IDEAS home Printed from https://ideas.repec.org/a/eee/jeeman/v68y2014i3p480-506.html
   My bibliography  Save this article

Utility rebates for ENERGY STAR appliances: Are they effective?

Author

Listed:
  • Datta, Souvik
  • Gulati, Sumeet

Abstract

We estimate the impact of utility cash rebates on the market share of ENERGY STAR appliances by exploiting the variation in timing and size of rebates across US states. We find that a dollar increase in the population-weighted utility rebate raises the share of ENERGY STAR qualified clothes washers by 0.4%, but does not affect dishwasher and refrigerator shares. Using information on energy saved by an ENERGY STAR appliance and assuming a redemption rate of 40%, the cost per tonne of carbon saved is about $140 for the clothes washers rebate program. The corresponding cost of a megawatt hour saved, about $28, is lower than the estimated cost of building and operating an additional power plant and the average on-peak spot price. We conclude that the ENERGY STAR clothes washers rebate program is, on average, a cost-effective way for utilities to reduce electricity demand.

Suggested Citation

  • Datta, Souvik & Gulati, Sumeet, 2014. "Utility rebates for ENERGY STAR appliances: Are they effective?," Journal of Environmental Economics and Management, Elsevier, vol. 68(3), pages 480-506.
  • Handle: RePEc:eee:jeeman:v:68:y:2014:i:3:p:480-506
    DOI: 10.1016/j.jeem.2014.09.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0095069614000722
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jeem.2014.09.003?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. Mark E Schaffer & Steven Stillman, 2006. "XTOVERID: Stata module to calculate tests of overidentifying restrictions after xtreg, xtivreg, xtivreg2, xthtaylor," Statistical Software Components S456779, Boston College Department of Economics, revised 15 Jan 2016.
    2. Karla Hemming & Jen Marsh, 2013. "A menu-driven facility for sample-size calculations in cluster randomized controlled trials," Stata Journal, StataCorp LP, vol. 13(1), pages 114-135, March.
    3. Kenneth E. Train & Terry Atherton, 1995. "Rebates, Loans, and Customers' Choice of Appliance Efficiency Level: Combining Stated- and Revealed-Preference Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 55-70.
    4. Gallagher, Kelly Sims & Muehlegger, Erich, 2011. "Giving green to get green? Incentives and consumer adoption of hybrid vehicle technology," Journal of Environmental Economics and Management, Elsevier, vol. 61(1), pages 1-15, January.
    5. Webber, C. A. & Brown, R. E. & Koomey, J., 2000. "Savings estimates for the E S(R) voluntary labeling program," Energy Policy, Elsevier, vol. 28(15), pages 1137-1149, December.
    6. Chandra, Ambarish & Gulati, Sumeet & Kandlikar, Milind, 2010. "Green drivers or free riders? An analysis of tax rebates for hybrid vehicles," Journal of Environmental Economics and Management, Elsevier, vol. 60(2), pages 78-93, September.
    7. Toshi H. Arimura, Shanjun Li, Richard G. Newell, and Karen Palmer, 2012. "Cost-Effectiveness of Electricity Energy Efficiency Programs," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    8. William D. Nordhaus, 2007. "A Review of the Stern Review on the Economics of Climate Change," Journal of Economic Literature, American Economic Association, vol. 45(3), pages 686-702, September.
    9. 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.
    10. Nadel, Steven & Geller, Howard, 1996. "Utility DSM : What have we learned? Where are we going?," Energy Policy, Elsevier, vol. 24(4), pages 289-302, April.
    11. Stern,Nicholas, 2007. "The Economics of Climate Change," Cambridge Books, Cambridge University Press, number 9780521700801, October.
    12. Sanchez, Marla C. & Brown, Richard E. & Webber, Carrie & Homan, Gregory K., 2008. "Savings estimates for the United States Environmental Protection Agency's ENERGY STAR voluntary product labeling program," Energy Policy, Elsevier, vol. 36(6), pages 2098-2108, June.
    13. B. Howarth, Richard & Haddad, Brent M. & Paton, Bruce, 2000. "The economics of energy efficiency: insights from voluntary participation programs," Energy Policy, Elsevier, vol. 28(6-7), pages 477-486, June.
    14. James M. Sallee, 2011. "The Surprising Incidence of Tax Credits for the Toyota Prius," American Economic Journal: Economic Policy, American Economic Association, vol. 3(2), pages 189-219, May.
    15. Thompson, Patrick A & Noordewier, Thomas, 1992. "Estimating the Effects of Consumer Incentive Programs on Domestic Automobile Sales," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 409-417, October.
    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. Souvik Datta & Massimo Filippini, 2012. "Analysing the Impact of ENERGY STAR Rebate Policies in the US," CEPE Working paper series 12-86, CEPE Center for Energy Policy and Economics, ETH Zurich.
    2. Galarraga, Ibon & Abadie, Luis M. & Ansuategi, Alberto, 2013. "Efficiency, effectiveness and implementation feasibility of energy efficiency rebates: The “Renove” plan in Spain," Energy Economics, Elsevier, vol. 40(S1), pages 98-107.
    3. 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.
    4. Lim, Seong-Rin & Schoenung, Julie M., 2011. "Measurement and analysis of product energy efficiency to assist energy star criteria development: An example for desktop computers," Energy Policy, Elsevier, vol. 39(12), pages 8003-8010.
    5. Sun, Shanxia & Delgado, Michael & Khanna, Neha, 2017. "Hybrid Vehicles and Household Driving Behavior: Implications for Miles Traveled and Gasoline Consumption," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258502, Agricultural and Applied Economics Association.
    6. Garth Heutel & Erich Muehlegger, 2015. "Consumer Learning and Hybrid Vehicle Adoption," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(1), pages 125-161, September.
    7. Parry, Ian W.H. & Evans, David & Oates, Wallace E., 2014. "Are energy efficiency standards justified?," Journal of Environmental Economics and Management, Elsevier, vol. 67(2), pages 104-125.
    8. Jeremy Dijk & Nathan Delacrétaz & Bruno Lanz, 2022. "Technology Adoption and Early Network Infrastructure Provision in the Market for Electric Vehicles," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(3), pages 631-679, November.
    9. Jonathan E. Hughes & Molly Podolefsky, 2015. "Getting Green with Solar Subsidies: Evidence from the California Solar Initiative," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 2(2), pages 235-275.
    10. Schleich, Joachim & Gassmann, Xavier & Faure, Corinne & Meissner, Thomas, 2016. "Making the implicit explicit: A look inside the implicit discount rate," Energy Policy, Elsevier, vol. 97(C), pages 321-331.
    11. Jiménez, Juan Luis & Perdiguero, Jordi & García, Carmen, 2016. "Evaluation of subsidies programs to sell green cars: Impact on prices, quantities and efficiency," Transport Policy, Elsevier, vol. 47(C), pages 105-118.
    12. Maxime C. Cohen & Ruben Lobel & Georgia Perakis, 2016. "The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption," Management Science, INFORMS, vol. 62(5), pages 1235-1258, May.
    13. Hunt Allcott & Michael Greenstone, 2012. "Is There an Energy Efficiency Gap?," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 3-28, Winter.
    14. Mills, Bradford & Schleich, Joachim, 2010. "What's driving energy efficient appliance label awareness and purchase propensity?," Energy Policy, Elsevier, vol. 38(2), pages 814-825, February.
    15. Nathan Delacrétaz & Bruno Lanz & Jeremy van Dijk, 2020. "The chicken or the egg: Technology adoption and network infrastructure in the market for electric vehicles," IRENE Working Papers 20-08, IRENE Institute of Economic Research.
    16. Azarafshar, Roshanak & Vermeulen, Wessel N., 2020. "Electric vehicle incentive policies in Canadian provinces," Energy Economics, Elsevier, vol. 91(C).
    17. James M. Sallee, 2011. "The Taxation of Fuel Economy," Tax Policy and the Economy, University of Chicago Press, vol. 25(1), pages 1-38.
    18. Lori S. Bennear & Jonathan M. Lee & Laura O. Taylor, 2013. "Municipal Rebate Programs for Environmental Retrofits: An Evaluation of Additionality and Cost‐Effectiveness," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 32(2), pages 350-372, March.
    19. Gulati, Sumeet & McAusland, Carol & Sallee, James M., 2017. "Tax incidence with endogenous quality and costly bargaining: Theory and evidence from hybrid vehicle subsidies," Journal of Public Economics, Elsevier, vol. 155(C), pages 93-107.
    20. Muehlegger, Erich & Rapson, David S., 2022. "Subsidizing low- and middle-income adoption of electric vehicles: Quasi-experimental evidence from California," Journal of Public Economics, Elsevier, vol. 216(C).

    More about this item

    Keywords

    Eco-labelling; Energy efficiency; Appliances; Utility rebates; Carbon saving; Energy saving;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • L68 - Industrial Organization - - Industry Studies: Manufacturing - - - Appliances; Furniture; Other Consumer Durables
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    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:jeeman:v:68:y:2014:i:3:p:480-506. 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/inca/622870 .

    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.