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CONSISTENT RESIDENTIAL EFFICIENCY IMPROVEMENTS ACROSS END-USES: THEORETICAL AND EMPIRICAL INSIGHTS
Mike BlackhurstAssistant ProfessorThe University Of Texas At AustinCivil, Architectural, & Environmental Engineering
Multiple Perspectives on Technical Efficiency
What happens if you double the efficiency of your air conditioner?
The technologist says, “You use half the energy.”
The economist says, “You turn down the thermostat.”
The social scientist says, “Who made the decision?”
The “Rebound Effect”
o aka “Jevon’s paradox” or “the energy efficiency paradox”
o Efficiency decreases resources needed for service
o Efficiency also decreases the cost of service, which…
o Induces income and substitution effects and…
o Likely other behavioral responses and drivers
Rebound Terminology
Category Description Example
Direct rebound
Homeowners use more of the more efficient service
Consumer drives more with a more fuel efficient car
Indirect rebound
Homeowners re-spending on other goods and services
Savings from efficient lighting spend on 2nd refrigerator
Economy-wide rebound
More efficient production and shifts in demand alter economic structure and growth
A more efficient steam engine increases production changes structural relationships and leads to economic growth
Magnitude of Rebound DebatedN
et
Energ
y E
last
icit
y
(% C
hange in E
nerg
y /
% C
hange in
Effi
ciency
)
Technically Feasible After Direct ReboundAfter direct + indirect
rebound
-100%
-80%
-60%
-40%
-20%
0%
Technically feasible energy savings
o Start with technical definition of efficiency:
o Direct rebound usually estimated as own-price elasticity of demand
o Indirect rebound (re-spending) is estimated by modeling by income and substitution effects in response to a discrete efficiency change
Single-Service Rebound Model
Challenge to Single Service Model
Modified from Blackhurst and Ghosh (under review)
Two Service Model
0 00 0
Two Service Model
Two Service Model: Re-Arranged
technical response (1st and 2nd order)
direct rebound for C (1st order)
indirect rebound from C to T ind. of e correlation (1st order)
indirect rebound from j to i from e correlation (2nd order)
indirect rebound from i to j from e correlation (2nd order)
Application of Two-Service Model
Would homeowners in more efficient homes drive more?
o Include electricity (C) and transportation (T) services
o Used constant elasticity of substitution (CES) production function
o Can provide draft manuscript for more details
Empirical Assumptions
ParameterBase Case Min. Max. Ref
Income category ($1,000) $25-30 $40-45$70-$75 BLS 2011
Short-run elasticity of sub., sSR 0.15 0.1 0.2 BLS 2011, Dahl 1993,Brons 2008,
Graham 2002Long-run elasticity of sub., sLR 0.8 0.7 0.9
Electricity Nominal Shares, aC 1.3% 0.4% 2.2% BLS 2011
Gasoline Nominal Shares, aT 2.9% 0.8% 5.1% BLS 2011
Electricity Real Shares 27% 26% 31% BLS 2011
Gasoline Real Shares 73% 74% 69% BLS 2011
Efficiency correlation, heT(eC) 2.1 0.5 6 Replacements assuming different code- and above-code
performanceheC(eT) 0.48 2.00 0.17
Energy Elasticity,
(-1)
Direct Rebound
[hei(Ei)+1] Ei/E
Technically feasible elasticity
-1(Ei/E + hei(ej)Ej/E)
Cross-sector,
From trans to resid with c.c.
hei(ej) hej (Ei )Ei/E
Cross-sector (indirect),
independent of c.c.
hei(Ej) Ej/E
Cross-sector, From resid to trans
with c.c.
hei(ej) [hej(Ej)+1] Ej/E
Short-run response
Long-run response
Rebound Across Resid and Trans Sectors: Driven by Changes in Electricity Efficiency
Results shown for median income range ($40-$45k)
Energy Elasticity,
Direct Rebound
[hei(Ei)+1] Ei/E
Technically feasible elasticity
-1(Ei/E + hei(ej)Ej/E)
Cross-sector,
From trans to resid with c.c.
hei(ej) hej (Ei )Ei/E
Cross-sector (indirect),
independent of c.c.
hei(Ej) Ej/E
Cross-sector, From resid to trans
with c.c.
hei(ej) [hej(Ej)+1] Ej/E
Short-run response
Long-run response
Rebound Across Resid and Trans Sectors: Driven by Changes in Electricity Efficiency
Results shown for median income range ($40-$45k)
Rebound Across Resid and Trans Sectors: Driven by Changes in Vehicle Efficiency
Direct Rebound, hei(Ei)
Technically feasible elasticity
Cross-sector,
From resid to trans with c.c.
Cross-sector (indirect),
independent of c.c.
Cross-sector, From trans to resid
with c.c.
