Direct and Indirect Rebound Effects for U.S. Households With Input-Output Analysis
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Direct and Indirect Rebound Effects for U.S. Households With Input-Output Analysis
Brinda A. ThomasPh.D. Candidate, Engineering & Public Policy Dept.
Carnegie Mellon Universitybrindat@cmu.edu
Climate and Energy Decision-Making CenterAnnual Meeting
21 May 2012
Energy Efficiency Opportunities for Carbon Mitigation are Substantial & Cheap
Efficiency contributes 66% of CO2 abatement in 2020 and 52% of CO2 abatement in 2030
IEA 20092
Economic, Technical & Behavioral Limits to Energy Efficiency
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• Energy Efficiency “gap” (Jaffe and Stavins, 1994, Howarth and Sanstad, 1995, Sorrell et al., 2004)
• Engineering vs. Actual Conditions for Efficiency (Vine et al., 1994)
• Rebound Effects– Households or firms may increase energy service demand due to
• Direct Rebound: the lower price of energy services with efficiency• Indirect Rebound: re-spending energy cost savings and embodied energy• Macroeconomic Effects
– Basic definition: 1 – (Actual Savings/Potential Savings)– Measured by various elasticities (% in demand wrt % in price)
• Stakeholders include policymakers, utilities, program evaluators, and analysts involved with– State and federal energy efficiency policies, utility demand-side management
programs, and dynamic/forecasting models of energy demand
Rebound = Direct (Own-Price Elasticity) + Indirect (Cross-Price Elasticity )
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Direct + Indirect Rebound Effect Model
Assumptions1.Each fuel provides a single energy service2.Basic elasticity properties hold (Engel Agg., Cournot Agg. & Slutsky Decomp.)3.Compensated (constant-utility) cross-price elasticities for all goods are constant4.Ignoring capital costs of efficiency (overestimate: Henly et al., 1987)
Expected Efficiency Savings = % reduction in household energy expenditures = EsssI
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Dubin et al. (1983)Greening et al. (2000)Greene (2011)
Dubin et al. (1983)Greening et al. (2000)Greene (2011)
2004 U.S. Consumer Exp. Survey2004 U.S. Consumer Exp. Survey EIO-LCA 2002 model
www.eiolca.netEIO-LCA 2002 modelwww.eiolca.netHouthakker and
Taylor (1966, 2010)Houthakker and Taylor (1966, 2010)
Rebound Effects Vary by Unit of Analysis
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Rebound in Primary Energy & CO2e varies by fuel
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Error bars from uncertainty in direct rebound (± 3 - 11%) & in indirect rebound due to income elasticity functional form (± 1 - 2%)
Summary of Findings• 71-82% of expected efficiency savings can be achieved after
accounting for direct and indirect rebound effects– 10-20% direct and 5-11% indirect rebound effects, depending on fuel– Electricity and gasoline efficiency have lower rebound effects than natural
gas, depending on prices and budget shares
• Indirect rebound does not appear to be bounded by the energy share of GDP (Schipper and Grubb, 2000)
– We overestimate the rebound effect by ignoring effects possible higher capital costs of efficient appliances and vehicles
• Rebound highly sensitive to energy prices and electricity grid mix• States with high energy prices and cleaner electricity have higher
% rebound effects
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• Policies explicitly designed to counter rebound effects may not be needed– Difficult to target higher energy prices only to those households
making efficiency investments – this might impose even more barriers to efficiency investments
– A carbon price at the social cost of carbon ensures that rebound effects – and energy consumption in general – yield net social benefits
• Study of rebound effects allows for:– improved targeting of efficiency policies (by fuel and end-use)– better assessments of the cost-effectiveness of energy efficiency
investments– Improved forecasts of energy demand in scenarios with large
investments in energy efficiency
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Policy Implications
Thanks to Ines Azevedo, M. Granger Morgan, Scott Matthews, Karen Turner, Zeke Hausfather, and Chris Weber for useful discussions.
Funding by:
Contact Info: Brinda Thomas, brindat@cmu.edu
Acknowledgements
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