Investigating the economic and environmental impact on the sales of electric vehicles in the United States: A time-series approach

The Biden Administration intends to create a dominant electric market by 2030, as problems with global warming and increasing dependency on gasoline rise over time, requiring an alternative on the automotive industry. This study investigates the impact of gasoline prices, CO2 emissions and GDP of the U.S. on the sales of electric vehicles using time series data between the periods 2011 to 2021 on a monthly basis. To achieve this impact, we use an augmented dickey fuller test to first test the stationary of our data, from which we can then create an autoregressive distributed lags model to bound test our variables and establish co-integration, which in result leads to short-run and long-run estimations of our variables. Diagnostic tests are further implemented to test the stability and reliability of the test with critical bounds established. The results of our study indicate that significant relationships exist between these factors on the sales of electric vehicles, where a positive relationship exists between sales to gasoline prices and GDP, and a negative relationship exists between sales to CO2 emissions. These findings open room to further implications on factors such as tax benefits, electricity prices, and charging infrastructure. Based on these findings, we can view that the U.S. is on par with its promises of electrifying half of its fleet by 2030, however a lot of work is required on other minor factors to achieve a shift from conventional gasoline vehicles to electric vehicles.