The Diffusion of Energy Efficiency in Building
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Transcript of The Diffusion of Energy Efficiency in Building
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