Sustainable Asset Valuation (SAVi) Tool
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This presentation describes the Sustainable Asset Valuation (SAVi) tool, developed by the International Institute for Sustainable Development
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Sustainable Asset Valuation (SAVi) Tool
- 1. INTRODUCING THE SUSTAINABLE ASSET VALUATION (SAVi) TOOL Delivering insight for investing in sustainable infrastructure
- 2. Infrastructure projects must consider carbon and environmental footprints, social cohesion, stewardship of natural ecosystems and the financial viability of projects. Infrastructure is an enabler, and hence it has to be sustainable. The Sustainable Asset Valuation (SAVi) tool assesses: ā¢ environmental, social and economic risks and externalities. ā¢ socio-economic benefits, such as employment, income generation and contributions to GDP.
- 3. Investors use a SAVi analysis to assess the impacts of improved sustainability on future cash flows and financial returns.Disclosure statements (e.g. carbon) Environmental, social and economic co-benefits. CSR, impact investing Governments use a SAVi analysis to assess value for money for public investments, and determine changes in government revenues and expenditure. How does ESG performance increase value for money for tax payers? Do sustainable assets trigger positive externalities? (e.g. higher GDP) Can sustainable infrastructure increase fiscal sustainability?
- 4. SAVi puts a financial value on risks and externalities that are not well understood and therefore ignored in traditional investment assessments. SAVi calculates the impacts of various risks and externalities on levelized costs, gross margins, net present value, internal rates of return and credit risk ratios.
- 5. Potential risks and externalities Physical/Environmental Higher global temperatures, rising sea levels, water shortages, water and air pollution, land degradation, extreme weather, biodiversity. Social/Political Currency inconvertibility, wage fluctuations, industrial action, war, terrorism, civil disturbance. Technological/Legal Environmental and social safeguards, troubleshooting experimental or emerging technologies. Consumer/Reputational Changing public opinion, industrial action, environmental disasters, human rights abuses. Economic Contribution to GDP, household incomes, carbon taxes, changes in feed-in tariffs, fluctuations in resources, access to land.
- 6. population wastewater wastewater treatment n loadings from wastewater + +- agriculture land urban area + + + fertilizer use + total loadings + +forest cover wetlands - - - - natural nutrient absorption + + - sedimentation / siltation - health impacts productivity economic activity / grp employment + + + + - tourists + + infrastructure + + - water quality- - water in lake dal - - + + precipitation + <population> - cross border inflow + R1 R2 B5 B8 B2 B1 B3 B6 B7 B4 SAViās systemic lense: The rationale ā¢ Systems Thinking (ST) demands the identification of the underlying drivers of change that determine the need for and adequacy of infrastructure (projects) in the respective local context. ā¢ Infrastructure-related risks and externalities are often āhiddenā and so are the costs associated with them. ST contributes to identifying āripple-effectsā of infrastructure projects across sectors and actors. ā¢ System Dynamics (SD) allows for generating different projections (using simulation) to explore and reduce investment-specific uncertainties. Among all projects there is the necessity to identify opportunities and risks that affect asset performance and maintenance in the long run. Therefore, the asset must be regarded as part of the system rather than in isolation.
- 7. green gdp gdp natural capital additions + consumption demand of natural resources natural capital + + natural capital growth +natural capital extraction natural capital depletion natural capital reductions + + + - + ecosystem services productivity (tfp) + + + infrastructure (built capital)+investment depreciation + + + ecological scarcity - - human capital social capital (employment) job creation + retirement public expenditure health education human capital growth training + + + + + <human capital growth> + private profits + + + wages + + + + R R R R R B B GDP The green arrows show the impact of Natural Capital Stock on Productivity and GDPā¦ The yellow arrows show the impact of Consumption on Natural Capital and GDPā¦ The red arrows show the impact of Infrastructure Investments on GDPā¦ A View of the System Dynamics Model on Vensim
- 8. A snap shot of the project finance model built on Excel, following Corality SMART Methodologies
- 9. SAVi application to infrastructure We assess impacts across: - Dimensions of development - Sectors - Economic actors - Over time - In space Method: integrated cost benefit analysis
- 10. SAVi application to infrastructure We assess impacts across: - Dimensions of development - Sectors - Economic actors - Over time - In space Method: integrated cost benefit analysis
- 11. SAVi application to infrastructure We assess impacts across: - Dimensions of development - Sectors - Economic actors - Over time - In space Method: integrated cost benefit analysis
