Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings January 2018 Study on Using the Climate Auction Model to Catalyse Energy, and Resource Efficient Buildings January 2018 © 2019 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The Pilot Auction Facility is an innovative, pay-for-performance mechanism by the World Bank Group to stimulate investment in projects that reduce greenhouse gas emissions while maximizing the impact of public funds and leveraging private sector financing. The findings, interpretations, and conclusions expressed by World Bank Staff or external contributors in this work do not reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. 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Contents List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Definition of green buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Country and sector analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii Cost-benefit analysis of the potential auction in India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii Auction proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Pilot Auction Facility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Project overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Definition of Green Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Definition of resource efficient buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1  2.2 Metric selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Assessment of certification schemes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3  3 Country and Sector Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2 Geographical targeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.3 Sectorial targeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.4 Participant targeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4 Cost-Benefit Analysis of Potential Auction in India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.2 Cost-benefit analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 iv Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings 5 India Residential Housing Sector Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 5.2 India certification summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 5.3 Building policy review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 India building value chain and bidder identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 5.4  6 Auction Proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 6.1 Eligibility criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 6.2 Preparatory steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 6.3 Eligible participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 6.4 Disbursement of options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 6.5 Other criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Process for replication of the auction in other geographies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 6.6  7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 List of Abbreviations Abbreviation Meaning AFD Agence Française de Développement BEE Indian Bureau of Energy Efficiency BREEAM Building Research Establishment Environmental Assessment Method ECBC Energy Conservation Building Code EDGE Excellence in Design for Greater Efficiencies EE Energy Efficiency ESMAP Energy Sector Management Assistance Programme GRIHA Green Rating for Integrated Habitat Assessment LEED Leadership in Energy and Environmental Design IFC International Finance Corporation IGBC Indian Green Building Council KfW Kreditanstalt für Wiederaufbau MRV Monitoring, Reporting, and Verification NDC Nationally Determined Contribution PAF Pilot Auction Facility RISE Regulatory Indicators for Sustainable Energy SWH Solar Water Heater UNDESA United Nations Department of Economic and Social Affairs WRI World Resources Institute Executive Summary Introduction should be modelled percentage reduction in energy consumption per unit area versus a local benchmark. The Pilot Auction Facility (PAF) is an auction-based This is because the housing sector already uses unit pay-for-performance mechanism that was originally area (usually square meters) as the basic input to developed by the World Bank to attract investment to assess projects, making an auction mechanism easy projects that reduce methane emissions.1 The purpose to understand and thus more likely to succeed. of this study was to assess whether the PAF climate Energy, consumption is also directly linked to carbon auction model could be translated effectively to the emissions from buildings, providing a direct link to residential new building sector. climate change mitigation. A qualitative review of six countries2 was carried An assessment of three global and five national green out to inform the basic conditions that would need building certification schemes4 was then carried out to be met for the climate auction mechanism to be to identify which would be the most suitable to be successfully rolled out to the residential building used as the benchmark scheme for the purposes of sector. India was then selected as a case study to carry the auction. Each scheme was evaluated across four out a quantitative assessment of the potential impact categories: of the mechanism.3 1. Uptake: What is the scheme’s geographical coverage? How many certifications have there Definition of green buildings been to date? Green building definitions were reviewed to establish 2. Relevance: Is there an energy/emissions focus? the metric upon which the auction should rely to Does it apply to new-build construction? Does it assess bids and award the climate auction’s incentive. apply to residential buildings? It was concluded that the auction mechanism should use metrics that are relevant, credible, simple, 3. Cost: What is the certification price? What is the practical, and global: as such, the primary metric administrative burden? 1 https://www.pilotauctionfacility.org/ 4. Metrics: Does the scheme generate quantitative 2  Argentina, India, Indonesia, Mexico, South Africa energy/emissions reduction estimates? Is and Vietnam. ongoing monitoring and verification (M&V) 3  The choice of India as a case study country is by no required? means an indication of a preferential positioning of the country vis a vis others for the initial implementation of the auction mechanism. The ultimate decision on when, where, and how to implement the mechanism will depend upon discussions between the World Bank, potential programme 4  BREEAM, EDGE, Greenships, Greenstar SA, GRIHA, funders, and other relevant stakeholders. IGBC, LEED, LOTUS. viii Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Excellence in Design for Greater Efficiencies (EDGE) In terms of sectoral targeting, income level was found achieved the best scoring against each criterion. It was to be the most salient dimension, which incorporated therefore recommended that the EDGE scheme could other considerations such as building type. Four be adopted as the default certification scheme for an income segments (low, social housing, middle auction, but that any schemes able to demonstrate income, and high income) were assessed against their alignment with EDGE in terms of quantitative five criteria of relevance to the auction mechanism estimates of energy savings and third-party auditing (potential for poverty reduction, potential for carbon of such savings should also be accepted. reduction, readiness of the green supply chain, competitiveness and complexity of the housing value chain, and additionality of the auction mechanism). Country and sector analysis Middle income stood out as a priority, while low income presented the greatest challenges, with social This phase of the study sought to answer a number of housing and high income in the middle. The middle- key questions regarding the translation of the climate income segment has the best balance across all auction mechanism to the building sector. These were indicators. distributed across three key elements: Finally, in terms of participant targeting real estate 1. Geographical targeting: Where could an auction developers were identified as the most suitable target be implemented (e.g., single city, whole country, bidders for the auction. This is because they will have or some other geographical boundary)? ownership of the crucial design and engineering segment of the value chain, which is when decisions 2. Sectoral targeting: What factors are likely to that will determine the “greenness” of a building are be important for an auction (e.g., income level, made. building type)? 3. Participant targeting: Who is likely to be bidding into the auction (e.g., real estate developers, Cost-benefit analysis of the construction companies, project aggregators)? potential auction in India India was chosen as a case study to carry out a In terms of geographical targeting, UN population quantitative assessment of the potential impact of the data showed that the vast majority of future auction mechanism. This assessment was carried out population growth and thus housing demand will using the EDGE online modelling tool and cash flow come from large (300k+ inhabitants) cities. Based analysis. on this data, the most relevant target for the auction mechanism is large cities in middle-income countries. While the Indian government has commited to This produced a list of six target countries. reducing emission intensity by up to 35% on 2005 levels by 2030, and buildings are mentioned in the A policy review of the six target countries also Nationally Determined Contribution (NDC) as one showed that testing the auction mechanism at the of the key levers to achieve this goal, no explicit level of a single city or state within a single country, mention is made of building specific targets, and no or multiple cities within the same country at most, national policies exist that incentivise green new build gives the highest chance of success. This is because (UNFCCC, 2015). political responsibility for housing is usually devolved at the state or even municipal level, and also It was found that using a combination of low cost, because in larger countries climatic variation would passive measures which meet EDGE’s minimum make comparing bids nationwide more complicated5 20/20/20 threshold,6 the currently unfunded green (equally costed bids might deliver widely divergent cost premium of green buildings would vary between water savings in dry versus wet areas, for example). 3 and 8% of construction costs, and 17 to 29 USD/m2, with the lower-middle-income segment having the lowest premium and the high-income segment having the highest. 