2. Addressing the fragmented ESG data landscape of the infrastructure sector

Mamiko Yokoi-Arai

Infrastructure contributes to 79% of GHG emissions globally (UNOPS, 2021[1]). The bulk of the USD 100 billion needed for climate financing is expected to go towards infrastructure projects, and nearly half of this will come from the private sector (Climate Policy Initiative, 2021[2]). In addition, COVID-19 has made the need to support developing countries even stronger, as evidenced by G20 member initiatives such as the United States’ Build Back Better World (B3W) Partnership and the EU’s Global Gateway.

The COP26 demonstrated that financial intermediaries are committed to investing to achieve the Paris Agreement, as can be witnessed by the Glasgow Financial Alliance for Net Zero, which gathered financial institutions with a total of USD 130 trillion assets under management to achieve net zero. While there are uncertainties as to how this will lead to actual investments, larger financial institutions understand that they are expected to have a large role in achieving the Paris Agreement, which includes contributions to climate financing.

In order to unlock the potential private investment into infrastructure, governments need to provide frameworks in which various risks can be addressed, and develop an enabling environment that includes the various aspects promulgated by the G20 Principles for Quality Infrastructure Investment (QII). There has been a shift in the discussion related to sustainable infrastructure in recent years, with the increased need for environmental, social and governance (ESG) considerations to be applied to infrastructure projects. There is a need to establish certainty with mechanisms to ensure that public and private infrastructure financing contribute to the Paris Agreement and sustainable development goals (SDGs) in a way that responds to ESG considerations.

Infrastructure assets are exposed to long-term and complex risks that challenge investors in assessing and managing risks over time. While some institutional investors with a long-term horizon may consider such assets attractive for asset-liability management purposes, this has not translated to actual investment in practice, creating a wide investment gap for infrastructure assets. There is thus a need to create an environment in which investors have access to relevant information and data in order to make better investment decisions related to infrastructure assets.

There have been numerous sustainable finance and sustainable infrastructure initiatives to date, which has added to the confusion about which standard should be applied and how. This has affected ESG standards and ESG data for infrastructure assets, with limited data that is ESG assessed to date. Standards related to sustainable infrastructure kick started from the 2018 Principles for QII, and while G20 and other stakeholders have made efforts to advance the sustainable infrastructure agenda over the years, the complexity and long-term nature of infrastructure projects have made it difficult for data to be collected and ESG analysis to be developed.

The lack of data has been raised as an issue at various international discussions. In particular, it was reflected in Policy Message VII of the Outcome Document of 2021 G20 Infrastructure Investors Dialogue Financing Sustainable Infrastructure for the Recovery (October 2021) as a way to “[p]romote further consistency in data collection through improved methodologies and common terminologies, in particular in the ESG and new technologies area…” which proposes action to address this data gap.

This report brings together the various approaches taken towards sustainable finance and sustainable infrastructure by various initiatives in order to find areas of convergence and to identify what standards would bring the greatest common denominator for sustainable infrastructure.

The objective of this report is to identify how ESG data can be better made available to investors and governments making decisions on infrastructure investments. This requires an understanding of what data is already available for the infrastructure sector and what constitutes ESG data for infrastructure. Having more data available is meant to address the information asymmetry in infrastructure financing, lead to greater certainty and clarity for investors when they consider investments into sustainable infrastructure, and hopefully lead to a greater contribution by investors into sustainable infrastructure.

Section 2.2 examines the definition of infrastructure which is the basis for any data collection related to infrastructure assets. Currently, an internationally agreed definition of infrastructure does not exist, and without this, discussion of data gaps cannot be sufficiently advanced.

Section 2.3 is based on a mapping exercise of the various sustainable finance and sustainable infrastructure initiatives that have taken place globally. The mapping allows a clearer identification of areas of convergence of the various initiatives, and what is meant by sustainable infrastructure given the various efforts that have been made so far.

Section 2.4 provides an overview of the existing databases that collect data on infrastructure assets. It examines publicly available infrastructure and then ESG infrastructure data, how these databases assess ESG, and the extent to which it corresponds to the convergence of standards.

The final section discusses challenges and opportunities to address the data gaps identified and how governments, investors and other stakeholders can address them.

While infrastructure has been subject to policy debate for decades, there is no internationally recognised definition for infrastructure that could be applied for the purpose of data collection. Without a common understanding on what constitutes infrastructure and related classifications, infrastructure related data will continue to lack consistency and comparability across various data sources.

Neither the United Nations Fundamental Principles of Official Statistics nor the Central Product Classification provide a definition for data collection purposes of what is commonly referred to as infrastructure. The United Nations Fundamental Principles of Official Statistics and Central Product Classification refer to the concept (such as institutional infrastructure or IT infrastructure in both cases),but does not provide a clear indication of what elements should be included.

In the OECD publication Implementation Handbook for Quality Infrastructure Investment, “[i]nfrastructure provides the backbone of modern well-functioning economies by providing connectivity through enabling the flow of goods, people and information, and by supplying the necessary inputs in the form of energy and water that constitute the foundation for most commercial and industrial activity. Infrastructure is also critical for delivering many services, such as electricity, water and sanitation, digital telecommunications, public transport, health care and education, and flood protection that are essential for health and quality of life, and for providing protection against natural elements” (OECD, 2021[3]). While describing the objectives and areas of infrastructure, this definition is descriptive without specifying the sectors that should be covered by infrastructure.

