Private Sector Participationin Infrastructure: Can the Priceof Risk Transfer be Efficient?

08

Discussion Paper 2016 • 08
Dejan Makovšek

International Transport Forum,
Paris, France

Marian Moszoro

University of California,
Berkeley, USAPrivate Sector Participation in Infrastructure:
Can the Price of Risk Transfer be Efficient?

Discussion Paper No. 2016-08

Dejan Makovšek
International Transport Forum
Paris, France
Marian Moszoro
University of California at Berkeley
USA

February 2016

Makovšek and Moszoro – Private Sector Participation in Infrastructure

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Makovšek and Moszoro – Private Sector Participation in Infrastructure

Abstract
There is a drive towards delivering and operating public infrastructure through public-private
partnerships as opposed to traditional approaches. The assessment of the value for money achieved by
the two alternative approaches rests on both the cost of financing, and the efficiency in delivery andoperation. This paper focuses on the cost of financing, and in particular the cost associated withtransferring risk from the public to private sphere. If capital markets are efficient and complete, the costof private and public financing should be the same, with the relative delivery and operational efficiency
remaining as the primary determinant of value for money. However, evidence suggests the risk transfer
to a public-private partnership entails an inefficient risk pricing premium. We argue that a high price forpublic-private partnerships results from large risk transfers, risk treatment within the private sector, anduncertainty around the past and future performance of PPP consortiums. The corollary of the finding isthat the efficiency gains from a PPP need to be much higher than previously understood to deliver better
value for money than under a traditional approach.

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Table of contents
Introduction ................................................................................................................................. 5
Scope ............................................................................................................................................. 6“Efficient” pricing of risk ........................................................................................................... 7
Methodology................................................................................................................................. 8
Risk pricing efficiency in a Public-Private Partnership........................................................... 9
Availability of risk performance information at the SPV level ............................................... 10
Are there abnormal returns possible for PPPs?........................................................................ 10
Indirect inference on risk performance – demand risk ............................................................ 11
Indirect inference on risk performance – construction risk ..................................................... 12
Competition for the contract .................................................................................................... 15
Discussion ................................................................................................................................... 16
Conclusion .................................................................................................................................. 17
Bibliography............................................................................................................................... 19

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Introduction

Many countries have identified substantial infrastructure investment needs, particularly in thetransport sector. Initiatives to increase the volume of available finance, including the promotion ofprivate participation in infrastructure through Public-Private Partnerships (PPPs)1, have been advanced toaddress these needs. Transport infrastructure represented a substantial part of the total PPP transaction
volume in recent years (EIB 2014). Against this trend, the debate on the relative cost of public andprivate finance is still not settled (Green et al. 2015).
Various countries attempt to determine when a PPP would be expected to offer a better value formoney than traditional infrastructure procurement (World Bank 2013). The relative cost of public capitalversus the cost of private capital is one of the essential components of these assessments.
At face value, it appears that private financing always requires a higher cost of capital than publicborrowing, which would make a value for money comparison difficult. However, this is at least partly
due to the way that risks and their costs are expressed in each case (Helm 2010, 19; Klein 1997). For
publicly financed investments, borrowing is at a low, risk-free rate ex ante, yet the taxpayer implicitly
bears much of the risk (covering cost overruns ex post). For the private sector, there is no “ex post
taxpayer” option, so the risk must be expressed ex ante. That is, since the true risks and costs ofgovernment borrowing are partly obscured, they cannot be directly compared with those of the private
sector, which are clearly expressed in the required rate of return.
One solution to the challenge of incomparability of costs of capital is to argue that the Efficient
Markets Hypothesis (EMH) holds in the market for PPPs. If the relevant capital markets are competitiveand complete (i.e. all risks can be traded), the private cost of finance will represent the efficient cost of
the risks involved in the project: the financing costs of the public and private approaches would beequivalent (Brealey et al. 1997). Under this approach, value for money assessments would depend solely
on the efficiency differential between public and private ownership and management.
There is empirical evidence that suggests that the EMH does not adequately describe PPP-related
capital markets so that the cost of capital question cannot so easily be swept away. Specifically, theevidence suggests that investors in PPPs have made excessive returns, PPP bidders demand excessive
risk premiums, and there is insufficient competition for contracts. This paper reviews this empiricalevidence and concludes that governments pay a high price for public-private partnerships primarily due
to large risk transfers, risk treatment within the private sector, and uncertainty.
Section two of this paper presents the subject of our analysis – capitally intensive project finance
PPPs. Section three sets out the theoretical background on risk pricing efficiency, including some1

PPP covers a variety of arrangements, from management concessions of existing infrastructure to project financecontracts for the delivery and operation of new infrastructure. This paper treats the latter. We are grateful to Michael
Spackman and Daniel Veryard for support and comments on an earlier version of this paper.

