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Household Solar Analysis for Policymakers: Evidence from U.S. Data

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  • Rohan Best and Ryan Esplin

Abstract

There is a vast literature on household solar-panel uptake but there are mixed results for many explanatory variables such as income, education, age, and race. This creates a major challenge for policymakers, who devise solar-panel policies that relate to variables such as income. This study uses logit, probit, and linear probability models, along with the matching method of entropy balancing. We use household data from the 2019 American Housing Survey. Results using entropy balancing suggest that high housing values and older respondent age are key factors promoting solar-panel uptake. Income has some positive impacts, although detailed analysis tends to show insignificance. Education and race variables have insignificant coefficients when controlling for key variables. This paper could provide a basis for future policy approaches, such as means testing based on asset thresholds rather than income thresholds.

Suggested Citation

  • Rohan Best and Ryan Esplin, 2023. "Household Solar Analysis for Policymakers: Evidence from U.S. Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    • Handle: RePEc:aen:journl:ej44-1-best
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    Cited by:

    1. Paul Simshauser, 2022. "The 2022 energy crisis: horizontal and vertical impacts of policy interventions in Australia's national electricity market," Working Papers EPRG2216, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    2. Nepal, Rabindra & Best, Rohan & Taylor, Madeline, 2023. "Strategies for reducing ethnic inequality in energy outcomes: A Nepalese example," Energy Economics, Elsevier, vol. 126(C).

    More about this item

    JEL classification:

    • F0 - International Economics - - General

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