5  While there is nothing that would prevent an auction being piloted at the national level, state-level deployment would be simpler and as such maximise the chances of success. National level scale-up could follow the initial pilot 6  20% energy savings, 20% water savings, 20% embodied demonstration. energy savings against a local benchmark. Executive Summary ix Based on this, a USD 50 million auction could while guaranteeing a minimum level of energy and potentially expect to catalyse 1.7 to 2.9 million m2 of carbon savings and poverty reduction. green building space,7 delivering between 1.4 and 2.3 MtCO2 of carbon savings, 1,400 to 2,100 GWh of 1. The financial incentive should be awarded to energy savings, 56 to 146 bn litres of water savings, bids putting forward the lowest price per square while reducing energy bills for 100,000 to 410,000 meter and achieving a minimum performance people. The highest carbon, energy, and water savings improvement of 20% in energy use, water use, would be in the lower-middle-income segment, while and embodied energy over the local baseline (as the highest number of people supported would be in per EDGE criteria). Equivalent local certifications the low-income segment. should also remain eligible should they be able to demonstrate to the auction host they are using a A USD 50 million auction would also create greater comparable process. or equivalent total savings in the economy of the target country, largely benefitting the poorest citizens 2. Bids should only be accepted from developments in the lower income segments. This would be highly expecting to sell housing units at or below a dependent on the discount rate, but at 10%, up to given price to ensure that developers targeting 60 million USD in energy savings could be created, the higher income segments of the population are while with no discount rate, the savings would not subsidised—this should be aligned with the amount to USD 250 million. considered government definitions of housing affordability. The auction could also support an awareness raising effort to increase understanding of the financial 3. There should be no limitation on which type benefits associated with green buildings among of entity is allowed to bid; however, proposed Indian consumers, particularly in the lower income developments should have secured land rights segments. before being allowed to bid. The quantitative analysis confirms that the lower 4. Overall, real estate developers and housing income segments are the best target for the auction associations represent the main target for a mechanism. However there is a trade-off between potential auction and should be targeted by people supported and carbon saved; targeting the awareness raising and promotion efforts. low-income segment supports more people but the lower-middle-income segment offers more carbon The option to receive the financial incentive should savings. be awarded when the preliminary certification is achieved, after the design phase. In line with the results-based principle of the climate auction model, Auction proposal the actual payment would be disbursed upon confirmation of certified status by a third-party The overarching aim of a potential auction should auditor at construction completion. be to keep the mechanism as simple as possible to maximise chances of success. Based on the analysis Eligibility criteria could be extended or altered to described in this study, four main eligibility criteria meet funder requests or World Bank priorities, but it have been identified. These are mostly focused on is recommended that these are only considered after ensuring that the process is kept simple for bidders, an initial run of the mechanism in the housing sector has proven successful. Different weightings could be applied to savings, or the focus could be directly on a particular kind of savings, such as carbon or energy. Other criteria 7  Large developers such as Tata Housing, DLF, or VHBC which could be considered include poverty reduction might have up to 7 million m2 under construction at any criteria, an urban density/proximity to city centre point in time, while medium sized ones such as 3C or VGN criterion, a vulnerability to extreme weather event, or could have 2–3 million m2. a waste management criterion. Acknowledgments The Carbon Trust would like to thank the Pilot ▲▲ World Bank India (Shruti Narayan) Auction Facility team at the World Bank for funding this study and to the wider World Bank panel for ▲▲ Manipal University (Professor Pradeep G. Kini) their contributions to this report: ▲▲ Carbon Trust Colleagues Pilot Auction Facility (Scott Cantor and Tanguy De ▲▲ Bienassis) ▲▲ UK Green Building Council ▲▲ ESMAP (Energy, Sector Management Assistance Programme) (Martina Bosi) We would also like to express our gratitude to those that were interviewed as part of the consultation for ▲▲ International Finance Corporation (Autif this project. Mohammed Sayyed) ▲▲EDGE (Corinne Figueredo and Prashant Kapoor) 1Introduction 1.1 Pilot Auction Facility The analysis sought to identify the key dimensions that should be considered when translating the The Carbon Trust has been commissioned by the auction mechanism to the building sector. This World Bank to carry out a study to understand how included defining what a green building is for the a climate auction model based on the Pilot Auction purposes of the auction and which metric should Facility (PAF) could be used to catalyse energy, and be used to award the subsidy; carrying out a resource efficiency in the residential building sector, prioritisation exercise to assess which dimensions focusing on new build developments. (such as geography, sector, and building type) would have the most impact on the success of the The PAF is an auction-based pay-for-performance mechanism; and understanding the type of bidders mechanism that was originally developed by the who would likely participate. World Bank to attract investment to projects that reduce methane emissions. According to the World In the second phase of the study, India was selected Bank, the auction platform provides a transparent as a case study to carry out a more in-depth analysis means for allocating and determining the value of a of the potential implementation of the potential financial incentive that private firms need to make auction. The Carbon Trust quantitatively analysed investments in emission reductions. The competitive the financial implications of the auction mechanism nature of the auction reveals the minimum price considering different income groups, different required by the private sector to make emission climatic zones, and different green building scenarios. reduction investments, therefore maximizing the The analysis provided data on the incremental impact of public funds and achieving the highest construction cost premium for green buildings, the volume of climate benefits per dollar. potential emissions reductions associated with the mechanism, and the number of people supported. The first phase of this study analysed the potential This analysis was used to derive minimum eligibility geographies, markets, and sectors that could benefit from criteria and preparatory steps which could be used by the climate auction model. The second phase developed the World Bank or another funder as a “blueprint” to a proposal to implement the mechanism and explored introduce the mechanism to the residential building the financial costs and benefits of the intervention. sector in India and other countries. It is important to note that the selection of the six 1.2 Project overview countries does not represent a commitment by the World Bank to implement the auction mechanism The first part of the study looked at a selection of in any of those countries. The ultimate decision countries which could provide an analytical basis of whether, where, and when to implement the to test how the auction could work in practice. Six mechanism will be taken up by the World Bank markets were selected (Argentina, India, Indonesia, or another funder in consultation with all relevant Mexico, South Africa and Vietnam) based on a stakeholders and in due course. number of criteria, including residential energy, use, projected building growth, and carbon intensity. 2 Definition of Green Buildings To qualify for the auction mechanism, residential The auction mechanism should use metrics that are developments will need to be constructed to a verified relevant, credible, simple, practical, and global: green buildings standard. This section defines what green buildings are in the context of the potential ▲▲ Relevant: Metrics should reflect the goal to reduce auction mechanism, identifies the key performance CO2 emissions and reduce poverty, and should metrics and criteria that need to be assessed, and therefore primarily focus on emissions or energy. analyses the main certification schemes that could be used by the mechanism to assess and verify buildings’ ▲▲ Credible: Metrics needs to be able to robustly eligibility. demonstrate the auction’s impact. They must therefore be based on sound methodologies and solid evidence, and quantitative if possible. Definition of resource 2.1  ▲▲ Simple: For the auction to gain traction, efficient buildings metrics need to be easy to understand by its There is no universally agreed definition of green or target audience. They should be familiar to the resource efficient buildings, with different definitions construction industry, and a single metric is incorporating different green themes (e.g., energy, preferable to multiple. emissions, water, waste, biodiversity, air quality) and building life cycle stages (e.g., design, construction, ▲▲ Practical: Metrics need to be straightforward and operation, demolition, and renovation). Some sample low cost to measure. Metrics should not require definitions by relevant institutions are provided significant post-construction monitoring and in Table 1. Agreeing on a precise definition in the verification. context of the climate auction is important because it will form the basis for selecting metrics to evaluate ▲▲ Global: For the auction to be fully scalable, metrics building projects and award financial incentives. should be applicable globally—but also able to reflect local contexts. As such, we recommend that the auction 2.2 Metric selection mechanism’s primary metric should be modelled A wide range of qualitative and quantitative metrics percentage reduction in energy, consumption per exist for different green themes and building life cycle unit area versus a local benchmark, i.e., a green stages, some examples of which are summarised in building certification. Table 2. 4 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Table 1: Definition of green buildings Institution Green building definition World Green A green building is a building that in its design, construction, or operation reduces or eliminates negative Building impacts, and can create positive impacts, on our climate and natural environment. Green buildings pre- Council serve precious natural resources and improve our quality of life US EPA Green building is the practice of creating structures and using processes that are environmentally respon- sible and resource efficient throughout a building’s life cycle from siting to design, construction, operation, maintenance, renovation, and deconstruction. This practice expands and complements the classical build- ing design concerns of economy, utility, durability, and comfort. Green building is also known as a sustain- able or high performance building USGBC . . . the planning, design, construction, and operations of buildings with several central, foremost consider- ations: energy use, water use, indoor environmental quality, material section, and the building's effects on its site Sustainable . . . green buildings are structures that are sited, designed, built, renovated, and operated to energy-­ Build efficient guidelines, and that will have a positive environmental, economic, and social impact over their life cycle EU DG Resource efficiency in the context of moving toward more sustainable buildings is understood as the Environment broad concept aiming to reduce resource use and limit the environmental impacts from buildings through- out their life cycle—from material extraction for use in the construction phase, through resource use dur- ing occupancy and maintenance, to material recovery at demolition Table 2: Example of green building metrics Green themes Energy Emissions Water Waste Other Design • Modelled • Modelled CO2e • Modelled • Incorpo- • Incorporation energy, con- emissions per water con- rate waste of biodiversity sumption per unit area sumption per minimisation measures unit area • Use of low- unit area strategies for • Use of energy, emissions • Use of water construction efficient equipment efficient and demolition equipment or equipment low-carbon generation Construction • Energy, • Embed- • Measured • % of construc- • Minimiza- intensity of ded CO2e in water usage tion waste to tion of social Life cycle stage construction construction per day landfill impacts (noise, processes materials (directly disruption, etc.) • Sustainability abstracted and of construction mains) materials Operation • Actual metered • Actual CO2 • Actual metered • Actual waste • Evidence of energy, con- emissions per water con- generated per sustainability sumption per unit area sumption per person codes and unit area unit area • Recycling practices levels Demolition & • Energy, inten- • Life cycle • Measured • % of demoli- • Site reme- renovation sity of demoli- assessment water usage tion waste to diation and tion processes of embedded per day landfill restoration CO2 in materi- (directly als (linked to abstracted and waste) mains) Definition of Green Buildings 5 The following section will provide more detail schemes use a variety of different approaches to on global building certification schemes and their determine the overall green rating of a building. Eight applicability to the auction mechanism. certification schemes were shortlisted and assessed in detail to determine their applicability to the auction mechanism. Assessment of certification 2.3  Assessments covered four themes, as summarised in schemes Table 4. Certification schemes were rated against each There are a large number of certification schemes theme on a red/amber/green scale according to their around the world that assess the performance of applicability to the mechanism. buildings against a given set of green criteria. These Table 3: Summary of certification schemes assessed Scheme Summary BREEAM is a holistic sustainability assessment method that can be applied to multiple building types. Founded in the UK in 1990, it was the world’s first sustainability assessment method for buildings. EDGE was set up in 2013 by the IFC as an output-based certification tool. EDGE uses an online soft- ware platform to estimate the performance of a building against a local baseline. The software calculates the financial viability of a green project. Greenship rating system is a holistic sustainability assessment method that can be applied to multiple building types. The scheme was established by the Green Building Council of Indonesia. Green Star SA is a scheme used in South Africa, based on the Australian Green Star scheme. The scheme was managed and designed by the South Africa Green Building Council. GRIHA is a green building rating scheme used in India for new buildings over 2,500 m2 focused on the full life cycle of a building. GRIHA was developed by TERI. IGBC rating system is a holistic sustainability assessment method that can be applied to multiple build- ing types. IGBC Rating Systems was established by the Indian Green Building Council and has replaced LEED in India. LEED is a widely used holistic sustainability assessment method that can be applied to multiple build- ing types. LEED was formed by the US Green Building Council in 1994. LOTUS is a holistic sustainability assessment method that can be applied to multiple building types. LOTUS was formed under the Vietnam Green Building Council. 6 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Table 4: Assessment themes and questions Theme Questions Considerations Uptake • What is the scheme’s geographical coverage? Global coverage is desirable but not essential. • How many certifications have there been to date? Number of certifications gives a sense of a scheme’s traction. Relevance • Is there an energy/emissions focus? Schemes need to align with all three areas of rel- • Does it apply to new build construction? evance. Partial alignment may be acceptable (e.g., if • Does it apply to residential buildings? schemes apply to residential buildings but only over a minimum size). Cost • What is the certification price? Ideally schemes will be cheap and require minimal • What is the administrative burden? administration. Schemes that are both expensive and time consuming should be avoided if possible. Metrics • Does the scheme generate quantitative energy/ Quantitative reduction estimates are essential. Some emissions reduction estimates? degree of ongoing M&V is acceptable, but not if it • Is ongoing monitoring and verification (M&V) extends over multiple months or years. required? Table 5 provides a summary of the assessments. across the four themes, which suggests they could be considered for the auction mechanism in The only certification scheme to be rated ‘green’ for certain circumstances. The remaining four schemes all four themes is the IFC’s EDGE scheme. EDGE (BREEAM, Greenships, GreenStar SA, and LEED) was launched by the IFC in 2013 to specifically target were rated ‘red’ for one or more theme, which emerging markets, given the greater focus of existing suggests they should not be considered for a climate schemes on developed countries (Kapoor, 2014). auction. EDGE provides a freely available software modelling tool which can be used by developers to estimate the We therefore recommend that the EDGE scheme potential savings of their building. Three categories could be adopted as the default certification of savings are included: energy, savings, water scheme for the auction, but that any schemes able savings, and embodied energy, in materials savings. to demonstrate their alignment with EDGE in the Achieving a 20% reduction of all three against a local following key areas should also be considered: benchmark means the project achieves the minimum EDGE Certification. At construction completion, a ▲▲ Minimum performance criteria of a 20% reduction third-party auditor confirms that the building has across energy, consumption, water consumption, incorporated the measures listed in the design phase and embodied energy and assigns the certification. ▲▲ Requirement for quantitative estimates to be Three other schemes (GRIHA, IGBC and LOTUS) validated by a third-party auditor were rated a combination of ‘green’ and ‘amber’ Table 5: Certification scheme assessment summary Uptake Relevance Cost Metrics Summary assessment* Generates Energy/ Applies quantitative Requires Geographical Number of emissions to new Applies to Admin reduction ongoing coverage certifications focus? build? residential? Price burden estimates? M&V? Uptake Relevance Cost Metrics BREEAM Global 561,270 Y Y Y H M N N G G A R EDGE Global >100 Y Y Y L L Y N G G G G Greenships Indonesia 41 Y Y Min. L H N N A A A R 2,500 m2 Greenstar South Africa 304 Y Y Multi-unit H H N N A A R R SA only GRIHA India 650 Y Y Min. L H Y N A A A G 2,500 m2 IGBC India 4,077 Y Y Y L H Y N A G A G LEED Global 80,000 Y Y Y H H Y N G G R G LOTUS Vietnam 12 Y Y Y L H Y Y A G A A *Explanation of colour coding: Green = scheme is fully applicable to the auction mechanism; Amber = scheme is partially applicable to the mechanism; Red = scheme is not applicable to the mechanism. Definition of Green Buildings 7 3Country and Sector Analysis 3.1 Introduction To provide a sensible boundary for the research, six countries were selected based on a number of This phase of the study sought to answer a number criteria. The research included both literature review of key questions regarding the translation of the and stakeholder consultation in each of the selected auction mechanism to the building sector. These were countries. Finally, a single country was chosen to act distributed across three key elements: as a more in-depth case study to carry out a cost- benefit analysis of the potential auction mechanism. 1. Geographical targeting—where should the auction be implemented. A single city, a whole As stated before, the selection of a number of country, or some other geographical boundary countries does not imply a formal endorsement on the part of the World Bank of any of those countries 2. Sectoral targeting—what factors are likely to for implementation of the auction mechanism at this be important for the auction, e.g., income level; stage. building type (single family homes, multifamily) 3. Participant targeting—who is likely to be bidding into the mechanism. Real estate developers, 3.2 Geographical targeting construction companies, project aggregators. Following an assessment of over 40 countries, the following countries were selected for review: The analysis also sought to identify additional criteria Argentina, India, Indonesia, Mexico, South Africa beyond energy and carbon savings and poverty and Vietnam. The assessment criteria are summarised reduction which might be added as eligibility criteria in Table 6, below. to the auction mechanism. Table 6: Country selection criteria Sufficient market size Population growth projections Growth of total building stock and proportion that will be green buildings Additionality of auction intervention Presence of green building policies Listing of buildings in Nationally Determined Contributions Existence of green building supply chain World Bank Regulatory Indicators for Sustainable Energy (RISE) Domestic green building certification Likelihood of success for auction mechanism Existence of World Bank operations in the country Ease of doing business rankings for real estate 10 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings A subset of the geographical targeting analysis housing market, large variation in economic consisted in identifying which of the six countries conditions, and federal structure allowing for presented the best characteristics to act as a case study political analysis at different levels. for a more in-depth analysis of the potential costs and benefits of the proposed auction mechanism. The key Drawing from UN population data, we were able to criteria used are listed in Table 7. conclude that the vast majority of population growth and thus demand for new residential buildings will Each of the six countries was assessed along those take place in rural areas in lower- and upper-middle- dimensions. The process was primarily qualitative, income countries (UNDESA, 2015). Across all income relying on literature review and expert consultation. segments, the global urban population will grow by more than one billion 2016–2030, while the rural Based on our assessment, two countries scored fairly population will remain stable (with increases in lower high across most indicators: India and South Africa. income countries being offset by declines in upper- India was picked as the ideal location for the case middle-income ones). study analysis given its large and competitive Table 7: Criteria for prioritisation of case study country Theme Metrics used Overview of metric Rationale for inclusion Building New buildings Estimation of new building stocks up Important to define the volume of new sector growth (2016–2030) to 2030. Data sourced by EDGE from buildings required and it can be used New green build- Navigant to assess the degree to which a country ings (2016–2030) is expected to develop green buildings given current policies. Population Absolute growth National population growth from 2017 to Useful proxy for new build growth to growth 2030 check against other estimates. Faster Annual growth Annual percentage population growth growth indicates greater strain on the from 2017 to 2030 housing stock, while absolute growth indicates the total market opportunity. Housing House deficit Cumulative shortfall in homes. House- Useful proxy for the level of priority a deficit holders in this category may be living in government will give to increase the new informal developments build rate to close the housing deficit Homes that In this category households have a home require that lacks the basic services required, or is improvement in a dilapidated condition so needs to be replaced Energy profile Energy Ranks countries on sustainable energy Illustrates the overall sustainability of the trilemma index through 3 dimensions: Energy security, energy supply in that country. A lower energy equity (accessibility and afford- trilemma score would be indicative of ability), environmental sustainability potential greater additionality. Residential % of total energy consumption going to Useful to assess the overall importance of energy the residential sector the residential sector consumption Carbon Residential Overall carbon intensity of the residential Useful benchmark to understand where intensity energy emission sector based on the fuel mix from IEA the auction would have the greatest car- factor (including direct fuel use for cooking, bon emission reduction impact heat) Country and Sector Analysis 11 Table 8: Ranking of selected countries Theme Argentina India Indonesia Mexico South Africa Vietnam Building sector growth MEDIUM HIGH MEDIUM LOW LOW HIGH Population growth LOW