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Direct and Indirect Rebound Effects for U.S. Households With Input-Output Analysis Brinda A. Thomas Ph.D. Candidate, Engineering & Public Policy Dept.

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Presentation on theme: "Direct and Indirect Rebound Effects for U.S. Households With Input-Output Analysis Brinda A. Thomas Ph.D. Candidate, Engineering & Public Policy Dept."— Presentation transcript:

1 Direct and Indirect Rebound Effects for U.S. Households With Input-Output Analysis Brinda A. Thomas Ph.D. Candidate, Engineering & Public Policy Dept. Carnegie Mellon University Climate and Energy Decision-Making Center Annual Meeting 21 May 2012

2 Energy Efficiency Opportunities for Carbon Mitigation are Substantial & Cheap Efficiency contributes 66% of CO 2 abatement in 2020 and 52% of CO 2 abatement in 2030 IEA MotivationMethods & DataResultsConclusion

3 Economic, Technical & Behavioral Limits to Energy Efficiency 2 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 MotivationMethods & DataResultsConclusion

4 Rebound = Direct (Own-Price Elasticity) + Indirect (Cross-Price Elasticity ) 3 Direct + Indirect Rebound Effect Model Assumptions 1.Each fuel provides a single energy service 2.Basic elasticity properties hold (Engel Agg., Cournot Agg. & Slutsky Decomp.) 3.Compensated (constant-utility) cross-price elasticities for all goods are constant 4.Ignoring capital costs of efficiency (overestimate: Henly et al., 1987) Expected Efficiency Savings =  % reduction in household energy expenditures = E s s s I  MotivationMethods & DataResultsConclusion 3 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. Survey EIO-LCA 2002 model EIO-LCA 2002 model Houthakker and Taylor (1966, 2010)

5 Rebound Effects Vary by Unit of Analysis 4 MotivationMethods & DataResultsConclusion

6 Rebound in Primary Energy & CO 2 e varies by fuel 5 MotivationMethods & DataResultsConclusion Error bars from uncertainty in direct rebound (± %) & in indirect rebound due to income elasticity functional form (± 1 - 2%)

7 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 6 MotivationMethods & DataResultsConclusions

8 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 7 Policy Implications MotivationMethods & DataResultsConclusions

9 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, Acknowledgements 8


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