Institutional and Political
Determinants of Private
Participation in Infrastructure

15

Discussion Paper 2014 • 15
Marian Moszoro, Gonzalo Araya,
Fernanda Ruiz-Nuñez
and Jordan Schwartz
The World Bank,
Washington D.C., USA

Institutional and Political Determinants ofPrivate Participation in Infrastructure
Discussion Paper No 2014-15
Prepared for the Roundtable:

Public Private Partnerships for Transport Infrastructure:
Renegotiations, how to approach them and economic outcomes
27-28 October 2014,
George Mason University, Washington D.C., USA

Marian Moszoro, Gonzalo Araya,
Fernanda Ruiz-Nuñez and Jordan Schwartz1

Revised October 2014
1

Gonzalo Araya, a former Junior Professional Associate in the Sustainable Development Department of theWorld Bank’s Latin America and Caribbean Region, now at the Ministry of Transport and Telecommunicationsof Chile; Marian Moszoro is a Professor of Finance at Kozminski University, Poland, Visiting Scholar at the
University of California, Berkeley, a Senior Financial Consultant at the World Bank, and former Undersecretaryof Finance of Poland; Fernanda Ruiz Nuñez is a Senior Infrastructure Economist at the Infrastructure Policy
Unit, PPPs Group at the World Bank; and Jordan Schwartz is Manager at the Infrastructure Policy Unit, PPPs
Group at the World Bank, based at the Bank’s Center for Infrastructure & Urban Development in Singapore. The
authors’ email addresses are: gonzaloarayaa@gmail.com, mmoszoro@berkeley.edu,
fruiznunez@worldbank.org, and jschwartz3@worldbank.org.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table of Contents

Abstract .................................................................................................................................................... 4
1.

Introduction ...................................................................................................................................... 5

2.

Theoretical Background to Understand the Determinants of PPI .................................................... 8
Existing literature ............................................................................................................................. 8
Methodology .................................................................................................................................. 10

3.

Data Description............................................................................................................................. 13

4.

Results ............................................................................................................................................ 14

5.

Conclusions .................................................................................................................................... 18

Bibliography .......................................................................................................................................... 19
Annex I ................................................................................................................................................... 22
Annex II ................................................................................................................................................. 23
Annex III ................................................................................................................................................ 24

Washington D.C., October 2014

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 20143

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Abstract
We assembled a large panel of project-level technical and financial data and country-level economic,
institutional, political, and governance variables to assess the determinants of private financing of
infrastructure in emerging markets and developing economies. Controlling for economic
characteristics, we find that overall private participation of infrastructure financing increases withfreedom from corruption, rule of law, quality of regulations, and decreases with court disputes. We
provide plausible explanations of deviations from this pattern when data is disaggregated at thesectoral level. We also found that legal systems—types of democracy or dictatorship—do not play arole in whether the private sector invests in infrastructure. Our results do not vary when controlling forincome inequality and across quartiles of experience, country wealth, and wealth per capita. The study
shows that upstream “enabling” institutions, policies, and regulations and sector economics need to beaddressed simultaneously to facilitate private infrastructure investment financing.
JEL Classification: D73, H54, L33, L51, R42
Keywords: Private Participation in Infrastructure, Bureaucracy, Corruption, Regulation, Rule of Law_________________________
Moszoro: University of California, Berkeley and Kozminski University, Poland,
mmoszoro@berkeley.edu; Araya: Ministry of Transport and Telecommunications of Chile,
gonzaloarayaa@gmail.com; Ruiz-Nuñez: PPPs Group at the World Bank, fruiznunez@worldbank.org;
Schwartz: PPPs Group at the World Bank, jschwartz3@worldbank.org. The authors are grateful toAlex Jett for his support with the PPI Database, Francesca Guiso for assisting with the data analysis,
and Conor Healy for sharing digitalized data on Disputes. The findings, interpretations, andconclusions expressed herein do not necessarily reflect the views of the Board of the Executive
Directors of the World Bank or the governments they represent.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

1. Introduction
The links between infrastructure and development are well established. They include the impact of
infrastructure on poverty alleviation, equity, growth, and specific development outcomes such as job
creation, market access, health, and education (Straub 2008; Calderόn and Servén 2004, 2008, 2010).
These relationships are complex and dynamic; even with respect to growth and job creation;
infrastructure’s effects are felt through multiple channels.2 The demand for infrastructure is rising withthe accelerating pace of globalization and urbanization. Every month in the developing world, morethan five million people migrate to urban areas. This trend is compounded by the growing need for
low CO2 and climate-resilient investments to combat the challenges of climate change (Fay andToman 2010; Bhattacharya and Romani 2013).
As a result of the fiscal constraints in many economies caused by the onset of the global financial
crisis, government budgets—traditionally the major source of financing for infrastructure—cannot
alone be expected to finance the infrastructure needs in emerging markets and developing economies(EMDEs). Yet the volume of private participation in financing infrastructure projects in EMDEs
remains modest.
While private sector financial commitments to infrastructure projects have risen to about
USD 181 billion per year in EMDEs, this is less than 20% of the overall current infrastructure
investment in these economies. There has been an important increase in private participation in
infrastructure financing (PPI) over the last two decades.3 Annual commitments4 to PPI projects haveincreased from USD 22 million in 1990 to USD 181 million in 2012 (see Figure 1). Importantly, mostof this growth since 2000 has been mainly in the energy and transport sectors (see Figure 2).

2

See Agénor and Moreno-Dodson (2006) for an overview and Estache et al. (2013) and Schwartz et al. (2009)
for a treatment of infrastructure’s effects on jobs and growth.
3

Private participation in infrastructure can be treated as equivalent to public-private partnerships.

4

Investment in this paper refers to the resources the project company commits to invest in facilities during thecontract period. Investments can be either in new facilities or in the expansion and modernization of existing
facilities. Data entry varies across sectors: For projects other than telecommunications and large energy utilities,
the total cost of developing or expanding the facility during the contract period is entered as investment data
during the year of financial closure (for which data are typically available). For telecommunications projects andsome large energy utilities, annual investments on facility expansion and modernization are entered as
investment data in the year of investment when information is publicly available. Investments are recorded inmillions of US dollars in either the year of financial closure or the year of investment as indicated above.

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Figure 1: Private Investment in Infrastructure in Low andMiddle Income Countries
Number of projects

2012 billions USD*

200

450
400
350

150

300
250

100
200
150

50

100
50

0

New Investment

Additional Investment

Source: World Bank and PPIAF, PPI Project Database.

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Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

2012

2011

2010

2005

2000

1995

1990

0

Number of Projects* Adjusted by US CPIINSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Figure 2: Private Investment in Infrastructure in Low andMiddle Income Countries, by Sector
2012 US$ billions*

Number of projects

200

450
400
350

150

300
250

100
200
150

50

100
50

0

EnergyTelecom

Transport

Water and sewerage

Source: World Bank and PPIAF, PPI Project Database.

2012

2011

2010

2005

2000

1995

1990

0

Number of Projects* Adjusted by US CPIThere are a number of current and emerging challenges that are expected to undermine theattractiveness of long-term private investments such as furthering infrastructure. The weakness in anddeleveraging of commercial banks and the regulatory constraints such as Basel III is likely to persist
into the medium term, which implies a growing mismatch between the time horizon of available
capital and that of productive long-term investment projects (World Bank, 2013).
Even under more normal credit conditions, the costs and risks faced by private investors ininfrastructure are high, particularly in EMDEs, where economic and financial conditions tend to be
weaker and less stable. Another critical and overarching pre-condition to attract private investors is anenabling institutional framework, including peace and stability, the rule of law, good governance withaccountability and transparency, the absence of corruption, clear property rights, and enforceable
contracts.
From a public policy perspective, given the positive economic, social, and environmental externalities
that quality infrastructure can provide, efforts to lower the overall riskiness of infrastructure
investments and enhance the availability of efficient risk-sharing instruments can have important
implications in efficiency and distribution. At the same time, there is a need to ensure that efforts toencourage private sector participation in infrastructure offer optimal benefits but do not impose aninappropriate burden on the public sector.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Against this background, this paper aims to assess the determinants of private financing of
infrastructure with a special focus on institutional, political, and governance characteristics. The paper
then identifies areas in which additional efforts are required if the private sector were to play a largerrole in financing infrastructure development in EMDEs.