HIGH MEDIUM MEDIUM HIGH LOW Housing deficit LOW HIGH MEDIUM MEDIUM LOW HIGH Energy, profile LOW MEDIUM MEDIUM MEDIUM HIGH LOW Carbon intensity LOW HIGH MEDIUM MEDIUM HIGH MEDIUM Housing policy MEDIUM LOW LOW HIGH HIGH MEDIUM Overall score MEDIUM- MEDIUM- MEDIUM MEDIUM MEDIUM- MEDIUM LOW HIGH HIGH Sources: Building growth projections sourced from data obtained by the EDGE team from Navigant, population growth data sourced from UNDESA, housing deficit data sourced from country level reports, energy, profile and carbon intensity data sourced from IEA, housing policy data sourced from RISE Energy Efficiency Building score. Sixty percent of this population increase will be could be deployed. The overarching driver for the driven by cities with more than 300,000 inhabitants, of selection was to look at reducing implementation which there will be 1,692 in the world in 2030. Eighty complexity to maximise the chances of success. This percent of this increase will be driven by middle- recommendation is specifically targeted at the pilot income countries. This trend held true for the six stage, where the main incentive would be to achieve countries analysed (Figure 1). Based on this data, it a successful demonstration of the mechanism. More was concluded that the most relevant target for the complexity could be introduced in the scale-up phase, auction mechanism would likely be large cities in rendering some of the considerations below less middle-income countries. relevant. Having established large cities as the most fruitful Our conclusion is that testing the auction potential target for the auction, we sought to identify mechanism at the level of a single city or state the geographical level at which the mechanism within a single country, or multiple cities within the Figure 1: Share of population growth 2015–2030 in cities with 300k+ inhabitants 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Mexico Vietnam Argentina South Africa India Indonesia 12 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Table 9: Geographical target analysis for a proposed auction Geographic dimension Advantages Disadvantages Single city/single state • Reduction in administrative complexity and • Risk of lower competition and less bidders transaction costs • Specificities of single city environment • Higher comparability of bids might make the auction mechanism less • Easiest to rapidly implement replicable elsewhere • Lower risk of failure leading to higher chance of scale-up Multiple cities/state in • Greater competition among bidders • Greater administrative complexity one country • Greater variation in bidder and building • Less comparability between bids due to types provides broader testing of the auction larger climatic variation which make for mechanism example water savings more expensive to achieve in drier areas • More risk of failure Multiple cities/states • Provides solid information for future scale- • High transaction costs and likely manage- in multiple countries up of the auction mechanism ment burdens on World Bank implementa- • Ability to compare and adapt success of the tion team due to regulatory and market mechanism in cities with different policy differences between cities and countries and regulatory frameworks • It might not be possible to have stan- dardised eligibility criteria • High risk of failure Multiple countries • Tests the pilot already at the scale the auc- • Greatest administrative complexity tion mechanism is ultimately expected to • Will almost certainly require country-­ reach specific eligibility criteria • Bids will likely be submitted by the stron- • Requires complex evaluation of multiple gest developers in each country competing certification schemes • Greatest risk of failure same country at most, gives the highest chance of for the purpose of the study. Social housing was success. Table 9 provides a summary of the reasoning extracted as a subset of low income, while lower and behind this recommendation. upper middle income were aggregated. The rational and description of each segment is provided in Table 10. 3.3 Sectorial targeting Income is particularly relevant because it is directly Following an analysis of the residential building correlated with energy use and the potential for market in each of the six selected countries, income efficiency, in a concept known as the energy ladder segments emerged as the most useful dimension (Figure 2) (WHO, 2006). As income increases, energy to carry out an effective sectoral breakdown and use becomes more modern, more sophisticated, and segmentation. Other relevant dimensions such as higher. At lower income levels the main intervention building type tend to be dependent upon income, is fuel switching to cleaner, more modern fuels. At for example with the low-income segment being higher incomes, efficiency becomes more important. characterised by single family dwelling, usually At the same time subsidies provided to the low- informal in less developed markets. income segments in some of the countries, such as Mexico, might also make this segment more The World Bank Group uses four income definitions: interesting for local governments, as more efficient low income, lower middle income, upper middle buildings would reduce the burden of subsidies on income and high income (World Bank, 2017). Some public finances. adjustments were made to these four categories Country and Sector Analysis 13 Table 10: Description of income segments across the six selected countries Market segment Description Low income Average 40–80% of the residential market. Building type is (typically) single family dwelling or one story multifamily; at the poorer end of the spectrum in poorer countries informal housing (shacks, huts) are an important component Social housing A subsegment that deserves separate analysis is social housing, defined as housing provided via gov- ernment programmes to the poorest income segment. Limitations on government budgets usually confine support to a small portion of the low-income segment Lower middle Average 20–40% of the market. Greater formality, more middle and high rises in more central urban and upper locations. There is great variation in income levels within this segment, with the lower middle income middle income end comprising a great share of households who would be considered poor by developed country standards High income Average 1–10% of the market. Approaches developed country standards, with presence of interna- tional developers. Largely urban in Tier 1 cities,8 with luxury high rises and gated developments an important component Figure 2: Energy ladder Fuel switching Energy efficiency Very low income Low income Middle income High income Increase in energy use per capita Electricity Natural gas LNG, LPG Kerosene Coal Charcoal Traditional biomass Crop waste, dung Increase in income per capita The income segments in the six countries were ▲ Carbon reduction: There is generally a linear assessed across five core indicators which are likely connection between energy efficiency and carbon to be crucial in ensuring the success of the auction emission reductions, modulated by a country’s mechanism:8 overall residential energy mix. The characteristics of residential energy supply will be an important ▲ Poverty reduction: The potential for the auction driver of carbon emission reductions, with coal- to reduce poverty by reducing energy bills for based electricity grids and oil-based heating vulnerable households. systems providing greater carbon savings than gas-based systems. ▲ Green readiness: This indicator assesses the degree 8  The Indian government categorizes cities in three tiers, of availability of a green supply chain, in terms with the eight largest cities belonging to Tier 1. There are of capacity for certifying buildings, but also to 26 cities in Tier 2 and 33 in Tier 3. There are also 5,000 Tier 4 provide the required technologies and construction towns and 638,000 villages. materials. 14 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings ▲▲ Housing value chain: This indicator assesses Experience from programmes such as the UNEP the size, complexity and skills of the housing Sustainable Social Housing Initiative shows developers who are active in each income segment. that considerable technical assistance should be The success of the auction mechanism will depend expended to upskill this sector before it is ready for on the presence of housing developers with green buildings. sufficient scale and skills to successfully bid into the mechanism. Volatility of residential housing ▲▲ Housing value chain: Large scale formal markets is also considered as housing crises can developments/social housing: greater participation lead to developers defaulting. of large developers, particularly in South Africa and Mexico, usually operating on government contracts ▲▲ Additionality: Whether the auction would achieve or with subsidies; greater use of high rises. a transformational impact, or at least impact over and above what existing policies and interventions ▲▲ Additionality: The involvement of government in would realize. this sector broaches the question of whether a more effective approach to making social houses more green would be through government policy and Low-income segment procurement. ▲▲ Poverty reduction: Greatest potential for poverty reduction, as this segment is characterized by Middle income slums and informality, with a lack of access to many housing amenities. ▲▲ Poverty reduction: Lower potential; however, in lower income countries the middle-income ▲▲ Carbon reduction: While there would be a high segment still incorporates a large share of the absolute potential reduction due to the fact population which would be considered poor by that this segment comprises the majority of the developed country standards. population in most countries analysed, per capita reduction would be smaller given lower energy use ▲▲ Carbon reduction: This is the fastest growing as per the energy ladder. segment in terms of energy consumption and emissions due to rising incomes, and would ▲▲ Green readiness: Given the high degree of present a great opportunity for carbon reduction. informality and the simple nature of the dwellings, this segment would struggle with sourcing the ▲▲ Green readiness: Housing units are more technologies and materials required to green advanced, meaning there is greater potential for buildings. There would also be a greater weight of the green solutions, with some potential for transfer green cost premium due to low construction costs. from higher income segments. ▲▲ Housing value chain: Informality means ▲▲ Housing value chain: Developers serving this developers are often the house owners themselves, segments tend to be medium to large sized and or are very small and informal. more plugged into the formal economy. There is also considerable competition. ▲▲ Additionality: There are no government policies explicitly supporting or incentivising green ▲▲ Additionality: Government policies in some buildings in this sector at the moment in the six countries support green buildings in this countries analysed. segment, and at the higher end of this segment a case could be made for unsubsidised green buildings, particularly with stronger policies in Social housing place. However, the vast majority of this segment ▲▲ Poverty reduction: Very high as this segment remains in need of further support. directly services people in the low-income segment who have difficulty accessing formal housing. High income ▲▲ Carbon reduction: This segment is characterised ▲▲ Poverty reduction: Nonexistent potential. by larger developments and high rises, meaning a higher chance of deeper decarbonisation. ▲▲ Carbon reduction: Very high potential, particularly on a per capita basis due to high energy consumption. ▲▲ Green readiness: The capability and skills in this sector are low for building green buildings. Country and Sector Analysis 15 Table 11: Results of income segmentation analysis Poverty Carbon/ Green Income level reduction energy readiness Value chain Additionality Overall score Low