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conventional challenges to the EMH. Section four sets out our analytical approach that looks at some
PPP-specific challenges to the EMH. Section five presents the implications of uncertainty on the ex-anteversus ex-post risk performance of PPPs and reviews the evidence on competition in PPPs. Section six
discusses implications of the findings and concludes.
Many countries have identified substantial infrastructure investment needs, particularly in thetransport sector. Initiatives to increase the volume of available finance, including the promotion ofprivate participation in infrastructure through public-private partnerships (PPPs)2, have been advanced toaddress these needs. Transport infrastructure represented a substantial part of the total PPP transaction
volume in recent years (EIB 2014). Against this trend, the debate on the relative cost of public andprivate finance is still not settled (Green et al. 2015).

Scope

The analysis in this paper will focus on risk pricing efficiency in capitally intensive project finance
PPPs in public infrastructure, such as roads and railways. Project financing of an infrastructure project isbased on a financial structure where investors and the lenders are repaid from the cash flow generated
from the project once it is operational, and where investors have limited or no recourse.
Building on Yescombe (2013) several general features distinguish PPPs from traditional
infrastructure procurement:

2

6



Normally a project-dedicated company is created, called the Special Purpose Vehicle (SPV),
which enters the contractual relationship with the public sector.

A high leverage is characteristic for the SPV (e.g. a 90:10 debt to equity ratio).



The public-private agreement defines an output specification i.e. what the project is meant toachieve, as opposed to what the project is (the input).



There is a bundling of all procurement phases from design to operations in one long-term
contract (e.g. the Design Build Finance Maintain Operate contract).



PPPs commit the public sector to paying a pre-agreed income to the SPV, provided the required
service delivery and quality criteria are met. Alternatively the public sector can grant the SPV
the right to collect revenues from the use of the infrastructure.



Lenders generally require that risk is transferred from the SPV to other parties to the extent
possible to reduce the risk exposure for the SPV.

PPP covers a variety of arrangements, from management concessions of existing infrastructure to project financecontracts for the delivery and operation of new infrastructure. This paper treats the latter.

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Makovšek and Moszoro – Private Sector Participation in InfrastructureWith regard to the last point in PPPs, and project finance in general, risk is managed through a
network of contracts (Blanc-Brude 2008, Gatti 2013). For example, fixed-price and date-certain turnkey
contracts3 are required to transfer construction risk.

“Efficient” pricing of risk

In standard finance theory, investors in any project or asset face two types of risk: systematic andnon-systematic risk. Systematic risk relates to the risk that is not diversifiable. Non-systematic risk
relates to idiosyncratic project characteristics, such as geology, complexity of construction, country or
counterparty risk, which is diversifiable. The private sector’s standard tool for pricing risk within aportfolio of assets is the Capital Asset Pricing Model (CAPM) (Markowitz, 1952). In CAPM, therequired rate of return on a risky asset is derived from (i) the risk-free rate, (ii) the market-risk premiumand (iii) the correlation between the asset and the market (“beta”4) alone. Non-systematic risk is not
relevant for pricing as it can be diversified away by including other assets in the portfolio.
In practice, potential investors do not blindly follow CAPM outputs when setting required rates ofreturn, but instead apply minimum “hurdle” rates of return or include a mark-up for non-systematic risks(Jensen and Meckling 1976; Tan 2007; Mehra and Prescott 1985; Fama and French 1992). Arrow and
Lind (1970) also note that from the perspective of an individual manager’s career and income, thevariance of returns on a single investment may be important. A mark-up may therefore be applied as apremium for the non-systematic risk – even if this risk is not a material concern to shareholders.
Against the argument of return mark-ups is the possibility that competition between investors may
be sufficient for any extraordinary profits to be eroded in the long-run. In this case, the CAPM-estimatedprices for risk can (eventually) be considered as efficient. That is, the market will be efficient if theconditions for the EMH hold, including that prices reflect all available information.
Depending on how “all available information” is defined, financial theory distinguishes between
three versions of the EMH. The version closest to reality and mainly accepted from financial economics
is the weak version (Doran et al., 2010). It assumes prices incorporate information on past prices and willchange only when new information becomes available.
The applicability of the EMH to asset markets has been questioned on methodological grounds (e.g.
Mandelbrot and Hudson 2004 criticize the inadequacy of the random walk assumption) and on a more
3

Alternatively, in cases (e.g. construction companies in developing countries), where the construction companies arefinancially unable to accept the construction risk, the construction budget of the SPV includes a sizeablecontingency. Clearly though in this case the incentive for the construction company to efficiency manage risk will bemuch reduced and an important part of the PPP rationale is lost.

