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Influence of Political Affiliation Toward Support of Solar Energy in Florida Gulf Coast Counties
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Influence of Political Affiliation Toward Support of Solar Energy in Florida Gulf Coast Counties

Kiersten Ursula Cavender
Master of Science (MS), University of West Florida
Spring 2022

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Abstract

The lack of growth of solar energy in the Sunshine State of Florida has not been reflective of trends seen within the United States. The dominant explanation for the current trends in solar energy point to the politicization and polarization of renewable energy in general. Due to this observation, research was conducted to determine the influence political affiliation may have on support of solar energy in counties along the Gulf Coast of Florida, namely, Escambia County south to Monroe County. These counties were selected the implementation of criterion sampling based on level of solar potential. The goal of the research extended to if other criteria such as cost, care for the environment, energy independence, or government regulations had an impact on solar support. Respondents were selected based on those individuals who were registered to vote in the selected list of counties available through publicly accessible data. Results show that political affiliation is not independent from the way respondents answered many questions regarding solar energy. Republican Party of Florida respondents typically responded positively to hypothetical factors of cost-saving capability, policy that implemented statewide solar fields, and energy independence. Democratic Party of Florida respondents responded positively to hypothetical factors of reduction of CO2 and other Greenhouse Gas Emissions, increased government regulations, and further policy initiatives to increase solar. Questions gauging concern of an increase or decrease in energy independence showed that political affiliation was independent of responses. An ordinal logistic regression determined that the two questions have no relationship and the political affiliations were not statistically different than one another. These results can be used by decision makers to identify future policies and incentives that encourage or increase preference for support of solar energy.
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