New Value Flows: Impact modelling and Financing neighbourhood retrofit, v0.1

Dark Matter Labs
Dark Matter Laboratories
11 min readJan 21, 2022

This is part of a series of Weeknotes as part of our TransCap x CivicValue x CommCap exploration. We have republished it here in our Provocations to spark a conversation on how we can rethink value flows in neighbourhood-level climate transitions.

Neighbourhoods are facing an imminent need to transition for climate change and deal with deep-seated issues of fuel poverty and other injustices. One of the most intractable challenges is the financial cost-benefit balance in undertaking a neighbourhood retrofit programme.

Under current conventional approaches, the comprehensive range of benefits and co-benefits projects generated are often unaccounted for, with the result being some projects being deemed (reductively) unviable investments, or worse, a liability. For example, as we have seen in our TreesAI project, urban trees are often seen as costs to municipalities, rather than value-creating natural assets, a logic that justifies trees being removed rather than nurtured.

Dark Matter Labs’ approach to the TransCap x CommCap project is based our working hypothesis, ‘Transitioning Together’, which aims to lay the framework of a system that puts streets and neighbourhoods in the driving seat of their climate transition, empowering residents to be able to sense-make, deliberate, implement, and access financing for their neighbourhood’s climate transition projects.

A fundamental part of our hypothesis is about rewiring value flows in order to make these community-driven climate transitions possible. This includes an alternative approach that attempts to account for a project’s benefits and co-benefits in a comprehensive, efficient and holistic way. This also includes wiring a project’s revenue and financing to its impact as a way of incentivising the maximisation of benefits.

While the community will be the primary beneficiary of climate transition, there will be other stakeholders/actors who too will co-benefit: such as public or philanthropic bodies who may have their liabilities reduced, nearby property-owners who may benefit from land value uplift, or local businesses that may benefit from revenue uplift. By putting in place mechanisms (e.g. Smart Covenants or outcome-buying contracts / social impact bonds) to capture these co-benefits, we would provide a long-term revenue source that can shift the cost-benefit balance in favour of doing these necessary projects, and also provide a framework for stakeholders to invest in outcomes-based preventative measures to reduce their liabilities (such as investing in housing retrofit, rather than spending on healthcare system costs for dealing with the health consequences of substandard, unhealthy homes).

The Transitioning Together model so far: revenues from captured co-benefits replenish a city-wide evergreen fund that funds community-driven climate transition projects.

Initial experiments in value modelling

As part of our work developing this model, Dark Matter Labs and Civic Square are engaging with the community of Link Road (in Edgbaston, Birmingham) as a pioneer community for this approach. Based on data from the tangible, real-world context of this neighbourhood in Birmingham, we have taken a first attempt at creating this value model that represents a climate transition project’s costs, comprehensive estimates of its various benefits and co-benefits, and also the potential for these co-benefits to be captured.

Some questions that are beginning to emerge from this work include:

  • Is this model based on rewiring value flows and capturing co-benefits viable for funding community-driven climate transition projects?
    In particular, we want to find out the approximate scale of the potential revenues that could derive from capturing co-benefits, and how they compare to the costs of a project.
  • Is it possible to quantify and model the comprehensive set of co-benefits being created by climate transition projects?
    For each type of climate transition project, it is necessary to develop an understanding of the types and quantities of (co-)benefits being generated, from the perspectives of the resident, a co-beneficiary, and an investor — is there enough research to allow this to be estimated, and how can we avoid double-counting?
  • How can qualitative co-benefits be accounted for in the model?
    While capturing co-benefits and outcomes requires some degree of quantification, how they are metricised and captured opens up a space for contestation. More critically, we are reflecting on how qualitative benefits can be factored into the model.
  • How do we model the value that is created beyond the projects themselves?
    Value created by such an approach can exist beyond the projects themselves: for example, the capacity a community develops and experience they gain after successfully implementing their first project can unlock further, more ambitious projects — this has ‘sequential’ value. The coexistence of multiple projects in a neighbourhood can also create a ‘systemic’ value that is greater than the sum of its parts. How can we account for these in the model?
  • Finally, are there any ethical risks of financialisation civic or public value, including any perverse incentives created by doing so? This work also represents a transition from a model of centralised state taxation and spending, where the creation of civic value, captured or not, is considered part of the state’s remit. While this model has both its opportunities and risks, we must also consider the new set of opportunities and risks by taking a more decentralised approach to civic value creation.

Value modelling approach

Diagram showing the components of the interactive value model.

The structure of our initial value model is set out in the diagram above: the model is designed to take several global inputs (e.g. assumptions on inflation, the investment horizon, base interest rate, etc.). The model also allows the selection of a portfolio of different types of civic assets and climate transition projects (e.g. home energy efficiency retrofit, urban agriculture, community-owned PV energy generation, etc.), and the scale of the project (e.g. number of homes retrofitted, m2 of gardens used for growing, m2 of PV panels, etc.). Based on these inputs, the model calculates for each civic asset/project:

  • Costs: This calculates the upfront and ongoing costs of building and operating the project, based on fixed costs and costs that scale per unit of the asset.
  • Impacts/benefits generated: This calculates the impacts generated over a comprehensive set of factors quantified in their natural units (tonnes of carbon emissions prevented and/or sequestered, health outcomes improved through no. of avoided hospitalisations/deaths, no. of employment opportunities created, litres of stormwater retained, no. of households brought out of fuel poverty, etc.) The calculations use assumptions based on local statistics and review of academic literature, and is part of our ongoing work to refine and test these calculation methods through further research.
  • Revenues: This calculates the revenues generated over a comprehensive set of factors quantified in the local currency (GBP) — this includes direct revenues such as one-off or annual grants, but also potential revenues from spillover value capture. The spillover capture calculation takes each benefit generated and identifies third party liability holders who may see potential liability reductions and therefore cost savings. A percentage of these estimated cost savings can be captured as a revenue source for the project, to be negotiated with these liability holders as potential ‘outcome buyers’ (for example, the local NHS Clinical Commissioning Group may pay for the outcome of reduced cold weather hospitalisations from home retrofit, based on a percentage of savings from costs of x fewer patients not going to A&E per year).

These cost, impact, and revenues calculations will then be aggregated across the entire portfolio, giving an idea of financing requirements and potential investment returns. We are still reflecting on how secondary value, such as the ‘sequential value’ and ‘systemic value’ described above can be incorporated into the model’s current working form. Double-counting remains challenging to disentangle, especially in areas such as the mutually linked nature of physical and mental health outcomes.

A version 0.1 of our model

We have created a first attempt of the model based on the logic above in a spreadsheet. The estimates for costs, impacts, and revenues in this version are ‘back of the envelope’ calculations based on common sense assumptions and high-level research we have done so far. This model will be further developed as part of our next stage of work, as the types of impacts modelled are expanded, and deeper research is done to quantify and predict these impacts with more rigour. We have tried to make this modelling as tangible as possible by basing the modelling on the real-world location of Link Road, Birmingham, where Dark Matter Labs and Civic Square are working with a group of residents to test this approach.

Main dashboard of the interactive model, with current work being done to replace placeholder figures with more research.

The main interface of the model is the dashboard, which gives an overview of the neighbourhood climate transition portfolio, and the whole portfolio’s estimated costs, impacts and revenues. The dashboard allows global inputs, such as investment horizon and the assumed annual inflation rate. The dashboard also allows different civic assets/climate transition projects to be included as part of the neighbourhood portfolio, and the scale of those assets (e.g. no. of homes retrofitted, m2 of urban agriculture, etc.). By changing these inputs to model different scenarios, the user of this modelling tool, whether it is the residents themselves or their advisors, can experiment and find an ideal portfolio of projects that work for their vision of their neighbourhood, and test its viability both in financial terms and the benefits/impacts the community is seeking.

Beyond the dashboard, each civic asset will have its own page with a more detailed breakdown of the capital and operating costs, its impacts and co-benefits, and also potential both one-off and recurring direct revenues (e.g. government grants/subsidies) and revenues from captured spillover values, with the calculated values updated based on the scale of the asset, and also global inputs. In this version 0.1 of our model, we have begun to build out these costs, impact and revenue models for an average home retrofit (up to EPC C rating), with the ambition to refine the model with more research and sophisticated modelling methods.

Financial modelling assumptions and findings:

The key assumptions on the cost side are:

  1. Cost per home of retrofitting the home: This is the most significant variable and will depend on characteristics and size of existing home, lifestyle of occupants, target improvement levels and the local supply chain. The literature appears to include a wide range of costs. Most helpful for Link Road are probably the actual average costs incurred through the BEIS supply chain pilots which were mainly undertaken on owner-occupied ‘early adopters’ seeking to do whole-house retrofits. This ended up costing in the region of £20-£25k per home. We acknowledge that some homeowners would be comfortable with improving to EPC C and including a low/zero carbon heat source such as an Air-Source Heat Pump (ASHP). Therefore we’ve assumed a total cost of around £20k per home for this work, but acknowledge that it could be more expensive.
  2. We have factored in operating/maintenance costs as a overall percentage of the capital costs, acknowledging that at regular periods and the end of the horizon (e.g. 30 years), the buildings and their retrofitted work may need to undergo periodic maintenance and upgrades. We hope to make this more granular depending on the type of intervention in future versions of the model.
  3. Our approach to deep retrofit beyond the individual house means we should consider improving the streetscape and open spaces as part of retrofit. In our model, we have treated public realm improvements as a separate civic asset. These costs tend to be modest in comparison with the domestic improvements.

