Assessing the impact of support policies for energy efficient technology in Switzerland

Abstract

This study uses data of a representative sample of Swiss rms to assess the effectiveness of policy measures directed at the diusion of energy ecient technology (EET). Three different outcome variables (number of EET applications implemented, CO2 reduction, and EET related investment) are analysed using methods based on the estimated propensity score in an attempt to overcome the problem of non-random assignment. I conclude that, even after controlling for non-random assignment, diusion support from the two institutions taken into consideration has indeed been benecial in spurring adoption of energy saving technology and in reducing emissions of CO2. Additionally, an estimator for Average Treatment Effects on the Treated (ATT) that directly relies on the propensity score has been found to produce better results, in terms of eciency, than the widely used Nearest Neighbour Matching (NNM) procedure.