probably not only -- used to nance tangible

infrastructure.

If such risk factor exposures can also be shown to be new and unique, they are much more likely to be

attractive to investors since they create opportunities to improve diversi cation, hedging and risk control

strategies.

We propose to focus on project nance instruments because, as argued above, they are the result of an

investment selection process that focuses on demonstrating certain nancial characteristics, including

delivering predictable cash ow over long periods of time.

And while instruments with similar characteristics may be found elsewhere (e.g. a utility could issue

a private long-term bond) the advantage of project nancing is to capture the majority of investable

infrastructure projects while offering a clear de nition setting it apart form corporate debt or equity, or

other alternative investments.

Starting from the notion that project nance is the relevant underlying that can lead institutionalinvestors to channel signi cant amounts to nance infrastructure because it can be used tocreate instruments that help improve the outcome of the asset allocation process, our roadmap

aims to lists the necessary steps to arrive at this result.

The rst step, as discussed in section 2, is to benchmark project nance instruments. This, in turn, allows

the design of investment solutions addressing different investment strategies while takingmarket capacity

into account. Robust benchmarking also has direct implications of the regulatory treatment of such

investments, especially risk-based prudential framework like Solvency-2, which directly impact the ability

of investors to use certain instruments. Finally, since most investable infrastructure projects are tendered

by the public sector as long-term contracts delegating investment in public infrastructure projects, the

design, standardisation and number of these contracts are of direct relevance to the development of

signi cant positions by pension funds and insurers. Hence, public procurement reform is an essential

element of this roadmap.

We discuss each point in more detail below.

5.1 Benchmarking unlisted project nance instruments

5.1.1 Objectives

The rst step of our proposed roadmap is to create a benchmark of the expected behaviour of project

nance debt and equity. In turn, this requires the development of riskmeasurement and valuationmethod-

ologies designed to use a minimum amount of standardised cash ow data.

A dedicated methodology is necessary to measure risk and value in infrastructure project nance instru-

ments because their risk pro le is highly dynamic i.e. it follows predictable changes in time spanning

several levels of risk. This is a unique feature of such instruments.

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21

Such a methodology is to be designed with the aim of mass producing investment benchmarks using

the relevant building blocks at the underlying level. Hence, we argue that it should rely in the smallest

possible amount of standardised cash ow data.

In other words, the type of standardised data points that need to be collected should be determined by

methodological choices, themselves the result of theoretical insights but with the aim of keeping data

collection as simple and low cost as possible.

In turn, this approach requires the standardisation of cash ow reporting by infrastructure investors and

their managers. In particular, a minimum cash ow reporting standard would both improve trans-

parency for investors in infrastructure products and allow the ongoing benchmarking of infrastructure

investments by applying the corresponding methodology.

Hence, we outline the following steps towards the adequate benchmarking of infrastructure project

nance debt and equity at the underlying level:

1. Develop the most parsimonious yet robust methods to measure risk and value in infrastructure

project nance equity and debt;

2. Ensure the academic and industry validation and support of these methods;

3. Based on the data inputs required to apply these methods, de ne a minimum data requirement(MDR) for the risk and value measurement of infrastructure project nance instruments;

4. Develop this MDR into a standardised reporting tool recognised by investors, regulators, policy

makers and managers as the best practice in infrastructure investments.

5.1.2 Recent developments

In two recent papers, we highlight the rst attempts at creating dedicated, parsimonious and robust

methods to measure risk in infrastructure project nance debt and equity.

In Blanc-Brude and Ismail (2013b), we develop a framework to measure the credit risk of unlisted infras-

tructure debt, including the rst formulation of "distance to default" in infrastructure project nance. We

propose to use the debt service cover ratio (DSCR or the ratio of the rm's free cash ow to its debt service

in a given period), which is routinely collected by project nance lenders, to measure and benchmark credit

risk in infrastructure project nance.

We argue that knowledge of the rst two moments of distribution of the DSCR in project nance are

suf cient to measure and predict the credit risk of individual loans. We show that the distribution of the

DSCR captures asset value and volatility and allows measuring distance to default in project nance. The

distribution of the DSCR also provides an unambiguous default point and can thus be used to build a

mapping of expected default frequencies (EDFs) in project nance.

Once characterised, the distribution of the DSCR allows the computation of an expected value, a condi-

tional probability of default at time t and a conditional probability of emergence from default.

We show that these variables are suf cient to compute loss given default (LGD) and the expression of a

loss density function of project nance loans at each point in the project lifecycle. Thus, the knowledge

of the distribution of the DSCR in project nance allows the calculation of a value-at-risk (VaR) measure

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22

of infrastructure project debt, which can be used, for example, to calibrate a risk module, such as those

used in risk-based prudential frameworks.

We also conclude that a large sample of observed or simulated project debt cash ows and their respective

DSCR in each period, could be used to derive either a functional form for the distribution of the DSCR or

an empirical mapping of distance to default and probabilities of default in project nance at each pointin the project lifecycle.