Most definitions portray infrastructure as a basis of providing basic functions in support of the economy and society. In some cases, a narrower definition may be employed that only encompasses economic infrastructure. Other definitions use the broad definition of infrastructure, meaning that they include social infrastructure or so-called “soft infrastructure”, which covers structures that support the provision of services in the areas of education, health, public order and safety, culture and recreation (OECD, 2021[4]).

The Global Industry Classification Standard (GICS) was developed by MSCI and S&P Dow Jones to classify sectors and is widely accepted among rating agencies and data providers as an industry framework for portfolio management and asset allocation. It is a four-tiered, hierarchical industry classification system that consists of 11 sectors, 24 industry groups, 69 industries and 158 sub-industries (S&P Global, 2022[5]). While energy, health care, information technology, communication services and utilities are covered, there is no specific category to target the infrastructure sector. Classifications that include digital infrastructure often include internet connectivity and broadband access, however only few include assets that enable the storage and exchange of data through a centralised communication system (OECD, 2021[4]).

The OECD’s Working Party on National Accounts developed an infrastructure definition to facilitate the data collection and comparison of statistics based on the System of National Accounts. This OECD Working Party is mandated to improve the quality of national accounts data. It is responsible for the improvement of internationally comparable methodologies and standards based on the System of National Accounts (OECD, 2021[4]).

The OECD’s Working Party on National Accounts has identified four countries that collect infrastructure data through their national accounts: Canada, the Netherlands, the United Kingdom, and the United States. Three of them focus on infrastructural investments and capital stocks. The Dutch study on the other hand is focusing on the value added generated by economic activities related to infrastructure.

Based on their discussions, the OECD’s Working Party on National Accounts proposes the following basic definition for infrastructure: [S]et of fundamental facilities and systems that support the provision of goods and services essential to enable, sustain, or enhance societal living conditions and protect the surrounding environment from erosion and other disasters that reduce the usefulness for economic purposes.

Following this, the OECD further categorises the respective infrastructure sectors that could be covered and is listed in Table 2.1. While renewable energy is not separately classified, categories are present for wind, solar and hydroelectric power generation which are the main renewable energy sectors.

The Infrastructure Company Classification Standard (TICCS) created by EDHECinfra to capture the characteristics of infrastructure investment considers infrastructure assets’ financial and corporate structure and expected risk profiles (see Table 2.1). It provides four classifications of infrastructure assets, which are the business risk classification, industrial classification, geo-economic classification and the corporate-governance classification. Under the TICCS classification, a number of economic criteria have to be present for an asset to be considered infrastructure, for instance large size and long repayment period, and inflexible total cost structure (EDHECinfra, 2018[6]).

The TICCS industrial classification applies a broad definition of infrastructure, including social infrastructure. It categorises infrastructure assets in three detailed levels: industrial superclass, industrial class and industrial sub-class. While the classification has a separate category for renewable power and energy and water resources, it does not include flood protection and water management related infrastructure.

While there is considerable overlap between the OECD definition and TICCS, for data collection purposes, and in particular for national account data, the OECD definition would create sufficient granularity and it is proposed that this definition be applied for data purposes.

Also, considering that Global Industry Classification Standard (GICS) has similar industry classifications, having an agreed definition of the infrastructure sectors may permit industry-based financial information to be aggregated to a certain extent.

For data collection to be better carried out in the infrastructure sector, there needs to be sound basis across the various databases and initiatives. Without infrastructure being clearly defined, uncertainties could arise when considering ESG factors, as some sub-sectors may not be included depending on the definition (such as whether soft/social infrastructure should be included). Thus, it is important to have a common understanding on what constitutes infrastructure to be able to then apply ESG considerations.

Going even further, a definition on infrastructure could permit the collection of infrastructure investment and capital stock to be executed at the national account level, which would support wider private sector efforts and create a basis for comparison across countries. Given the efforts of some countries, data collection of national account-based infrastructure statistics already has a basis upon which to expand to more countries.

Long-term strategies of countries, such as nationally determined contributions (NDCs),1 the National Adaptation Plans (NAP)2 and National Biodiversity Strategies and Action Plans (NBSAPs)3 are pivotal in mitigating climate change impacts and to improve environmental sustainability. In order to achieve these plans and to obtain the desired socio-economic outcomes, it is important that corporates and investors have guidance, measurement tools and requirements available to assess their environmental and social approach.

A number of sustainable finance and infrastructure initiatives have been developed in recent years reflecting the increasing interest and need for financing to consider ESG factors more carefully and closely. The G20 agreed on the G20 Principles on Quality Infrastructure Investment (QII) in 2018 (G20, 2018[7]), which creates a good basis for such initiatives to draw on and creates a need to consider ways in which to assess financing for sustainable investment purposes.

To have a better understanding of how QII Principles could be implemented for data purposes, 21 sustainable finance and infrastructure initiatives, which are widely recognised and applied in financial and infrastructure context, were mapped in terms of the conditions by which they made requirements.