4

Beta is the (weighted) covariance between the return on the asset and the return on the equity market. A beta of one
signifies the asset is perfectly correlated with the market (e.g. the traffic demand for a road project is strongly
dependent on the state of the national economy, so will have a beta close to one). The equilibrium return on the asset
in this case is the return on the market portfolio. A beta with the value of zero implies no correlation between theasset and the market, hence the equilibrium return is the risk-free rate of return. In theory investors shoud demand
the equilibrium expected return to be compensated for “receiving” or “holding” the risk.

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fundamental level for assuming rational behaviour by investors (Thaler and Sunstein 2008). Numerous
relevant biases of human decision making under uncertainty have been documented, including
overconfidence (Fischoff and Slovic 1980; Barber and Odean 2001; Gervais and Odean 2001),
overreaction (DeBond and Thaler 1986), herding (Huberman and Regev 2001), psychological accounting(Tversky and Kahneman 1981), miscalibration of probabilities (Licthenstein et al. 1982), hyperbolic
discounting (Laibson 1997), regret (Bell 1982; Clarke et al. 1994) and loss aversion (Kahneman andTversky 1979; Shefrin and Statman 1985; Odean 1998).
In response to criticisms, EMH proponents insist that the effects of the biases are temporary so thatthe market will eventually always bring the prices to rational levels (Lo 2004). Several studies attempt todemonstrate that markets in developing and developed economies asymptotically approach efficiency,
though the issue remains contested (Hull and McGroarty 2014; Alvarez-Ramirez et al. 2012). This
interpretation of the EMH assumes all uncertainty will ultimately become quantifiable as a distribution ofprobabilities. Unknowable (Knightian) uncertainty5, if present, is eventually resolved.

Methodology

If risk in PPPs is priced efficiently as per the EMH, then value for money questions in PPPs can begreatly simplified. To date, the debate over the applicability of the EMH has generally taken place in thecontext of homogeneous risky assets such as equities, where deep historical datasets are available. Little
current research has accounted for the specific context of PPPs and infrastructure, where past information
on asset performance is difficult to access or compare. The debate also largely ignores the complexity ofrisk treatment and allocation within a PPP contract.
The efficiency of risk pricing in the case of PPPs primarily depends on two related components: thedegree of competition for contracts, and the way in which investors/lenders understand and price risk.
Competition for the contract is the more straightforward element to assess. Reasonable data isavailable on the number of PPP consortiums bidding for the contract, and it can be assessed for the
project as a without considering the nature of each consortium’s internal structure. The second
component (which also influences the first) is more difficult to assess due to the complexity and diversityof the risk transfer contracts within each PPP consortium.
58Knight (1921, 233) defined risk as a situation in which the distribution of the outcome in a group of
instances is known and uncertainty, when it is “impossible to form a group of instances, because thesituation dealt with is in a high degree unique”. Later, Ramsey and De Finetti developed the methods ofmeasurement and handling of subjective probabilities (Gillies 2003). In effect, when we have nohistorical data (and are subject to uncertainty in line with Knight), we can derive a subjective probability,
by asking the investors or groups of investors on the bets they would be willing to place. To the extent
that the individual facing the lack of historical statistical data to inform his decision and doubts his own
subjective bet against uncertainty, he may assume that the rest of the world is perhaps better informed.
Effectively, the individual becomes influenced or follows the behaviour of the majority or the average.
This situation is then referred to as intersubjective probability. Both the subjective or intersubjective
probabilities are in line with Keynes (1936, 161-162) subject to his “animal spirits”, the fluctuations in
the investors disposition, optimism or pessimism.

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Our approach to the second component of risk pricing efficiency is to look for direct evidence ofsystematic abnormal profits earned by private parties in PPPs, and for indirect evidence of a lack of
information prohibiting efficient risk pricing under the EMH. The approach necessarily takes a numberof different angles, including one that considers the contract structure holistically. The efficiency of risk
pricing in a PPP depends on the total “volume” of the transferred risk – the part at the level of the SPV
and each part transferred to related parties. Ideally each part of transferred risk should be assessed
separately.
Risk pricing efficiency performance would be easiest to assess at the SPV level, because any market
index would reflect the performance of SPVs alone. For risks that are transferred out of the SPV thiswould be more difficult. In construction companies for example the outcomes of specific PPP projects
will be private information held within the cash-flows of numerous other activities a construction
company may pursue. In these cases we attempt to assess the risk performance indirectly, by measuringsystematic project performance in terms of major project risks, such as construction or operations risk. If
the materialized (ex-post) risk systematically undershoots the expected (ex-ante) risk, then this could
indicate abnormal profits and one or both of the conditions for efficient pricing is not met.
In this paper we review existing empirical studies using large samples to tackle the following:

Direct observation of PPP risk pricing efficiency:o Is there a homogenous market index of PPP risk performance available and is inference
on EMH efficiency possible?
o Can systematic abnormal returns be observed in PPPs?
Indirect observation of PPP risk pricing efficiency:o Can the risk performance of PPPs be indirectly inferred through ex post outcomes of themain building blocks of risk and return in a PPP - demand, construction risk, andoperations risk?
What is the level of competition for the contract in PPPs to work towards reducing the risk
premium?

In our analysis we assume that the incentives present within the contractual framework of a PPP
will be the same regardless of the sector and therefore that findings are transferable between sectors. For
example, Blanc-Brude and Makovšek (2013) find that insights on construction risk (excellent on-timeand on-budget construction of infrastructure under project finance) do not depend on the project sector,
geography or time.

Risk pricing efficiency in a Public-Private Partnership

Several decades after the roll-out of the PPP model in the UK and the model’s proliferation to othercountries, there is still a dearth of information on the financial performance of such projects.
Nevertheless, a coherent picture is beginning to emerge based on the partial information available.

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The following sections follow the design of the analytical approach outlined above. (Though norelevant research was encountered on operations risk so this is not treated.)
Availability of risk performance information at the SPV level
While there is some information available on the exposure of the lenders to risk in PPP contracts6
there are no consolidated data sources about the exposure of investors. A recent review of literatureconcluded that – for our purposes – all existing papers or indices on infrastructure suffer from a study
design problem, aggregating “financial instruments that are labelled as ‘infrastructure’ based on
industrial categories and without attempting to isolate methodically the contractual and regulatory
characteristics” (Blanc-Brude 2013, 57). The performance and risk profile of a regulated utility will be
substantially different from a PPP and having such information pooled is not very useful. A related
challenge is that a lot of the investment performance information is private and not publicly available(ibid).
The lack of information on the infrastructure investment performance directly contradicts the “fullinformation” requirement for the EMH to hold, suggesting that any quantitative testing for EMH ispointless. This gap has also prompted several initiatives to collect the relevant data (e.g. EDHEC Risk
Institute7, OECD8, FSB9).
Are there abnormal returns possible for PPPs?
To observe abnormal returns, a view on the “normal” returns is necessary. Not having ahomogenous market index makes it impossible to directly establish this view empirically. Nevertheless,there are studies that indirectly indicate abnormal returns by observing a systematic differential between
expected returns at financial close (when the financing of the project was secured and contracts weresigned) and ex-post returns. This will not reveal the full range of potential abnormal returns (as they may
have already existed at the financial close), but it will provide some indication between expected risk
exposure and materialized risk.
NAO (2012) and Vecchi et al. (2013) used an alternative approach to the classic financial
assessment or risk and return (e.g. assessing volatility, Sharpe ratio). They compared expected ex-ante
returns at financial close and actual ex-post returns.
NAO (2012) analysed 118 projects, and in 84 cases expected returns were equalled or exceeded,while in the remaining 34 cases the returns were lower than expected. NAO (ibid.) noted that the projects
were still in operation and had not yet reached the stage where significant refurbishment might beneeded, so their conclusions (based on the realisation of costs) could change.
Vecchi et al. (2013) using a similar, but a more elaborate approach than NAO on a sample of 77 UK
availability-based PPP hospital projects, showed that the ex-post returns to investors were substantially6

Moody’s study (Davidson et al. 2013) of 954 PPPs for example notes, that “The 10 year cumulative default rate is3.9%, which is consistent with 10 year cumulative default rates for corporate issuers in the Baa ratings category.”7

http://www.edhec-risk.com/multistyle_multiclass/Meridiam_Infrastructure_and_Campbell_Lutyens_
Research_Chair8

http://www.oecd.org/finance/private-pensions/institutionalinvestorsandlong-terminvestment.htm

9

http://www.financialstabilityboard.org/wp-content/uploads/r_140916.pdf

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above expected ex-ante returns at the financial close. The average blended equity IRR10 was 9.3% (with arange of 4.5% to 17.4%) above average expected financing cost at financial close.
Thus the available evidence suggests the distribution of PPP returns is skewed to the left withreturns on average being substantially above expected returns. This is the case despite the fact that in thecited examples the only real risk exposure comes from operations (and potential contractor default), as allother risks are negligible:Regulatory and political risks are not a serious issue in the UK. A survey of 171 PFI projects
from all sectors showed that changes in the contracts amounted to a mere 1.1% of the annual
service payments from the state to the private provider (unitary charges) for projects in question(NAO, 2008). The majority of changes (82%) involved values of £5000 or less and almost all
originated from the public sector requests.