income HIGH MEDIUM LOW LOW HIGH MEDIUM- LOW Social housing HIGH MEDIUM LOW MEDIUM MEDIUM MEDIUM Lower middle MEDIUM HIGH MEDIUM MEDIUM MEDIUM MEDIUM- and middle income HIGH ▲▲ Green readiness: The new build in this segment is reasoning shown above. Middle income stands out often led by international developers or highly skilled as a priority, while low income presents the greatest boutique constructors using efficient equipment and challenges, with social housing and high income materials. The presence of international developers in the middle. The middle-income segment has the means best practice can be imported from developed best balance across all indicators. countries with green building practices. However, the ultimate decision on which segment ▲▲ Housing value chain: Developers serving this to proceed with, or whether to include multiple segment tend to be large, often international, and segments, will hinge upon the relative weighting with strong capabilities, and would be very suited assigned to each indicator. to bidding into the auction mechanism. ▲▲ Additionality: Overall, this segment should not be receiving public subsidies and would 3.4 Participant targeting not align with the World Bank's goals. A more An important aspect of this study is to map out effective intervention would be to encourage and assess the relevant individuals or institutions the government to introduce green standards in the building value chain that could bid into the for higher income homes and provide technical auction. The residential construction value chain assistance to developers. is very complex and involves a multitude of actors and stakeholders (Figure 3). There is a high degree Table 11 provides a qualitative ranking of the four of between country variation. As such the analysis income segments across the five criteria based on the in this section presents a high-level view of the key Figure 3: Housing value chain Land Design & Operation & Demolition Construction Acquisition Engineering Maintenance Renovation MAINTENANCE HOUSING FUNDS HOUSING FUNDS CONTRACTOR CONTRACTOR COMPANY BUILDING BUILDING BUILDING OWNER ARCHITECT ARCHITECT OWNER OCCUPANT ARCHITECT ENGINEER BUILDING OWNER BUILDING OWNER ENGINEER PLANNING AUTHORITIES 16 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings characteristics that would be expected of auction outsource or subcontract other phases of the value bidders, while more detailed conclusions will be chain. On average, larger companies will tend to provided in Chapter 4. directly own more of the supply chain, while smaller ones will outsource or subcontract most of the For the auction mechanism it will important to work. In the low-income segment of most analysed ensure that bidders have contractual responsibility countries, a large part of housing development is over the design and engineering phase of building carried out directly by future homeowners, who development, because this is the point at which key subcontract small-scale builders. decisions are made that will influence how green a building ends up being, particularly for structural All of the target market analysis countries have decisions such as thickness of walls, reflectivity of sufficiently developed housing markets able to roof, window to wall ratio, and other such passive provide a good number of medium to large bidders measures. as long as the geographical boundary is appropriate. While the overall value chain is fairly similar across The most relevant entities for the design and the six countries analysed, there are important engineering segment are real estate developers. This variations between the size and role of the different term can include housing funds, building owners stakeholders. Overall, all markets have sufficient and contractors as shown in Figure 3. competition at the developer level, with thousands of companies of different sizes operating across all Real estate developer is a broad term which can income segments. Carbon Trust analysis indicates define different institutions carrying out different that there is typically 5–10 large developers operating activities along the value chain. Real estate developers in each market. will more often focus on land acquisition and 4Cost-Benefit Analysis of Potential Auction in India 4.1 Introduction benchmarked against real data from more than 30 Indian cities and is considered a robust tool to As mentioned in Chapter 3, India was picked as assess the theoretical performance of a building. The a case study country to carry out a more in-depth EDGE outputs were modelled on a cash flow model assessment of the potential impact of the auction to estimate the full impact of the auction, using India mechanism. To this end, quantitative analysis was specific construction cost data. For this analysis EDGE carried out using the EDGE green building software version 2.1.1 was used. and cash flow modelling in Excel to quantify the costs and benefits of a USD 50 million financial incentive The four main income groups modelled are low dispersed via an auction mechanism in several income, lower middle, upper middle and high different regions of India. income, and these income groups were redefined to the Indian government definitions. The low-income The results of this analysis were combined with more segment should not be considered to include highly qualitative research and the outputs of the previous informal developments, as those are unlikely to be chapter to provide an initial auction proposal able to participate in the auction mechanism and structure and eligibility criteria. are too basic to feature into the EDGE modelling of housing characteristics. However it would include social housing. 4.2 Cost-benefit analysis The study varied the building unit size based on Methodology the income segment. All six climatic zones in India This study has carried out an economic cost- were modelled (montane, humid subtropical, benefit analysis to assess the potential impact of tropical wet and dry, tropical wet, semiarid, and a USD 50 million auction on the Indian market. A arid). The analysis accounted for three different number of different dimensions were modelled building scenarios using a different combination of across income, climate zones, green scenarios, unit interventions. size and building types. The EDGE tool was used to assess energy, water and embodied energy reductions The results were compared against the base case that could be achieved using three different green results in the EDGE software tool, with all the building scenarios. The EDGE software has been parameters left to the default settings. 18 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Table 12: Green building scenarios Passive measures Active measures Max green Design-based measures to improve More efficient appliances installed Combination of active and passive   building performance   to improve building efficiency measures to improve building perfor- Focused on: Focused on: mance. This maximises all elements of • Building fabric • Efficient lighting, heating and hot the passive and the active scenarios to • Insulation water systems achieve the highest possible savings • Air tightness • Renewable energy generation across all dimensions • Natural light • Systems to recycle or harness • Solar gain energy/water Figure 4: Green cost premium as a share of construction costs 30% 25% Share of construction cost 20% 15% 10% 5% 0% Low income Lower middle income Upper middle income High income Passive measures Active measures Max green Results cost of construction (for example by reducing use of expensive materials like glass). In monetary terms, Overall, while single family dwellings are cheaper to Figure 5 illustrates that the green cost premium varies build compared to high rises, the relative additional cost of green compared to underlying construction cost is greater, making them a less valuable target for the auction mechanism. As such, the analysis in this chapter focuses on high rises (Langdon & Seah Figure 5: Green cost premium in US$/m2 Consulting India, 2016). 80 70 Figure 4 displays that the construction cost premium 60 for a green building can vary between 3% and 25% 50 across income segments.9 USD/m2 40 The small difference between active measures 30 and max green is attributed to some passive 20 measures included in max green that reduce the 10 Low Lower Upper High 9  It is important to note that the green cost premiums income middle middle income shown below are calculated as a percentage of construction income income costs excluding land. A more detailed discussion of land rights issues and their impact on the viability of Passive measures Active measures construction projects will be provided in Section 5.4. Max-Green Cost-Benefit Analysis of Potential Auction in India 19 Table 13: Savings by Indian climate zone Humid Tropical wet Savings Montane subtropical and dry Tropical wet Semiarid Arid Carbon savings 2.81 1.00 0.73 0.86 0.77 0.90 Energy savings 1.65 1.00 0.77 0.93 0.83 0.92 Water savings 0.99 1.00 1.00 1.04 1.00 0.99 Share of population 2.5% 35% 32.5% 9.8% 14.5% 5.7% between ~USD 17 and ~USD 70 per square meter. Figure 6: Carbon savings per building Again, this is largely driven by the different measures 8,000 being included in each scenario, and the different unit 7,000 sizes within each income segment. 6,000 5,000 Assuming an auction of USD 50 million, the carbon tCO2 4,000 savings (in million tonnes of CO2) for the low-income 3,000 segment would be US$24 compared to US$37 for the 2,000 high-income segment (based on the passive scenario). 1,000 The next variable to consider is whether a potential Low Lower Upper High auction could have more or less impact in a particular income middle middle income climate zone in India. There is a degree of variation income income in savings across climate zones, which could impact a potential auction’s result. In Table 13 the humid Passive measures Active measures Max green subtropical region has been used as a baseline to normalise the data, as it accounts for approximately 35% of the population. Overall the variation in low-income segment versus ~390k in the lower savings across different climate regions indicate that middle income). climate could be an important factor to be considered when deciding where to target a potential auction. In the active and max green scenarios, a clear inverse relation appears between people and carbon, with The analysis also confirms that carbon and energy, more people being supported in the lower income savings on a per capita basis increase by income segments but more carbon being saved in the high- level. The spread in the total savings per building income ones. among different scenarios also increases with income, showing the potential for a greater degree of While greener buildings can reduce a low-income decarbonisation at higher income levels. household’s energy spending by up to US$200 per year, which is 5% of their total yearly spending on Table 14 illustrates the result of an auction of USD all goods and services, there is no evidence for a 50 million being implemented in India across a willingness by Indian consumers to pay a premium weighted average of climatic zones. Overall, the for green buildings. Meanwhile, commercial passive scenario delivers the largest absolute properties appear to command ~2% higher rents savings across all dimensions, due to its lower green according to a study by Vestian/Assetz, which cost premium per square meter. However a slight explains the dominance of the commercial sector trade-off emerges between people and carbon, in green building developments in India to date as more carbon is reduced in the lower-middle- (Vestian, 2016). The main reason for this reluctance income segment (2.3 MtCO2) versus the low-income appears to be lack of trust in the purported bill segment (2 MtCO2), while the reverse is true for savings of greener buildings. The proposed auction people supported by the mechanism (~410k in the mechanism could also support an awareness raising 20 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Table 14: Potential impact of a USD 50 million auction Carbon Energy Water Income segment Scenario People (000) (MtCO2) (TWh) (bnLT) Low income Passive measures 411.3 2.0 1.9 1,161.1 Active measures 119.9 0.9 1.0 310.0 Max green 110.6 1.1 1.2 380.9 Lower middle income Passive measures 392.2 2.3 2.1 1,469.4 Active measures 107.0 0.9 1.0 368.7 Max green 95.0 1.2 1.2 436.0 Upper middle income Passive measures 148.6 1.4 1.3 701.1 Active measures 81.6 1.2 1.3 359.2 Max green 57.8 1.2 1.2 334.3 High income Passive measures 100.7 1.4 1.4 560.9 Active measures 60.9 1.3 1.5 308.6 Max green 40.9 1.3 1.4 273.0 effort, coupled with operational monitoring of green paid back to funders, it would create greater or buildings, to show that the savings are realized equivalent total savings in the economy of the target and are sizeable, particularly for lower income country, largely benefitting the poorest citizens in households. the lower income segments. This would be highly dependent on discount rate, but at 10%, up to Regardless of their recognition in the market, 60 million USD in energy savings could be created, the auction mechanism would create substantial while with no discount rate savings would amount to monetary savings. There are two important USD 250 million. considerations to highlight, the first on whether these savings would “pay back” the additional cost of green measures, and the second on whether they would pay Conclusions back the cost of the subsidy. The quantitative analysis confirms that the lower In the first case, while the cost of the green measures income segments are the best target for the auction would be borne by housing developers, the savings mechanism. However there is a trade-off between would accrue to tenants. As such, the payback people supported and carbon saved, with low period itself is not measuring anything that figures income supporting more people but lower middle in any single private actor’s financial calculations. income saving more carbon. In particular, as the Nonetheless, taking a social perspective at a 10% complexity of the green measures implemented discount rate,10 most green measures outside of the increases from passive measures such as greater most basic passive scenarios were found not to pay solar reflectivity of walls to more active measures back within a 30 year time horizon. At a 0% discount such as solar water heating, the trade-off becomes rate, measures usually had average payback periods more stark and linear, with the high-income segment of 5 to 15 years, as usually measures beyond meeting delivering the greatest energy, consumption, and the bare minimum 20/20/20 criteria were used. carbon remission reductions but the smallest number of people being supported. The second case is more relevant for the auction mechanism. While the subsidy itself would not be Ultimately, the choice of which income segment to target, and how this influences the eligibility criteria, will depend upon the priorities of the funders of 10  According to World Bank guidance, a discount rate of the auction mechanism and the characteristics of between 8–12% is appropriate for developing countries with the housing market of the country in which it is rapidly growing economies (>5%). India’s per capita growth implemented. rate over the past 20 years has been 5.5% and in the last 10 years has fluctuated between 4–6%. 5India Residential Housing Sector Review 5.1 Introduction Figure 8: Distribution of IGBC registered projects This chapter provides an in-depth assessment of the residential housing sector in India with the purpose of supporting the quantitative analysis of Chapter 4 in Health Retail Other care providing a set of eligibility criteria that will form the 2% 2% 17% basis of the auction proposal in Chapter 6. Educational The key elements analysed are the certification building 5% infrastructure of the country, looking at the Commercial current development of green buildings and the Hospitality 55% characteristics of the relevant certification schemes; 6% Residential policies, regulations, and incentives schemes at both 13% national and subnational levels; and the composition of the housing value chain. 5.2 India certification summary India has the second largest building footprint registered for green certification after the U.S. but only 13% of this relates to the residential sector India has two domestic green building certifications, (Vestian, 2016). Green building certification is Indian Green Building Council (IGBC) and Green stronger in the commercial sector due to the Rating for Integrated Habitat Assessment (GRIHA). presence of multi-national firms who need to According to discussions with green building experts meet international corporate social responsibility in India, both schemes have been adapted to suit the commitments, and therefore opt to certify their real Indian market and are available for residential and estate. The Indian government has outlined minimum commercial properties (Professor Kini, 2017). Up to energy performance standards for commercial 2016 the IGBC scheme accounted for 99% of the green buildings through the ‘Energy Conservation Building building certification market (Vestian, 2016). EDGE Code’ (ECBC) (Chaturvedi, 2015). At the time of and Leadership in Energy and Environmental Design writing, there are no plans to extend the ECBC code (LEED) certifications are the two main international to the residential sector. Tier 1 cities such as Mumbai, certifications in India.11 A summary of the four Pune, Bangalore, and Chennai have almost half of the certification schemes can be found in Table 15. total certified footprint. This is partly attributed to the number of corporates and the availability of state support for green buildings. 11  Based on consultations with Mili Majumdar. 22 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Table 15: Review of Indian green building certification schemes EDGE GRIHA IGBC home LEED V4 Total certifications 7 925 (based on all 3,186 (based on all 623 (India)* GRIHA schemes) IGBC schemes) Approach Quantitative Qualitative Qualitative Qualitative Ratings Pass, good, very 1 star to 5 star Certified, silver, gold, Certified, silver, gold, good, excellent, and and platinum and platinum outstanding Lifecycle stage Design and Design, construction, Design and Design, construction, construction and ongoing operation construction and ongoing operation Fees Low Low Low High Time frame < 1 month– 1–3 months 1–3 months 1–3 months 1.5 months Administrative Low High Medium Medium complexity *Covers all certification scheme variants including home, office, retail, interior, etc. Taken from each of the certifications host website on 29/06/2017. 5.3 Building policy review auction (Severac, 2017). There could be some justification for allowing this, as a potential auction While the Indian government has commited to would only provide the finance once all construction reducing emission intensity by up to 35% on 2005 activities have been complete, therefore the developer levels by 2030, and buildings are mentioned in the will need to fund the additional construction cost NDC as one of the key levers to achieve this goal, no premium in the interim, and potentially they can explicit mention is made of building specific targets, use the SUNREF programme to obtain a cheaper and no national policies exists that incentivise green form of capital. The Sustainable Housing Leadership new build (UNFCCC, 2015). Consortium (SHLC) has been convened by the IFC in 2016 under European Union funding. The However, more targeted incentives exist at the consortium has partnered with India’s leading real state level. Given the federal structure of India, this estate developers and financial institutions to develop suggests that states would be a better political unit to innovations to lower the cost of green building, engage for the auction mechanism. support capacity building, and mainstream green building policy (Narayan, 2017). The SHLC and the Multilateral Development Banks (MDBs) have auction could be complementary, with the SHLC also targeted green building programmes in India, supporting building developers with knowledge although support aimed specifically at residential and the auction providing the required financial buildings has been more limited. The MDB assistance. interventions are summarised in Table 17. At a national level the Ministry of Housing and The KfW programme has financed some 2,000 home the Bureau of Energy Efficiency would need to be loans and has saved more than 42,000 MWh of consulted and informed, but political support and electricity, the equivalent of removing 50,000 Indians cooperation on implementation should be sought at from the electricity grid, and the programme has the state level, targeting those states which have green estimated annual CO2 savings of 37,000 tons (KfW building incentives in place, to maximise the chances Development Bank, 2016). The AFD programme of a successful rollout of the pilot. State governments is expected to be published in August 2017, and could be the primary partners for implementation potentially there is some risk of providing a double of a potential auction, targeting those with the most subsidy to those that benefit from the AFD support ambitious policies. and later receive an option as part of a potential India Residential Housing Sector Review 23 Table 16: Summary of Indian state green building incentives States with Policy Description Applicability to the auction mechanism Additional floor Additional allowances on the FAR made Provides the developer with an eco- Maharashtra, to area ratio (FAR) to developers for meeting a green build- nomic incentive to build to a green Punjab, Raj- allowance for ing certification. The incentive economi- building certification. Potentially it asthan, Uttar meeting a green cally benefits the developer without a could lower the green construction Pradesh, West building standard financial cost to the local state. There are cost premium as the cost of the mea- Bengal potential issues with incentivising devel- sures could be spread across a greater opers with developing green space with- number of properties or on larger out monitoring actual energy savings higher value units. This is a particu- and environmental improvements. larly relevant issue for India due to the high cost of land. Subsidy on green A subsidy is made available for building Where such a mechanism is already Andhra Pradesh measures to a green standard or utilising a certain present for meeting a green building proportion of the developments energy certification, it would not be highly needs from a renewable clean power additional to introduce the subsidy source. mechanism as participants have an existing incentive that combined with the auction mechanism would poten- tially give them an unfair competitive advantage. Street lighting Requirements to install energy efficient This initiative has developed a local Chandigarh, programmes street lighting. supply chain for energy efficient Himachal lighting. Pradesh Energy, audit Subsidised audits are available for prop- The policy could be additional to the Maharashtra programme erty developers to improve the energy auction if it reduced the cost of obtain- efficiency of the development. ing the green building certification. Solar water Either mandatory or optional require- One such measure for certain climatic Haryana, heater (SWH) ment to have all hot water installed regions to increase energy efficiency. Rajasthan programmes through a solar water heater. Some states This should reduce the cost and in have helped residents or developers some cases local subsidies are avail- purchase a solar water heater through a able to cover the SWH. There is a subsidy scheme. small risk that this subsidy could later be removed for participants in the auction. 