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Determinants of Households' Investment in Energy Efficiency and Renewables: Evidence from the OECD Survey on Household Environmental Behaviour and Attitudes

Author

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  • Nadia Ameli

    (OECD)

  • Nicola Brandt

    (OECD)

Abstract

Many studies on household energy efficiency investments suggest that a wide range of seemingly profitable investments are not taken up. This paper provides novel evidence on the main factors behind consumer choices using the OECD Survey on Household Environmental Behaviour and Attitudes. The empirical analysis is based on the estimation of binary logit regression models. Empirical results suggest that households’ propensity to invest in clean energy technologies depends mainly on home ownership, income, social context and households’ information. Indeed, home owners and high-income households are more likely to invest than renters and low-income households. On the other hand, social context, such as membership in an environmental non-governmental organisation, and households’ knowledge about their energy spending and use may play a relevant role in technology adoption. Les déterminants de l'investissement des ménages dans l'efficacité énergétique et les énergies renouvelables : Résultat de l'enquête de l'OCDE sur les comportements et attitudes des ménages face aux questions d'environnement De nombreuses études sur les investissements des ménages en matière d'efficacité énergétique suggèrent qu'une large gamme d'investissements apparemment rentables n’est pas exploitée. Cette étude fournit de nouveaux éléments de preuve sur les principaux facteurs qui expliquent les choix des consommateurs à l'aide de l'Enquête de l'OCDE sur les comportements et les attitudes des ménages avec l’environnement. L'analyse empirique est basée sur l'estimation des modèles de régression logit binaires. Les résultats empiriques suggèrent que la propension des ménages à investir dans les technologies d'énergie propre dépend principalement de la propriété, du revenu, du contexte social et de l'information sur le sujet qu’obtiennent les ménages. En effet, les propriétaires de maison et les ménages à revenu élevé sont plus susceptibles d'investir que les locataires et les ménages à faible revenu. D'autre part, le contexte social, tels que l'appartenance à une organisation non gouvernementale pour la protection de l'environnement, la connaissance des ménages sur leurs dépenses d'énergie et l'utilisation peut jouer un rôle important dans l'adoption de la nouvelle technologie.

Suggested Citation

  • Nadia Ameli & Nicola Brandt, 2014. "Determinants of Households' Investment in Energy Efficiency and Renewables: Evidence from the OECD Survey on Household Environmental Behaviour and Attitudes," OECD Economics Department Working Papers 1165, OECD Publishing.
  • Handle: RePEc:oec:ecoaaa:1165-en
    DOI: 10.1787/5jxwtlchggzn-en
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    Citations

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    Cited by:

    1. Trotta, Gianluca, 2018. "Factors affecting energy-saving behaviours and energy efficiency investments in British households," Energy Policy, Elsevier, vol. 114(C), pages 529-539.
    2. Ashwini K. Aggarwal & Asif Ali Syed & Sandeep Garg, 2021. "Diffusion of RT Solar PV in Suburbs of Delhi/NCR, India: Triggers of Architect Recommendation Intent," Vision, , vol. 25(3), pages 285-299, September.
    3. 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.
    4. Angelika Goliger & Aalia Cassim, 2018. "Household tipping points in the face of rising electricity tariffs in South Africa," WIDER Working Paper Series wp-2018-33, World Institute for Development Economic Research (UNU-WIDER).
    5. Ang, James B. & Fredriksson, Per G. & Sharma, Swati, 2020. "Individualism and the adoption of clean energy technology," Resource and Energy Economics, Elsevier, vol. 61(C).
    6. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    7. Heiskanen, Eva & Matschoss, Kaisa, 2017. "Understanding the uneven diffusion of building-scale renewable energy systems: A review of household, local and country level factors in diverse European countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 580-591.
    8. Burlinson, Andrew & Giulietti, Monica & Battisti, Giuliana, 2018. "Technology adoption, consumer inattention and heuristic decision-making: Evidence from a UK district heating scheme," Research Policy, Elsevier, vol. 47(10), pages 1873-1886.
    9. Angelika Goliger & Aalia Cassim, 2018. "Household tipping points in the face of rising electricity tariffs in South Africa," WIDER Working Paper Series 033, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    adoption de la technologie; choix discret; comportement des consommateurs; consumer behaviour; discrete choice; efficacité énergétique; energy efficiency; technology adoption;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • R22 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Other Demand

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