There is no demand-based risk in the samples considered; andConstruction risk is fully passed to the company with the construction contract (NAO 2012).

Indirect inference on risk performance – demand risk
Demand risk performance relates to whether actual ex-post demand undershot, met or overshot
expected demand ex ante. If the pricing for this risk were efficient, then on average over many projects
risk performance should not exhibit a significant systematic error. Put simply, systematic demand
shortfalls should not exist, since this would imply lenders/investors are on average losing money.
Conversely, a small systematic excess of actual demand (as opposed to expectations) would however be
acceptable as a reflection of the risk aversion of investors. A large systematic excess of actual demand on
the other hand would signal that either the lenders/investors have a poor idea about the actual risks,
which manifests in large risk aversion, and/or there is insufficient competition.
Most evidence of ex-post analysis comes from toll roads and rail and concerns only risk exposure,without a view on returns. Demand risk in this case cannot be managed and relates to traffic forecasting.
This is not an exact science and systematic errors have been observed in traditionally procured projects
and private toll concessions.
Traffic risk must be assessed for each project specifically, using historical information and expecteddevelopments in the future. Traffic forecasting is a scientific field in its own right. An investor or alender cannot directly observe the riskiness of the project by comparing some of his characteristics tosimilar projects. But he may get a limited view by observing systematic errors in expectations for similar
projects. This is the subject of ex-post analysis. Related evidence is summarized below.
Bain (2009) presented evidence on 104 toll road concessions from around the globe to find that on
average traffic demand is 23% overestimated. By contrast, in the sample of traditionally procured and
10

The equity stakes plus the subordinated portion of debt in the SPV end up in each sponsor’s balance
sheet (i.e. the blended equity). The remuneration for these investments is represented by the blended IRRof the SPV. Sponsors need to have a view whether or not the project will increase the wealth of theirshareholders and will compare the blended equity IRR with their respective WACC. If this difference ispositive, the project is economically attractive for each of the sponsors (Vecchi et al 2013, 248), with the
expected earnings above average.

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predominantly European road projects Flyvbjerg et al. (2005) and Naess et al. (2006) found a systematic
error in the opposite direction: actual traffic averaged 9.5% higher than forecasted traffic. Button andChen (2014) examine pure public and public–private US highway investment traffic demand forecasts tofind no evidence that latter are more accurate.
In the case of rail, Dehornoy (2012) reviews cases of PPPs with demand risk since the 1980s. Of the
14 projects reviewed, 5 were not yet developed enough to allow analysis, but in the remaining 9 theaverage ridership, assessed at different years of operation, was 63% below estimates. Flyvbjerg et al.
(2006) reports a -54% average error on 25 projects, though these may include many of the ones alreadystudied by Dehornoy (ibid) (which the authors did not reveal).
The demand forecasting errors in PPPs noted above should not be simply interpreted as losses toinvestors, however. Contract renegotiation experiences from around the world show that many PPPs are
subject to strategic behaviour from the public and the private sector, although this challenge appears to
be greater in developing, rather than developed, countries (Makovšek et al. 2015).
That being said, there are cases, where systematic errors do translate to investor/lender losses. Bainand Oxera (2012) show that in Australia all 7 toll road projects have underperformed since 2005 andargue that this is the result of deliberate overestimation by (private) project sponsors to attract investors11.
Recently EPEC (2014) reported that in 2012 over 90% of PPP transactions12 closed were without
demand risk. It is plausible to assume that given the considerable uncertainty of demand investors (andlenders) have learned to avoid its transfer.
Indirect inference on risk performance – construction risk
Construction risk relates to cost and schedule overruns against the contract or estimates at financial
close13. The logic here is slightly different than in the case of demand risk, because the construction risk
performance of the construction contractor in a PPP is private information embedded within the fixedprice charged for the project. How this was approached at the level of the construction contractor is
explained further below. Construction risk however has an impact at both the SPV level and theconstruction contractor level. The SPV level is treated first.
Construction risk at the SPV level
Lenders and investors generally do not have good understanding of construction risk exposure andseek to transfer the construction risk to the party best able to manage it, namely the construction
contractor.

11

The private sponsors of the failed projects have become the subject of class action law suits as in the caseof CLEM7 tunnel in Brisbane(http://www.wsj.com/articles/SB10001424052702304434104579379351959645932).

