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Heterogeneity in the Effect of Home Energy Audits – Theory and Evidence

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  • Manuel Frondel

    ()

  • Colin Vance

Abstract

A longstanding question in the study of energy demand concerns the role of information as a determinant of home-efficiency improvements. Although the provision of information via home energy audits is frequently asserted to be an effective means for governments to encourage the implementation of efficiency-enhancing renovations, empirical support for this assertion is tenuous at best. Apart from self-selection issues with respect to receiving an audit, two other factors have complicated attempts to measure their effect: first, the nature of the information provided by the audit is typically unobserved, and, second, the response to this information may vary over households. Using household-level data from Germany, we address both sources of heterogeneity by estimating a random-parameter model of four retrofitting alternatives. In addition to confirming the importance of costs and savings as determinants of renovation choices, our results suggest that the effects of consultancy vary substantially across households, with some households responding negatively to the provision of information.

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Paper provided by Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen in its series Ruhr Economic Papers with number 0335.

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Length: 20 pages
Date of creation: Apr 2012
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Handle: RePEc:rwi:repape:0335

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Keywords: Energy audit; mixed logit; random-coefficient models;

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References

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  1. Peter Grosche & Colin Vance, 2009. "Willingness to Pay for Energy Conservation and Free-Ridership on Subsidization: Evidence from Germany," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 135-154.
  2. Hirst, Eric & Goeltz, Richard, 1985. "Estimating energy savings due to conservation programmes : The BPA residential weatherization pilot programme," Energy Economics, Elsevier, vol. 7(1), pages 20-28, January.
  3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, April.
  4. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
  5. Scott, S., 1997. "Household energy efficiency in Ireland: A replication study of ownership of energy saving items," Energy Economics, Elsevier, vol. 19(2), pages 187-208, May.
  6. Paul C. Stern, 1986. "Blind spots in policy analysis: What economics doesn't say about energy use," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 5(2), pages 200-227.
  7. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
  8. Jaffe, Adam B. & Stavins, Robert N., 1994. "The energy-efficiency gap What does it mean?," Energy Policy, Elsevier, vol. 22(10), pages 804-810, October.
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Cited by:
  1. Achtnicht, Martin & Madlener, Reinhard, 2012. "Factors influencing German house owners' preferences on energy retrofits," ZEW Discussion Papers 12-042, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.

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