2. Theoretical Background to Understand the Determinants of PPI
Existing literature
There is considerable economic and financial literature attempting to explain the determinants ofinvestment and the relationship between investment and risk. Most of the theoretical literature points
to access to capital, investment efficiency, the social (as opposed to the financial) discount rate,
operational efficiency, bundling of investment and operations, risk allocation, and contract flexibility
as the main economic drivers of private investment in infrastructure (see Annex I for a literaturetaxonomy and mapping of these drivers).
The empirical literature is focused on foreign direct investment rather than infrastructure investments,and most of the works utilize cross-country specifications. For example, Chakrabarti (2001) concludes
that market size is a robust determinant of FDI, and Nunnenkamp (2002) identifies exchange rate,
openness, growth rate, and trade balance as determinants of overall investment levels.
The literature on infrastructure investments and risk is thinner. Araya et al. (2013) analyses therelationship between private participation in infrastructure and country risk. They show that adifference of one standard deviation in a country's sovereign risk score is associated with a 27%
increase in the probability of having private participation in infrastructure commitment and a 41%
higher level of investment in dollar terms with the energy sector (among infrastructure sectors) andconcessions (among contractual types). They also show that conflict-affected countries typicallyrequire six to seven years to attract significant levels or forms of private investments in infrastructurefrom the day that the conflict is officially resolved. Private investments in sectors in which assets are
more difficult to secure — such as water, power distribution, or roads — are slower to appear or
simply never materialize.
Hammami et al. (2006) use the World Bank PPI Database to analyze the determinants of PPI andconclude that lower levels of corruption and more effective rule of law are associated with more
Public-Private Partnership projects. This study captures the effect on the number of projects
committed, but not the investment levels per se, leaving room for further study, especially if we
consider that bigger projects (committing more resources) may be more sensitive to the risk of thecountry.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

The empirical evidence on determinants of PPIs uses a cross-country panel regression approach,looking at whether indicators of macroeconomic stability, measures of institutional and regulatory
quality, and a variety of other controls impact the total amount of PPI received by a country. For
example, Pragal (2003) and Kirpatrick et al. (2006) look at the importance of the regulatory
framework as a determinant of PPI respectively for Latin America and the Caribbean (LAC) and thebroader set of developing countries. Pragal (2003) finds that the most significant determinant of PPI is
the passage of legislation liberalizing the investment regime, while Kirpatrick et al. (2006) find that
institutional framework and regulation matter most. Similarly, Banerjee et al. (2006) look at thequestion of whether institutions matter for PPI. While their results indicate that property rights andbureaucratic quality play a significant role in promoting PPI, they find that countries with higher levelsof corruption attract more PPIs.
A study by Tewodaj (2013) analyse the determinants of private participation in infrastructurecomparing Sub-Saharan Africa (SSA) with low and middle income countries (LMICs). The study
finds that PPI investments in LMICs seem to be, in principle, determined by the expected factors (i.e.
larger, open, more developed democracies with lower tax burden and more stable macroeconomic
environment receive more PPI), PPI into SSA countries is — from a social planner’s perspective —sub-optimally allocated. In particular, when it comes to larger PPI investments the findings suggestthat corrupt countries with inefficient governments seem to attract more PPI in infrastructure. Basilio(2011) shows that market size and purchasing power are critical determinants of infrastructure flows.
The institutional quality matters mostly for the decision to invest in emerging countries, but it is lessimportant with regard to the intensity of the investment than financial and economic conditions.
Jensen et al. (2005) analyze the institutional determinants of private sector participation in the waterand sanitation sector in 60 developing countries. The regression results provide support for the
hypotheses that PPI is greater in larger markets where the ability to pay is higher and where
governments are fiscally constrained. The protection of property rights and the quality of thebureaucracy emerge as the most important institutions that encourage PPI. Gasmi et al. (2010) assess
the extent the level of development of financial sector is a determinant of private investment in the
power sector in 37 developing countries. The results suggest that investors tend to take countries’
governance quality into account in their decisions to invest. The empirical results highlight that thedevelopment of the financial sector also plays a significant role in private investors’ decisions to enter
infrastructure sectors.
The objective of this paper is to contribute to the literature by disentangling the relevant institutional,
political, and governance determinants of country risk at a granular level through providing atheoretical framework to derive the testable hypotheses, using a novel dataset on quality of governanceMarian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

and on number of PPI disputes,5 and extending previous analyses with a cross-country panel for 19842012 period.6

Methodology
To identify the determinants of PPI, we construct a toy model that captures institutional and politicalvariables along with economic and financial variables.
Let's assume a three-stage-investment, predictable cash flows, and terminal value model:
1. In t0, the public agent and/or private investor invest I with certainty (construction risks areabsorbed by the constructor; there may be a differential in investment efficiency though);
2. In t1,2,...,n, predictable cash flows CF are realized (in financial modeling, these are cash flows
broken down year by year, e.g., 5-8 years);
3. In tn+1,...,∞, the terminal value (TV) is realized with uncertainty (in a Discount Cash Flow —DCF —valuation, the TV accounts for ca. 40-70% of the present value of the asset, depending on the
discount rate)7;
4. The public agent, unlike the private investor, can receive transfers TR conditional on states of TV:
if TV is low, the public agent can levy taxes from the public at large and subsidize the project; if
TV is high, the public agent will lower prices (directly or through regulation) to gain politicalsupport;
5. TR have an expected value of zero, so that the public agent's TV + transfers (TR) have the same
expected value, but lower volatility than TV alone; i.e., E(TV+TR) = E(TV) and SD(TV+TR) <SD(TV).
The TV is relevant for the private investor inasmuch as she has a stake in the long-term operations of
the asset. For institutional arrangements (e.g. joint ventures), the private investor has an interest inpreserving the value of the assets. For finite-time contractual arrangements (e.g., concessions), thesalvage value of the asset for the private investor is not greater than its market value. Therefore, fromthe public agent’s standpoint, the volatility of the TV increases in private ownership and decreases incontract duration, in line with assumption (5).
5Previous literature has only used the number of calendar days to resolve a payment through courts from
Djankov et al. (2007), but not PPI disputes specifically.
6
The latest study is by Tewodaj (2013) and uses data up to 2008.
7

The following stylized numerical example illustrates this point: Let us assume a series of USD 100 perpetualcash flows (CF) discounted at a rate (r) of 10% annually. The first 10 years (n) account for 61% of the present
value, while the terminal value—i.e., the cash flows from year 11 onwards—for 39% of the present value. The
shorter the period accounted for the foreseeable cash flows, the lower the discount rate, and the higher theterminal value cash flows growth in perpetuity are, the higher the proportion the terminal value will have in thepresent value. For example, for n = 5 and r = 7%, the terminal value represents 71% of the present value.

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Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

From Assumptions (1)-(5), the Net Present Value for public investments equals:𝑛𝐶𝐹𝑝𝑢,𝑗𝑁𝑃𝑉𝑝𝑢 = −𝐼𝑝𝑢 + ∑

𝑗=1 (1 + 𝑟𝑝𝑢 )𝑗+𝑇𝑉 + 𝑇𝑅|𝑇𝑉(1)𝑛(1 + 𝑟𝑝𝑢 )and for private investments:𝑛

𝑁𝑃𝑉𝑝𝑟 = −𝐼𝑝𝑟 + ∑𝐶𝐹𝑝𝑟,𝑗𝑗=1 (1 + 𝑟𝑝𝑢 )𝑛= −𝐼𝑝𝑟 + ∑

𝑗

+

𝑇𝑉

𝑛 =

(1 + 𝑟𝑝𝑢 + 𝑟𝑝𝑟𝑒𝑚𝑖𝑢𝑚 )𝐶𝐹𝑝𝑟,𝑗𝑗=1 (1 + 𝑟𝑝𝑢 )

𝑗

+

(2)

𝑇𝑉
𝑛

(1 + 𝑟𝑝𝑟 )where rpu is the social discount rate and rpr is the private discount rate equal to the social discount rateplus a risk premium for higher variance (higher beta) of TV without TR. Under these assumptions thediscount rate during the predictable period n is the same for both the public and private sectors; therisk premium is only realized in the terminal value The risks during the predictable period areabsorbed in the expected value of the cash flows, not the discount rate. If the distribution of the cash
flows is unknown, then n should be shortened and the discount rate adjusted.
Arguably, if investments and cash flows are different under public and private provision, so are cash
flows after period n captured in the terminal value TV. For simplicity, we assume that TV are equal
under public and private provision (secular trend) and all rents from the private to the public sector are
extracted through transfers TR, in accordance with assumption (4).
At the margin (i.e. where the choice between traditional procurement and PPI is indifferent), NPVpu =NPVpr, therefore:𝑛−𝐼𝑝𝑢 + ∑𝐶𝐹𝑝𝑢,𝑗𝑗=1 (1 + 𝑟𝑝𝑢 )𝑛

