[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v52y2015is1ps30-s40.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988315002364
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2015.08.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anna Alberini, Will Gans, and Charles Towe, 2016. "Free Riding, Upsizing, and Energy Efficiency Incentives in Maryland Homes," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    2. 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.
    3. Papineau, Maya, 2017. "Setting the standard? A framework for evaluating the cost-effectiveness of building energy standards," Energy Economics, Elsevier, vol. 64(C), pages 63-76.
    4. Boogen, Nina & Datta, Souvik & Filippini, Massimo, 2021. "Estimating residential electricity demand: New empirical evidence," Energy Policy, Elsevier, vol. 158(C).
    5. Boogen, Nina & Datta, Souvik & Filippini, Massimo, 2017. "Demand-side management by electric utilities in Switzerland: Analyzing its impact on residential electricity demand," Energy Economics, Elsevier, vol. 64(C), pages 402-414.
    6. Olayinka Oyekola & Olapeju C. Ogunmokun & Martha A. Omolo & Samuel Odewunmi, 2023. "Gender, Legal Origin, and Accounting Disclosure: Evidence from More Than 140,000 Firms," Discussion Papers 2313, University of Exeter, Department of Economics.
    7. Tilov, Ivan & Farsi, Mehdi & Volland, Benjamin, 2020. "From frugal Jane to wasteful John: A quantile regression analysis of Swiss households’ electricity demand," Energy Policy, Elsevier, vol. 138(C).
    8. Miller, Mark & Alberini, Anna, 2016. "Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: Evidence from U.S. Data," Energy Policy, Elsevier, vol. 97(C), pages 235-249.
    9. Schleich, Joachim & Fleiter, Tobias, 2019. "Effectiveness of energy audits in small business organizations," Resource and Energy Economics, Elsevier, vol. 56(C), pages 59-70.
    10. Apps, Patricia & Mendolia, Silvia & Walker, Ian, 2013. "The impact of pre-school on adolescents’ outcomes: Evidence from a recent English cohort," Economics of Education Review, Elsevier, vol. 37(C), pages 183-199.
    11. Tymon Słoczyński, 2015. "The Oaxaca–Blinder Unexplained Component as a Treatment Effects Estimator," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 588-604, August.
    12. Fatema, Naureen, 2019. "Can land title reduce low-intensity interhousehold conflict incidences and associated damages in eastern DRC?," World Development, Elsevier, vol. 123(C), pages 1-1.
    13. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    14. Mano, Yukichi & Akoten, John & Yoshino, Yutaka & Sonobe, Tetsushi, 2014. "Teaching KAIZEN to small business owners: An experiment in a metalworking cluster in Nairobi," Journal of the Japanese and International Economies, Elsevier, vol. 33(C), pages 25-42.
    15. Pedro Linares & Xavier Labandeira, 2010. "Energy Efficiency: Economics And Policy," Journal of Economic Surveys, Wiley Blackwell, vol. 24(3), pages 573-592, July.
    16. Fullerton Jr., Thomas M. & Macias, David R. & Walke, Adam G., 2016. "Residential Electricity Demand in El Paso," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 46(2), December.
    17. Esaka, Taro, 2013. "Evaluating the effect of de facto pegs on currency crises," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 943-963.
    18. Robert W. Hahn & Robert D. Metcalfe, 2021. "Efficiency and Equity Impacts of Energy Subsidies," American Economic Review, American Economic Association, vol. 111(5), pages 1658-1688, May.
    19. Sánchez-Braza, Antonio & Pablo-Romero, María del P., 2014. "Evaluation of property tax bonus to promote solar thermal systems in Andalusia (Spain)," Energy Policy, Elsevier, vol. 67(C), pages 832-843.
    20. Ensieh Shojaeddini & Ben Gilbert, 2023. "Heterogeneity in the Rebound Effect: Evidence from Efficient Lighting Subsidies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(1), pages 173-217, January.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:52:y:2015:i:s1:p:s30-s40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.