Energy Elasticity,
Short-run response
Long-run response
Results shown for median income range ($40-$45k)
Other Behavioral Drivers
Behavior or Driver
Effect on technology… Reference(s)
Choice Use
Cost minimization, income constraint
High implicit discount rate observed Hausman 1979;Sanstad et al. 1995
Demographic Education levels, ownership, & tenure increased technology adoption
? Hartman 1998; Michelson & Madner 2011
Physical household characteristics
Increased home age and size promote technology adoption
? Michelson and Madner 2011
Environmental awareness and valuation
Increased awareness & valuation increased adoption
? Cummings and Taylor 1999; Hanley et al. 1990; Bateman et al. 2011
Technological awareness
Homeowners misperceive technology performance at extremes; Self-reported awareness increased adoption
? Attari 2010;
Nair et al 2010
Other Behavioral Drivers
Do homeowners correlate or compensate drivers of energy technology choice and use?
o Limited qualitative insights • Correlation and compensation observed across a
variety of “green” behaviors [Thøgersen & Ölander 2003]
• Self-reported behavior changes with PV adoption [Keirstead 2007; McAndrews; Schweizer-Reis et al. 2000 ]
o Implications for rebound?
Empirical Research
o Estimate the impact of marginal technical change within and across end uses on electricity use and rebound
• If choose technology A versus • If choose both technology A and technology B
Pecan Street Research Institute
Static data High resolution consumption data
Representative Sample Data
Variable Range
Climate Monthly CDD Mean= 292, SD= 257
Structural Floorspace (square feet)Windows area (square feet)Age of the house
Mean= 2,019, SD= 719Mean= 245, SD= 106Mean= 21.4, SD= 23.6
Demog-raphic
Occupancy TenureHH income
Mean= 2.7, SD= 1.2Mean= 6.6, SD= 7.6Mean= $128k SD= $62k
Self-reported behaviors
Thermostat set point – summerTV hours per monthDishwasher loads per monthClothes washer loads per monthEducation (interval)
Mean= 76.9, SD= 2.2Mean= 107, SD= 71.9Mean= 14.3, SD= 8.1Mean= 17.1, SD= 9.2
Technology choices
Attic insulation R-valueAir conditioning Energy Efficiency Ratio (EER)No. of devicesDummy variables, Programmable thermostat, Double pane windows, Energy star appliances, Solar PV (count = 37), EV (count = 14), Electric heater
Mean= 28.6, SD= 8.4Mean= 10.5, SD= 1.7Mean= 3.34, SD= 1.8
Electricity Electricity consumption (KWh/month) Mean= 963, SD= 938
Sample includes one year of monthly electricity consumption for 79 homes
Model Specification
o Where
• Yitλ represents monthly electricity consumption
• βj are the predictor coefficient fixed effects
• βi are the coefficient estimates for random effects
• Sijλ represents a series of household structural factors
• Dijλ represents a series of household demographic factors
• Bijλ represents household behaviors and cognitive factors
• Xij interaction terms for different technology choice combinations
• Ri represents the household identification codes
Results with No Interaction Terms
Explanatory variable Coefficient p-value % change in Y for: 1 unit (or *10%) increase in XProgTherm -0.236 0.026 -21.0%
ES Refrig -0.164 0.025 -15.1%
1/sqrt(Sq Ft) -75.7 < .0001 8.35%*
Devices 0.067 0.027 7.00%
CWloads -1.958 0.053 1.20%*
Home R value -0.009 0.087 -0.91%
Cooling Degree Days 0.001 < .0001 0.14%
EV 0.087 0.339 9.14%
ES DW -0.085 0.325 -8.14%
2-P window -0.081 0.346 -7.78%
ES Clothes washer -0.069 0.378 -6.68%
PV 0.054 0.487 5.61%
AC EER 0.006 0.738 0.65%
1/occupancy 0.141 0.465 -0.21%*
Dishwasher loads 0.001 0.879 0.09%
1/Window Sq Ft -2.086 0.924 0.09%*
Income 2.00E-07 0.78 0.00%Constant (b0) 8.348 < .0001 -
Rebound from Marginal Efficiency Gains: Demonstrative Empirical Results
Rebound with Marginal Efficiency Gains
Multi-pane windows installed, AC efficiency increased
Multi-pane windows installed at indicated AC efficiency
Rebound with Marginal Efficiency Gains
Preliminary PV Results
o Order of technical change matters
Order of technical change
Increase AC Efficiency
Increase Insul.
