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Franz Fuerst University of Cambridge, Department of Land Economy Elias Oikarinen

How important is building energy efficiency in markets with cold winters? Pricing and liquidity evidence from Finland. Franz Fuerst University of Cambridge, Department of Land Economy Elias Oikarinen University of Turku, School of Economics elias.oikarinen@utu.fi.

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Franz Fuerst University of Cambridge, Department of Land Economy Elias Oikarinen

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  1. How important is building energy efficiency in markets with cold winters? Pricing and liquidity evidence from Finland Franz Fuerst University of Cambridge, Department of LandEconomy Elias Oikarinen University of Turku, School of Economics elias.oikarinen@utu.fi European Real Estate Society Conference Bucharest, June 2014

  2. Background Buildings are estimated to be responsible for 20% of greenhouse gas emissions There is growing awareness of the role of real estate in reducing the greenhouse emissions Do energy efficiency ratings create desired incentives? Do they include ’independent’ pricing information in the real estate market?

  3. Previous literature on the theme The seminal studies (e.g. Miller et al., 2008; Fuerst and McAllister, 2011; Eichholtz et al., 2011, Reichardt, Fuerst and Zietz, 2012) provide first valuable insights but are characterised by important limitations: Typically focus on specific sectors, in specific countries and over specific timeframes – results not readily generalisable (the majority of studies use data from the US office market) Rely on a very small number of data sources (notably from the CoStar Group) Academic studies regarding the residential sector are quite scarce despite its obvious importance for both the general economy and sustainable development The existing evidence of the residential market points to a significant green premium (e.g. Banfi et al., 2005; Fuerst et al., 2012; Zheng and Kahn, 2008; Kok and Kahn, 2012)

  4. The aim of the study To provide more information on the influence of energy efficiency (EE) ratings on the value and liquidity of housing Main questions & hypotheses: Do EE ratings include ‘independent’ information w.r.t. housing prices? H1: The high tier ratings induce a price premium, but no difference between the other ratings (‘clientele effect’) H2: EE ratings affect housing values and liquidity even when catering for the observed maintenance costs that include the energy costs, i.e., ratings have an ‘independent’ impact on housing prices

  5. The contributions of the study First study using data for a market located in cold climate We cater for the maintenance costs that include energy costs First article investigating the liquidity effect

  6. Empirical data Transaction level data for apartments in Helsinki from 2007Q4 to 2012Q2 Transaction price and date, time-on-the-market, detailed unit level characteristics capturing the key housing price determinants Maintenance costs including general building level energy costs Source: Kiinteistömaailma (private real estate agent, app. 25% market share) 5943 observations that include the energy rating

  7. Empirical methodology Baselineanalysis: hedonic (OLS) regression models Robustnessanalysis: Quantileregressions Potential complication: Until 2013, the rating was based on the actual energy consumption that is dependent on the habits and number of people living in the building, not only on the building characteristic Fortunately, the energy rating is not largely dependent on the number of people staying in the building Our main aim is to study whether the ratings contain independent pricing information and information regarding the liquidity of apartments. For this purpose, the before-mentioned complication should not cause major problems

  8. Baseline results The A-B ratedsell at a notablepremium, but the pricingeffectbetween the otherratings is small The inclusion of maintenancecostsdoesnotinfluence the parameterestimates for EE ratings Thereis no ’liquidityeffect’ Holdsregardless of the inclusion of maintenancecosts

  9. Conclusions We find a significant price premium for the high-rated (A-B) apartments even when catering for the maintenance costs ’Clientele effect’: There is a small share of ’enviromentally aware’ buyers that aim to buy the highest rated units (increases demand and thereby prices for these units); Willingness to ’live green’ & Expected fast growth of energy prices The liquidity of apartments is not dependent on the energy efficiency rating Implications: EE ratings contain valuable pricing information that can be useful for e.g. developers, investors, and real estate agents High EE rating is financially rewarded – incentives to construct above average EE buildings Gives incentives to adopt EE certicates / ratings (they do matter!)

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