Association for Public Policy Analysis & Management

In recent years, solar energy has experienced tremendous growth in the United States. Due to continuously decreasing solar hardware costs, the average cost of solar photovoltaic (PV) panels has fallen more than 60% since 2010. However, unlike declining hardware costs, non-hardware (soft) costs of solar energy have held steady. Soft costs—such as labor, taxes, permitting fees, and transaction costs—currently account for more than 50% of the total system installation cost. By standardizing local solar permitting processes, city governments can potentially reduce the soft costs of solar PV installation and facilitate the deployment of solar PV at the local level. However, while most extant literature has examined the role of federal and state governments and policies in solar PV development, less work has examined their local counterparts.

In this paper, the author examines the influences of municipal capacity and resources, political factors, and demographic, socioeconomic, and climate characteristics on the adoption of local solar approval processes. Local solar approval processes offer an administrative, nondiscretionary review procedure for permitting residential rooftop solar energy systems that are no larger than 10 kilowatts (kW). The primary data that indicates whether a city has adopted a local solar approval process was drawn from California’s annual statewide planning surveys, which were delivered to all local governments and inquired about local planning activities. With high response rates of 86% in 2011 and 87% in 2012, the respondents consist of California cities that vary in size, socioeconomic, institutional, and climate conditions. To the author’s best knowledge, this article is the first study that explicitly quantifies the impact of local solar approval processes on both the size (kW) and quantity of small-scale residential solar PV installations in California cities (previous analyses measured only one outcome to evaluate local solar policy impact). The author constructs a pooled cross-sectional dataset (n=561) and employs a logit regression model to examine the predictors for the adoption of local solar approval processes, using data from 2010 and 2011. In the second model, the author constructs a two-year panel dataset (n>720) and utilizes ordinary least squares regression, negative binomial regression, and fixed effects models to evaluate the impact of local solar approval processes on residential solar PV installations. The findings demonstrate that cities with high municipal resources and high proportions of pro-environment, educated constituents are more likely to adopt solar approval processes. Additionally, the presence of local solar approval processes is found to increase both the number and total capacity of installed small-scale residential solar PV, holding all else equal. The empirical evidence presented in this research confirms the important role of local governments and policies in facilitating the deployment of solar PV panels at the local level.