Two-stage DEA model to evaluate technical efficiency on deployment of battery electric vehicles in the EU countries

Abstract

The transportation sector represents an important barrier to decarbonising economies. The introduction of electric vehicles seems to be a promising solution; however, the intensive use of such vehicles remains a challenge for economies. By using the two-stage Data Envelopment Analysis (DEA) method, this paper aims to provide useful insights to enlarge Battery Electric Vehicles (BEV) market share. In the first stage, it calculates the efficiency scores for 20 European countries for both BEV adoption and policies supporting electric mobility, considering an output-oriented DEA method with constant returns to scale, and using annual data from 2010 to 2018. It is a non-parametric method, which makes it possible to determine the technical efficiency of the countries under study, i.e., the ability of these countries to transform their inputs into outputs. It calculates the efficiency frontier and determines if the countries are (or not) on this frontier. In the second stage, it examines the role of some determinants of electric mobility using the efficiency scores previously calculated by applying a fractional regression model. The main findings show that few countries are performing on the efficiency frontier. Additionally, renewable electricity generation increases a countries’ DEA score and contributes to bringing the inefficient countries closer to the efficiency frontier. Contrary, the existence of peak periods of electricity consumption decreases the DEA score and moves the inefficient countries further away from the frontier. This paper highlights the need to design transport and electricity policies jointly in order to ensure that the intensive use of BEV contributes towards renewables accommodation.