24 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Table 17: MDB green building related programmes, sourced from Indian Renewable Energy and Energy Efficiency Database, funder websites, and expert consultations Targeted Active? Name Funder Implementer Overview of support at Yes Partial Risk World Sidbi/YES The programme supports energy efficiency through Developer/ Sharing Bank BANK providing grants for energy efficiency initiatives. ESCo’s Facility Although the programme has not specifically tar- geted the building sector, it has benefitted green buildings, and developers are eligible for the fund- ing if they can prove the energy efficiency benefit. Ended Indo-Swiss Swiss BEE Four components: (i) 3 to 4 day workshops for com- Developers 2016 Building Aid mercial building developers, (ii) technical assistance Energy, in developing building material testing infrastruc- Efficiency Proj- ture, (iii) design of guidelines and tools to design ect (BEEP) energy efficient residential and public buildings, (iv) dissemination. Ended Residential KfW National This programme creates a market for green build- Tenant/ 2014 energy Housing Bank ings through the provision of: occupier efficiency • Concessionary finance to individual borrowers programme for purchasing an energy efficient house (€50 million credit) • Technical assistance tool developed to calculate the level of energy savings of energy efficiency (EE) houses (€1.5 million grant). Starting SUNREF AFD National The scheme disperses finance to commercial banks Commer- in 2017 Housing India Housing Bank and housing finance corporations to be lent against cial banks (4 year multi-story residential properties that meet an IGBC and HFCs prog.) (gold or above) or GRIHA (4 star or above) certifi- targeted cation. In total €100 million of credit along with a but finance €12 million technical assistance/financial incentive provided to grant will be provided. both devel- oper and occupant India building value chain 5.4  impact the poorest segment of the population as they could move into social housing. and bidder identification Informality remains a huge issue in the Indian In order to prevent subsidies being disbursed to the housing market, which means that a potential auction high-income segment, a “selling price” cap on the will be unlikely to be able to target the lowest income proposed projects could be included in the eligibility segment. It is estimated that up to 47% of urban criteria. It is suggested that this cap be placed at Indian households live in informal housing with no the “Low-Income Group” level according to Indian property rights or land rights (FSG Mumbai, 2016). government definitions. This corresponds to the lower-middle-income group in our analysis and However, the social housing segment could be would ensure that the mechanism was targeted at the approached, with developers such as Tata Value most vulnerable segment of the population. This is Housing entering a potential auction with an illustrated in Table 18. affordable housing development; this could indirectly India Residential Housing Sector Review 25 Table 18: Income segments and house prices in India Number % of of housing Cost of Cost of Average Indian census housing units house house cost definition Income level Size of unit need (millions) ($ million) (USD) per m2 Economically weaker Less than $6.37 Up to 30 m2 40 18.4 0.5 $7,720 $257 sections (EWS) per day Low-income group (LIG) $6.37 to $12.75 30 to 60 m2 30 13.8 1.5–2.0 $23,170– $600 per day $30,890 Middle-income group $12.75 to $42.48 60 m2 to 20 9.2 4.0–4.5 $61,780 to $767 (MIG) per day 111 m2 $69,510 High end and luxury Above $42.48 per N/A 10 4.6 Above 5.0 $77,240 + N/A day The Indian housing value chain is strongly affordable credit for social housing, but this support is characterised by geography with most developers only available for occupants rather than developers. A operating locally. This reinforces the recommendation common method for developers is to fund properties of adopting a “State by State approach.” Table 19 through incremental construction payments from provides a summary overview of the Indian housing customers. Finance that is available for affordable market and provides a brief description for each credit for social housing is only available for income segment. occupants rather than for the developer. Two further factors reinforce the recommendation of The second and most important one is land rights. targeting the lower-middle-income segment, where Land price estimates vary from 45% of the final poverty reduction can still be achieved at the same development cost to 60% (inclusive of profit, time as developers are likely to be of a sufficient administration costs, etc.). Land prices are high due to size and complexity to be able to handle the auction a shortage of available land to develop, land banking mechanism and the complexities of achieving green speculation, and complex restrictions on land use. building certification. Land prices are particularly high in cities such as Mumbai and New Delhi. Estimates on the time it The first one is finance, which remains difficult to takes to acquire land and obtain development permits obtain for developers at the smaller end of the scale. vary from Restrictions on access to credit can impede the growth ~2 months to five years. Therefore it is recommended of the sector. At present no dedicated finance facility that only bidders with fully secured land rights exists for real estate developers; this restricts growth are accepted into the mechanism. This means that, within the sector. The sector is further hampered outside of rare cases, financial institutions would by restrictions on access for formal finance for land likely be excluded from bidding. acquisition. Options are available to support the Table 19: Evaluation of Indian Housing Value Chain, adapted from (Sarma, 2016) 26 Local small Local medium sized Established local National Examples Mahabaleshwara, Savvy Adani, VGN, 3C company Lodha, Prestige, Sobha DLF, Tata Housing, VHBC Number of Concentrated Concentrated A couple of these players for each Few participants state Portfolio under < 1 million 1–3 million 3–4 million 4–8 million construction (m2) Focus Small standalone developments. Medium sized developments in Medium to large developments, in Medium and large developments specific locations within a region. multiple locations within a region. across multiple sectors in multiple states. Greater use of in-house expertise across the value chain. Customer base Local customer and investor base. Reputation Local brand with strong brand awareness Nationally recognised brands. often developed through word of mouth. in city or state. Access to capital Limited access to capital, projects financed through down payments at Access to capital reserves or can borrow finance from investors or com- points of construction and completion of a development. Commercial mercial institutions. finance available, albeit at a high interest rate. Green Low: Usually does not have the financial Medium: May have in-house green exper- High: Motivated by CSR goals and investor guide- technology resources to invest in green buildings. How- tise and can afford to consult external lines, likely to have in-house experts on green expertise ever, niche developers may specifically build advice. building. and develop green properties at a premium to sell to climate conscious citizens. Applicability to Potentially more nimble to new requirements and more receptive to Developers in these two groups have showcase developments to show the auction consumer demands than larger developers. However, may not have green building capabilities but generally do not apply green building the economies of scale to provide the most financially competitive measures universally, unless there is an economic case to do so. These green buildings and are generally not familiar with green building players are likely to be able to provide green buildings at an economic certification. price and have specific divisions for affordable housing. They either have in-house expertise for meeting green building certification or can easily finance advice on this matter. Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings 6Auction Proposal The overarching aim of the design of a potential should also remain eligible should they be able auction should be to keep the mechanism as simple to demonstrate to the auction host that they are as possible to maximise chances of success. A positive using a comparable process. demonstration at the pilot level would greatly increase the likelihood that the mechanism could secure further 2. Bids should only be accepted from developments funding at both international and national levels to expecting to sell housing units at or below a given achieve scale-up and rollout to multiple countries. price to ensure that developers targeting the higher income segments of the population are not As such, this section proposes a simple set of eligibility subsidised—this should be aligned with Indian criteria that should be considered for the pilot stage of government definitions of housing affordability. the auction mechanism. Additional criteria could be added to later bidding rounds, once the auction has 3. There should be no limitation on which type demonstrated its credibility and results. of entity is allowed to bid; however, proposed developments should have secured land rights The criteria developed here are derived from before being allowed to bid. research and consultation carried out in six specific countries, with a particular focus on India for the 4. Overall, real estate developers and housing quantitative analysis. However the same reasoning associations represent the main target for a could be applied to any other market. In Section 6.6 potential auction and should be targeted by of this chapter we present a schematic approach to awareness raising and promotion efforts. replicating the auction mechanism in other countries. 6.2 Preparatory steps 6.1 Eligibility criteria The auction host would need to seek the relevant Based on the analysis described in the previous national and state political approvals when chapters, four main eligibility criteria have been implementing an auction in a new country. In India, identified. These are mostly focused around ensuring there is an expectation that the proposed auction that the process is kept simple for bidders, while should have to secure the political support of the guaranteeing a minimum level of energy and carbon Ministry of Housing and the Bureau of Energy savings and poverty reduction. Efficiency.12 Consultations with these entities could lead to additional technical and financial assistance. 1. The financial incentive should be awarded to Political support is likely to be very important for a bids putting forward the lowest price per square successful implementation, and it is recommended meter and achieving a minimum performance improvement of 20% in energy, water and embodied energy, over the local baseline (as per 12  Depending on the positioning of the programme, the EDGE criteria). Equivalent local certifications Ministry of External Affairs could also be important. 