Key assumptions on the revenue side:

  1. Energy savings are hard to quantify as again they depend on the home, occupants and selected level of comfort. We have used high-level government assumptions around improving to EPC level C saving around £220 per household per year. This could be an underestimate especially given rising energy costs. These can be capitalised at a suitable discount rate and a reasonable life-cycle of the elements installed to achieve these outcomes.
  2. Carbon emissions avoided are also based on the same government assumptions, approximately 1.69 tonnes of carbon per house per year. Although these emissions reductions are not all currently traded, there is a potential for this to be financialised beyond the existing ETS system — we have used the current (possibly underpriced) value of carbon in the UK ETS market as a conservative indication of a potential source of revenue. This is subject to change based on the carbon intensity of the grid, the price of carbon, and other regulatory changes in emissions trading.
  3. We have also started to estimate other outcomes. These include social outcomes (e.g. fuel poverty alleviation), health outcomes (e.g. excess winter mortality, respiratory hospitalisations), and environmental outcomes (e.g. reduction of NOx emissions), with more in the pipeline. These are high-level back-of-envelope estimations using data as specific to the context (Link Road / Birmingham / West Midlands / UK) as possible. We are also in the process of reviewing approaches of modelling precedents, such as the C40 Cities model, GMCA’s Unit Cost Database, or the UK Government’s HIDEEM model, as a way of informing our own modelling methodology.

Emerging findings & next steps

The model is preliminary and requires substantial development as part of the second stage of work. The following points are findings that are beginning to emerge.

  • Energy savings make the biggest contribution in the average household. This range could be around 15–30% of up front costs depending on capitalisation assumptions, modelled savings, lifestyle and poverty of household etc. At the time of writing, energy costs are rising and there is a general expectation that OFGEM will increase the tariff cap. Without further intervention this will result in greater fuel poverty, but will further strengthen the case for using energy savings as part of the model.
  • Carbon emissions savings (if traded) makes up around 10–20% of the up front capital if this can be realised. Alternative avenues beyond the ETS system should be considered as a way of realising the value of these emission savings.
  • The potential revenue from other spillover values such as health appear to be small based on the first tranche of research. However, we are seeing in some implemented projects, such as Warm Homes Oldham which is co-funded by the local public health service, where estimated savings to public healthcare are on a comparable scale to energy savings. This requires further exploration and verification and does not rule out the viability of capturing these spillover values when they are aggregated across neighbourhoods and considered at a city scale (as proposed by the Transitioning Together model). This means that the contractual, technological and other mechanisms to allow this value capture would have to be tested at a small scale, albeit with negligible returns, in order for this to be scaled. This would also help us understand if the returns on these values can be efficiently measured and distributed.

We are now entering the Strategic Design phase of the project. This has a number of strands. For the impact and finance workstream we will:

  • Refine and test the assumptions and modelling approach.
  • Improve our understanding of the scale at which different elements of the model would work best, both in terms of any internal cross-subsidy required, but also in terms of efficiency.
  • Shortlist the liability holders and commence discussions with them, to test the political viability of outcome contracting.
  • Build a legible, user-friendly model that can be used in engagement with residents and other stakeholders

We’ll be posting further updates of our progress as the work progresses. Stay tuned!

This blog was written by Calvin Po and Dan Hill. Tom Beresford and Jack Minchella are also a part of the TransCap x CivicValue x CommCap exploration. Raj Kalia has also developed the work on the ‘Transitioning Together’ hypothesis.

Sign up to discover human stories that deepen your understanding of the world.

Free

Distraction-free reading. No ads.

Organize your knowledge with lists and highlights.

Tell your story. Find your audience.

Membership

Read member-only stories

Support writers you read most

Earn money for your writing

Listen to audio narrations

Read offline with the Medium app

Published in Dark Matter Laboratories

Dark Matter Labs team works with partners, clients, and collaborators across the world, researching and developing new institutional support frameworks for collaborative system change.

Written by Dark Matter Labs

We are building options for the next economies.

No responses yet

What are your thoughts?