𝐼𝑝𝑢 − 𝐼𝑝𝑟 + ∑𝑗+

𝑇𝑉 + 𝑇𝑅|𝑇𝑉𝑛(1 + 𝑟𝑝𝑢 )𝑛𝐶𝐹𝑝𝑟,𝑗𝑗=1 (1 + 𝑟𝑝𝑢 )

𝑗

−∑

𝑛

= −𝐼𝑝𝑟 + ∑𝐶𝐹𝑝𝑟,𝑗𝑗=1 (1 + 𝑟𝑝𝑢 )𝐶𝐹𝑝𝑢,𝑗𝑗=1 (1 + 𝑟𝑝𝑢 )𝑗=𝑇𝑉 + 𝑇𝑅|𝑇𝑉𝑛(1 + 𝑟𝑝𝑢 )

𝑗

−

+

𝑇𝑉
𝑛

(1 + 𝑟𝑝𝑟 )𝑇𝑉𝑛(1 + 𝑟𝑝𝑟 )

(3)

(4)

Since SD(NPVpu) < SD(NPVpr), in equilibrium rpu < rpr (conf. CAPM; otherwise no investor would
invest in a riskier project).
𝑗𝑛Normalizing by 𝐼𝑝𝑢 − ∑𝑛𝑗=1 𝐶𝐹𝑝𝑢,𝑗 ⁄(1 + 𝑟𝑝𝑢 ) = (𝑇𝑉 + 𝑇𝑅|𝑇𝑉)⁄(1 + 𝑟𝑝𝑢 ) :Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 201411

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

𝐼𝑝𝑟 − ∑𝑛𝑗=1

𝐶𝐹𝑝𝑟,𝑗𝑗𝑛𝑇𝑉 ∙ (1 + 𝑟𝑝𝑢 )(1 + 𝑟𝑝𝑢 )=𝑛𝐶𝐹𝑝𝑢,𝑗(𝑇𝑉 + 𝑇𝑅|𝑇𝑉) ∙ (1 + 𝑟𝑝𝑟 )𝐼𝑝𝑢 − ∑𝑛𝑗=1
𝑗(1 + 𝑟𝑝𝑢 )(5)

Given that TR is a mean-preserving spread [E(TR) = 0],
𝐼𝑝𝑟 − ∑𝑛𝑗=1
𝐼𝑝𝑢 − ∑𝑛𝑗=1

𝐶𝐹𝑝𝑟,𝑗𝑗

1 + 𝑟𝑝𝑢(1 + 𝑟𝑝𝑢 )=()
𝐶𝐹𝑝𝑢,𝑗1 + 𝑟𝑝𝑟(1 + 𝑟𝑝𝑢 )

𝑛

(6)

𝑗

i.e. the preference for private participation in infrastructure will be given by:
∑𝑛𝑗=1
∑𝑛𝑗=1

𝐶𝐹𝑝𝑟,𝑗(1 + 𝑟𝑝𝑢 )𝐶𝐹𝑝𝑢,𝑗(1 + 𝑟𝑝𝑢 )𝑗 − 𝐼𝑝𝑟𝑗 − 𝐼𝑝𝑢𝑛

1 + 𝑟𝑝𝑢+() >0
1 + 𝑟𝑝𝑟(7)

This toy model yields the following comparative statics:

Variable

Meaning

1 – Ipr/Ipu

Investment efficiency

CFpr/CFpunrpu/rprProductivity
differential
Industry stability(inverse of industry
risk)
Political stability(inverse of politicalrisk)

Preference for
PPI
Pr[NPVpr >NPVpu]++

Captured econometrically byCountry dummies and subsample sector
regressions; GDP per capita controls
Country dummies and subsample sector
regressions; GDP growth control+

Subsample sector regressions; regulatory
quality+

Political variables: rule of law, corruption
perception, regulatory quality, andnumber of disputes; corporate taxationand country exchange rate volatility
controls

Controlling for economic and industry factors, we derive a number of testable predictions:
Prediction 1: An increase in the rule of law — following North and Weingast (1999) — will be
associated with a lower differential in the public and private discount rates and thus higher PPI.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Prediction 2: An increase in regulatory quality will be associated with higher predictability of cash
flows and thus higher PPI.
Prediction 3: An increase in freedom from corruption will be associated with a lower political risk
premium and thus higher PPI.
Prediction 4: An increase in the number of disputes will be associated with a higher political risk
premium and thus lower PPI.

3. Data Description
Data is an unbalanced panel assembled from the World Bank’s Private Participation in Infrastructure
dataset, Quality of Government dataset, UNCTAD Database of Treaty-based Investor-State Dispute
Settlement Cases, and country-level economic variables from the World Development Indicators
Database.
In order to obtain PPI levels, we utilized the World Bank PPI Database. This source offers detailed
information by year, country, sector and form of public-private partnership. Within sectorialcategories, it distinguishes among primary and secondary sectors by investment.8 It also provides theform of private investments, so we can distinguish between Greenfield projects and concessions ofexisting assets among other types of partnerships and investments.
The database, however, captures both public contributions to the infrastructure investments as well asprivate contributions. That is, the database notes total project size in commitments, later adjusted toactual disbursements, investments, or transfers, where information is available. Those commitments
combine private and, in many cases, public sources. Only projects that have come to financial closure
are included in the database. If a purely public investment is carried out in tandem with a private
operator or a private management contractor, the database does not include them. All project figures
are noted in the year that the project comes to financial closure.
For the purpose of this paper, the PPI database is an appropriate source of information because itreports the commitments of the investments for each year by country and by sector once a contract hascome to financial closure; that is, a license, sale, concession, lease, BOT, or other contractual
agreement is signed by both parties and financial arrangement have been secured. Having thecommitments instead of the actual investments allows us to establish a clearer relationship between
investments and institutional, political, and governance variables at a given point in time. The decision
8

As examples, Energy and Transport are “primary sectors,” whereas Electricity Distribution and Airports are“secondary sectors.”

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

of investing (commitment) and the willingness of financiers to come to closure on that commitment
are made, inter alia, in the context of the political conditions, economic performance, sovereign credit
worthiness, and fear of expropriation at the time of financial closure. Because there may be exogenous
reasons for differentiation between an original commitment to invest and the eventual disbursementlevels — including external shocks, canny renegotiations, or changes in tariffs or relative prices — thebest time to value an investment relative to country risk is the moment at which the commitment
comes to financial closure.
Taking the data from the PPI database, we gather information regarding 130 developing countries
from 1990 to 2010. The panel data were complemented by data from World Development Indicatorswith variables such as GDP, GDP growth, inflation, country openness, and population.
The Quality of Governance Standard Database (Teorell et al., 2013) is a panel data that draws on anumber of freely available data sources related to quality of governance and its correlates. This is our
main source for the following variables: freedom from corruption, rule of law, quality of regulations,bureaucracy quality and political regimen, parliamentary democracy, mixed (semi-presidential)
democracy, presidential democracy, civilian dictatorship, military dictatorship, and royal dictatorship.
A detailed description of these variables is presented in Annex II.
Furthermore, we rely on the UNCTAD Database of Treaty-based Investor-State Dispute Settlement
Cases to construct the variables on a number of disputes and average time to solve them by sector andcountry. This database has 394 observations covering disputed cases pending and concluded, whichwere disclosed by the parties or arbitral institutions from 1987 to 2010.
Summary statistics and the correlation of independent variables are presented in Annex III,
Tables 1 and 2.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

