the economics of green building

The Economics of Green Building

Transatlantic Evidence

Nils Kok UC Berkeley

Maastricht University

Connecticut Green Building Council October 2010

Energy and buildings Property sector consumes and pollutes

  Carbon emissions and buildings are closely related   30% of global CO2 emissions   70% of U.S. electricity consumption

  Impact of energy costs directly affects tenants and investors   Energy costs are single largest expense in provision of office space

  30% of operating expenses   Energy represents 10% of total occupancy cost

  Salience can only increase with rising energy prices

  Awareness is growing…   Legislation

  US: Waxman-Markey bill   Europe: EPBD, CRC

  Corporate real estate as part of CSR policy (e.g., Chevron, BoA, …)   “Sustainable” property funds (e.g., Hines/CalPERS)

Usage of “green building” in the popular press…

…and visitors at the “Greenbuild” conference

“Green” building in the marketplace? Top-10 “green” commercial office markets

Economic significance of “green” building Implications upon the market for commercial space   Trends in “green” building may have economic implications

  A higher initial outlay…   Not clear how much higher (0 – 20%)   ‘Smarter’ building managers/software

… may be compensated by “green” value drivers   Cost savings

  Energy savings (up to 35%)   Emission reduction

  Increased rents   Reputation effects   Improved indoor air quality

  Increased economic lives, reduced depreciation

  Case studies on the economic implications   Focus often on new buildings   Results are hard to generalize

Economic value of “green” label? Academic research on Energy Star and LEED certification

Sample of 28,000 office buildings (2009 cross section), 3,000 of which are certified by EPA or USGBC

1.  Evidence on economic premium for green office buildings   Rigorous control for quality differences (PSM)   Label vintage

2.  Identify the sources of rent and value increments   Explicit link to

  EPAs measures of energy efficiency   USGBC measures of “sustainability”

Sample of 8,000 office buildings (2007 – 2009 panel), 694 of which are certified by EPAs Energy Star or the U.S. Green Building Council

3.  Short-run price dynamics of green office buildings   Returns during turbulent 2007 – 2009 period

“Green” buildings Two programs: Energy Star (EPA) and LEED (USGBC)

  Dataset of existing sustainable office properties (U.S.)   EPAs Energy Star for Commercial Buildings (1995)

  Efficiency in source energy use is in top quarter relative to CBECS   Standardized for building use (occupancy, hours) and climate   Certified by professional engineer   Based on real energy consumption (at least one year of bills)

  USGBCs Leadership in Energy and Environmental Design (1999)   Scoring systems based on 6 components of “sustainability”   Energy efficiency is just one component   Various systems and versions (eg. NC, EB, O&M, ...)   Based on design stage (and now verified after construction)

  Similar programs exist in Australia, Japan, the UK, …

Example: 101 California St, San Francisco Energy Star certified, LEED Gold

Defining conventional comparables Systematic match on location   Based upon longitude and latitude, we use GIS to identify all

conventional office buildings in a 0.25 mile radius

Example: 101 California St, San Francisco Energy Star certified, LEED Gold

Clusters of “green” and control buildings Minimum of one control building per cluster

Chicago, IL Houston, TX Columbus, OH

Evidence on the “green” premium Cross section of green buildings at the end of 2009

  October 2009 sampling of green office buildings   Rental sample

  1,943 green buildings   18,858 control buildings

  Transaction sample   744 green buildings   5,249 control buildings

  To further control for differences in quality, we estimate a propensity score for each building (Rosenbaum and Rubin, 1983)   The probability ρ that a building is certified, as a function of its hedonic

characteristics

Green buildings and conventional comparables Propensity score weighting substantially reduces differences

Methodology How to further correct for differences in location and quality?   Standard real estate valuation framework

(1)

  Rin is the rent, effective rent, or transaction price per sq.ft.   Xi is a vector of hedonic characteristics

  Size, age, renovation, class, amenities, public transport, …   Percent change in employment in service sector (CBSA) to control

for regional variation in demand for office space   Cluster cn dummies to control for location – 1,943 (744) separate

dummies in the rental (transaction) sample   gi = dummy variable if building i has green label   Dummy variables for year of sale in transaction sample

Propensity-weighted regression results Market implications of Energy Star and LEED

Conclusions and implications (I) Eco-investment real estate sector is not only “doing good”

  Ceteris Paribus, green buildings 1.  Have Higher Rents by 2-6% 2.  Have Higher Effective Rents by 6-8% 3.  Have Higher Selling Prices by 11-13%

  The average non-green building in the rental sample would be worth $5.6 M more if it were converted to green.

  The average non-green building sold in 2004-2009 would have been worth $11.1 M more if it had been converted to green.

  The implied cap rate (3%) suggests that property investors value the lower risk premium inherent in certified commercial office buildings

  The missing piece…what are the costs of “greening” properties?

The greener the better? Unique premium for each “green” building   What is the relation between the variation in the “green” premium

and the LEED-score or energy consumption?

