PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 26, 2026Transport Reviews2 citationsOpen Access

Access for appraisal: a systematic review of estimating transport benefits via real-estate uplift

View Full Paper
IMIsaac MannDLDavid M. Levinson

Key Points

Key points are not available for this paper at this time.

Abstract

Transport investments generate benefits that extend well beyond mobility, yet canonical cost–benefit analysis (CBA) remains dominated by travel-time savings. This paper advocates the use of real-estate value uplift as an alternative approach to quantify project benefits, arguing that increased accessibility commands a locational premium. We use a targeted systematic search to identify empirical studies that both quantify the real-estate capitalisation effect and apply it within transport appraisal. Across the fourteen studies identified, the ex post appraisals largely use difference-in-differences for causal inference, yet applicability to ex ante appraisal is ambiguous; the ex ante studies rely on cross-sectional models with limited efforts to address endogeneity. Once capitalisation effects are quantified, appraisal applications are demonstrative, aggregating property value changes while neglecting externalities, supply-side responses, and the validity of model assumptions; many report uplift magnitudes exceeding direct user benefits. We thus outline a framework and research agenda for real-estate-based transport appraisal, incorporating key elements of benefit transfer, the supply and demand of floorspace, agglomeration, hedonic price model design, and value capture. Further theoretical development and empirical work, particularly focussed on causality, transfers, and land use supply shocks, are needed to build confidence for broader adoption within CBA practice.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Mann et al. (2026) studied this question.

synapsesocial.com/papers/6a5bd56b9b5d0f06daf7a803https://doi.org/10.1080/01441647.2026.2627191
Ask AI
Helpful
Bookmark
Share
View Full Paper