Sun-sational Incentives

Solar power provides cheap, clean electricity generation. But because of its high installation cost, incentives are commonly used to encourage residential adoption. This dissertation presents an analysis of the impact of income on the effectiveness of these incentives in California.

The analysis focuses on two research questions: How do incentives affect the size and characteristics of individual installations at the census tract level, considering such factors as ownership type, material, and storage? How do incentives influence installation rates across the broader population? The author built a novel dataset from multiple sources—installation rates from the three major investor-owned utilities in the state, a comprehensive census of statewide solar installations, demographic data from the census, and other data to act as controls—to answer them.

Using linear regression models and Monte Carlo simulations, the author finds that income significantly moderates incentive effectiveness. Specifically, incentives yield greater installation rates and capacity in higher-income areas than in less affluent ones. This finding suggests that previous research may have underestimated the role of income in shaping solar adoption patterns.

The results also highlight notable reversals in incentive allocation trends within California. These insights carry important implications for policy design: If maximizing solar capacity is the primary goal, incentive programs should be structured to appeal to more-affluent homeowners who are better positioned to capitalize on them.