  The increment to rent or market value for green buildings varies:

Detailed information on LEED-rated buildings Standardized indices of buildings’ sustainability

  For 209 (103) LEED-rated buildings, we have information on:

The sources of economic premiums for “green” Relating the premium to LEED and Energy Star data

  Relating increments in rent and market value to the characteristics of LEED and Energy Star-rated buildings:

(2)

Estimated by GLS (Hanushek 1974)

Regression results (I) The rental increment for LEED rated buildings

  LEED-certified, score 40: effective rent of 2 percent higher than otherwise identical, registered building

  LEED-certified, score 60: effective rent of 20 percent higher   Energy Star and LEED are complementary

Interpretation of regression results The increment for LEED rated buildings

Information on Energy Star-rated buildings Emissions of efficient buildings are substantial…

  For 1,719 Energy Star-rated buildings, we have information on:

  Average emission of a building in our sample: 4,326 tons of CO2   750 cars, 9,000 barrels of oil, …   Energy Star-rated buildings emit at least a quarter less carbon as

compared to conventional office buildings

Regression results (I) The rental increment for Energy Star rated buildings

  A $1 saving in energy costs is associated with an increase in effective rent of 95 cents

Regression results (II) The transaction increment for Energy Star rated buildings Energy efficiency is reflected in “green” price increment

  A $1 saving in energy costs is associated with a 4.9 percent premium in market capitalization, which is equivalent to $13/sq.ft.

  This implies a cap rate of about 8 percent

Conclusions and implications (II) LEED and Energy Star labels seem to be complimentary

  The green increment is systematically related to the underlying characteristics of energy efficiency or “sustainability”   Market seems to be relatively efficient in pricing these aspects

  Direct capitalization of energy efficiency important information for investments in building retrofits

  LEED and Energy Star measure somewhat different aspects of “sustainability” and complement each other   Low correlation between LEED-score and EUI-score

2007 – 2009 office market dynamics Office rents, vacancy rate, and unemployment

Office rents –30%

Vacancy rate +40%

Unemployment +115%

2007 – 2009 office market dynamics Office rents, vacancy rate, and unemployment

Unemployment x2

Office rents –30%

Vacancy rate +30%

(3)

  Rint is the rent or effective rent per sq.ft.   Xit is a vector of hedonic characteristics

  Size, age, renovation, class, amenities, public transport, …   Cluster cn dummies to control for location – 694 separate dummies   git is a green dummy

Short-run price dynamics of green buildings Substantial increase in rated space in a contracting economy   8,182 observations as of September 2007

  694 rated buildings and 7,488 nearby control buildings   Rents, occupancy rates, effective rents

  Same sample matched to financial information in October 2009   Drop buildings that were converted to “green” during the sample period

  We estimate developments in rents, occupancy rate, effective rents:

€

logRint = α0 +αt + βiΧ it + γ ncn +δtgit +ε intn=1

N

∑

Results: rental levels and green ratings The “green” premium has slightly declined….

Regression results: logarithmic changes in rent Returns to “green” comparable to (high quality) buildings

Conclusions and implications (III) “Green” is getting mainstream   Increased awareness of energy efficiency and the role of the real

estate sector have increased attention upon “green” building

  Energy efficient and sustainable office space is now a large share of the commercial property sector -- getting mainstream

  This may have economic implications for investors, tenants, and policymakers

  Buildings certified by Energy Star or LEED command higher rents and prices in the marketplace   The “green premium” has slightly decreased during a period of volatility

in property markets…

…but the relative rents of green buildings have remained unchanged compared to identical conventional buildings

Conclusions and implications LEED and Energy Star labels seem to be complimentary

  Market seems to be relatively efficient in pricing aspects of “sustainability”

  Implications for investors:   These developments will affect the existing stock of non-certified office

buildings   Environmental characteristics are a risk factor that should be priced in

  Policy implications:   Modest programs by government and non-profit institutes to provide

information are effective and incorporated by market participants   Directly affects energy consumption (and emissions)   More aggressive policies?

What happens in Europe… (?)

EU Energy Performance of Buildings Directive Originated January 2003, revised December 2009

“Member states shall ensure that, when buildings are constructed, sold or rented out, an energy performance certificate is made available by the owner to the prospective buyer or tenant”

Program evaluation of energy labels…Energy certificates, efficiency, and market pricing 1.  The adoption process:

  Adoption rate dynamics   Adoption determinants

2.  The influence of energy certificates on the transaction prices of dwellings   Attempt to disentangle labeling effects in:

  Quality of home   Energy features

3.  The real energy use (gas and electricity) for all individual dwellings   What determines energy consumption?   How strong is the link between EPC and usage?   Is energy use capitalized? (for labeled versus non-labeled dwellings)

The laboratory The Netherlands introduced energy certificates in Jan 2008

Stylized facts:

Population: 16.5 mln. Homes: 7.2 mln. Ownership: 55% Temperature: 50 F

(34 F–64 F)

Average home price: $322,000 Net mortgage: $1,120/month Gas bill: $133/month Electricity bill: $74/month

Adoption rate Diffusion slows down, but higher in “weak” regions

Adoption rate Diffusion slows down, but higher in “weak” regions

Energy labels and home prices Energy efficiency is clearly reflected…

Energy labels are incorporated in prices Partial reflection of NPV energy savings

  Labels will become mandatory (per EU regulation)

  Private homebuyers take labels into account

  What about tenants?   Labels will become part of rental policies

  Labels are “popular” in the commercial property market   Green procurement GSAs (minimum label C, or two label steps)   Pressure of corporate tenants

Questions/remarks?

kok@haas.berkeley.edu