4. Results
The model is specified in logarithms. We use a moving average of 15 years for water projects,
10 years for energy (plants and transmission) projects, 8 years for transport projects, and 5 years fortelecom projects - roughly 1/3 of the depreciation time estimated by the World Bank, i.e. arguably anapproximation of refurbishing time — to account for the fact that data is on discrete observations ofcommitments.
We explore the intensity of the different determinants given that a country has received private
investments in infrastructure. We run the following OLS regression with country-fixed effect and year
dummies to capture for changes over time that are common across countries (e.g. the financial crisis):log 𝑃𝑃𝐼𝑖𝑡 = 𝛼𝑖 + 𝛽1 log 𝐺𝐷𝑃𝑖𝑡−1 + 𝛽2 log 𝑃𝑂𝑃𝑖𝑡 + 𝛽3 log 𝐺𝑅𝑂𝑊𝑇𝐻𝑖𝑡−1+ 𝛽4 log 𝐼𝑁𝐹𝐿𝐴𝑇𝐼𝑂𝑁𝑖𝑡−1 + 𝛽5 log 𝑂𝑃𝐸𝑁𝑁𝐸𝑆𝑆𝑖𝑡−1+ 𝛽6 log 𝐷𝐸𝐵𝑇𝑖𝑡−1 + 𝛽7 log 𝐴𝐶𝐶𝐸𝑆𝑆𝑇𝑂𝐹𝐼𝑁𝐴𝑁𝐶𝐸𝑖𝑡−1(8)+ ∑ 𝛽𝑗 log 𝑋𝑖𝑡𝑗 + 𝜀𝑖𝑡
Equation (8) shows that log PPIit equals logarithms of the levels of the moving average of private
investment in infrastructure for country i at the period t. Most econometric specifications dealing with
GDP and Investments suffer from endogeneity. We address this problem by assuming that theinvestments are being affected by events of the previous year. GDPit–1 is the Gross Domestic Productpurchasing power parity in current US millions of dollars for the country i in the year t–1. GROWTHit–
1 is the GDP’s growth and both are expected to have a positive impact on investment levels. POPitcaptures the size of the population and INFLATIONit–1 captures the monetary instability for the country
i in the year t–1 and is expected to have a negative impact. OPENNESSit–1 is a proxy of the opennessof the country calculated as the sum of exports and imports over the GDP; ACCESSTOFINANCEit–1
captures the access to commercial bank credit for the country i in the year t–1 and is expected to havea positive impact; and Xitj are the political and institutional variables including for country i at time t:(a) freedom from corruption; (b) government effectiveness; (c) rule of law; (d) quality of regulations;and (e) number of court disputes.
The regression results are presented in Tables 3-7. All specifications control for the main
characteristics of the economies as commonly used in the previous literature:Size of the market: GDP and population. PPI tends to be more common in larger markets where
demand is larger.
Inflation: PPI is more prevalent in countries with more stable macroeconomic conditions. Higher
inflation is less attractive for investors as it imposes an inflation risk premium.
Openness (proxied by trade): more open countries are more likely to attract big foreign investors.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Debt: countries with higher levels of debt are more likely to require the private sector to invest in
infrastructure. However, they could be perceived as a higher risk of default by the private sector.
As a debt measure we use the total debt service divided by the gross national income.
Access to finance, i.e. access to commercial bank credit.

Table 3 presents the results using country-fixed effect and year dummies. In these specifications, theoverall R-squared is around 50%, a high value for a panel data model.9
The coefficients associated with large markets, stable inflation, access to finance, freedom from
corruption, rule of law, quality of regulations, and number of disputes, are statistically significant
indicating that they are relevant channels for the determination of investments in PPIs.
Interestingly, the political regimens such as parliamentary democracy, mixed (semi-presidential)
democracy, presidential democracy, civilian dictatorship, military dictatorship, and royal dictatorshipdo not affect significantly the level of PPI infrastructure investment.
Countries with large markets and high demand for infrastructure (larger population and higher laggedGDP) tend to have more PPI.
Governments with less inflation have a more stable environment fostering private sector investments
in infrastructure PPIs.
The higher a country score on freedom from corruption, the higher the average level of investmentswith private participation in infrastructure. Decreasing corruption by 10 points can increase PPI by
6.7%. That is, if a country like Serbia can lower its corruption level and become like South Africa(which has similar GDP per capita), the private sector will invest 7% more.10
The higher a country score on rule of law, the higher the average level of investments with private
participation in infrastructure. Improving rule of law by one standard deviation (i.e. by 0.1) can
increase PPI by 4.3%. That is, if a country like Bhutan can improve its environment of property rights
and enforceability of contracts and become like Jordan (which has a similar GDP per capita), theprivate sector will invest 4% more.11
Breach of contract and regulatory issues remain the most important political risk concerns forinvestors into developing economies, according to the annual MIGA-EIU Political Risk Survey. Forty9

Values over 10% are accepted in the common literature, due to the bi-dimensional nature (countries and time)of the panel data model.
10

In the year 2011, Serbia had a GDP per capita USD 9,687 and a freedom of corruption index of 35 while
South Africa had a GDP per capita of USD 9,830 and a freedom of corruption index of 45.
11

In the year 2011, Bhutan had a rule of law index of .12 and a GDP per capita of USD 5,162, while Jordan had
a rule of law index of .22 with a GDP per capita of USD 5,268.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

five per cent of investors in developing countries named breach of contract and 58% named adverse
regulatory changes as the most important political risks they will face in the next three years. Forty percent of the survey respondents mentioned that they experienced financial losses through adverse
regulatory changes and 34% through breach of contract over the past three years. Therefore, it is not
surprising to observe that both quality of regulations and number of previous disputes are statisticallysignificant.
The model also shows that an improvement of one standard deviation (0.1) in quality of regulation
produces an average increase of 3.2% in the level of infrastructure investment in PPIs. For example, if
we consider two countries with the same level of GDP per capita such as Mexico and Turkey, Mexico
can gain a 3% increase in infrastructure investment in PPIs if the country achieves the quality of
regulations of Turkey.12
On disputes, the estimation indicates that the higher the number of disputes, the lower the level ofinvestments. Having one more project going to court decreases investments by 4%13. We presumed
that the number of disputes could have a non-linear effect on private investments (e.g. no disputes
could also reflect an anticipation of risk and therefore lack of private investments); however, adding
disputes squared was found to be statistically not significant. Unfortunately, the variable on time tosolve a dispute was incomplete for half of the sample, impeding its proper use.
We estimate the determinants of PPI by sector to see whether the impacts vary among the energy,transport, telecom, and water sectors (see Table 4). Freedom from corruption is statistically significant
for all sectors except for transport. While corruption generally reduces the prospects for investment inall sectors, the lack of sensitivity of the transport sector could be explained by the fact that corruption
matters primarily regarding investors’ decision to enter the transport market, not the subsequent levelof investment, which may indicate that the investors are protected against such risks once they doinvest.
Transport is one of the most corrupt sectors of infrastructure. Kolstad and Wiig (2013) find that
“increased corruption within a country is associated with increased extractive industry FDI, but at adiminishing rate as corruption increases grow large.” Thus, while threats to ownership rights deter
investments into resource sectors (Bohn and Deacon 2000; Cust and Harding 2013), increased
corruption would not follow this ‘rule’ because available measures of (perceived) corruption do not
capture such a threat, because corruption has been a means of securing ownership rights, or because
countries perceived as getting more corrupt offered better opportunities for FDI beyond ownershiprights (such as geological prospects and reduced regulatory constraints). Although corruption may be
12

In the year 2011, Mexico and Turkey had a GDP per capita of USD 12,813 and USD 13,468, respectively,
while their quality of regulation indexes were .34 and .42, respectively
13

We used the number of disputes in the last 10 years before the commitment in order to capture the countries’
reputation in this matter.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

costly, it is a cost that also offers flexibility and has helped secure deals for companies to maximize
profits (Shaxson, 2007).
Rule of law is statistically significant for overall PPI, but it is not significant at the sector level. The
coefficients are of almost the same magnitude but not significant due to smaller sample size when werun regressions at the sector level.
Quality of regulation is statistically significant for all sectors except water. Regulatory quality includes
measures of the incidence of price controls and perceptions of the burdens imposed by excessive
regulation. Improving the quality of regulations in a country can attract more private investors to
infrastructure PPIs, but since water is a socially sensitive sector and very likely to be politically
influenced, investors may prefer price controls and strong regulation, as they limit ex ante the risk of
domestic politics around water.14
The coefficient on disputes is statistically significant for all sectors except for energy. PPI investments
in telecoms and water are particularly sensitive to the accumulated number of disputes in thatparticular sector. Having one more dispute can decrease PPI investments in those sector byapproximately 12%.
Variables in institutional and political regimens such as parliamentary democracy, mixed(semi-presidential) democracy, presidential democracy, civilian dictatorship, military dictatorship, androyal dictatorship were also included as controls, but none of them was statistically significant.
As a robustness check, we have run the regressions without year dummies (see Tables 5 and 6).
Insignificant changes in the main results were found.
We expected that countries with more experience on PPIs and higher income would have PPI
investments less sensitive to institutional and governance variables. However, we found that results
did not vary by quartile of experience, GDP and GDP per capita (see Table 7). According to field
experts, it is not the quantity, but the quality of experience (i.e. successful projects) that matters, forwhich we do not control.

