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A Top-Down Economic Efficiency Analysis of U.S. HouseholdEnergy Consumption

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  • J. Wesley Burnett
  • Jessica Madariaga

Abstract

This study analyzes the efficiency of household-level energy consumption using a rich microdata set of homes within the United States. We measure efficiency by extending a cost-minimization model that treats the total amount of energy services produced as latent or unobserved due to technological differences in household consumption. The empirical strategy consists of applying latent class modeling to cost frontier analysis, which helps to identify heterogeneous subsets of units that require the fewest energy resources. Our estimates of efficient units form an empirical cost frontier of best practices within each subset. In order to understand the determinants of household-level energy efficiency, we condition the cost frontier analysis on numerous physical, climate-related, and socio-economic characteristics of the household. We find that state-level energy building code regulations, on average, induce a one-to-four percent marginal increase in household energy consumption.

Suggested Citation

  • J. Wesley Burnett & Jessica Madariaga, 2018. "A Top-Down Economic Efficiency Analysis of U.S. HouseholdEnergy Consumption," The Energy Journal, , vol. 39(4), pages 1-30, July.
    • Handle: RePEc:sae:enejou:v:39:y:2018:i:4:p:1-30
    DOI: 10.5547/01956574.39.4.jbur
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    1. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    2. Gilbert E. Metcalf & Kevin A. Hassett, 1999. "Measuring The Energy Savings From Home Improvement Investments: Evidence From Monthly Billing Data," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 516-528, August.
    3. Richard G. Newell & Juha Siikamäki, 2014. "Nudging Energy Efficiency Behavior: The Role of Information Labels," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 1(4), pages 555-598.
    4. Grant D. Jacobsen & Matthew J. Kotchen, 2013. "Are Building Codes Effective at Saving Energy? Evidence from Residential Billing Data in Florida," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 34-49, March.
    5. Antonio Alvarez & Julio del Corral, 2010. "Identifying different technologies using a latent class model: extensive versus intensive dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(2), pages 231-250, June.
    6. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    7. Kim, Hyung Chul & Keoleian, Gregory A. & Horie, Yuhta A., 2006. "Optimal household refrigerator replacement policy for life cycle energy, greenhouse gas emissions, and cost," Energy Policy, Elsevier, vol. 34(15), pages 2310-2323, October.
    8. Arik Levinson, 2016. "How Much Energy Do Building Energy Codes Save? Evidence from California Houses," American Economic Review, American Economic Association, vol. 106(10), pages 2867-2894, October.
    9. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    10. Hunt Allcott, 2013. "The Welfare Effects of Misperceived Product Costs: Data and Calibrations from the Automobile Market," American Economic Journal: Economic Policy, American Economic Association, vol. 5(3), pages 30-66, August.
    11. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
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    Cited by:

    1. Andersen, F.M. & Gunkel, P.A. & Jacobsen, H.K. & Kitzing, L., 2021. "Residential electricity consumption and household characteristics: An econometric analysis of Danish smart-meter data," Energy Economics, Elsevier, vol. 100(C).
    2. Harker Steele, Amanda J. & Bergstrom, John C., 2018. "Does Energy Efficiency Effect Energy Security? An Analysis of Energy Efficient Upgrades and Household Energy Security," 2018 Annual Meeting, August 5-7, Washington, D.C. 274186, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    Energy efficiency; energy rebound effect; household energy consumption;
    All these keywords.

    JEL classification:

    • F0 - International Economics - - General

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