Auction-based pay-for-performance mechanism for greener housing

Context 

The Indian government has committed to reducing the emissions intensity of its GDP by up to 25% by 2030. Buildings are identified in its nationally determined contributions (NDC) as one of the key levers to achieve this goal. 

The World Bank identified India as a prospective case study to carry out a quantitative assessment of the potential impact of the mechanism due to its complex housing market, economic conditions and Federal structure. 

An economic cost-benefit analysis was conducted using the Excellence in Design for Greater Efficiencies (EDGE) green building software and cash flow modelling to assess the potential impact of a USD50m auction on the Indian market. 

Stakeholders involved 

• World Bank / Multilateral Development Banks (MDBs) 
• Ministry of Housing 
• Bureau of Energy Efficiency 

Problem 

• Despite the NDC identifying buildings as a key to reducing the emissions in India, there is a lack of national policies to incentivise green new builds.  
• More than 50% of urban infrastructure needed in India until 2030 including housing, energy, transport, water, and waste disposal are not yet built. 

Innovation 

• The World Bank developed the auction-based pay-for-performance mechanism to attract investment for projects aimed at reducing methane emissions. 
• This auction platform provides the minimum price private firms need to invest in emission reductions while maximising the impact of public funds and the volume of climate benefits for each dollar. 
• It provides price guarantees for future climate results which are determined by an auction. These price guarantees provide holders the right, but not the obligation, to sell future climate results to energy facilities at a predetermined price.  
• Funds are only disbursed once the climate results have been independently verified and there is a shared risk shared between the public and private sector for green investments 

Results and impact 

• India has no national policy that incentivises the development of new green buildings. As a result, the study assessed the potential impact of a USD50m auction budget to close the unfunded cost premium and found that such an incentive could lead to:  
  • Construction of 1.7 to 2.9 million m² of green building space,
  • Avoided carbon emissions ranging from 1.4 to 2.3 MtCO2 
  • Energy savings ranging from 1,400 to 2,100 GWh, 
  • Water savings ranging from 56 to 146 billion litres, and 
  • Lowering of the energy bills for 100,000 to 410,000 people. 

• The analysis also confirms that carbon and energy, savings on a per capita basis increase by income level: Assuming an auction of USD50m, the carbon savings (in million tonnes of CO2) for the low-income segment would be USD24 and USD37 for the high-income segment (based on the passive scenario). 

• Lower income segments are the best target for the auction mechanism. A USD50m auction would also create greater or equivalent total savings in the economy of the target country, largely benefitting the poorest citizens in the lower income segments. However, there is a trade-off between people supported and carbon saved, with low income supporting more people but lower middle income saving more carbon. 

Key lessons learnt

• Consumers in India are reluctant to pay extra for green buildings despite the associated household energy cost savings: Evidence indicated that greener buildings can reduce energy costs of low-income households by up to USD200 per year (5% of their total yearly spending on all goods and services). However consumers are reluctant to pay a premium for green buildings due to lack of trust in the purported bill savings of greener buildings. The proposed auction mechanism should also involve awareness raising initiatives to increase understanding of the financial benefits associated with green buildings among consumers, particularly in the lower income segments. 
• Funder priorities and housing markets will influence the selection of income segment and eligibility criteria: The choice of income segment to target, and how this influences the eligibility criteria, will depend on priorities of the funders of the auction mechanism and the characteristics of the housing market of the country in which it is implemented.