12

Looking only at the transport sector is still representative of the market. Transport accounts for the
majority of the PPP volume on the market in Europe (over two thirds in 2014; EIB 2015), with roadprojects typically dominant.

13

Another definition of construction risk measures ex-post costs against those at the formal decision tobuild (i.e. well before the contract letting/financial close). That definition is more relevant to the processof investment appraisal and investment selection, such as in the research by Bent Flyvbjerg and others.

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Yet construction risk has an impact also at the SPV level. In the only such study, the risk transferfrom the SPV to the construction contractor is found to be fully successful, with a median cost overrun ofzero across 75 large project-finance infrastructure projects worldwide (Blanc-Brude and Makovšek
2013). This implies that, for the investors in the SPV (including lenders), construction risk is fully
diversifiable, and hence should not be relevant to the cost of financing (save for the transaction cost of its
diversification). Historical analysis has shown that this was not the case, and that the required return ofthe projects declined sharply after the construction phase was finished (Blanc-Brude and Ismail 2013).
Accordingly refinancing is common after the completion of the construction phase, suggesting lenders
applied a premium to the construction phase of the project, in spite of the risk being fully diversifiable.
This is indicative of abnormal returns at the SPV level and may reflect the insufficient portfolio size oflenders that constrains them from diversifying their risk.
Construction risk and the construction contractor
For the construction company the relevant measure of risk exposure is a risk contingency, which isan amount added to a central estimate of cost to cover future cost overruns that are realised. A range oftechniques for quantifying construction risk have been propounded in academic construction literature,including deterministic methods, probabilistic methods and fuzzy-logic (Baccarini 2006). However, there
is a lack of historical information and inherent complexity to allow construction companies to apply
these methods to major infrastructure construction projects. Accordingly, construction risk (and theresulting contingency amount) is normally estimated subjectively through risk workshops, experts
scrutinise the design and assign probabilities and impacts of various events (IRG 2013). Though such
exercises are invaluable in terms of due diligence, there is no empirical research available on their expost accuracy, making it difficult to form a view on the accuracy of contractors’ perceptions of risk.
Studies like that of De Silva et al (2008, 164) confirm that private sector assessments of risk forcomplex projects are rough. The study treated traditional highway procurement, where the risk exposureof the construction company is lower than in PPP projects. Oklahoma’s Department of Transportation
changed its procurement policy to make the state’s internal cost estimates public during tendering. After
this information was released winning bids on average reduced by 11% for more risky/complex (bridge
construction) projects but were unaffected for low risk projects (asphalt pouring). The authors applied a
difference-in-difference approach, observing thousands of bids over multiple years. In general theavailability of the state’s estimates improved bidders’ willingness to reduce their contingencies.
Ideally we would directly assess expected and ex-post outcomes for the construction contractor,
however this private information is unavailable. Instead, we must make observations at the level of theoverall PPP contract between the SPV and the state. Here, we attempt to match the probability of risk
transferred from the state, with the cost they paid for it. This requires two pieces of information:
The extent of the construction risk transferred from the state to the PPP (and from the SPV tothe construction contractor); andThe cost of infrastructure, when built by the state (traditionally) and the cost of infrastructure,when built by the PPP.

The extent of construction risk transferred from the state to the PPP can be inferred from thecomparative performance of traditional procurement and PPPs. The previous subsection highlighted that
construction risk appears to be fully transferred from the state to the SPV and from the SPV fully to theconstruction contractor in PPP contracts: the median cost overrun was zero, and the average overrun was
2.3%, for a large sample of projects (Blanc-Brude and Makovšek, 2013). In contrast, for traditionally

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procured road projects, large cost overruns were absorbed by the state. These cost overruns (measured
against the detailed design or contract value) reached on average up to 9% over large samples in different
studies (ibid).
Whether the project is delivered using traditional procurement or a PPP, the primary cause of cost
overruns is scope creep, at least in the case of transport infrastructure (Makovšek 2013). Under the termsof either contract, it is the responsibility of the procuring authority to define what it wants to build, so ineither case the cost overrun is not necessarily a risk to the construction company or the SPV as the
additional cost can be passed back to the procuring authority. To the extent that much of the 9 %mentioned above would reflect the responsibility of the procurement authority in defining the scope, theactual risk to be managed in a PPP would be smaller.
Despite the relatively small amount of risk transferred to PPPs, there is clear evidence that the costof infrastructure is higher when built via a PPP than when it is built via the state traditionally. BlancBrude et al. (2006) observed ex-ante construction cost (contract prices) in 162 traditionally procured and
65 PPP road projects in Western Europe. The PPPs were found to be 24% more costly on average thanequivalent traditionally procured projects (ceteris paribus).
Makovšek (2013) argues that given the level of cost overruns at contract close phase in traditional
procurement, PPPs are still substantially more costly even after the expected cost overruns risk in
traditional procurement is accounted for: He illustrates the cost advantage over PPPs in the Blanc-Brudeet al sample remains around 14–19% without accounting for cost growth in PPPs (to illustrate - wewould have to add the 3.2% mentioned above to establish the full difference). The Blanc-Brude et al
approach was also replicated using US data and yielded an even greater cost premium of 64% for PPP
road projects over traditionally procured ones (Daito and Gifford 2014). Figure 1 below illustrates thetwo dimensions described above: higher cost overruns with traditional procurement, yet higher overall
construction costs with PPPs.
Figure 1. Traditional procurement and PPP cost performance, cost overruns vs total cost