The following 21 initiatives were mapped in this exercise:

  • Investment Principles and Eligibility Criteria (ACGF, 2020[8])

  • Aligned Set of Sustainability Indicators for Infrastructure (IDB, 2020[9])

  • CEEQUAL (BRE, 2022[10])

  • Equator Principles (Equator Principles, 2020[11])

  • Climate Bond Standards (Climate Bonds Initiative, 2020[12])

  • Climate Policy Initiative (CPI) Global Landscape of Climate Finance (CLCF, 2019[13])

  • EU Green Taxonomy (EU Commission, 2020[14])

  • GIB (SuRe) (GIB, 2022[15])

  • Green Bond Principles (ICMA, 2018[16])

  • Green Loan Principles (LSTA, 2018[17])

  • GRESB (GRESB, 2022[18])

  • Harmonised MDB Frameworks on Climate Finance Tracking (IDB, 2019[19])

  • IDB Sustainable Infrastructure Framework (IDB, 2018[20])

  • IFC Definitions and Metrics for Climate-Related Activities (IFC, 2017[21])

  • IFC Environment & Social Performance Standards (IFC, 2017[21])

  • Infrastructure Sustainability Council of Australia (ISCA) (Infrastructure Sustainability Council, 2022[22])

  • ISI (Envision) (Institute for Sustainable Infrastructure, 2022[23])

  • Social Bond Principles (relevant infrastructure categories) (ICMA, 2021[24])

  • Sustainability Linked Loan Principles (LSTA, 2022[25])

  • UN Social and Environmental Standards (UNDP, 2021[26])

  • UNDP SDG Impact Standards for SDG Bonds (UNDP, 2022[27])

A number of initiatives have been developed by multilateral developments banks (MDBs), such as the Investment Principles and Eligibility Criteria (ASEAN Infrastructure Fund), Aligned Set of Sustainability Indicators for Infrastructure (ASSI), Harmonised MDB Frameworks on Climate Finance Tracking, IDB Sustainable Infrastructure Framework, IFC Definitions and Metrics for Climate-Related Activities and IFC Environment & Social Performance Standards. UN related initiatives are UN Social and Environmental Standards and UNDP SDG Impact Standards for SDG Bonds.

The EU Green Taxonomy will be applied in EU member states, so it will have the strongest impact in terms of implementation.

There are a number of private sector initiatives, such as BRE (CEEQUAL), Equator Principles, Climate Bond Standards, Climate Policy Initiative, SuRe, Green Loan Principles, GRESB, Infrastructure Sustainability Council of Australia, ISI, Social Bond Principles, and Sustainability Linked Loan Principles. Most are coalition of private sector stakeholders or non-profit initiatives.

The most common methods of assessment used by each initiative have been classified in Table 2.2.

Due to the strong focus on environmental factors in recent years and some of the initiatives, such as the CBI – Climate Bond Standards, Climate Policy Initiative (CPI), EU Green Taxonomy, Green Bond Principles, Green Loan Principles, IFC Definitions and Metrics for Climate-Related Activities, are solely focused on climate change, environmental factors are strongly represented and require a number of granular conditions.

Governance factors are covered the least, with only four initiatives requiring them. Social factors are covered by 1/3 of the initiatives. Assessment areas related to both social and governance factors are fairly consistent across the various initiatives. Social factors include stakeholder engagement, human and labour rights compliance, and gender. Governance factors include anti-corruption, and corporate governance and sustainability disclosure across the board.

As for the environmental factors, most initiatives have an assessment approach. Greenhouse gas (GHG) emissions reduction and pollution control are the main way in which environmental factors are assessed by nearly half of the initiatives. Otherwise, biodiversity and ecosystem conservation, waste reduction, and energy and water efficiency are applied for environmental factors.

Turning to these assessment methods more closely, Table 2.3 addresses each one specifically in order to better understand their respective approached in practice. This is complemented by the work that the International Finance Corporation (IFC) is developing in the G20 Compendium of Quality Infrastructure Indicators (QII Indicators).

There are five main environmental factors that are applied across the initiatives. These encompass GHG emissions reductions, pollution control, biodiversity and ecosystem conservation, energy efficiency, and waste reduction. They are primarily focussed on climate mitigation measures, and not on climate resilience or adaptation.

GHG emissions reductions inquire on whether reduction against business-as-usual baseline was achieved (Y/N) and on the annual reduction of CO2 emissions by tonnes. Annual CO2 emissions reduced by tonnes corresponds with the QII Indicators.

Pollution control is made up of air, water and soil pollution related items but most assessment methods come from the ASSI.

Water pollution assessment methods are freshwater withdrawal (kL/year – annual volume of fresh water used by an infrastructure project), watershed management (Y/N – existence of watershed assessment/management programme), or number of water pollution exceedances (Y/N – non-compliance with wastewater quality standards).

Air quality is assessed by fine particulate matter emission4 (yes/no response or mean PM2.5 and PM10 emission). This is reflected in the QII Indicators but uses a different measurement of local air pollutants reduced in tonnes per year.

For biodiversity and ecosystem conservation, assessments focus on whether endangered species are impacted, and the number impacted, previously disturbed land (percentage of land used that had previously been non-disturbed or maintained as non-disturbed), and biodiversity and ecosystem management.

Energy efficiency measures come primarily from the EU Green Taxonomy and the Green Bond Principles. For energy efficiency, the EU Green Taxonomy requires at least 30% reduction in emissions compared to the baseline performance of the building before the renovation and sets direct emissions below 50g CO2e/p-km. Otherwise, total energy consumed per output scaling factor, or energy efficiency are measured in kwh per cubic metre billed/unbilled authorised water supply (water treatment). They require at least a 20% average decreased in energy consumption of system. The Green Bond Principles recommend measuring energy efficiency by the use of renewable energy or energy savings. Here, the method that is recommended is MWh/GWh for annual energy savings, as well as for annual renewable energy produced. QII Indicator considers energy consumption by kWh or MWh per year.

Waste reduction is covered primarily by the Green Bond Principle, which draws on measurements from various public requirements. This includes reduction of waste (metric tonnes or percentage of total over lifetime of project), waste prevented/minimised/reused/recycled (benchmarked to EU Waste Policy), energy recovered from waste (benchmarked to SWM-GHG calculator,5United States Environmental Protection Agency’s Waste Reduction Model6), waste collected and treated or disposed (benchmarked to EU Landfill Directive), and improved access to municipal waste collection (number of people/percentage of population).

