The causal relation between off-street parking and electric vehicle adoption in Scotland

2026-04-10

AI Summary

This study investigates whether the association between off-street parking availability and electric vehicle (EV) adoption among Scottish households stems from infrastructural constraints or merely reflects underlying socioeconomic disparities. Leveraging nationally representative household survey data and employing a probabilistic causal inference framework to control for confounding factors, the analysis addresses selection bias inherent in conventional observational models. Findings indicate that off-street parking significantly accelerates EV adoption only among high-income households, increasing adoption probability from 3.3% to 5.6%—a relative increase of 70%. However, income itself constitutes the primary barrier to market entry, accounting for a 23.1 percentage-point gap in participation. These results suggest that infrastructure-focused policies, if implemented without addressing income constraints, risk exacerbating inequalities in EV adoption.

Technology Category

• Game Theory and Economic Paradigms: Social Choice / Voting
• Knowledge Representation and Reasoning: Preferences
• Humans and AI: Voting

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Social and technical mechanisms of refusal for web technologies and applications

Abstract

The transition to electric mobility hinges on maximising aggregate adoption while also facilitating equitable access. This study examines whether the'charging divide'between households with and without off-street parking reflects a genuine infrastructure constraint or a by-product of socio-economic disparity. Moving beyond conventional predictive models, we apply a probabilistic causal framework to a nationally representative dataset of Scottish households, enabling estimation of policy interventions while explicitly neutralising the confounding effect of other causal factors. The results reveal a structural hierarchy in the EV adoption process. Private off-street parking functions as a conversion catalyst: enabling access to home-charging increases the probability of EV ownership from 3.3% to 5.6% (a 70% relative, 2.3 percentage point absolute increase). However, this effect primarily accelerates households already economically positioned to purchase an EV rather than recruiting new entrants. By contrast, household income operates as the fundamental affordability ceiling. A causal contrast between lower- and higher-income strata, shows a reduction in market non-participation by 23.1 percentage points, identifying financial capacity as the principal gatekeeper to entering the EV transition funnel. Crucially, the analysis demonstrates that standard observational models overstate the isolated effect of off-street parking infrastructure. The apparent effect emerges from selection bias: higher-income households are disproportionately likely to possess both private parking and the means to purchase EVs. These findings support a dual-track policy strategy: lowering the affordability ceiling for non-participants through financial instruments, while addressing EV home-charging access for the'latent intent'cohort in high-density urban contexts.

Problem

• electric vehicle adoption
• off-street parking
• causal inference
• socio-economic disparity
• charging divide

Innovation

• causal inference
• probabilistic causal framework
• electric vehicle adoption
• charging divide
• confounding control