Taken together these strands of evidence suggest that the cost to governments of the transferringrisk to the private party in a PPP is significantly above the efficient price (The unexplained costdifference in Figure 1 above). Two further arguments may compound this finding. First, lenders andinvestors may avoid the riskiest of projects, suggesting the portfolio of projects delivered as PPPs isactually lower risk than the traditionally procured one. Second, traditional procurement mainly relies on

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cost-plus contracts, which provide fewer incentives to efficiently manage risk while the PPP model relies
on fixed-price turn-key contracts, which are likely to be better managed. Interestingly, practitioners
report that the use of lump-sum turnkey construction contract generally involves a premium of 20%
against less restrictive contract types, such as design-bid-build, regardless of whether it is part of a PPP
or not (Yescombe 2013).
An argument against a conclusion that these outcomes are a source of inefficient risk pricing or
extraordinary profits in PPP projects is that higher quality infrastructure is being built to optimise the life
cycle cost of infrastructure management. This should be true for capital intensive PPPs in any sector.
There is however little evidence to suggest that this is the case or that in all traditionally procured
projects the opposite is true. On a declarative level there is a widespread embrace of life-cycle cost
optimisation principles in PPPs in UK (Meng and Harshaw 2013), but there are practical obstacles to its
execution. The single available study by NAO (2007) suggests the contrary. A construction review of
PPP hospitals in the UK found that these were not built to a higher standard of quality than traditionallyprocured hospitals.
Competition for the contract
Competition is one of the key conditions for the EMH to hold. It is generally accepted thattransferring risk to a risk-averse private party will incur a risk premium, with the size of the premium
depending on the level of risk aversion and the degree of competition.
Empirical data on competition for PPP contracts is currently limited to the UK, though this evidence
consistently suggests that competition is limited, due to complexity and transaction requirements (Houseof Commons Treasury Committee 2011). For example:


The NAO (2007) found that one third of PFI projects attracted two bidders or fewer between
2004 and 2006 mainly because of lack of bidder interest since very few firms have theeconomies of scale and asset base to absorb the exposure and high bid costs.



Zitron (2006) reported that on average there were three bidders for each SPV contract in his
sample of 86 PPPs in the UK, and in a quarter there were fewer than three bidders.



Hellowell (2012) finds that over the period 1997–2010 that the market for private finance of
PPP hospitals is an oligopoly with a very limited number of firms, and that churn and market
penetration rates are extremely low. In addition he finds no improvement over time.

Blanc-Brude (2013) suggested that the transfer of risk deters smaller firms unable to absorb or
manage it from bidding. He finds evidence in the UK PFI school market that the distribution ofbidding firms is skewed towards the largest firms (which also have the most capacity to absorb
major risk transfers through fixed-price/fixed-date contracts).

