Abstract

Sustainability has become a global issue of widespread concern and renewable energy sources are among the most important areas of sustainability research. The solar photovoltaic panel, as a new product, has shown promise but is far from reaching its market potential. This is partly because installation of solar panels requires substantial upfront investment, a critical factor especially for households who want to install them on their rooftops. We use a micro modeling approach to study the adoption of rooftop solar panels among households. We model household adoption as a forward-looking investment in a new sustainable product. Since rooftop solar panels are easily observable in the neighborhood, they enable potential adopters to infer about the investment return of new installations without explicitly asking anyone. We build this social learning mechanism in our model and estimate it using a rich household-level data set on the adoption timings of the solar panels in Germany. Besides, an aggregate version of our micromodel has been proposed to estimate the parameters of adoption using aggregate data. We have contrasted the results of the two models. Through a series of counterfactual policy experiments, we demonstrate the effectiveness of different incentive policies including Feed-In Tariff (FIT). Through policy experiments we show that by understanding the underlying adoption mechanisms policy makers can choose the most efficient incentive policy to accelerate the adoption of solar panels. Our proposed models (micromodel and aggregate model) are general enough to be adapted to other new sustainable products by incorporating economic and social factors.

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