28 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings that high level conversations would take place in estate sector are fairly extensive, with up to five years advance of the first round of bidding from conceptualisation to construction, and therefore funder’s expectations should be aligned with these The main public sector implementation partners timelines. are expected to be state governments. A single state with progressive green building legislation should be targeted for the initial pilot phase, with the pilot 6.3 Eligible participants targeting one or more Tier 2 cities to sidestep issues with high land prices in Tier 1 cities. A promotion A potential auction should not limit eligibility to phase of at least six months in duration should potential participants, but the expectation is that follow the political agreements to give developers participation will vary and a real estate developer will with eligible projects in the pipeline sufficient time have the most straightforward role in the auction. In to prepare their bids and make the required design Table 20 we have outlined the pros and cons of the modifications. Overall, timelines in the residential real main potential participants. Table 20: Potential participants that could bid into a potential auction Expected Expected Organisation take up impact Pros Cons Real estate High Medium • Number of participants • Less concerned with long-term developer to high • Potential for economies of scale operation costs • Adoption of green technologies and • More concerned with using green practices could be replicated by credentials as a sales platform competitors • Potentially the auction will only award funds to the largest com- panies who can build to the green standards at the lowest costs due to economies of scale • Could target developers who already have a propensity to build green Housing High High • Concerned with long-term operation • Scale and number of housing association and maintenance costs so will con- associations sider actual performance compared to theoretical • Benefits those poorer in needy households Commercial Medium Medium • Could be offered as part of a green • Less clear role in the auction, Bank to low lending product, and will reduce the question over how they will eco- certification costs nomically benefit from the auction • Funds may not be dispersed if the bank does not capitalise on adver- tising the auction • Funding could be insignificant compared to commercial banks’ lending portfolio • Adds an additional actor into the supply chain and could therefore add funds State/municipal Low High • Potentially easier to target lower • Slow to disseminate funds government/ income groups and more ethically local authority conscious • Could be incorporated as part of another green buildings programme • Network with local developers • Could take over the programme management Auction Proposal 29 Figure 8: Construction timeline and auction mechanism milestones Business Post-construction development Pre-construction Construction 18–60 months ~2 months 12–18 months 18–60 months (depending on size) (depending on size) Preliminary Contracts & Award of Land Legal Completion of Operation by Design green project Construction green building g acquisition approvals construction occupier certification management certification Promotion of auction Auction and winner Receipt of funds awarded At any point onward from the award of the option, the winner of the incentive payment could sell on the contract to another bidder who meets the eligbility requirements of the scheme 6.4 Disbursement of options A poverty reduction criteria could be added prioritising bids from projects with an expected sell There are three distinct phases in the auction: the price within the affordable housing segment, or promotion of the auction, the eligibility to bid, and the with explicit participation from public authorities final receipt of funds. The timelines of these phases certifying the social housing character of the should be synced with the timelines of the residential real development. Bids from areas with higher incidence estate market. Based on market research and consultation of poverty could also be prioritised. with independent experts, this study has defined the residential timelines for a potential auction in India. An urban density/proximity to city center criterion could be added to ensure that no developments are While eligibility to bid should be allowed at any point supported which strand their tenants far from job in time, the option should be awarded only when the opportunities. This would be highly contingent on preliminary certification is achieved after the design the geographical origin of the bid and might require stage. The actual payment would only be disbursed detailed heat mapping of target cities to determine upon construction completion and award of certification. which areas should be off limits for the mechanism. A vulnerability to extreme weather event criterion 6.5 Other criteria could be added, excluding developments in high- risk areas from bidding; this would require detailed Eligibility criteria could be extended or altered to mapping of high-risk areas, which might not be meet funder requests or World Bank priorities. available for all geographies and all weather risks. Further analysis should be carried out at the implementation to the design stage to precisely A waste management criterion could be added determine how to maximise a potential auctions asking bidders to submit documentation proving they impact against World Bank and other funder’s goals. have a strategy in place to reduce or recycle the waste produced during the construction process. Different weightings could be applied to savings, for example, in water stressed geographies such as Bangalore in India, greater weight could be given to water savings (as measured by the World Resources Process for replication of the 6.6  Institute (WRI) water stress index tool) so that auction in other geographies equivalently priced bids with greater water than The Carbon Trust has established an eight-step energy savings could be prioritised. framework to replicate the auction mechanism in other countries. This includes a listing of all the key Alternatively, the focus could be directly on a particular analytical steps that should be undertaken to ensure the kind of savings, such as carbon or energy, in which case mechanism has a high likelihood of success in a new bidders might be requested to present a USD/tCO2/ geography. m2 metric. This would be easy to apply using the EDGE platform and comparable across bids, although the disadvantage is it could preclude other certifications. 30 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Country Prioritisation Geographical Focus • Decide which criteria to use to pick a • Decide at which geographical dimension country within the country to target the auction— • Select most promising countries to run national, regional, city more detailed feasibility studies Sectoral Focus Housing Value Chain • Decide on income segment and other • Map the local real estate value chain criteria (e.g., building types) • Identify number and characteristics of potential bidders Eligibility Criteria Political Support • Establish minimum eligibility criteria, to be • Engage with relevant public authorities, validated via EDGE or equivalent local especially those with responsibility on certification schemes housing policy • Assess whether additional criteria should be developed to meet donor or WBG priorities Promotion Implementation • Ensure a sufficiently long awareness • Timeline for implementation will depend raising phase is carried out so that on local construction times bidders have time to prepare • Monitoring, Reporting, and Verification (MRV) and evaluation should be used to update the eligibility criteria for subsequent funding rounds and to check that certification criteria have been met 7Conclusions The purpose of this study was to assess whether the have a large and positive impact on both poverty climate auction model as piloted by the Pilot Auction reduction and carbon emission reduction. It would Facility (PAF) deployed by the World Bank in support also generate considerable financial savings to an of methane emission reductions could be translated amount greater than the initial investment by the effectively to the residential new build sector. auction’s funder. The study carried out both qualitative and The choice of India as a case study country is by no quantitative analysis, including in-depth policy and means an indication a preferential positioning of the market reviews of six developing countries. India country vis a vis others for the initial implementation was selected as a case study based on a number of the auction mechanism. The ultimate decision on of criteria plus discussions with the World Bank, when, where, and how to implement the mechanism and a modelling effort was completed to estimate will depend upon discussions between potential the potential impact that a USD 50 million auction programme funders and other relevant stakeholders. targeting buildings would have in the country in terms of poverty reduction, energy savings, carbon In addition to this report, two slide decks presenting savings, and water savings. the analysis and the emerging conclusions were produced and shared with World Bank, and are The conclusion is that the mechanism could be available as technical annexes. replicated in the housing sector, and that it would References Chaturvedi, A. (2015). Green Buildings: The Indian Sarma, G. J. (2016). Residential Real Estate in India: A Perpective. JGLS. New Paradigm for Success. Bain & Company. FSG Mumbai. (2016). Informal Housing, Inadequate Severac, C. (2017, July 18) (O. Houlden & A. Johnson, Property Rights. Understanding the Need of India’s Interviewers). Informal Housing Dwellers. UNDESA. (2015). World Population Prospects: The 2015 Kapoor, P. (2014). IFC’s Green Buildings Market Revision. New York: United Nations Department of Transformation Programme. IFC. Economics and Social Affairs. KfW Development Bank. (2016). Energy Efficiency— UNFCCC. (2015, September 25). India’s Intended India. Federal Ministry for Economic Cooperation and Nationally Determined Contribution. Retrieved from Development. http://www4.unfccc.int/submissions/INDC/ Published%20Documents/India/1/INDIA%20 Langdon & Seah Consulting India. (2016). INDC%20TO%20UNFCCC.pdf Construction Cost Handbook: India. Arcadis. Retrieved from http://www.langdonseah.com/en/ga/files/ Vestian. (2016). Sustainable Construction Practices in download/3773 India. Assetz. McKinsey Global Institute. (2010). India’s Urban WHO. (2006). Fuel for Life: Household Energy and Awakening: Building Inclusive Cities, Sustaining Health. World Health Organisation. Economic Growth. McKinsey & Company. World Bank. (2017). Consumption. Retrieved from Narayan, S. (2017, July 25). Interview to discuss World Bank Databases: http://datatopics.worldbank Indian Sustainable Housing Leadership Consortium .org/consumption/detail#datasource (O. Houlden, Interviewer). Professor Kini, P. (2017). Consultation on green building in India. Interviews Name Role Organisation Abimbola Olukemi Windapo Quantitative Social Researcher Cape Town University Agustina Galli   LEED AP Alejandra Rueda   Agencia de Protección Ambiental Andrés Schwarz Independent LEED Expert LEED AP Autif Sayyed Green Building Specialist IFC Chandan Bhavnani Vice President YES BANK Dr. Fatma Mohamed   University of Dar es Salaam Dr. Gehan Nagy Assistant Professor of Architecture The British University of Egypt Ernesto Infante Barbosa Deputy Director of Multilateral Affairs Sociedad Hipotecaria and Sustainability Fabby Tumiwa Executive Director Institute for Essential Reform (IESR) Felipe Faria CEO Green Building Council of Brazil Grahame Cruickshanks EDGE Expert Green Building Council South Africa Guillermo Simon-Padros CEO Argentina Green Building Council Idris F. Sulaiman Technical Advisor Indonesia Green Building Council Llewellyn Van Wyk Principal Researcher Council for Scientific Research Manfred Braune Chief Technical Officer Green Building Council South Africa Megan Sager Director Sustainable Solutions South Africa Mili Majumdar Managing Director GBCI Odón de Buen General Director CONUEE Pablo Barcos Real Estate Manager Compass Group Pradeep G. Kini Architect Faculty of Architecture, Manipal University Prem Zalzman Director de Nuevas Tecnologías para el Ministerio de Ambiente y Desarrollo Desarrollo Sustentable Sustentable Roberto Malvido Arriaga CEO CASAS PAQUIMÉ Sanjay Seth Senior Fellow & Senior Director TERI Sanjith Naik Managing Director Mahabaleswara Builders Shruti Narayn Lead—Green Building Program World Bank India 36 Study on Using the Climate Auction Model to Catalyse Energy and Resource Efficient Buildings Name Role Organisation Songo Didiza Executive Director Green Building Design Group, South Africa Sonia Rani Fellow and Area Covenor The Energy Resources Institute (TERI) Srinath Komarina President, Responsible Banking YES BANK Steven Piro Director Synergy Efficiency Totok Sulistiyanto Energy Consultant Indonesia Green Building Council Xavier Leulliette Technical Manager Vietnam Green Building Council