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Discussion

Economic theory assumes the public and the private sector can both diversify non-systematic risk
well. It disagrees about whether the systematic risk equity market premium is relevant to the taxpayer.
Given the review of the available evidence for PPPs, the current perspective of economic theory appears
to be too narrow and possibly focused at the wrong end of the problem.
EMH in economic theory assumes that non-systematic risk is quantifiable and can be eliminated bydiversification of a portfolio. There is evidence that a limited version of the EMH applies forhomogeneous assets, such as equities or commodities. However, this paper has raised significant doubts
about the applicability of the EMH to infrastructure assets, particularly to project finance PPPs.
A central challenge to the applicability of the EMH in PPPs is the difficulty in quantifying risk. The
heterogeneity of contracts and project scopes means that the pricing performance history that could
enable modelling and quantification of risks has not been available to bidders or governments. If risks
cannot be clearly identified or quantified, it is implausible that market actors will be able to eliminate
non-systematic risk of an infrastructure asset through careful diversification, since they will not be able
to identify those assets with imperfectly correlated returns.
Several international institutions are seeking to establish PPPs as a formal asset class by collecting
performance data on contracts between governments with SPVs. Additional contract and performancedata will clearly help to illuminate the nature and magnitude of the risks taken on by SPVs. If successful,
this initiative should lead towards a reduction in the risk premiums demanded by SPVs as informationand competition improves.
Unfortunately, the picture is not so simple within a PPP. The contractual arrangements between the
SPV and other parties generally disperses significant risks beyond the scope of the SPV. For example,
the risk of cost overruns often gets transferred away from the SPV onto the construction contractor so as
to reduce the risk exposure of lenders and reduce the debt interest rate. Consequently, newly collected
SPV data is not expected to illuminate the nature or the pricing of these transferred risks.
Construction contractors and other private participants accept the risks transferred to them as part of
the PPP contract at a premium. They lack the data to support the quantification of these risks, but also theopportunities to adequately diversify their portfolio. As such, the premium they charge is likely to be
above the efficient level that might be predicted by the EMH.
Evidence examined in this paper provides some support for this position. Construction costs forequivalent infrastructure were found to be higher under PPPs than traditional procurement. Thisdifference is not explained simply by SPVs having incentives to minimise whole of life costing throughconstruction of better assets upfront. Instead it is more likely attributable to the inability to quantify risk
and the PPP risk transfer both deterring competition in the bidding and attracting high risk premiums
among those consortiums who do bid. Within the PPP contract structure, the construction company
carrying the construction cost risks is likely to embed a relatively large risk contingency in their costestimate.
The risk premiums embedded by parties within the PPP structure (such as construction cost
contingencies) will drive costs above those charged by a government. There are two reasons to expect
this: First, in contrast to the private parties in a PPP, the state is generally reasonably well placed to16

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diversify risks due to its large balance sheet, and diverse set of risks to its outlays and revenues it
naturally faces. Second, the state can face the lack of information about risk with risk neutrality 14,
because it can draw on taxpayers ex post to pay any shortfalls if and when they occur.
This does not imply the state should not care about risk or that it should not try to assess it and use it
in decision making. It means that the taxpayers in traditional procurement pay a price that is closer to theactual cost of risk than they would under a PPP.

Conclusion

This paper is a contribution to the long debate on the comparative cost of public and private
financing in traditional procurement and project finance PPPs. In an interdisciplinary effort, we have
explored if the assumptions of the EMH fit with the practice of risk transfer to PPPs and its allocation
within a PPP. The aim was to pool available empirical evidence and to propose a narrative that would
adequately explain it.
Our findings suggest that defining infrastructure as an asset class will be insufficient to achieve
efficient risk pricing for PPPs, when considered holistically. Much of the risk is transferred off the SPV
as well. These risks will still be difficult to identify and quantify.
Evidence on construction risk suggests that with a lack of information about risk, combined withlarge risk transfers through high powered fixed-price/fixed-date contracts, yield high risk premiums andinherently reduce competition. These contracts reduce the risk exposure for the lenders (and the cost offinancing they offer) at the level of the SPV, but in-turn increases the principal that has to be financed,
since the construction company will charge a high contingency value.
In this way, it can then be argued that the state has an advantage in the cost of financing
infrastructure PPPs. It is better able to spread diversifiable project risk and has the ability to approach thelack of information about risk in a risk neutral manner, paying for any shortfalls if and when they occur.
A basic corollary to these findings is that the efficiency gains from a PPP would need to be muchhigher than previously understood to be preferred to the traditional approach. In light of the limited
available evidence, this conclusion must be regarded as tentative. Future research would benefit from
more data on project performance in diverse sectors.
Two recommendations follow from our analysis. Firstly, a clearer understanding on which risk
items are manageable (and to what extent) might give us a better picture of which risks should remain
with the state (or be shared with the private sector). Secondly, the incentives and efficiency outcomes in
14

A given overspend has the same direct social cost with either public or private financing (the risk of suchan overspend will be reflected in private financing costs, and ex post also in public financing costs). The
private contractor and/or private shareholders may be more averse than the government to such risks,because of the possible subsequent collapse of the contractor and/or serious personal or reputational loss
to the financiers. While if the cost falls on taxpayers there will be no further costs or this kind as thefinancial loss is widely spread.

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both PPPs and other options for private participation in infrastructure need to be better understood. Thereis a wealth of evidence that suggests economic regulation with privatisation can bring increased
efficiency (e.g. privatisation of regulated utilities) yet we understand little about the value for money ofthat model compared to project finance PPP.

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