14

For a robustness check, we have added the Gini coefficient as an explanatory variable, expecting that, whencontrolling for income inequality, the coefficient will become significant for water. However, it is still notsignificant.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

5. Conclusions
Fostering private-sector investment in infrastructure depends on investors facing an appropriate
investment climate. Currently private sector investment is a small portion of the total infrastructure
investment (less than 20%). The costs and risks faced by investors are high, particularly in emerging
market and developing economies (EMDEs) where the economic, institutional, and financial
conditions are weaker and less predictable. One of the main concerns of private sector investors
considering investment in infrastructure in EMDEs is the quality of the underlying investment climate.
A supportive enabling environment reduces the costs and risks of investing in infrastructure.
Investment climate is affected by many factors, including political instability, regime uncertainty, ruleof-law and property rights, government regulations, government transparency, and accountability. The
existence of a stable and predictable environment in which both domestic and foreign investors canoperate is vital for providing confidence to investors.
This paper provides empirical evidence of the relationship between institutional, political, andgovernance variables and the level of PPI investments in infrastructure in developing countries. Our
results support the arguments that industry and political stability are key ingredients to increase thelevel of PPI investments in infrastructure.
We conclude that PPI investment in infrastructure is highly sensitive to the quality of government
variables such as freedom from corruption, rule of law, quality of regulations, and the number ofdisputes in the sector; decreasing corruption by 10 points can increase PPI by 6.7%, improving rule oflaw by one standard deviation (i.e. by 0.1) can increase PPI by 4.3%, improving quality of regulation
by one standard deviation (0.1) produces an average increase of 3.2% in the level of infrastructure
investment in PPIs, and having one more project going to court decreases investments by 4%.
These results hold when data is disaggregated at the sectoral level. However, transport investments are
not found to be sensitive to improvements in “freedom from corruption,” water investments toimprovements in quality of regulations, and energy investments to the number of accumulated disputes
in the sector: more work needs to be done to understand the cause of these discrepancies.
Importantly, the evidence does not show any significant difference in the results across experience andeconomic level quartiles.
A sound investment climate is a critical factor affecting the supply of infrastructure investment
financing. The challenges from upstream “enabling” institutions, policies, and regulations and sector
economics down to pipeline development need to be addressed simultaneously. Tackling such acomplex and interconnected agenda requires analysis of synergies and adoption of a holistic approach
to infrastructure development.

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

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INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Annex I
Determinants of PPI — Literature Taxonomy and Mapping
Theoretical Framework
Economics/FinanceDiscount rate

Social discount rate (Arrow& Lind, 1970); interest rate
differential (Moszoro,
2014a)

Access to capital

Access to external financing(Esty, 2011)

Variables

Investment efficiency
Productivity
differential
Bundling

Lower investment outlays
and shorter investment
period (Moszoro, 2014a)
Lower operational costs(Moszoro, 2014b)
Incentive theory andeconomies of scope (Iossa& Martimort, 2013)

Risk allocation

Contracting flexibility& regulation

Corruption, politicalstability & rule of law
Bureaucracy

Political Economy

Empirical Studies

Lower government beta
and access to capital vs.
investment efficiency andproductivity differential(Grout, 2003)

Expropriation risk and
LPVR (Engel, Fischer &Galetovic, 2001)
Post-tender renegotiations(Iossa & Martimort, 2011)

Institutional
Analysis

Incomplete contract theory:
bundling of investment andoperations (Hart 2003; Hart,
Shleifer &Vishny 1997);
governance of hybrids andboundaries of bureaucracy(Williamson 1979, 1999)

Low third-party opportunism risk (Moszoro & Spiller,
2014)

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Regulatory and institutionalframework (Pragal 2003;
Kirpatrick et al. 2006; Basilio2011); property right and qualityof the burocracy (Jensen et al.
2005).; corruption and rule oflaw (Hammami et al., 2006);
bureaucratic quality (Barnejee etal. 2006; Gasmi et al., 2010;
Tewodaj, 2013)

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Annex II
Definition of Variables
Quality of Government is the mean value of the ICRG variables “Corruption,” “Law and Order,” and“Bureaucracy Quality,” scaled 0-1. Higher values indicate higher quality of government.
Freedom from Corruption relies on Transparency International’s Corruption Perceptions Index(CPI), which measures the level of corruption in 152 countries to determine the freedom from
corruption scores of countries that are also listed in the Index of Economic Freedom. The CPI is basedon a 10-point scale, in which a score of 10 indicates very little corruption, and a score of 0 indicates avery corrupt government. In scoring freedom from corruption, the authors convert each of these raw
CPI data to a 0-100 scale by multiplying the CPI scores by 10.
Government Effectiveness combines into a single grouping responses on the quality of public service
provision, the quality of the bureaucracy, the competence of civil servants, the independence of thecivil service from political pressures, and the credibility of the government’s commitment to policies.
The main focus of this index is on the “inputs” required for the government to be able to produce andimplement good policies and deliver public goods.
Rule of Law includes several indicators which measure the extent to which agents have confidence inand abide by the rules of society. These include perceptions of the incidence of crime, theeffectiveness and predictability of the judiciary, and the enforceability of contracts. Together, these
indicators measure the success of a society in developing an environment in which fair and predictable
rules form the basis for economic and social interactions and the extent to which property rights areprotected.
Regulatory Quality includes measures of the incidence of market-unfriendly policies such as pricecontrols or inadequate bank supervision as well as perceptions of the burdens imposed by excessive
regulation in areas such as foreign trade and business development.
Regimen Institutions: The classification contains the following regimes: parliamentary democracy,
mixed (semi-presidential) democracy, presidential democracy, civilian dictatorship, military
dictatorship, and royal dictatorship. This classification is elaborated by Cheibub, Gandhi, andVreeland (2010).

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Annex III
Table 1. Summary Statistics
Variableln GDP_1
ln Inflation_1
ln Trade_1
Debt_1
Growth_1
ln Population
Access to financeFree of corruption
Government
effectiveness
Rule of law
Regulatory quality
Gini coefficient
Disputes

Obs
7,388
6,588
6,938
4,242
7,140
8,178
2,291
2,987

Mean
22.76985
1.95406
4.141784
4.927175
2.0511215.33762
7.47474
40.07265

Std. Dev.
2.411881
1.402989
0.638758
6.766934
6.012271
2.106291
17.92406
23.22481

Min
15.99307-13.4379-1.175050-50.2904
8.982059
00Max30.33849
10.19474
6.13225
208.0971
92.58597
21.01901
150
100

2,437
2,492
2,438
2,710
4,780

-0.05928-0.06741-0.06711
41.53993
0.687657

0.997779
0.993558
0.991987
9.80825
3.303972-2.45416-2.67015-2.67544
20.96
02.407654
2.001923
2.247345
74.33
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1.00
0.02 1.00
ln Trade_1
0.30 0.02 1.00
Debt_10.01 0.05 0.19 1.00
Growth_1
0.06 0.02 0.17 0.02
ln Population
0.80 0.07 0.48 0.06
Access to finance 0.28 0.04 0.06 0.21
Free of corruption 0.23 0.12 0.12 0.13
Government
effectiveness0.42 0.14 0.06 0.08
Rule of law
0.22 0.14 0.11 0.07
Regulatory quality 0.31 0.21 0.06 0.08
Gini coefficient
0.04 0.10 0.09 0.01
Disputes
0.43 0.02 0.21 0.05

Disputes

Rule of law
Regulation
qualityGini
coefficient

Growth_1
ln
Population
Access tofinanceofFree
Governmen
corruptionteffectivenessDebt_1ln Trade_1

ln GDP_1
ln
Inflation_1

Table 2. Correlation of Independent Variables

ln GDP_1
ln Inflation_1

26

1.00
0.03 1.00
0.06 0.10 1.00
0.06 0.09 0.18 1.00
0.02 0.10
0.01 0.04
0.01 0.01
0.20 0.12

0.26 0.72 1.00
0.20 0.72 0.85 1.00
0.28 0.66 0.81 0.74 1.00
0.02 0.25 0.22 0.11 0.25 1.00

0.05 0.32 0.09 0.06 0.20 0.06 0.09 0.11 1.00

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Main Results
Table 3. Determinants of Private Participation in Infrastructure. Dependent Variable: Log of Total Private Investments
in Infrastructure. Specification with Country Fixed Effects and Year Dummies
VARIABLES
ln GDP_1
ln Inflation_1
ln Trade_1
Debt_1
Growth_1
ln Population
Freedom from
corruption
Government
effectiveness
Rule of law
Quality of regulation
Access to finance(1)
ln_PPI
0.699***(0.145)-0.0561*(0.0305)
0.0736(0.183)-0.00509(0.00553)-0.0161**(0.00643)
2.304***(0.610)0.00718*(2)
ln_PPI
0.605***(0.152)-0.0242(0.0309)-0.147(0.186)-0.000334(0.00561)-0.00844(0.00669)
1.434**(0.639)0.0166***(3)
ln_PPI
0.694***(0.144)-0.0504*(0.0302)0.141(0.182)-0.00444(0.00548)-0.0130**(0.00641)
2.062***(0.607)0.00669*(4)
ln_PPI
0.104(0.180)-0.0643*(0.0331)-0.115(0.209)-6.26e-05(0.00608)
0.00111(0.00745)
0.716(0.692)0.0110**(5)ln_PPI
0.103(0.208)-0.0732**(0.0368)-0.150(0.230)-0.00268(0.00619)-0.00243(0.00840)
0.116(0.792)0.0161***(6)
ln_PPI
0.579***(0.150)-0.0173(0.0305)-0.0775(0.184)-2.83e-05(0.00554)-0.00409(0.00668)
1.189*(0.633)0.0155***(0.00406)
0.0587(0.00420)-0.107(0.00402)
0.120(0.00459)-0.109(0.00497)
0.0178(0.00416)-0.0461(0.178)0.404**(0.180)0.431***(0.152)0.00455**(0.00196)(0.180)0.279(0.179)0.638***(0.150)0.00539***(0.00195)(0.177)0.431**(0.178)0.317**(0.153)0.00355*(0.00195)(0.201)
0.463**(0.201)0.660***(0.173)0.00205(0.00220)(0.215)0.436**(0.219)0.598***(0.185)0.00251(0.00244)(0.179)0.325*(0.177)0.515***(0.150)0.00405**(0.00195)