Social factors converge on four factors: stakeholder engagement, community development, human and labour rights, and gender.

Stakeholder engagement can be broken down into overall plan for engagement, people and lands affected, and public health and safety. The assessment gathers responses about whether a stakeholder engagement plan exists (yes/no) and whether a free, prior, and informed consent to projects (FPIC) (yes/no through establishment of FPIC).

In terms of people and lands, the following are covered: the need for resettlement (over lifetime of project, the number of people physically displaced by project), heritage assessment (yes/no on existence of protection procedures), consultation/participation of affected parties in design/review/implementation of a project, impacts on vulnerable groups/communities/indigenous peoples/cultural systems, and protection of cultural property/heritage.

The QII Indicators adopt similar areas with the existence of a stakeholder engagement plan and whether the design minimises land acquisition and involuntary resettlement.

Community development focuses on public health and safety in terms of areas examined. The factors examined are having a public health and safety management plan (yes/no on implementation of plan), protection of community health/safety, and health and safety of community, contractors, customers, and supply chain.

In terms of the community development, QII Indicator covered contributions to community development in terms of monetary value, whether the infrastructure would improve local community, and the total number of rural infrastructure assets established or improved by the project.

Human and labour rights compliance covers adherence to human and labour rights policies (yes/no in terms of alignment to International Labour Organization Conventions), human rights commitment and human rights complaints and violations.

Focusing more on labour rights, the assessments include occupational health and safety (OH&S) management systems (yes/no on existence/implementation of system), frequency rates of fatal and non-fatal occupational injuries (number of cases per hours worked), fair wages (percentage of employees paid fair wage), local jobs created (number during construction and operation), non-discrimination, cumulative impacts of existing projects, fire prevention and life safety and workforce sustainability.

The QII Indicators includes the number of fatal and non-fatal occupational accidents.

In terms of gender, the assessments look at inclusiveness, and empowerment (yes/no on existence/implementation of gender action plan) and social sustainability plan for maximum benefit inclusion for disadvantaged groups (women, the poor, among others).

The QII Indicator includes the number of female director jobs supported by the project.

Governance factors covers anti-corruption, and corporate governance and sustainability disclosure.

For anti-corruption, assessments included whether there is an anti-corruption procedures (yes/no on existence of procedure), anti-bribery and corruption management systems, and financial transparency on taxes and donations.

The QII Indicators highlights the number and percentage of governance body members that have received training on anti-corruption, and the existence of anti-corruption protocols and procedures.

On corporate governance and sustainability disclosure, the assessments covered sustainability in project award (yes/no in terms of sustainability being included in tender of project), specific board composition, cybersecurity, legal compliance and oversight, environmental and social management systems, and stakeholder identification and engagement planning.

The QII Indicator takes a slightly different approach on governance from the aforementioned, with yes/no on whether fiscal sustainability assessment is available, yes/no on information disclosure of the purpose, scope, costs and implementation of infrastructure projects is open and accessible to the public, and finally, yes/no on measures to adopt or enforce principles of transparency and accountability in procurement and financial management are implemented in the context of the project, which are considerations specific to the infrastructure governance.

An examination of the 21 initiatives makes clear that there is convergence in sustainable finance and infrastructure initiatives. This is particularly the case in relation to ‘E’ factors, as some of the initiatives are focussed on climate change. However, the initiatives are focussed on climate mitigation and not climate adaptation and resilience which requires greater consideration given the impact that climate change is having on infrastructure assets, in particular in relation to disasters.

Many initiatives only list the areas of considerations, and do not elaborate on how this could be specifically assessed. This means that while the various initiatives cover similar areas, initiatives that provide a more risk-based approach and enabling a more granular understanding are limited in number.

This is also reflected when the assessment of an area is based on a yes/no response which leads to a binary or tick box approach of assessment. While this is helpful in terms of ensuring that the issue is considered, and in some instances having a broader binary response could be preferable to a limited detailed assessment, it may not encourage projects to improve their performance on ESG over time. To bring greater contextualisation, the areas of convergence are listed below avoiding, where possible, binary response assessments.

Environmental factors are converging on some areas, such as:

  • GHG emissions reduction in terms of tCO2e/year

  • Air pollution: fine particulate matter emission PM2.5 and PM10 emission or reduced air pollutant tonnes per year

  • Direct emissions less than 100g CO2/kWh (lifecycle emissions, applicable to electricity and heating/cooling generation)

  • Number of species impacted, and percentage of land impacted/disturbed by project

  • Renewable energy used MWh/year

  • Reduced waste in metric tonnes.

GHG emissions, air pollution, and energy efficiency assessment methods are also aligned with the QII Indicators.

For social factors, there are a number of areas of divergence in terms of the approaches that are taken, although some areas of convergence can be observed. Areas of convergence for social factors include:

  • Existence of stakeholder engagement plan

  • Number of displaced people, including minorities and indigenous people

  • Existence of heritage assessment and protection procedures

  • Existence and implementation of protection of community health/safety plan

  • Adherence to International Labour Organization Conventions and existence and implementation of occupational health and safety (OH&S) management systems

  • Frequency rates of fatal and non-fatal occupational injuries (number of cases per hours worked)

  • Fair wages (percentage of employees paid fair wage)

  • Local jobs created (number during construction and operation)

  • Existence of gender equality, inclusiveness and empowerment plan.

