Effects of Attribute-Based Regulation on Technology Adoption – The Case of Feed-In Tariffs for Solar Photovoltaic

Abstract

Feed-in tariffs are a widely used policy instrument to support deployment of renewable energy technologies. The aim of this paper is to estimate the causal effect of a cut in feed-in tariffs on solar photovoltaic (PV) installations. I isolate this effect by a differences-in-differences approach using data on all grid-connected PV systems within Germany from 2009 until 2013 on a county level. A policy change of administrative size classes in 2012 provides exogenous variation in feed-in tariffs. I find that a cut in feed-in tariffs of five percent leads to a decrease in newly installed capacity of around 46 kilowatt (kW) in a county per month. This is equivalent to approximately three percent of the average annual solar PV deployment on a national level from 2009 to 2011. The re-evaluation of size classes implies de facto the introduction of attribute-based regulation for small installations. The design of differentiated rates incentivizes smaller individual capacity choices at the border of size classes. This leads to excess bunching at the ceiling of the smaller size class. Neglecting this leads to overestimating treatment effects by around double the size. This potential bias underlines the impact of attribute-based regulation on technology adoption for solar PV.