The Diffusion of Energy Efficiency in Building

Nils Kok Maastricht University

AEA Meetings, Denver January 2011

Marquise McGraw UC Berkeley

John M. Quigley UC Berkeley

The “energy paradox,” revisited Increasing number of buildings certified as efficient   Energy consumption and building technology are closely related

  30 percent, 40 percent, 70 percent, …   Durability of real capital: existing structures continue to have impact

  Slow diffusion of more efficient technology   Measures are profitable: CFLs, HVACs, …   “Energy paradox” (Jaffe and Stavins, 1994)   High discount rates (Hausman, 1979)   Lower returns? (Metcalf and Hassett, 1999)

  Substantial increases in commercial buildings labeled as energy-efficient or “green”

Energy-efficiency labels and property markets Energy Star (EPA) and LEED (USGBC)

  EPA’s Energy Star for Commercial Buildings (1995)   Efficiency in energy use 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)

  USGBC’s 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 (e.g., NC, EB, O&M, ...)   Based on design stage (and now verified after construction)

Program growth: Energy Star and LEED 48 MSAs, 1995 – 2010 Dominant forces in the commercial and institutional market

  2010:   10 percent of buildings   30 percent of stock

  2010:   5 percent of buildings   10 percent of stock

  Registered: 27,000 buildings (6b sq.ft.)

  Size effect (Snyder, et al., 2003)

Labels reflect building technology Energy paradox in commercial building?   Labels verify hard-to-observe energy efficiency technology

  Comparable to role of patents in production technology (Keller, 2004)

  Certified buildings have lower resource consumption   Energy Star: 35 percent less energy consumption, on average   LEED: efficiency of new construction unclear, existing certified buildings

on par with Energy Star requirements.

  Are measures profitable?   Investments costs include: consultancy services, incremental cost of

construction, design, equipment and materials   Evidence on returns to investments

  Increased rents and asset values (Fuerst and MacAllister, 2011)   Capitalization of incremental energy savings into asset values

(Eichholtz, et al., 2010)

  Building technology (i.e., labels) should diffuse quickly across markets

New York

Los Angeles

Diffusion of certified space Substantial differences in timing and growth across MSAs

New York

Los Angeles

The diffusion of energy efficiency in building (I) Determinants of timing and growth

1.  Variations across markets in expected cost savings

  Climatic conditions (Degree days; NWS)   Adverse climatic conditions increase expected economic payoff

  Energy prices (Cents/kWh; utility data EIA)   Higher prices increase expected payoff from improvements   Lower energy consumption in more expensive areas

  Property market conditions (Stock, vacancy, rents, prices; CBRE-EA)   New construction depends on stage of property cycle   Green “premium” varies with market conditions

“What determines the geographic dispersion in the timing and growth of energy efficient technology in office buildings?”

Variations in the expected cost savings Simple correlations, 2010 cross-section

The diffusion of energy efficiency in building (II) Determinants of timing and growth

2.  Local economic conditions that affect appropriability of gains   Income (Average wages and salaries; BEA)

  Ancillary benefits of “green” buildings   “Green” as a luxury good (Roe, et al., 2001); “warm glow”

  Size of service sector (Fraction of people employed in service sector; BLS)   Demand for office space

  Size of government (Fraction of people employed by government; BLS)   “Green” procurement policies

  Building professionals (LEED APs, architecture grads; GBCI, NAAB)   Overcome information barriers (Hall, 2003)

3.  Building-specific characteristics that influence expected profitability   Building size (Average building size, CBRE-EA)

  Spread fixed costs over larger base (Snyder, et al., 2003)

Local economic conditions Simple correlations, 2010 cross-section

The diffusion of energy efficiency in building (III) Determinants of timing and growth

4.  Institutional characteristics   Political ideology (Vote for Reagan ‘84, Bush ’92; CQ Press)

  Political ideology may influence tenant and investor choices

  Regulation and incentives (LEED public policies; USGBC)   Government policies may stimulate innovations (Lanjouw and Mody,

1996; Jaffe and Palmer, 1997)   Some cities have included LEED in building codes for new

construction and renovations   Numerous LEED-specific incentives: “fast-tracking” permits,

subsidies, tax credits

Institutional characteristics Simple correlations, 2010 cross-section

Dynamic models Levels, first differences and Arellano-Bond We model the dynamic relationship between the diffusion of energy

efficiency over time and across geographic markets as:

(1)

  Where is a vector of income, prices and economic conditions   We use a two-year lag to account for real time necessary to complete

renovations and new construction   Serial correlation addressed by estimating AR(1) using FGLS

(2)

  First differences to control for time-invariant unobserved heterogeneity   Alternatively, we estimate (2) following Arellano-Bond (1991),

instrumenting all covariates by their own lagged values

€

Fractionit =α + βX it−2 + εit

€

ΔFractionit = α+ βΔXit−2 +ε it

€

X it−2

Basic regression results LEED explained by income, Energy Star by energy prices

Arellano-Bond GMM Regression Results Healthy market fundamentals increase technology diffusion

Conclusions and implications Economic conditions important for energy efficiency diffusion

  Built environment important in reducing resource consumption   Much attention to the “energy paradox” in building sector

  Diffusion of energy efficiency and “green” technologies in commercial property sector widespread and rapid   30 percent of all commercial office space certified by Energy Star   11 percent of all commercial office space certified by LEED

  Considerable variation in adoption of energy efficiency technologies   Diffusion has been more rapid in areas with higher incomes and sound

property market fundamentals (low vacancy rates, high rents and prices)   This has important implications for underperforming markets (e.g.,

Dallas, Detroit, and Tampa); these markets will lag behind in energy efficiency improvements

Conclusions and implications (II) Energy paradox less important for commercial buildings

  Technology seems to diffuse faster in larger properties   Improving energy efficiency of smaller buildings may need additional

“nudge”

  Diffusion of energy efficient technology more responsive to energy prices than “green” technology   Lends additional support for efficiency of investment decisions in

commercial property sector (as opposed to residential sector)

  Diffusion of “green” technology is facilitated by human capital (i.e., LEED APs) and governmental policies   The environmental implications of this innovation remains unclear