Future of Construction


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Sustainable Asset Value IISD (SAVi) Model

The challenge

Conventional project finance valuation methodologies ignore a range of material externalities.

The main barrier to deploying sustainable and natural infrastructure is the difficulty of structuring financially viable projects. Traditional valuation methodologies often provide a less convincing business case for sustainable assets than for grey infrastructure, due to their elements such as higher upfront capital costs, prominent technology risks, greater attention to safeguards, and higher project preparation costs. The problem lies in the inadequate identification and pricing of risks leading to inaccurate asset valuation and feasibility assessments.

What is sustainable infrastructure? Sustainable infrastructure includes assets that:

  • Have lower carbon and environmental footprints
  • Provide for the stewardship of natural ecosystems
  • Trigger green technological and industrial innovation across domestic and international value chains
  • Spur investment in education, skills building and R&D
  • Increase employment and the growth of green jobs
  • Are financially viable
  • Crowd-in domestic investors and businesses
  • Increase FDI and domestic value- added
  • Optimize value for money for taxpayers and investors across the asset life cycle.

The idea

The SAVi Model addresses challenge above by providing the necessary quantitative evidence that sustainable infrastructure is the right choice, when considering its holistic impacts, even from a pure financial perspective.

SAVi is based on the following methodologies:

System Dynamics, which serves as a knowledge integrator, generating a conventional cost-benefit analysis as well as a more comprehensive assessment of the broader social, economic and environmental impacts of sustainable and grey infrastructure. This includes the estimation of required investments and resulting co-benefits, avoided costs and project risks. For example, forecasted impacts could include reduced fish stock following the installation of a hydropower dam. An example of avoided costs could be reduced energy consumption in sustainable buildings or reduced construction costs in the case of better road siting. One example of an added benefit could be increased productivity triggered by improved human health, which in turn was afforded by improved ambient air quality. This methodology also allows project risks to be identified and estimated quantitatively, filling an important information asymmetry for investors.  Examples of these risks are provided below:

  • Regulatory risks: carbon taxes, changes in feed-in tariffs, changes in availability payments, air pollution laws
  • Market risks: price volatility and disruptions in supply of inputs (coal, building materials, water, feedstock) and outputs (energy and water services)
  • Technology risks: unexpected costs in installation and O&M, losses related to poor performance, cost of decommissioning, losses related to extreme weather, insufficient track records,
  • Social risks: issues related to land acquisition, disputes and delays related to environmental impact assessments and social impact assessments, disputes and delays related to other safeguards such as clearances and permits.

Corality SMART Financial Modelling Methodology is used as the framework to demonstrate how the project risks identified as part of the system dynamics modelling influence the financial viability of sustainable versus business-as-usual infrastructure projects. These additional risk variables are integrated into the sensitivity analysis as part of the financial assessment.

Lenders and equity investors build project finance models to estimate the financial sustainability and profitability of the project by mapping the various cash flows during the life of the asset. Using financial models built with Corality SMART Financial Modelling Methodology, SAVi demonstrates how the different project variables (such as capital expenditures, construction time, operation costs, operation efficiency, corporate tax rate, etc.) change under a wide range of risk scenarios. The scenarios modelled illustrate how the elements identified as part of system dynamics model influence the overall bankability of green verses the business-as-usual infrastructure projects. Such elements include change in carbon pricing policy, delays in construction, disruption in operation due to social or technological risks, the impact of climate change such as heat waves on the operation of the asset, among others.

The Corality SMART Financial Modelling will also allow policy makers and investors assess how fiscal and financial incentives are important to increase the deployment of sustainable infrastructure. For example, tax rebates and allowances for sustainable infrastructure can positively enhance project finance parameters such as base interest rate and corporate tax rates. Similarly, Financial instruments to hedge against currency risks could allow a greater crowding in of domestic inventors and suppliers that would in turn increase productivity and green industrialisation in the domestic economy.

 The Asset Categories

SAVi is first being developed for four asset categories: energy, roads, water management and buildings. Other asset categories will be added in the latter half of 2017.


In the energy sector, various electricity generation options are compared to identify economic, as well as social and environmental advantages and disadvantages. These are assessed for various economic actors (i.e. private sector, government and households) to gain a comprehensive view of the existing motives for investing in grey vs. green infrastructure. The SAVi Model customized to electricity supply includes macro-economic drivers to estimate demand, which in turn drives the estimation of required investments, capacity construction and ultimately electricity supply from conventional thermal options (i.e. oil, coal and gas), renewables (i.e. wind, solar, biomass and hydropower) and nuclear power. Employment and income are estimated for both the construction and operation and management of these plants. Other direct inputs to production, in addition to plant capacity and labour are energy sources (e.g. fossil fuels) and water. Land use, along with cement and steel used are also estimated for each technology across its lifetime. Finally, CO2, NOX, SO2 emissions and Pm are estimated, including their economical valuation (e.g. using the Social Cost of Carbon). Risks to production are also assessed through scenarios, which includes the impact of climate change (e.g. on water use for the cooling of thermal capacity).


