will give a presentation on
Empirical literature about the energy transition has focused on the impact of energy prices or energy policy on the rate of technological change, see Popp (2009, 2019). However, very few papers have attempt to estimate the impact of technological progress on energy investment decisions. I am trying to fill this gap using an AutoRegressive Distributed Lags (ARDL) model on yearly US data. I estimate the elasticity of the renewable energy share in the US energy production with respect to biased technological progress, oil prices, GDP and domestic investments. Results show a short run elasticity of 0.31-0.34 for technology differential and of 0.004-0.006 for oil prices, while it rejects the presence of any long-run elasticity for these two variables. The main novelty of the paper lies in the computation of biased technological progress through USPTO patent, and its use to infer the behavior of the renewable energy share instead of its production.
To join the seminar, please follow the following instructions: