Estimating and forecasting the impact of nonrenewable energy prices on US renewable energy consumption

This paper measures the impact of nonrenewable energy prices on renewable energy consumption in the U.S. We do so using monthly data for the period 1973:1-2018:12, and a series of recursively identified VAR models with nonrenewable energy prices ordered ahead of renewable energy consumption measures in each of the VAR models. We also investigate whether information on nonrenewable energy prices can be used to improve forecasts of renewable energy consumption. Our general findings are as follows (i) Shocks to nonrenewable energy prices have positive and statistically significant impacts on renewable energy consumption. (ii) Allowing for nonlinearities/asymmetries in nonrenewable energy prices lead to more statistical significance in the responses of the various renewable energy consumption measures (iii) The percentage of the variation in renewable energy consumption that is explained by nonrenewable energy prices is quantitatively small. (iv) In many cases, models with nonrenewable energy prices improve the forecast performance of simple AR models.

Automated summary

This paper measures the impact of nonrenewable energy prices on renewable energy consumption in the U.S. using VAR models with nonrenewable energy prices ordered ahead of renewable energy consumption measures. The findings suggest that shocks to nonrenewable energy prices have positive and significant impacts on renewable energy consumption. Including nonlinearities/asymmetries in nonrenewable energy prices improves the statistical significance of the responses of renewable energy consumption measures. The percentage of the variation in renewable energy consumption explained by nonrenewable energy prices is quantitatively small, and models with nonrenewable energy prices improve forecast performance compared to simple AR models.