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Modelling a green recovery for housing

This week the New Economics Foundation has published its proposed green recovery package for housing, which we co-authored with Donal Brown of the University of Leeds.

To deliver minimum SAP C by 2030, the New Economics Foundation identified a package of measures that would cost the taxpayer £8.66bn for four years, to:

  • unlock a cumulative total of around £71.95bn of private capital investment
  • deliver 1.58% higher annual GDP (or £36.34 billion in 2020 prices) than otherwise expected in 2023/24
  • deliver deep retrofits to 8.69m UK homes
  • save an average £418 on the energy bills for those homes
  • create 117,811 new direct jobs in year one, rising to 382,885, in year four
  • create 515,157 jobs when factoring in indirect employment
  • save an estimated £0.42 for the NHS for every £1 spent retrofitting fuel-poor homes
  • reduce emissions by approximately 19.23MtCO2/year by 2023/24, or 21% of 2019 emissions from the UK’s homes.
  • This is a cumulative 40.9 MtCO2 by 2023/24, meaning this policy proposal alone could surpass the UK’s fourth carbon budget targets.

The proposals trailed for the summer Budget fall short of this proposed stimulus, but equally they only cover £3billion of the £9.2 billion manifesto commitment, and there is a suggestion that there is more to come. And more does need to come.

A model for a green recovery

Parity Projects role in the report was the use of its Policy tool to identify the opportunities for retrofit in the UK’s homes, and the optimal pathway to deliver that decarbonisation as a result.

The tool can be used to test the impact of any policy options on the carbon emissions and risk of fuel poverty in the UK’s homes.

Clients are asked to provide their scope and related assumptions, such as:

  • Targets: carbon emissions, SAP, and/or fuel bills
  • Maximum cost per home or the whole policy cost
  • Test our 2400 options for improvements, or
  • Specify a list of measures, or
  • Specify measures to be excluded
  • Set a target year so we can apply the relevant BEIS/National grid projections for grid decarbonisation
  • Specify assumptions on the future cost or future performance of measures, or use our current market-tracking dataset
  • Set out assumptions on the impact of different policy interventions on the uptake of individual measures or the programme as a whole

Given these, we model either how targets can be delivered in terms of costs and most cost-effective measures across the housing stock; or we can identify how far a cost-limited programme will get you towards that target, still applying our least-cost pathway tests.

If you have a package of policies to test against a national sample of homes, please get in touch. There is no single answer, we need to be on a journey of continuous learning and improvement, but we know the Government’s current answer falls short of what is required.