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Demand-Side Management and Energy Efficiency Revisited

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  • Maximilian Auffhammer
  • Carl Blumstein
  • Meredith Fowlie

Abstract

The key finding of Loughran and Kulick (2004) is that utilities have been overstating electricity savings and underestimating costs associated with energy efficiency demand-side management (DSM) programs. This claim is based on point estimates of average DSM-related savings and costs implied by an econometric model of residential electricity demand. We first argue that the chosen test statistics bias results in favor of rejecting the null hypothesis that utility-reported savings reflect true values. We also note that utility estimates of average program savings and costs are rejected based on point estimates alone. We use the same data and econometric model to estimate the appropriate test statistics. We then construct nonparametric bootstrap confidence intervals. These intervals are quite large; we fail to reject the average electricity savings and DSM costs reported by utilities. Our results suggest that the evidence for rejecting utility estimates of DSM savings and costs should be re-interpreted.

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Bibliographic Info

Article provided by International Association for Energy Economics in its journal The Energy Journal.

Volume (Year): Volume 29 (2008)
Issue (Month): Number 3 ()
Pages: 91-104

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Handle: RePEc:aen:journl:2008v29-03-a05

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Cited by:
  1. Xavier Labandeira Villot & Pedro Linares, 2009. "Energy Efficiency: Economics and Policy," Economic Reports 06-09, FEDEA.
  2. Gillingham, Kenneth & Palmer, Karen, 2013. "Bridging the Energy Efficiency Gap: Policy Insights from Economic Theory and Empirical Evidence," Discussion Papers dp-13-02-rev, Resources For the Future.
  3. Jackson, Jerry, 2010. "Improving energy efficiency and smart grid program analysis with agent-based end-use forecasting models," Energy Policy, Elsevier, vol. 38(7), pages 3771-3780, July.
  4. Arimura, Toshi H. & Newell, Richard G. & Palmer, Karen, 2009. "Cost-Effectiveness of Electricity Energy Efficiency Programs," Discussion Papers dp-09-48, Resources For the Future.
  5. Diffney, Sean & Lyons, Sean & Malguzzi Valeri, Laura, 2009. "Advertising to boost energy efficiency: the Power of One campaign and natural gas consumption," Papers WP280, Economic and Social Research Institute (ESRI).
  6. Thomas, Brinda A. & Azevedo, Inês L., 2014. "Should policy-makers allocate funding to vehicle electrification or end-use energy efficiency as a strategy for climate change mitigation and energy reductions? Rethinking electric utilities efficienc," Energy Policy, Elsevier, vol. 67(C), pages 28-36.
  7. Delmas, Magali A. & Lessem, Neil, 2014. "Saving power to conserve your reputation? The effectiveness of private versus public information," Journal of Environmental Economics and Management, Elsevier, vol. 67(3), pages 353-370.
  8. 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.
  9. Sudarshan, Anant, 2013. "Deconstructing the Rosenfeld curve: Making sense of California's low electricity intensity," Energy Economics, Elsevier, vol. 39(C), pages 197-207.
  10. Chong, Howard, 2012. "Building vintage and electricity use: Old homes use less electricity in hot weather," European Economic Review, Elsevier, vol. 56(5), pages 906-930.

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