- 12. Fishing Water quality Forest Agriculture Population Tourism Biodiversity Employment Culture, education GDP Population 80,000 60,000 40,000 20,000 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) Person Population : Bita 28Aug - BAU Population : Data total value added 400 B 300 B 200 B 100 B 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) Pesos/Year total value added : Bita 28Aug - BAU total value added : Data Biodiversity 1.098 1.023 .9489 .8744 .8 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) Dmnl Biodiversity : Bita 28Aug - BAU fallow / Forest Land 247,000 246,500 246,000 245,500 245,000 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) Ha "fallow / Forest Land" : Bita 28Aug - BAU "fallow / Forest Land" : Data water quality index .9 .85 .8 .75 .7 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) water quality index : Bita 28Aug - BAU Agriculture Land 3000 2250 1500 750 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) Ha Agriculture Land : Bita 28Aug - BAU Agriculture Land : Data Governance 0 -.075 -.15 -.225 -.3 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) Dmnl Governance : Bita 28Aug - BAU ornamental fishing 35.04 31.28 27.52 23.76 20 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Time (Year) Ton/Year ornamental fishing : Bita 28Aug - BAU SAVi application to infrastructure
- 13. Fishing Water quality Forest Agriculture Population Tourism Biodiversity Employment Culture, education GDP SAVi application to infrastructure
- 14. SAVi application to infrastructure We assess impacts across: - Dimensions of development - Sectors - Economic actors - Over time - In space Method: integrated cost benefit analysis A B Total avoided costs and benefits (A+B+C) Societal avoided costs and benefits (B+C) Firm avoided costs and benefits C Direct cost reduction for public budget items (e.g. health) Total investment
- 15. SAVi application to infrastructure We assess impacts across: - Dimensions of development - Sectors - Economic actors - Over time - In space Method: integrated cost benefit analysis
- 16. SAVi application to infrastructure We assess impacts across: - Dimensions of development - Sectors - Economic actors - Over time - In space Method: integrated cost benefit analysis
- 17. Integrated CBA A B C Traditional CBA (capital, O&M, fuel and carbon tax) including SAVi estimates on the impact of climate change on thermal efficiency and fuel costs. Positive and negative externalities related to each technology analyzed. Summary of costs and benefits, estimation of the SAVi CBA. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Wind (off) Coal Gas Nuclear Biomass Hydro Solar Wind (on) Capital and O&M cost -58,454 -25,273 -5,886 -44,035 -25,273 -33,515 -44,452 -40,286 Fuel costs - -20,991 -49,925 - -48,550 - - - CC impacts on fuel costs - -692 -1,722 - - - - - Carbon tax - -9,196 -4,073 - - - - - Subto tal (1) -58,454 -56,153 -61,605 -44,035 -73,824 -33,515 -44,452 -40,286 Income spending 1,230 724 550 916 3,119 877 2,876 1,073 Defense payments -15 - - - - - - - Fisheries -13 - - - - - - - Sand mining -28 - - - - - - - Recreation -238 - - - - - - - Real estate - - - - - - - - Land use 4,111 -1,488 -88 -198 -614,800 -25,026 -13,528 -1,276 Waste management - - - -13,900 - - - - Social Cost of Carbon -281 -14,635 -6,567 -150 -174 -100 -438 -448 Valuation of emissions (SAVi+) - -89,128 -26,746 -65 -17,573 - - - Value o f externalities 4,765 -15,399 -6,106 -13,333 -611,854 -24,249 -11,090 -651 Subto tal (1 + 2) -53,689 -71,552 -67,711 -57,368 -685,678 -57,764 -55,542 -40,937 R evenues 52,440 52,440 52,440 52,440 52,440 52,440 52,440 52,440 Costsand Benefits -1,249 -19,112 -15,271 -4,928 -633,238 -5,324 -3,102 11,503
- 18. Current applications Clients include: The Ministry of Infrastructure and Water Management of the Netherlands, the Directorate of Tourism of Jammu & Kashmir in India, UN Environment, WWF, the Moroccan Road Agency, and the Senegalese Government Agency for the Implementation of the Plan for an Emerging Senegal.
- 19. Interested in alternative scenario?
- 20. Contact us today to find out more about how SAVi can help you Oshani Perera, operera@iisd.org Andrea Bassi, andrea.bassi@iisd.net Georg Pallaske, georg.pallaske@iisd.net
Notas do Editor
- System dynamics (SD) is a flexible methodology that allows to integrate social, economic and environmental indicators in a single framework of analysis. SD models are based on the assumption that structure drives behaviour and use causal relationships to link variables. Models can be customized to analyse the socioeconomic implications of different actions across sectors (social, economic and environmental) and actors (e.g., households, private sector and the government), within and across countries. In fact, SD models can be top-down or bottom-up, general or partial equilibrium. The pillars of SD models are feedback, delays and non-linearity. The former are identified through the creation of causal maps, or Causal Loop Diagrams (CLD) ā like the one shown above. A CLD has several purposes: (1) it brings the ideas, knowledge and opinions of the participants together; (2) it highlights the boundaries of the analysis; (3) it allows all stakeholders to reach a basic-to-advanced knowledge of the systemic properties of the issues analysed. Having a shared understanding is crucial for solving problems that touch upon several sectors, or areas of influence, which are normally found in complex systems (Sterman, 2000; Rouwette & Franco, 2014). Delays and non-linearity are captured through the creation of a quantitative model, which includes stocks and flows.
- IISD has developed a full fledged project financial model, following Corality Smart Financial modelling methodologies, to evaluate the financial viability of infrastructure projects and to assess the financial materiality of the externalities identified by SAVi. The project finance model demonstrates the following: How the financial viability of the project changes if externalities are integrated in the model as costs. How the key project finance indicators (internal rate of return, credit ratios) change under various climate risk scenarios (both physical and transitional).