For governance factors, there is convergence on:

  • Existence of anti-corruption protocols and procedures

  • Existence of corporate governance structures.

The Blue Dot Network seeks to establish a voluntary, inclusive, private-sector focused, government-supported project-level certification scheme to operationalise the G20 Principles for Quality Infrastructure Investment. The G20 Principles incorporate traditional ESG considerations as well as dimensions such as good public governance, resilience, economic efficiency over life cycle cost, debt sustainability and sustainable development, which are important to ensure that investments meet their objectives in a manner that benefits all of society. The Blue Dot Network does not create a new standard, but seeks to streamline and create interoperability between existing international standards in such a way as to increase both the efficiency and robustness of project development, and thus facilitate greater private investment in quality infrastructure.

FAST-Infra is a sustainable infrastructure initiative that seeks to put forward a globally applicable labelling system, the Sustainable Infrastructure Label (SI Label). Requirements that need to be fulfilled to obtain a label build on existing frameworks, taxonomies and standards, such as SDGs and G20 Principles of Quality Infrastructure Investment and IFC performance standards. Its labelling system encompasses four dimensions, covering adaptation and resiliency in addition to environmental, social and governance dimensions (Climate Policy Initiative, 2021[28]). FAST-Infra criteria are close to these areas of convergence for ESG assessment, so it could be a useful tool for projects to be assessed upon, and data collection to be based on. Project management programmes, such as SOURCE, could also assist countries consider such standards in a more routine manner.

To encourage greater adoption of ESG standards by infrastructure projects, mechanisms that incentivise implementation should be considered closely. The UN Principles for Responsible Investment presents a compelling example of a public-private initiative that has had an impact, with 4 800 signatories and many institutional investors and asset managers being asked whether they are a signatory when conducting business.

The infrastructure sector has a number of data vendors that have developed data on infrastructure over the years. Collection of data on infrastructure assets is challenging, given the complex and long-term nature of investments, and as a result of corporate reporting standards in each country. Construction could experience unexpected delays, political risks could emerge and revenue streams could be unpredictable for some projects. Projects based in emerging and developing countries (EMDEs) will have the additional burden of lacking access to some of the basic reporting and implementation of standards which could assist this process.

Another difficulty arises once the project advances from the preparation and construction phase into the operation phase. At this stage, it becomes difficult to trace and collect data on the same infrastructure project as it often falls into the hands of another entity.

With this caveat in mind, this section provides an overview of what data is currently publicly available. It should be noted that most data vendors charge a fee for access, while some are based on membership. In this respect, there is not a data source that is free of charge, given the high cost involved in collecting data on infrastructure funds and projects.

The objective of this section is to understand what data is available on infrastructure assets, but in particular for those that are ESG assessed. For more sustainable infrastructure projects to be pursued, investors would require data that can assess financial performance of projects, especially against sustainability goals.

The ESG assessment approaches will be considered against the various initiatives as discussed in Section 2.3.

Preqin is a private data provider that offers financial information with a focus on the alternative asset market. It offers a specific database on infrastructure assets and investments, as well as their ESG performance. Infrastructure data is available by investor, asset manager, funds, and deals and exits. It provides information about investors’ infrastructure fund portfolio with regard to fund name and type (e.g. core, core plus, fund of funds and debt), as well as fund performance. Further, the dataset captures information on investment allocation by listed, unlisted and direct infrastructure, and information on location and markets in which infrastructure investments are made, as well as project stages (greenfield, brownfield etc.).

Detailed infrastructure information by investor is limited to the current year and granular historical data is not available. The database does offer historical data by investors’ overall infrastructure investment (from 2013), however, this only encompasses the amount invested into infrastructure and is not broken down by allocation (listed, unlisted and direct), project stages and regions. Further, historical data of infrastructure funds is available, but only encompasses fund performance data.

Information on investors that are active in the infrastructure sector is limited for emerging and developing economies. Of an overall of 5 497 observations for investors that operate in this sector, there are only 149 results for Latin America and the Caribbean and 100 results for Africa. There are 978 observations for Asia, whereas results for investors in North America and Europe count 2 209 and 1 536 respectively. This reflects a more limited data availability for emerging and developing economies, which also holds true for Preqin’s data on funds and asset managers, as well as for infrastructure deals and exits.

ESG factors captured in the database are based on the level of ESG transparency with regard to the level an investor, fund manager or fund discloses its ESG information publicly. The level of ESG transparency is reflected with an overall ESG key performance indicator (KPI) from 0-10%, which is based on individual KPIs for 37 ESG criteria that are presented in the dataset.7

In total, the database offers ESG transparency information of around 2 008 investors and 730 fund managers active in the infrastructure sector. In terms of regions, data coverage ranges from Europe, Asia, Australasia, Middle East, Latin America and Africa. When filtering on investors that are assessed on ESG transparency and that are operating in the infrastructure sector around 780 observations are available for North America, 660 for Europe, 340 for Asia, 100 for Australasia, 50 for the Middle East, 30 observations for Latin America and the Caribbean, and 30 observations for Africa.

The ESG transparency information is based on publicly disclosed and self-reported data, and is not based on a third party ESG assessment. Nevertheless, Preqin’s ESG dataset is the broadest database with data on both infrastructure, as well as ESG performance that is publicly available. Risk evaluation and impact assessments of funds is only available for private equity, private debt and venture capital and does not include infrastructure.

