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

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

    • The Diffusion of Energy Efficiency in Building Nils Kok Marquise McGraw John M. QuigleyMaastricht University UC Berkeley UC Berkeley AEA Meetings, Denver January 2011
    • The “energy paradox,” revisitedIncreasing 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 marketsEnergy 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 LEED48 MSAs, 1995 – 2010Dominant forces in the commercial and institutional market  2010:   2010:   10 percent of buildings   5 percent of buildings   30 percent of stock   10 percent of stock  Size effect (Snyder, et al., 2003)   Registered: 27,000 buildings (6b sq.ft.)
    • Labels reflect building technologyEnergy 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
    • Diffusion of certified spaceSubstantial differences in timing and growth across MSAs New York New York Los Angeles Los Angeles
    • The diffusion of energy efficiency in building (I)Determinants of timing and growth “What determines the geographic dispersion in the timing and growth of energy efficient technology in office buildings?”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
    • Variations in the expected cost savingsSimple correlations, 2010 cross-section
    • The diffusion of energy efficiency in building (II) Determinants of timing and growth2.  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 conditionsSimple correlations, 2010 cross-section
    • The diffusion of energy efficiency in building (III)Determinants of timing and growth4.  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 characteristicsSimple 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) Fraction it = α + βX it−2 + εit   Where X it−2 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) ΔFractionit = α + βΔX it −2 + ε it   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
    • Basic regression resultsLEED explained by income, Energy Star by energy prices
    • Arellano-Bond GMM Regression ResultsHealthy market fundamentals increase technology diffusion
    • Conclusions and implicationsEconomic 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