Stochastic convergence of renewable energy intensity across US States: evidence from a panel unit root test with asymmetries and common factors

Abstract

This study examines the stochastic convergence of renewable energy intensity (REI) across US states. We test for the stationarity of relative REI (stochastic convergence) using a recently developed quantile panel unit root test that accommodates both cross-sectional dependence and asymmetric behaviour. Our overall finding is that most states exhibit convergence, which implies that economic growth is sustainable with a higher share of renewable energy in the energy mix. This result provides support for those advocating that state governments should increase investment in renewable energy in advancing the clean energy transition. However, over half of the states display asymmetric stochastic convergence, which implies that how effective policies will be in promoting renewable energy efficiency will depend on the size and type of shocks impacting REI. Our results imply that in states that encounter relatively large positive shocks to REI, it may be necessary to invest more in the diffusion of renewable energy technologies and set long-term targets. Asymmetric convergence behavior also makes it difficult to coordinate policy responses across states, providing support for a decentralized approach in which each state invests in renewable energy technologies specific to their unique economic circumstances, rather than adopting a mandated overall national policy approach.