Preqin’s ESG transparency methodology builds on 37 indicators derived from various ESG frameworks, such as investors’ affiliations with the UN Principles for Responsible Investment (UNPRI), Sustainability Accounting Standards Board (SASB), and the Task Force for Climate Related Financial Disclosure (TCFD) and the ESG Assessment Framework of the Institutional Limited Partners Association (ILPA).8 Indicators also use ESG ratings by MSCI, Sustainalytics, ISS, and other public market ratings providers. ESG information is derived from publicly available sources and matched to the indicators in a “Yes” or “No” format (Preqin, 2021[29]). Based on the indicators Preqin developed a transparency KPI, which gives a percentage that reflects the level to which ESG information is publicly disclosed.

Refinitiv’s (formerly Thomson Reuters) infrastructure database provides project information from pre-construction to the construction and analysis stage. The project-level data encompasses information of approximately 55 000 infrastructure projects from around 100 countries over 45 years. Of these 38 000 projects are categorised as renewable projects and labelled as ‘sustainable infrastructure projects’, covering biomass, geothermal, hydroelectric, solar, and waste and wind (Refinitiv, 2021[30]). Hence, in terms of ESG considerations, the dataset offers a category for renewable energy infrastructure projects, however it does not provide ESG information.

While the database offers detailed project level data, including project cost, sector and even information on if the project is considered part of the belt and road initiative, it does not capture information on investors that invested in the project nor on the amount invested.

Of all projects that were financed in 2021, 299 were based in Europe, 212 in North America, 198 in Asia-Pacific excluding Central Asia, 158 in Latin America and 44 in Africa, Middle East or Central Asia. While this number is higher for projects that are announced in the year 2021 the proportion is the same, and the number of projects in Africa, the Middle or Central Asia is significantly lower than the rest of the regions.

In the listed company database, Refinitiv uses its own Business Classifications (TRBC), which is a sector and industry classification. Each sector category is broken down into sub-categories. Like GICS, the classification does not include a specific infrastructure sector category, however it does encompass typical infrastructure sectors, such as energy, transportation and utilities as main headings, each broken down into various sub-categories (Refinitiv, 2022[31]).

Refinitiv’s listed company database offers ESG specific information based on a scoring methodology that additionally to the ‘E’, ‘S’ and ‘G’ aspects considers the level of controversy that a company received in these areas. However, this data is not offered in combination with the dataset that covers project level infrastructure data. As the sector can be selected, ESG information of listed companies operating in infrastructure sub-sectors can be retrieved, but this information is not available on the investor level.

EDHECinfra provides a database that contains information on the performance, valuation, risks and costs of unlisted infrastructure assets, measured against various indices. Performance information of unlisted infrastructure equity and debt is made into market indices (infra300 index, infra100 index), as well as the infraGreen index, which is specific to the renewable energy sector. The latter looks at equity and debt investments in solar and wind projects. The database also offers data on asset and risk valuation of unlisted infrastructure equity and debt (EDHECinfra, 2022[32]). The infra300 index is based on the TICCS classification and reflects market exposure of the different TICCS segments of unlisted infrastructure assets (EDHECinfra, 2021[33]; 2018[6]).9

While providing indices and performance data related to unlisted infrastructure assets, EDHECinfra does not provide information specific to ESG performance, but plans to put forward a climate and social risk and impact metric for infrastructure investors in the future to facilitate ESG reporting and data collection in the area (EDHECinfra, 2022[34]).

IJ Global has an infrastructure project and transaction database covering both project finance and corporate balance sheet financing transactions. The database provides details on transactions, including pricing details. It covers project finance for infrastructure sectors including oil and gas, renewables, power, transport and social and defence. In terms of regions, it covers Europe, North America, Asia Pacific, Latin America and the Middle East, but not Africa. The database does not have information on ESG aspects beyond transactions in the renewable energy sector (IJGlobal, 2022[35]).

Moody’s provides data on project and infrastructure finance including information on the performance of rated infrastructure project debts. Information on default and recovery experience in such debts can be used to analyse the risk profiles of the project finance debt. The dataset covers around 8 583 project transactions from the year 1983 to 2018. In terms of sub-sectors, until the year 2018 it counted around 1 006 social projects with 19 defaults, 1 114 transportation projects with 97 defaults, 305 water and waste projects with 18 defaults, 68 other infrastructure projects with five defaults, 395 media and telecom projects with 46 defaults, 278 oil and gas distribution and refining projects with 17 defaults, and 3 881 power generation and transmission projects with 240 defaults. Further, 5 909 projects were based in high income countries with 335 defaults, and 1 138 projects in middle- and low-income countries with 107 defaults (Kelhoffer, 2020[36]).

While Moody’s has a database that captures a wide range of historical infrastructure project transaction data, it does not provide information on ESG considerations. In addition, the regional coverage is largely tilted towards developed economies in relation to developing and emerging economies.

There are various databases that cover ESG specific information, amongst others Bloomberg and S&P Global. Since the focus of this report is infrastructure specific datasets, databases that only cover ESG information are not extensively examined.

For example, S&P Global’s Trucost Environmental database captures quantitative information on the environmental performance of around 15 000 listed companies. The data covers environmental issues, such as carbon emissions, water dependency and waste disposal and natural resource efficiency (S&P Global, 2020[37]). The Trucost physical risk database has information on companies’ and assets’ physical risk exposure to climate change (such as wildfires, sea level rise), providing a physical risk score, which can give an idea of the total value of assets considering these risks. However, the dataset does not provide infrastructure specific information and the infrastructure sub-sectors are limited to utilities, energy, communication services and health care. Further, it does not provide information on the investment level into these assets (S&P Global, 2022[38]).

