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Information v. energy efficiency incentives: Evidence from residential electricity consumption in Maryland

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  • Alberini, Anna
  • Towe, Charles

Abstract

We focus on two utility programs intended to reduce energy usage and the associated CO2 emissions—a home energy audit and rebates on the purchase of high-efficiency air-source heat pumps. We use a unique panel dataset from participating and non-participating households to estimate the average treatment effect of participating in either program on electricity usage. We fit models with household-by-season, season-by-year, and household-by-year fixed effects to account for all possible confounders that might influence energy usage. Since the programs are voluntary, we seek to restore near-exogeneity of the program “treatment” by matching participating households with control households. We deploy coarsened exact matching (CEM; Iacus et al., 2011) as our main matching method. We ask whether it is sufficient to match households based on past electricity usage, or if we gain by adding structural characteristics of the home, including heating system type. We find that the two programs reduce electricity usage by 5% on average. The effects are strong in both winter and summer for the energy audit groups but appear to be stronger in the winter for the heat pump rebate group. Adding house characteristics to the matching variables does seem to affect results, suggesting that using past usage alone, or house characteristics alone, may not be sufficient to identify the effects of program participation.

Suggested Citation

  • Alberini, Anna & Towe, Charles, 2015. "Information v. energy efficiency incentives: Evidence from residential electricity consumption in Maryland," Energy Economics, Elsevier, vol. 52(S1), pages 30-40.
    • Handle: RePEc:eee:eneeco:v:52:y:2015:i:s1:p:s30-s40
    DOI: 10.1016/j.eneco.2015.08.013
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    1. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential consumption of gas and electricity in the U.S.: The role of prices and income," Energy Economics, Elsevier, vol. 33(5), pages 870-881, September.
    2. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    3. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    4. Christian L. E. Franzke, 2014. "Nonlinear climate change," Nature Climate Change, Nature, vol. 4(6), pages 423-424, June.
    5. Gans, Will & Alberini, Anna & Longo, Alberto, 2013. "Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland," Energy Economics, Elsevier, vol. 36(C), pages 729-743.
    6. David S. Loughran and Jonathan Kulick, 2004. "Demand-Side Management and Energy Efficiency in the United States," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 19-44.
    7. Abadie, Alberto & Imbens, Guido W., 2011. "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 1-11.
    8. Paul L. Joskow & Donald B. Marron, 1992. "What Does a Negawatt Really Cost? Evidence from Utility Conservation Programs," The Energy Journal, , vol. 13(4), pages 41-74, October.
    9. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    10. Koichiro Ito, 2014. "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing," American Economic Review, American Economic Association, vol. 104(2), pages 537-563, February.
    11. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential Consumption of Gas and Electricity in the U.S.: The Role of Prices and Income," Sustainable Development Papers 99637, Fondazione Eni Enrico Mattei (FEEM).
    12. Michael Greenstone & Elizabeth Kopits & Ann Wolverton, 2013. "Developing a Social Cost of Carbon for US Regulatory Analysis: A Methodology and Interpretation," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 7(1), pages 23-46, January.
    13. Terry M. Dinan, 2013. "Testimony on Federal Financial Support for Fuels and Energy Technologies," Reports 43993, Congressional Budget Office.
    14. Hassett, Kevin A. & Metcalf, Gilbert E., 1995. "Energy tax credits and residential conservation investment: Evidence from panel data," Journal of Public Economics, Elsevier, vol. 57(2), pages 201-217, June.
    15. Terry M. Dinan, 2013. "Testimony on Federal Financial Support for Fuels and Energy Technologies," Reports 43993, Congressional Budget Office.
    16. Boomhower, Judson & Davis, Lucas W., 2014. "A credible approach for measuring inframarginal participation in energy efficiency programs," Journal of Public Economics, Elsevier, vol. 113(C), pages 67-79.
    17. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    18. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    19. Maximilian Auffhammer & Carl Blumstein & Meredith Fowlie, 2008. "Demand-Side Management and Energy Efficiency Revisited," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 91-104.
    20. Terry M. Dinan, 2013. "Testimony on Federal Financial Support for Fuels and Energy Technologies," Reports 43993, Congressional Budget Office.
    21. Hartman, Raymond S, 1988. "Self-Selection Bias in the Evaluation of Voluntary Energy Conservation Programs," The Review of Economics and Statistics, MIT Press, vol. 70(3), pages 448-458, August.
    22. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    23. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
    24. Lucas W. Davis, 2008. "Durable goods and residential demand for energy and water: evidence from a field trial," RAND Journal of Economics, RAND Corporation, vol. 39(2), pages 530-546, June.
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    More about this item

    Keywords

    Energy efficiency; Household behavior; Energy efficiency incentives; Electricity usage; Home energy audit;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • H3 - Public Economics - - Fiscal Policies and Behavior of Economic Agents

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