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 201427

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 3. (continued) Determinants of Private Participation in Infrastructure. Dependent Variable: Log of Total Private
Investments in Infrastructure. Specification with Country Fixed Effects and Year Dummies
VARIABLES
Gini coefficient(1)
ln_PPI(2)
ln_PPI
0.00318(0.00967)

Disputes (moving
sum)

(3)
ln_PPI(4)ln_PPI-0.0385***(0.00908)

Observations
R-squared
Number of countries

28(6)
ln_PPI-0.000675(0.00959)-0.0380***(0.0105)
0.0237(0.0227)-0.475(14.47)(0.00844)

651
0.540
95

867
0.559
98

-50.19***(10.74)-33.81***(11.57)-46.44***(10.67)(0.0104)
0.0335(0.0223)-10.15(12.26)

1,041
0.487
111

867
0.547
98

1.041
0.497
111

771
0.528
108

Dispute time
Constant-0.0378***(5)ln_PPI
0.00757(0.0116)-0.0350***

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014-29.32**(11.46)

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 4. Determinants of Private Participation in Infrastructure by Sector. Dependent Variable: Log of Total Private
Investments in Infrastructure by Sector. Specification with Country Fixed Effects and Year Dummies

VARIABLES
ln GDP_1
ln Inflation_1
ln Trade_1
Debt_1

Growth_1
ln Population
Freedom from corruption
Government
effectiveness
Rule of law
Quality of regulation(7)
ln_PPI_
energy0.510**(0.213)-0.0349(0.0453)-0.0952(0.268)0.00177(0.00685)(8)ln_PPI_
energy0.415*(0.229)0.00567(0.0478)-0.286(0.285)0.00279(0.00749)(9)ln_PPI_
energy0.506**(0.213)-0.0347(0.0453)-0.0910(0.268)0.00181(0.00686)(10)ln_PPI_
energy0.406*(0.229)0.00601(0.0478)-0.281(0.285)0.00282(0.00749)-0.00822(0.0101)-3.052***(1.073)0.00782(0.00608)(11)
ln_PPI_
transport
0.518**(0.257)-0.0840*(0.0499)
1.337***(0.296)0.00420(0.0115)
0.0586***(0.0113)0.152(1.229)0.00217(0.00777)(12)
ln_PPI_
transport
0.399(0.258)-0.0377(0.0499)
1.323***(0.300)0.0213(0.0146)
0.0431***(0.0116)-0.818(1.217)0.00617(0.00801)(13)
ln_PPI_
transport
0.567**(0.256)-0.0754(0.0497)
1.374***(0.295)0.00510(0.0115)
0.0540***(0.0114)0.152(1.221)0.00259(0.00772)(14)
ln_PPI_
transport
0.455*(0.258)-0.0299(0.0497)
1.367***(0.299)0.0217(0.0145)0.0389***(0.0116)-0.785(1.211)0.00688(0.00797)-0.0162*(0.00955)-2.214**(0.988)0.0121**(0.00567)-0.00894(0.0100)-3.010***(1.070)0.00811(0.00605)-0.0158(0.00963)-2.237**(0.992)0.0120**(0.00569)-0.218(0.243)-0.115(0.252)
0.466**(0.214)-0.297(0.260)0.160(0.268)0.460**(0.224)-0.217(0.243)-0.112(0.253)0.455**(0.218)-0.298(0.260)0.172(0.269)0.438*(0.228)-0.500*(0.291)0.359(0.297)1.081***(0.236)0.00549**(0.00243)

0.00426*(0.00250)

0.0108***(0.00264)-0.771***(0.294)0.176(0.302)1.500***(0.238)0.00972***(0.00257)-0.484*(0.290)0.501*(0.301)0.995***(0.237)0.00984***(0.00265)-0.753**(0.293)0.326(0.307)1.415***(0.239)0.00886***(0.00259)

0.00553**(0.00243)

0.00435*(0.00250)

Access to financeMarian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

29

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 4. (continued) Determinants of Private Participation in Infrastructure by Sector. Dependent Variable: Log of Total
Private Investments in Infrastructure by Sector. Specification with Country Fixed Effects and Year Dummies

VARIABLES
Gini coefficient(7)
ln_PPI_
energy(8)ln_PPI_
energy0.0369**(0.0144)

Number of disputes
energy sector(9)ln_PPI_
energy(10)ln_PPI_
energy0.0361**(0.0145)-0.00626(0.0208)-0.0119(0.0210)(11)
ln_PPI_
transport(12)
ln_PPI_
transport
0.0215(0.0150)

Number of disputes
transport sector
Constant

Observations
R-squared
Number of countries
ln GDP_1
ln Inflation_1
ln Trade_1
Debt_1
Growth_1
ln Population
30(13)
ln_PPI_
transport(14)
ln_PPI_
transport
0.0166(0.0150)-0.0589**(0.0250)-1.420(22.53)
512
0.335
67
0.701***(0.259)0.0153(0.0522)1.328***(0.339)0.0255*(0.0150)-0.0141(0.0116)-2.938**(1.293)27.64(17.71)42.96**(19.74)28.09(17.79)43.92**(19.82)-17.41(22.43)0.429(22.64)-0.0676**(0.0262)-18.76(22.31)

754
0.249
87
0.579***(0.152)-0.0323(0.0316)0.161(0.193)0.00187(0.00577)
0.00335(0.00669)
2.572***(0.653)

660
0.280
75
0.528***(0.173)-0.0283(0.0349)-0.0617(0.216)0.00583(0.00625)
0.00173(0.00759)
1.904**(0.741)

754
0.249
87
0.590***(0.151)-0.0305(0.0315)0.163(0.192)0.00278(0.00577)
0.00436(0.00669)
2.649***(0.653)

660
0.281
75
0.529***(0.172)-0.0249(0.0349)-0.0560(0.215)0.00618(0.00624)
0.00334(0.00761)
1.912***(0.740)

577
0.275
76
0.671***(0.250)-0.00966(0.0510)1.441***(0.324)0.0118(0.0101)-0.0251**(0.0110)-2.784**(1.250)

512
0.327
67
0.657**(0.263)0.00134(0.0528)
1.134***(0.337)0.0255*(0.0152)-0.0211*(0.0115)-2.941**(1.313)

577
0.285
76
0.731***(0.247)0.00749(0.0506)
1.627***(0.324)0.0120(0.00999)-0.0189*(0.0110)-2.920**(1.232)

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 4. (continued) Determinants of Private Participation in Infrastructure by Sector. Dependent Variable: Log of Total
Private Investments in Infrastructure by Sector. Specification with Country Fixed Effects and Year Dummies

VARIABLES
Freedom from
corruption
Government
effectiveness
Rule of Law
Quality of regulation
Access to finance(7)
ln_PPI_
energy(8)ln_PPI_
energy(9)ln_PPI_
energy(10)ln_PPI_
energy(11)ln_PPI_
transport(12)
ln_PPI_
transport(13)
ln_PPI_
transport(14)
ln_PPI_
transport

0.0129***(0.00450)

0.0231***(0.00497)

0.0129***(0.00449)

0.0229***(0.00496)

0.0165**(0.00745)

0.0161**(0.00815)

0.0164**(0.00734)

0.0154*(0.00803)-0.294(0.189)0.350*(0.192)
0.548***(0.159)0.00155(0.00203)-0.321(0.205)0.276(0.207)0.570***(0.170)0.00237(0.00219)-0.0122(0.0112)-0.258(0.189)0.298(0.193)0.566***(0.159)0.00115(0.00203)-0.277(0.206)0.234(0.208)0.579***(0.170)0.00194(0.00220)-0.0124(0.0112)0.239(0.338)0.296(0.298)-0.183(0.231)0.000438(0.00271)