Bloomberg’s ESG dataset includes ESG metrics and disclosure scores for approximately 11 800 companies worldwide. ESG areas covered are air quality, climate change, water and energy management, waste, health and safety, audit risk and oversight, shareholder rights, compensation, diversity and board independence (Bloomberg, 2022[39]). However, the dataset does not provide infrastructure specific information.

GRESB is a platform that provides assessment and scoring for ESG performance of listed infrastructure companies and funds, but does not disclose this collected data publicly. GRESB’s assessments are based on multiple reporting frameworks, and the scoring methodologies are publicly accessible. Members can receive these assessments on an annual basis, but only have access to other members’ data in an anonymised, relative or aggregated manner. The benchmark report that is provided after assessments details where the practitioner stands in the GRESB universe, thus in comparison to other members (GRESB, 2022[40]). For non-members, GRESB makes publicly available aggregated information in the form of figures and tables. This information also covers the names and respective sectors of the infrastructure funds and assets that had the highest score in any given year (GRESB, 2021[41]).

Data related to infrastructure assets is limited to several fee-based data vendors, Preqin, Refinitiv, EDHECinfra, Moody’s and IJGlobal. Preqin offers infrastructure data at the investor, fund and deals level, whereas Refinitiv, Moody’s and IJGlobal capture data at the project transaction level. EDHECinfra provides information on performance indices, as well as unlisted infrastructure assets data.

This shows that there are a number of databases that collect infrastructure asset and project level data. Yet, one aspect that is prevalent in all databases is that available data is skewed towards advanced financial market data, and limited for EMDEs markets. With regard to Preqin, significantly less observations on infrastructure investments and deals are available when selecting the regions Africa and Latin America and the Caribbean in relation to North America and Europe. IJGlobal’s project level transaction data does not cover the region Africa at all. Refinitiv’s coverage in 2021 with regard to Latin America was relatively large, but this was significantly less for African and other EMDE markets.

Databases that have an ESG approach for the infrastructure sector is Preqin only, with EDHECinfra planning one.

Data providers do have ESG approaches but assess different aspects of ESG and not necessarily a risk assessment against ESG factors. Preqin uses ESG transparency, whereby the infrastructure funds self-declare which of the 37 indicators it adheres to or not (a yes/no binary approach). Preqin’s ESG transparency provides useful insights into the types of activities the fund may be engaging in that is relevant to ESG considerations. However, it is a yes/no binary approach, heavily reliant on implementation of UN PRI, and does not provide a detailed insight into the funds approach to ESG factors.

GRESB provides aggregated level information on infrastructure funds’ and companies’ ESG performance in the infrastructure sector and only members are able to receive a more detailed analysis in this respect, but even members are not able to attain full access to GRESB’s database.

It is clear that while these ESG approaches are useful in having some information on ESG factors of infrastructure funds and projects, if one considers the sustainable finance and sustainable infrastructure initiatives discussed in Section 2.3, these databases would not be able to respond to providing a quantitative understanding of adherence to initiatives.

One of the main issues related to the development of an ESG assessed database is the weakness of corporate reporting regimes, as well as the disclosure requirements. Infrastructure projects are often private companies or special purpose vehicles (SPVs), with financial reporting not having to be publicly disclosed. Reporting could be paper-based, making data collection of such corporate information extremely resource heavy. While the recommendations of the Task Force on Climate-related Financial Disclosure (TFCD) (TCFD, 2017[42]) would be a useful non-financial disclosure regime, it is limited to environmental factors, and as of October 2021, only eight jurisdictions have TCFD-aligned official reporting requirements (TCFD, 2021[43]), for example.

Limited data is available on infrastructure assets’ risk exposures in general but especially not through quantitative risk reporting. Most ESG frameworks’ measurement approaches use process and output indicators, such as GHG emission, instead of measuring ESG impacts or ESG risks. Without a framework explicitly considering the direct and indirect risks that the ESG characteristics of infrastructure investments create, the relationship between ESG investments and the market value of these investments remains unclear. Consequently, investors might be less motivated to incorporate ESG considerations in their investments. EDHECinfra’s TICCS classification does provide an opportunity to classify infrastructure assets according to its risks and could facilitate data collection in this regard (EDHECinfra, 2021[44]).

Moreover, data on ESG considerations in infrastructure is skewed towards developed markets with limited coverage of emerging and developing markets. When considering the regional coverage of infrastructure-related ESG approaches, Preqin’s ESG Transparency coverage provides some insight into the challenges of this. In Preqin’s ESG Transparency data 780 observations are for North America, 660 for Europe, 340 for Asia, 100 for Australasia, 50 for the Middle East, 30 observations for Latin America and the Caribbean, and 30 observations for Africa. It is unclear whether this is the outcome of lack of projects, lack of coverage, or lack of available information. However, it does point to the paradox of where infrastructure investment is most needed, ESG-related data is least available, creating greater information asymmetry for investors.

For infrastructure data and ESG assessed infrastructure data to be publicly available, and at a scale that could allow investors to take them more readily into account, there are a number of considerations that could be made by policy makers, investors, project developers, and other stakeholders. The availability of data that would provide greater clarity and certainty for investors to make investment decision would contribute to addressing the information asymmetry and establish a better foundation for the private investment pipeline to be developed.

In addition, home biases that investors may have can only be addressed through a better understanding of foreign markets, and in particular for EMDEs, so having databases that have a time series that would permit assessment of financial performance and against sustainability goals would be important to finance more sustainable infrastructure projects.

