Learning-by-doing and the optimal solar policy in California

Much policy attention has been given to promote fledgling energy technologies that promise to reduce our reliance on fossil fuels. These policies often aim to correct market failures, such as environmental externalities and learning-by-doing (LBD). We examine the implications of the assumption that LBD exists, quantifying the market failure due to LBD. We develop a model of technological advancement based on LBD and environmental market failures to examine the economically efficient level of subsidies in California's solar photovoltaic market. Under central-case parameter estimates, including nonappropriable LBD, we find that maximizing net social benefits implies a solar subsidy schedule similar in magnitude to the recently implemented California Solar Initiative. This result holds for a wide range of LBD parameters. However, with no LBD, the subsidies cannot be justified by the environmental externality alone.