0.414(0.359)0.339(0.306)-0.208(0.248)-0.000832(0.00285)
0.0178(0.0171)0.324(0.334)0.357(0.294)-0.285(0.230)-4.93e-05(0.00268)

0.483(0.355)0.395(0.302)-0.298(0.246)-0.00135(0.00281)
0.0205(0.0169)-0.142**(0.0614)-0.141**(0.0689)-0.122***(0.0399)26.43(23.94)
334
0.470
40

-0.120***(0.0406)
27.98(25.25)
308
0.490
36

Gini coefficient
Number of disputes
Number of disputes
telecom sector
Number of disputes
water sector
Constant
Observations
R-squared
Number of countries-53.31***(11.49)
977
0.493
106

-40.45***(13.35)
821
0.492
91

-54.85***(11.48)
977
0.496
106

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014-40.63***(13.32)
821
0.495
91

26.47
(24.30)
334
0.452
40

30.14
(25.63)
308
0.473
36

31

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 5. Determinants of Private Participation in Infrastructure. Dependent Variable: Log of Total Private Investments in Infrastructure.
Specification with Country Fixed Effects (No Year Dummies)
VARIABLES
ln GDP_1
ln Inflation_1
ln Trade_1
Debt_1
Growth_1
ln Population
Freedom from
corruption
Government
effectiveness
Rule of law
Quality of regulation
Access to finance32(1)
ln_PPI
0.830***(0.0795)-0.138***(0.0284)0.298*(0.170)0.000734(0.00562)-0.0128**(0.00631)
4.337***(0.497)(2)
ln_PPI
0.843***(0.0798)-0.137***(0.0288)
0.201(0.178)0.00780(0.00581)-0.00323(0.00652)
4.466***(0.524)(3)
ln_PPI
0.863***(0.0801)-0.140***(0.0283)
0.366**(0.171)0.00130(0.00560)-0.0113*(0.00631)
4.401***(0.496)(4)ln_PPI
0.801***(0.0942)-0.148***(0.0313)0.296(0.204)0.00493(0.00635)-0.00323(0.00750)
4.245***(0.590)(5)ln_PPI
0.856***(0.101)-0.171***(0.0338)
0.311(0.228)0.00396(0.00643)-0.00163(0.00824)
3.999***(0.674)(6)
ln_PPI
0.874***(0.0803)-0.141***(0.0287)
0.273(0.179)0.00805(0.00579)-0.00153(0.00653)
4.569***(0.523)0.00720*(0.00417)

0.0159***(0.00442)

0.00692*(0.00416)

0.0111**(0.00484)

0.0169***(0.00527)

0.0153***(0.00441)

0.197(0.182)0.387**(0.183)0.227(0.153)0.00126(0.00154)

0.124(0.188)0.267(0.187)0.419***(0.155)0.00211(0.00162)

0.241(0.182)0.395**(0.182)0.140(0.155)0.000943(0.00153)-0.109(0.210)0.408*(0.209)0.465***(0.178)0.00246(0.00185)

0.120(0.226)
0.466**(0.227)0.388**(0.192)0.00239(0.00207)

0.171(0.188)0.285(0.186)
0.332**(0.158)0.00174(0.00162)

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 5. (continued) Determinants of Private Participation in Infrastructure. Dependent Variable: Log of Total Private Investments in Infrastructure.
Specification with Country Fixed Effects (No Year Dummies)
VARIABLES
Gini coefficient(1)
ln_PPI(2)
ln_PPI
0.00454(0.0100)

Number of disputes(3)
ln_PPI(4)ln_PPI-0.0256***(0.00917)-86.38***(6.838)-89.73***(7.458)-88.43***(6.853)-0.0234**(0.0109)
0.0755***(0.0226)-83.75***(8.221)

1.041
0.446
111

867
0.483
98

1.041
0.451
111

771
0.458
108

Dispute time
Constant

Observations
R-squared
Number of countries

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014(5)ln_PPI
0.00257(0.0120)-0.0214**(0.0109)
0.0653***(0.0230)-81.97***(9.777)(6)
ln_PPI
0.00139(0.0101)-0.0237***(0.00872)

651
0.468
95

867
0.488
98

-92.26***(7.484)33

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 6. Determinants of Private Participation in Infrastructure by Sector. Dependent Variable: Log of Total Private
Investments in Infrastructure by Sector. Specification with Country Fixed Effects (No Year Dummies)

VARIABLES
ln GDP_1
ln Inflation_1
ln Trade_1
Debt_1
Growth_1
ln Population
Freedom from
corruption
Government
effectiveness
Rule of law
Quality of regulation
Access to finance34(7)
ln_PPI_
energy0.625***(0.111)-0.130***(0.0421)0.344(0.244)0.00716(0.00703)-0.0116(0.00903)
1.395*(0.771)(8)
ln_PPI_
energy0.688***(0.115)-0.116**(0.0448)0.232(0.262)0.00859(0.00767)-0.00905(0.00937)
1.414*(0.833)(9)ln_PPI_
energy0.624***(0.112)-0.130***(0.0422)0.341(0.246)0.00715(0.00704)-0.0116(0.00907)
1.392*(0.773)(10)ln_PPI_
energy0.685***(0.115)-0.115**(0.0449)0.226(0.264)0.00859(0.00767)-0.00920(0.00940)
1.403*(0.836)(11)
ln_PPI_
transport
0.515***(0.133)-0.115**(0.0452)
1.500***(0.272)0.0128(0.0114)-0.0491***(0.0101)
0.843(0.918)(12)ln_PPI_
transport
0.556***(0.130)-0.0886**(0.0449)
1.489***(0.274)0.0353**(0.0143)-0.0393***(0.00999)
0.816(0.890)(13)
ln_PPI_
transport
0.532***(0.133)-0.117***(0.0450)
1.516***(0.271)0.0137(0.0114)-0.0467***(0.0101)
0.974(0.917)(14)
ln_PPI_
transport
0.569***(0.130)-0.0907**(0.0448)1.505***(0.273)0.0360**(0.0142)-0.0375***(0.0100)
0.923(0.889)0.00996*(0.00587)

0.00747(0.00629)

0.00998*(0.00588)

0.00756(0.00631)

0.00173(0.00779)

0.00551(0.00800)

0.00222(0.00776)

0.00601(0.00798)

0.00755(0.248)-0.0307(0.260)0.125(0.215)0.000128(0.00189)-0.0750(0.267)0.164(0.277)
0.0560(0.226)0.00139(0.00201)

0.00752(0.248)-0.0314(0.260)0.128(0.219)0.000128(0.00189)-0.0744(0.267)0.161(0.277)0.0649(0.231)0.00139(0.00201)-0.296(0.290)0.310(0.296)0.888***(0.232)0.00368*(0.00191)-0.505*(0.291)
0.0489(0.297)1.296***(0.233)0.00496**(0.00194)-0.263(0.289)0.415(0.298)0.808***(0.234)0.00327*(0.00191)-0.472(0.291)0.150(0.302)1.226***(0.236)0.00456**(0.00195)

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 6. (continued) Determinants of Private Participation in Infrastructure by Sector. Dependent Variable: Log of Total Private
Investments in Infrastructure by Sector. Specification with Country Fixed Effects (No Year Dummies)

VARIABLES
Gini coefficient(7)
ln_PPI_
energy(8)ln_PPI_
energy0.0520***(0.0146)

Number of disputes
energy sector(9)ln_PPI_
energy(10)ln_PPI_
energy0.0524***(0.0147)0.00178(0.0212)0.00431(0.0214)(11)
ln_PPI_
transport(12)
ln_PPI_
transport
0.0297**(0.0148)

Number of disputes
transport sector
Constant
Observations
R-squared
Number of countries
ln GDP_1
ln Inflation_1
ln Trade_1
Debt_1
Growth_1
ln Population-35.66***(10.97)
754
0.170
87
0.860***(0.0809)-0.0993***(0.0293)0.404**(0.176)0.00559(0.00579)-0.000759(0.00645)
4.505***(0.538)-39.25***(12.10)
660
0.196
75
0.872***(0.0874)-0.114***(0.0319)
0.295(0.200)0.0114*(0.00629)-8.70e-05(0.00717)
4.383***(0.607)-35.57***(11.03)
754
0.170
87
0.870***(0.0811)-0.101***(0.0293)0.414**(0.176)0.00631(0.00581)-3.02e-05(0.00647)
4.629***(0.545)-38.98***(12.18)
660
0.196
75
0.878***(0.0878)-0.115***(0.0320)
0.304(0.200)0.0116*(0.00629)
0.000437(0.00721)
4.449***(0.614)