Definition of infrastructure for data collection purposes: Currently, there is no internationally recognised definition of infrastructure for data collection purposes. The OECD’s Working Party on National Accounts has developed an infrastructure definition to facilitate the data collection and comparison of statistics based on the System of National Accounts, which could be a starting point for data collection.

Data collection at national account level: supporting data collection of infrastructure investment and capital stock could create a useful baseline to better understand the level of investments that are being made in the domestic context.

Improved reporting regimes and digitalisation: the lack of data in EMDEs and SMEs is related to the weaker corporate reporting regime in these markets. In addition, the lack of digitalisation of reporting also creates a barrier to collecting data from companies that are developing or operating infrastructure assets.

Complexity of infrastructure projects: infrastructure projects will change hands as they transition from the development/construction stage to operation phase. This creates challenges in terms of tracing the project and collecting continuous data of a project.


Recognising sustainable infrastructure: while there has been extensive discussions on sustainable infrastructure, there is not yet a clear understanding of what this might constitute. While there is much emphasis on climate mitigation, climate resilience and adaptation should also become a greater part of the discussion. In addition, greater discussion should take part on social and governance aspects, to encompass the entire ESG spectrum.

Converging on sustainable infrastructure initiatives: there have been a number of sustainable finance and infrastructure initiative from both the public and private sector over the years, which has allowed us to better understand the areas of convergence of these initiatives. While environmental factors have been better defined, and assessment measures can be identified, this is less the case for social and governance factors. Greater work needs to be carried out to ensure that assessment approaches are developed for S and G factors.

Developing a greater understanding of ESG assessment approaches: A shortcoming of some of the initiatives is the binary assessment method for a number of conditions that are being assessed. While having a binary approach is more useful than not having a condition being required, and could result in broader engagement, it does not provide an understanding as to which level the infrastructure project is adhering to any condition. Thus, as greater discussion takes place, it is hoped that more granular and possibly quantitative approaches can be developed for each condition.

Lack of comprehensive ESG data for infrastructure: one of the key findings of this report is that ESG-assessed data is not in fact publicly available. Some data vendors have ESG-adjacent data, but do not have available data that is assessing ESG comprehensively.

Cost of producing ESG data: given the nature of infrastructure projects, infrastructure data in itself is costly to produce, and ESG data would be even more resource heavy. Currently, the ESG-adjacent data that is available is thus self-reported on a voluntary basis by infrastructure companies and not assessed by the data vendors. This places a significant barrier on having true ESG data available for infrastructure assets.

Reflection of lack of understanding on sustainable infrastructure: many of the issues related to ESG data reflects back on the fact that there is not a common understanding of sustainable infrastructure, and the market for such data has not yet developed. This could evolve as governments start having clearer requirements related to the development and operation of their infrastructure projects.

Limited disclosure from unlisted infrastructure assets: many infrastructure entities are unlisted or private entities, which are subject to limited disclosure requirements. This further hampers applying ESG conditions.

Greater implementation of sustainable infrastructure labels and development of indicators: there are a number of initiatives that could facilitate greater application of assessed ESG conditions and advancement of understanding of how these labels could support infrastructure projects and investor decisions. Initiatives such as FAST-Infra, Blue Dot Network, and collection of QII Indicators could contribute and create a data repository for sustainable infrastructure going forward.


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← 1. NDCs are a climate action plans to cut emissions and adapt to climate impacts in accordance with the Paris Agreement. Each Party to the Paris Agreement is required to establish an NDC and update it every five years (United Nations, 2022[47]).

← 2. NAPs are strategies that consider medium- and long-term adaptation needs informed by the latest climate science (UNEP, 2022[46]).

← 3. NBSAPs are intended to define the current status of biodiversity, the threats leading to its degradation and the strategies and priority actions to ensure its conservation and sustainable use, in accordance with the Convention on Biological Diversity (United Nations, 2022[47]).

← 4. PM 2.5 refers to a category of particulate pollutant that is 2.5 microns or smaller in size. The average cross-section of a human hair is 50 microns. PM stands for “particulate matter.” PM 10 particles (particles less than 10 microns in size) can irritate your nose and eyes, but fewer of these particles penetrate deep into your lungs, so they do not cause the same health problems that smaller micron particles can, although they do increase rates of respiratory disease.

← 5. This is a tool for calculating greenhouse gases (GHG) in solid waste management (SWM) developed by Institut für Energie- und Umweltforschung Heidelberg GmbH. https://www.ifeu.de/fileadmin/uploads/Manual-SWM-GHG-Calculator_2010.pdf

← 6. EPA Waste Reduction Model (WARM) provides high-level estimates of potential greenhouse gas (GHG) emissions reductions, energy savings, and economic impacts from several different waste management practices. https://www.epa.gov/warm#:~: text=EPA%20created%20the%20Waste%20Reduction,several%20different%20waste%20management%20practices.

← 7. For instance, the asset manager BlackRock has a transparency score of 97%, which encompasses transparency scores of the 37 ESG criteria, including for instance a score on “an investment policy that includes ESG issues”.

← 8. In contrast to other ESG framework, the ILPA’s ESG Assessment Framework is designed for limited partners (LP) specifically. It was developed originally for the private equity asset class, but can also be applied to other asset classes (ILPA, 2022[45]).

← 9. An important element of TICCs is to provide a better understanding of characteristics and risk perception of each infrastructure asset. For example, business risk is allocated according to the perceived risk of the industry. In this context, transportation infrastructure is riskier than utilities and infrastructure corporates are riskier than special purpose vehicles (SPVs).

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