A county-level analysis of residential solar adoption in the United States

This thesis set out to achieve two major objectives, with a third objective added at the end. The first was the update and analysis of the zero-inflated negative binomial (ZINB) model used by Zahran et al. (2008) in regards to its validity and robustness as a predictor of the count of solar using households in a county. The second objective was to use the model to provide an empirical measure of the effect financial and regulatory incentives have on the count of solar using households. The final objective was to explore and explain an unexpected decrease in the count of solar using households. This was done by using a ZINB regression to model the number of occupied housing units that use solar heating at the county level over the period from 2000 to 2009. In addition to analyzing the effects of the explanatory variables, geographic information systems (GIS) modeling was used to provide geographic mapping of the distribution of occupied housing units that use solar heating. The results indicate that Zahran et al.'s (2008) model is a robust and accurate predictor of the count of solar using households. Financial incentives were found to have an insignificant impact on the count of solar-using households, while regulatory incentives decreased the odds of a zero count in a county, but also decreased the expected count. A correlation was found between densely populated counties and the decrease in the count of solar using households.