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

-29.01**(13.19)
577
0.230
76
0.474***(0.122)-0.125**(0.0500)
1.690***(0.284)0.0180*(0.0105)-0.0332***(0.0102)
0.187(0.932)-31.27**(12.99)
512
0.285
67
0.519***(0.128)-0.117**(0.0519)
1.395***(0.307)0.0407***(0.0156)-0.0289***(0.0106)
0.761(0.999)(13)
ln_PPI_
transport(14)
ln_PPI_
transport
0.0265*(0.0149)-0.0579**(0.0262)-31.63**(13.19)
577
0.238
76
0.485***(0.123)-0.126**(0.0500)
1.734***(0.295)0.0182*(0.0106)-0.0326***(0.0103)
0.278(0.946)-0.0452*(0.0248)-33.28**(13.01)
512
0.291
67
0.529***(0.129)-0.118**(0.0520)
1.445***(0.318)0.0412***(0.0156)-0.0282***(0.0106)
0.896(1.024)35

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 6. (continued) Determinants of Private Participation in Infrastructure by Sector. Dependent Variable: Log of Total
Private Investments in Infrastructure by Sector. Specification with Country Fixed Effects (No Year Dummies)

VARIABLES
Freedom corruption
Government
effectiveness
Rule of law
Quality of regulation
Access to finance(7)
ln_PPI_
energy0.0132***(0.00457)(8)
ln_PPI_
energy0.0235***(0.00507)(9)ln_PPI_
energy0.0132***(0.00457)(10)ln_PPI_
energy0.0234***(0.00507)(11)
ln_PPI_
transport
0.0174**(0.00777)(12)
ln_PPI_
transport
0.0149*(0.00850)(13)ln_PPI_
transport
0.0175**(0.00778)(14)
ln_PPI_
transport
0.0147*(0.00852)-0.174(0.190)0.278(0.194)0.423***(0.158)0.00175(0.00158)-0.117(0.207)0.206(0.210)0.401**(0.171)0.00174(0.00177)-0.0145(0.0113)-0.146(0.190)0.247(0.195)0.426***(0.158)0.00145(0.00159)-0.0966(0.209)0.191(0.211)0.399**(0.171)0.00161(0.00178)-0.0146(0.0113)0.669*(0.346)
0.603*(0.308)-0.545**(0.233)-0.00415**(0.00189)

0.760**(0.369)0.641**(0.318)-0.569**(0.250)-0.00539***(0.00204)
0.0315*(0.0177)

0.702**(0.351)0.622**(0.310)-0.577**(0.240)-0.00422**(0.00190)

0.792**(0.373)0.659**(0.320)-0.602**(0.256)-0.00544***(0.00204)
0.0321*(0.0178)-0.0869(0.0614)-0.0498(0.0692)-0.0260(0.0417)-33.24**(16.27)
308
0.368
36

Gini coefficient
Number of disputes
telecom sector
Number of disputes
water sector
Constant

Observations
R-squared
Number of countries36-91.61***(7.488)-89.87***(8.700)-93.89***(7.656)-91.12***(8.873)-19.26(14.14)-30.47*(15.64)-0.0238(0.0404)-21.22(14.54)

977
0.465
106

821
0.454
91

977
0.466
106

821
0.455
91

334
0.352
40

308
0.367
36

334
0.353
40

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 7. Determinants of Private Participation in Infrastructure by Quartile of Experience and GDP. Dependent Variable: Log of Total Private
Investments in Infrastructure by Quartile of Experience and GDP. Specification with Country Fixed Effects and Year Dummies

VARIABLES
ln GDP_1
ln Inflation_1
ln Trade_1
Debt_1

Growth_1
ln Population

Freedom from
corruption
Government
effectiveness
Rule of law(1)
ln_PPIEXPERIENCE(2)(3)
ln_PPI
ln_PPI(4)ln_PPI(1)
ln_PPI(2)
ln_PPIGDP(3)
ln_PPI(4)ln_PPI(1)
ln_PPI

GDP per capita(2)(3)
ln_PPI
ln_PPI-2.818***(0.802)-0.0446(0.0996)-4.217***(1.006)
0.0969**(0.0452)-0.260(0.422)0.0228(0.0480)-1.226***(0.385)0.0119(0.0221)0.870***(0.241)0.0200(0.0523)
0.668**(0.315)0.00572(0.0138)0.395(0.464)0.0107(0.0809)0.148(0.377)0.00175(0.00752)

1.458***(0.286)0.0394(0.0461)-0.989***(0.306)0.0242(0.0176)

0.592**(0.259)0.00834(0.0539)-0.275(0.330)0.0201(0.0189)-0.0420**(0.0208)
0.792(6.280)-0.0361-0.0108(0.0108)
0.254(1.220)0.0168**0.0274(0.0186)
6.589**(2.976)0.00433-0.00949(0.00995)
6.065***(1.269)0.00494-0.0217**(0.00982)-0.103(1.035)0.00869

0.855***(0.312)-0.148***(0.0543)1.743***(0.481)-0.0202*(0.0114)0.0653***(0.0128)-3.833**(1.506)-0.00896(4)
ln_PPI

0.662***(0.141)-0.00677(0.0294)
0.318*(0.175)0.000204(0.00719)-1.111(0.839)-0.0748(0.144)-1.613(0.994)0.00247(0.00857)

0.218(0.399)-0.0610(0.0701)-1.135**(0.457)0.0398(0.0286)-0.0210*(0.0123)-0.822(2.706)0.007681.360***(0.382)-0.118*(0.0672)
0.338(0.506)-0.00242(0.00633)
0.0354***(0.0121)3.914*(2.350)-0.00848-0.00495(0.00634)-0.397(0.801)-0.00907*-0.0140(0.0250)6.224**(2.948)0.0459*-0.00375(0.0136)
1.256(1.548)0.0171

1.361***(0.253)-0.121***(0.0457)
0.449(0.310)-0.0296**(0.0124)0.0443***(0.0126)
7.124***(1.177)0.0120*(0.0221)-0.315(0.00901)-0.300(0.0104)
0.522(0.00544)
0.0248(0.0230)0.676(0.0104)-0.0960(0.00673)
1.527***(0.00703)-0.440(0.00987)-0.0386(0.00730)
0.405(0.00650)
0.179(0.00780)
0.509(0.688)-0.102(0.724)-0.137(0.438)-0.101(0.394)0.216(0.476)0.679(0.467)-0.0276(0.191)0.110(0.182)0.648***(0.735)1.090(0.771)-1.302(0.468)0.288(0.474)0.384(0.340)1.144***(0.333)-0.688***(0.282)-0.175(0.270)0.731***(0.489)0.193(0.412)-0.192(0.279)0.110(0.307)0.729***(0.275)0.287(0.292)0.320(0.384)0.812**(0.388)-0.137

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 201437

INSTITUTIONAL AND POLITICAL DETERMINANTS OF PRIVATE PARTICIPATION IN INFRASTRUCTURE

Table 7. (continued) Determinants of Private Participation in Infrastructure by Quartile of Experience and GDP. Dependent Variable: Log of Total
Private Investments in Infrastructure by Quartile of Experience and GDP. Specification with Country Fixed Effects and Year Dummies

VARIABLES
Quality of
regulation
Access tofinance
Constant

Observations
R-squared
Number ofcountries38(1)
ln_PPIEXPERIENCE(2)(3)
ln_PPI
ln_PPI(4)ln_PPI(1)
ln_PPI(2)
ln_PPIGDP(3)
ln_PPI(4)ln_PPI(1)
ln_PPI

GDP per capita(2)(3)
ln_PPI
ln_PPI(4)ln_PPI(0.541)0.00586(0.394)-0.000321(0.351)0.000102(0.151)0.00173(0.894)0.0255(0.459)0.00472(0.236)-0.00287(0.222)0.00637**(0.390)0.0215**(0.278)0.00503(0.236)0.00303(0.271)0.00501(0.00601)
69.54(98.53)(0.00608)
25.25(40.77)(0.00435)-89.58**(39.31)(0.00157)-4.662(14.84)(0.0178)-55.09(43.07)(0.00629)-17.75(26.06)(0.00328)-141.5***(19.90)(0.00255)-24.02(23.85)(0.00925)-114.8**(46.29)(0.00309)-125.5***(23.02)(0.00348)-7.397(18.15)(0.00327)
40.06(28.19)

120
0.661

206
0.461

320
0.227

392
0.499

90
0.580

234
0.494

341
0.610

365
0.494

184
0.635

267
0.750

245
0.579

334
0.410

55

79

82

63

19

35

43

38

26

38

39

43

Marian Moszoro et al. — Discussion Paper 2014-15 — © OECD/ITF 2014

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