Install multi-pane Windows
Purchase EnergyStar Appliances
Have PV before efficiency
- - + -
Install PV after efficiency change
+ low EER- high EER
+ low R-values- high R-values
- -
+ Statistically significant increase in electricity consumption Statistically significant decrease in electricity consumption
-
Implications
o Literature is mixed as to whether consumers correlate or compensate valuations across energy technology choice/use
o Empirical work suggests consumers MAY leverage efficiency gains for services ACROSS end uses; our results are also mixed
o Rebound is relative to the current efficient technical state of the home and order of technical change
o These findings suggest the dominant single-service rebound paradigm is misleading
Implications
o Consistent efficiency change across end uses can mitigate consumer responses; however…
o Consumers can and do expend energy services; thus…
o Models of rebound need to recognize service expansion
Implications
o The literature assumes PV exclusively replaces conventional grid energy sources; however…
o Behavioral implications of PV are entirely unclear
o Consumers will treat long-run operating cost of PV as zero
o Results are mixed with respect to consumers responses to both efficiency change and installation of PV
Related Ongoing/Future Work
o Rebound across resources (water/electricity/natural gas/gasoline)
o Comparing Empirical and Estimated Energy Consumption (RECS/BeOpt)
o Does Weather Influence the Use of PV for Discretionary Electricity End Uses?
o Estimating Total and End-Use Residential Water (Energy) Demands Using Energy (Water) Demands
o Comparing the Observed and Estimated Performance of Residential Water Efficient Fixtures and Appliances
Acknowledgements
o This work was funded by • The University of Texas at Austin• Bill and Melinda Gates Foundation Fellowship
o PhD students• Nour El-Imane Bouhou• Pamela Torres• Alison Wood
o MS Students• Bruk Berhanu• Neftali Torres
o Post doc• Sarah Taylor-Lange
CONSISTENT RESIDENTIAL EFFICIENCY IMPROVEMENTS ACROSS END-USES: THEORETICAL AND EMPIRICAL INSIGHTS
Mike BlackhurstAssistant ProfessorThe University Of Texas At AustinCivil, Architectural, & Environmental Engineering
Referenceso Blackhurst, MF, and NK Ghosh. “The Rebound Effect with Consistent Efficiency Improvements and Implications for Cross-Sector
Rebound.” Ecological Economics (submitted for review).
o Attari, S. Z., M. L. DeKay, C. I. Davidson, and W. B. de Bruin. 2010. “Public Perceptions of Energy Consumption and Savings.” Proceedings of the National Academy of Sciences 107 (37): 16054–16059.
o Thøgersen, J., and F. Ölander. 2003. “Spillover of Environment-Friendly Consumer Behaviour.” Journal of Environmental Psychology 23 (3): 225–236.
o Keirstead, J. 2007. “Behavioural Responses to Photovoltaic Systems in the UK Domestic Sector.” Energy Policy 35 (8): 4128–4141.
o McAndrews, K. “To Conserve or Consume: Behavior Change in Residential Solar PV Owners.” The University of Texas at Austin, 2012.
o Hausman, Jerry A. “Individual Discount Rates and the Purchase and Utilization of Energy-Using Durables.” The Bell Journal of Economics 10, no. 1 (April 1, 1979): 33–54. doi:10.2307/3003318.
o Sanstad, Alan H., Carl Blumstein, and Steven E. Stoft. “How High Are Option Values in Energy-Efficiency Investments?” Energy Policy 23, no. 9 (1995): 739–743.
o Hartman, R. S. “Self-Selection Bias in the Evolution of Voluntary Energy Conservation Programs.” The Review of Economics and Statistics (1988): 448–458.
o Michelsen, C., and R. Madlener. “Homeowners’ Preferences for Adopting Residential Heating Systems: A Discrete Choice Analysis for Germany.” FCN Working Papers (2011).
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o Dahl, C. A. “A Survey of Energy Demand Elasticities in Support of the Development of the NEMS” (1993). http://mpra.ub.uni-muenchen.de/13962/.
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o BLS (U.S. Bureau of Labor Statistics). “Consumer Expenditure Survey,” 2011. http://www.bls.gov/cex/.
Single service rebound model
o Using technical definition of efficiency:
o Using CES production function
Rebound with Marginal Efficiency Gains
Multi-pane windows installed, AC efficiency increased
Multi-pane windows installed at indicated AC efficiency
Energy Elasticity,
(-1)
Direct Rebound
[hei(Ei)+1] Ei/E
Technically feasible elasticity
-1(Ei/E + hei(ej)Ej/E)
Cross-sector,
From trans to resid with c.c.
hei(ej) hej (Ei )Ei/E
Cross-sector (indirect),
independent of c.c.
hei(Ej) Ej/E
Cross-sector, From resid to trans
with c.c.
hei(ej) [hej(Ej)+1] Ej/E
Short-run response
Long-run response
Rebound Across Resid and Trans Sectors: Driven by Changes in Electricity Efficiency
Results shown for median income range ($40-$45k)
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