Panel Paper: Rooftop Revolution?: The Comparative Effectiveness of State Policy Incentives for Encouraging Residential Solar Power Adoption in the United States

Thursday, November 7, 2013 : 3:00 PM
Plaza II (Ritz Carlton)

*Names in bold indicate Presenter

Virgil Ian Stanford, George Mason University
The high cost of solar photovoltaic systems is one of the key factors preventing widespread adoption of residential solar power systems.  During the last decade, state governments have come up with an array of different policy incentives to bring down both the short and long-term costs of installing solar power systems.  These include a variety of tax incentives (income, property, and sales taxes), subsidized loans, grants, rebates, performance-based incentives, and net metering.  Still, solar resources and incentives vary widely between the states.  Moreover, past studies of residential renewable power adoption have identified a variety of environmental, economic, and social factors that influence adoption rates.  Additional information is needed to determine which of these incentives or combination of incentives is most effective, especially when controlling for several key factors including the availability of solar resources (i.e. solar radiation) and state economic conditions.

Are state policy incentives effective tools for encouraging private citizens to invest in their own solar power generation systems? Have the efforts of state governments over the last decade been successful in igniting a rooftop revolution, or is their effectiveness limited by the multitude of intervening factors including politics, environmental conditions, economic conditions, and various other social forces?  This study seeks to add to the growing literature about the diffusion of renewable energy by discovering which state-level policy incentives are most effective in promoting the adoption of residential solar photovoltaic power systems.  It will examine the number of residential solar photovoltaic installations per state between 2009 and 2012.  Data analysis will include a linear regression model and spatial comparisons between states using GIS maps.  Data for this study will come primarily from two public sources.  Information on the type and value of state policy incentives will come from the Database of State Incentives for Renewables and Efficiency (DSIRE).  Meanwhile, data on the size and location of solar photovoltaic system installations is housed at The Open PV Project, hosted by the National Renewable Energy Laboratory.

Full Paper: