Optimal switch from a fossil-fueled to an electric vehicle

Abstract

In this paper we propose and solve a real options model for the optimal adoption of an electric vehicle. A policymaker promotes the abeyance of fossil-fueled vehicles through an incentive, and the representative fossil-fueled vehicle's owner decides the time at which buying an electric vehicle, while minimizing a certain expected cost. This involves a combination of various types of costs: the stochastic opportunity cost of driving one-unit distance with a traditional fossil-fueled vehicle instead of an electric one, the cost associated to traffic bans, and the net purchase cost. After determining the optimal switching time and the minimal cost function for a general diffusive opportunity cost, we specialize to the case of a mean-reverting process. In such a setting, we provide a model calibration on real data from Italy, and we study the dependency of the optimal switching time with respect to the model's parameters. Moreover, we study the effect of traffic bans and incentive on the expected optimal switching time. We observe that incentive and traffic bans on fossil-fueled transport can be used as effective tools in the hand of the policymaker to encourage the adoption of electric vehicles and hence to reduce air pollution.

Ein Soziologe und Jurist erinnert sich

“…(3.1) Assumption 3.1 is a well known criterion that is typical in optimal stopping problems in order to derive the existence and uniqueness of a point b ∈ R + triggering the optimal stopping time (see, e.g., Alvarez (2001) and Falbo et al (2021)). It is crucial to notice that, at this point, no qualitative statements are possible regarding sufficient conditions on the parameters µ i , σ i that imply the suggested shape of the function (3.1) and thus of the monotonicity of A(•), as derived in (B.5).…”

“…Since then, the real option approach to environmental investments has received much attention (cf. Boomsma et al, 2012;Detemple and Kitapbayev, 2020;Falbo et al, 2021). Let us mention Abadie and Chamorro (2008), Brauneis et al (2013), Flora and Vargiolu (2020), and Insley (2003) that study emission reduction investments in the presence of diffusive carbon prices, as well as Basei et al (2023) and Flora and Tankov (2023) as recent contributions incorporating the feature of Bayesian learning.…”

The Problem of Evaluation of Individual Persistent Organic Pollutants Emissions From Road Transport (Illustrated by the Case of Odessa Industrial-and-Urban Agglomeration)

“…All over the world, much attention is paid to the monitoring of environmental pollution by road transport (Jason at al., 2021;Chengyong at al., 2021;Deya, Mehtab, 2020), in particular, to search for the most environmentally friendly fuel and transport (Longo at al., 2018;Falbo at al., 2020). This problem is also relevant to Ukraine, which seeks to meet the strict requirements of the European Union (EU) in environmental safety and adapts the procedures of atmospheric monitoring to the approach in EU countries (Ukrainian Ministry, 2019).…”