The SAVi buildings model assesses the construction, material manufacture, operation and management and demolition process of buildings. As a result, the definition of sustainable building used by SAVi accounts for economic and social outcomes in addition to environmental ones. The technologies considered include: construction materials; solar PV and solar heat water; heating, ventilation, and air conditioning; lighting; water recycling and appliances.


The SAVi roads model defines a sustainable road as one that limits environmental impacts throughout its life cycle, including manufacture of materials, construction, use, and decommissioning. Environmental concerns are related to the design of the road, the materials used in construction, and use patterns. In addition to addressing environmental and natural resource needs, the development of a sustainable road should focus on social concerns such as access (not just mobility), moving people and goods (not just vehicles), and providing people with transportation choices, such as safe and comfortable routes for walking, cycling, and transit. Three main cost categories are considered: (a) construction, maintenance, pavement upgrade and end-of-life costs; (b) vehicle operation, travel delay, social impact, and road accidents; (c) environmental costs such as noise, air quality, water quality, resource consumption, and solid waste generation.


The SAVi water model addresses sustainability issues relating to (1) water supply (e.g. surface and groundwater, including hydropower effects and diversions for irrigation), (2) water demand (e.g. losses in distribution and efficiency in the use of water) and (3) water management (e.g. water treatment and urban runoff and pollution). The model supports the analysis of Sustainable Urban Water Management options, addressing growing concerns over community well-being (rather than just public health), ecological health and sustainable development.

The impact

A more comprehensive methodology to quantify and monetize co-benefits, avoided costs and project risks of green vs. grey infrastructure.

 Across the different types of infrastructure, SAVi allows for a more robust stress-testing of projects by demonstrating that in the case of sustainable infrastructure, key variables that drive revenues, operating expenses and capital expenditures can be less volatile under a range of alternative scenarios. The additional risks modelled include climate risks (floods, freak weather, drought) leading to a reduction in resale value as well as risks related to the application of more stringent regulatory requirements on emission and waste.

Furthermore, SAVi allows for a more accurate estimation of sensitivities related to human health costs, volatile real estate prices, as well as support the assessment of the contribution of infrastructure to employment creation and productivity improvements. Short term side effects, such as disruptions during construction and operation due to low social acceptance of the project are also taken into account. These considerations are critical for the long term valuation and refinancing of the asset.

Policy-makers can use SAVi to appreciate the co-benefits and avoided costs of sustainable infrastructure as well as to justify spending on assets that may cost more to plan and build, but are more resilient during operation, maintenance and end of life decommissioning. Investors can use SAVi to understand how sustainable infrastructure is more resilient to a range of external risks and hence more bankable than traditional solutions.

The barriers to innovation – and the solutions

SAVi needs to demonstrate the business case for sustainable infrastructure, emphasizing different externalities depending on the stakeholder group addressed.

 Procurement regulations often do not allow procurers to materially deviate from the cheapest option when commissioning infrastructure. Thus the additional capital expenditure required for sustainable infrastructure can make the green alternative ineligible and / or hard to justify when making procurement decisions. A supportive legal and regulatory framework is needed for policy makers and procurers to assess projects by even going beyond a simple life cycle approach and also include other relevant environmental and social externalities.

The primary mandate of institutional investors, one of the main sources of infrastructure financing, is to allocate capital to projects with attractive risk-return profiles. Some of the externalities monetized by SAVi does not influence their asset allocation as these factors do not directly impact their bottom line. On the other hand, some of the externalities quantified can have a material impact on the bankability of investments, but are still not covered by the risk assessment of investors as they are either not aware of these risk and / or are not able to quantify them.

The way to overcome these barriers is to demonstrate the strong link between the financial viability of the project and the externalities measured by the SAVi Model. For policy makers, having a broader mandate than financial investors, the positive economic and social impact on their country / region should also be emphasized.

The way forward

Stakeholder participation is key.

 Key stakeholder groups need to be involved in the various stages of model development. Their involvement would ensure that SAVi is relevant for them, covering asset types and producing output, which can be easily integrated in their decision making processes. At the same time, their participation would build their trust in the robustness of the methodology and help them with interpreting the results. IISD is in the process of reaching out to beneficiary countries as well as setting up an investor advisory panel for SAVi.

To produce the most accurate output, the SAVi Model needs to be customized for each country and asset type. Collaboration of governments in the data collection is key, as the quality of the output depends on the quality of data used.

At the point of writing the framework model has been developed for buildings and energy infrastructure. Building on its experience in the development and implementation of the Sustainable Product Valuation Model in 2015, IISD is well placed to ensure the success of the SAVi Model and its utse at scale.