KOF Working Papers, KOF Swiss Economic Institute, ETH Zurich 321
This study uses data of a representative sample of Swiss firms to assess the effectiveness of policy measures directed at the diffusion of energy effcient 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, diffusion support from the two institutions taken into consideration has indeed been beneficial 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 efficiency, than the widely used Nearest Neighbour Matching (NNM) procedure.
Energy Efficiency Energy Policy Technology Diffusion Propensity Score Matching