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The Influence of Rebate Programs on the Demand for Water Heaters: The Case of New South Wales

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  • Wasi, Nada
  • Carson, Richard T.

Abstract

In the past decade the Australian Federal government and state governments have established a wide range of programs to cut greenhouse gas emissions from all sectors. This paper examines the role of hot water system rebate programs in shifting the existing stock of electric water heaters toward more climate friendly versions using two unique data sets from New South Wales homeowners. The first data set is based on a survey of households who recently purchased a water heater and exploits a natural experiment created by the rebate program to quantify its effects. The other data set is based on a set of stated preference questions asked of households who own an older water heater and will in the reasonably near future face a replacement decision. We find that recent rebate programs significantly increased the share of solar/heat pump systems. For households without access to natural gas, this increased share comes directly from inefficient electric water heaters. For households with access to natural gas, older existing electric water heaters would likely have been replaced with gas water heaters in the absence of the rebate programs. The rebate program appears to be much less effective when water heaters are replaced on an emergency basis. Data from discrete choice experiments was analysed using several flexible choice models. A newly proposed model that combines a latent class approach with a random coefficients approach clearly dominates the other models in terms of statistical fit. Predictions based on this model estimate are reasonably consistent with actual purchase data. Results from it point to considerable heterogeneity with respect to household preferences toward different types of water heaters and with respect to the discount rates they hold.

Suggested Citation

  • Wasi, Nada & Carson, Richard T., 2011. "The Influence of Rebate Programs on the Demand for Water Heaters: The Case of New South Wales," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100731, Australian Agricultural and Resource Economics Society.
  • Handle: RePEc:ags:aare11:100731
    DOI: 10.22004/ag.econ.100731
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    5. Brent, Daniel A. & Ward, Michael B., 2018. "Energy efficiency and financial literacy," Journal of Environmental Economics and Management, Elsevier, vol. 90(C), pages 181-216.
    6. Marlena Piekut, 2021. "The Consumption of Renewable Energy Sources (RES) by the European Union Households between 2004 and 2019," Energies, MDPI, vol. 14(17), pages 1-31, September.
    7. Ma, Ben & Yu, Yihua & Urban, Frauke, 2018. "Green transition of energy systems in rural China: National survey evidence of households’ discrete choices on water heaters," Energy Policy, Elsevier, vol. 113(C), pages 559-570.
    8. Caputo, Vincenzina & Scarpa, Riccardo & Nayga, Rodolfo M. & Ortega, David L., 2018. "Are preferences for food quality attributes really normally distributed? An analysis using flexible mixing distributions," Journal of choice modelling, Elsevier, vol. 28(C), pages 10-27.
    9. Doherty, Edel & Campbell, Danny & Hynes, Stephen, 2012. "Exploring cost heterogeneity in recreational demand," Working Papers 148832, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    10. Hlavinka, Alexander N. & Mjelde, James W. & Dharmasena, Senarath & Holland, Christine, 2016. "Forecasting the adoption of residential ductless heat pumps," Energy Economics, Elsevier, vol. 54(C), pages 60-67.
    11. David Hensher & Andrew Collins & William Greene, 2013. "Accounting for attribute non-attendance and common-metric aggregation in a probabilistic decision process mixed multinomial logit model: a warning on potential confounding," Transportation, Springer, vol. 40(5), pages 1003-1020, September.
    12. Higgins, Andrew & McNamara, Cheryl & Foliente, Greg, 2014. "Modelling future uptake of solar photo-voltaics and water heaters under different government incentives," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 142-155.
    13. Nada Wasi & Jirawat Panpiemras & Wanwiphang Manachotphong, 2016. "The Impacts of the Billing System on Healthcare Utilization: The Case of Thai Civil Servant Medical Benefit Scheme," PIER Discussion Papers 48, Puey Ungphakorn Institute for Economic Research.
    14. Shigeru Matsumoto, 2018. "Consumer valuation of energy-saving features of residential air conditioners with hedonic and choice models," Empirical Economics, Springer, vol. 55(4), pages 1779-1806, December.
    15. Tanaka, Takuro & Mizutani, Fumitoshi, 2023. "Determinants of the adoption of energy efficient water heaters in the residential sector: Evidence from a survey in Japan," Energy Policy, Elsevier, vol. 180(C).
    16. Jacksohn, Anke & Grösche, Peter & Rehdanz, Katrin & Schröder, Carsten, 2019. "Drivers of renewable technology adoption in the household sector," Energy Economics, Elsevier, vol. 81(C), pages 216-226.
    17. Nada Wasi & Jirawat Panpiemras & Wanwiphang Manachotphong, 2021. "The Impact of a Billing System on Healthcare Utilization: Evidence from the Thai Civil Servant Medical Benefit Scheme," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 228-251, February.

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    More about this item

    Keywords

    Environmental Economics and Policy; Resource /Energy Economics and Policy;

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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