Measuring equity risk requires adapting this approach: our intuition is that equity risk in infrastructure

project nance is bounded by the SPE's credit risk on one side, and by the project's total investment risk

on the other. We know that if the SPE defaults on its debt obligation, no payment will be made to equity

in that period. The dif culty is estimating equity risk i.e. the variability of the equity payoff, when the SPE

does not default.

In another paper (Blanc-Brude and Ismail, 2013a), we propose an equivalent methodology to measure

equity investment risk in infrastructure project nance using a structural approach and building on the

systematic nancial structuring of SPEs to derive the dynamics of the equity tranche. Our approach is

parsimonious and uses a minimum amount of standardised inputs: for comparable investments, ex ante(base case) and expected (a priori) or ex post cash ows, along with default or "lock-up" frequencies at

each point in an infrastructure project's life, are suf cient to derive upside and downside measures.

Both papers above draw a list of the minimum data requirement for the application of each method-

ologies.

Valuationmethodologies for both debt and equity instruments in infrastructure project nance are currently

being developed as part of the ongoingwork of the EDHEC-Risk Institute Research Chairs on infrastructure

equity investment (Meridiam & Campbell Lutyens Chair) and infrastructure debt (NATIXIS Chair).

Signi cant efforts remain to be done to make the case of why the industry should recognise the validity

of a standardised measure and reporting format under a uni ed, publicly available methodology, as well

as the need to contribute historical and future data to an independently managed database in charge of

producing a reliable investment benchmark.

5.2 Investment solutions

Once the risk and return characteristic of underlying infrastructure project nance debt and equity have

been adequately documented, they can be used as the building blocks of different types of investment

solutions: the combination of the dynamic risk pro le of both debt and equity instruments in order to

deliver a given investment strategy.

Standard strategies can then be used as benchmarks for investors.

The most obvious such strategy would be a maximum Sharpe ratio benchmark, optimising the risk-return

trade-off of the portfolio.

In a recent paper, we show that because of the dynamic risk pro le of infrastructure project nance,

the max Sharpe ratio portfolio should include instruments corresponding to the different periods in

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23

Figure 2: Simulated value-at-risk of the equity tranche in a generic economic infrastructure project

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Source: Blanc-Brude and Ismail (2013a, see paper for technical assumptions)

the project lifecycle, including "construction risk" that is, the earlier part of a project's life, when higher

leverage and uncertainty about the project's free cash ows lead to higher probabilities of losses (both on

the equity and debt sides) but also higher remunerations of risk (see Blanc-Brude and Ismail, 2013c, for

a technical discussion). Because of the low correlations between the returns of the earlier and later parts

of the lifecycle of different projects, the diversi cation potential of different moments in the lifecycle of

infrastructure projects is shown to be signi cant.

Using the underlying as a series of building blocks (across seniorities, the project lifecycle, and systematic

project risk factors like revenue risk), different investment solutions can be imagined, through fund struc-

tures (with and without leverage), co-investment models (e.g. institutional investor alongside project

nance bank) and direct investment.

Standardised solutions (benchmarks) will take into accounts investors' objectives, including duration and

target risk levels, as well as market capacity, in particular, the availability of a suf ciently large number of

investable underlying infrastructure assets using a recognisable project nance format. We return to this

last point in section 5.4.

5.3 Regulatory developments

Current prudential regulatory frameworks have been developed to encompass the risk factor exposures

of investors and their correlations.

Once standard investment solutions into infrastructure project nance can be adequately benchmarked

as discussed above, the question of what role such investments play in investor's portfolios and whether

or not they contribute to or limit systemic risk can be answered more accurately than is currently the

case.

For example, early calibration results in Blanc-Brude and Ismail (2013b,a) suggest that the one-year value-

at-risk of project nance instruments is much lower than its current treatment under the Solvency-2

framework suggests it is (see gure 2).

Indeed, under the current bundling of project nance debt with the "spread"module and of project nance

equity with the "other equity" module, infrastructure investment are consider to represent a potential

extreme shock (99.5% VaR) to net asset value in the region of 50% but our results suggest that a these

instruments may have a much lower value at risk.

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24

Once project nance instruments and the investment solutions that can be built using them are adequately

understood and documented in the context of prudential regulation, investors' ability to invest in such

instruments and nance the infrastructure sector will also be clearer.

5.4 Public policy and procurement implications

Finally, the nature and availability of the underlying in infrastructure project nance revolves primarily

around decisions made by the public sector in the context of its procurement policy.

Hence, there is a signi cant role to be played by the public sector in standardising and expanding the

procurement of public infrastructure through investable structures designed to create the instruments

that investors are after when pursuing their own investment objectives.

A recent example is the N33 road project in the Netherlands which was designed at the procurement stage

in partnership with pension funds, to issue in ation-linked debt. The evolution of public procurement to

create investable instruments that can be used to meet the needs of investors while respecting public

sector budget constraints and the speci cities of infrastructure project nancing is the last but most

important innovation on this roadmap.

These topics will also be further developed in forthcoming publications:

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25

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