Forecasting electricity supply shocks: A Bayesian panel VAR analysis

Abstract

Abstract The goal of this chapter is to investigate the relationship and the possible spillovers between electricity supply shocks and US macroeconomic performance, given that there is considerable evidence that this relationship has been unstable over time. The analysis uses monthly seasonally adjusted regional data from the US states, spanning the period January 2001 to September 2016 and combines a novel identification strategy for electricity supply shocks based on inequality constraints. With the estimation of a time-varying Bayesian panel VAR model (TVBPVAR). The main novelty of this chapter is that it combines the employment of a TVBPVAR model with accounting for the decomposition of electricity supply per fuel mixture and linking its possible interactions with the US macroeconomic conditions across US states. The empirical findings are in alignment with the existing literature, suggesting that GDP per capita increases after a positive electricity supply shock. Irrelevant to the source of energy that generates it. This finding confirms the important role of electricity for economic growth across US states.