Impacts from transportation measures in national appraisal guidelines: coverage and practices

Rasmus Bøgh Holmen; Benjamin Biesinger; Ivo Hindriks

doi:10.5604/01.3001.0015.9928

Authors

Rasmus Bøgh Holmen Institute of Transport Economics, Oslo Author https://orcid.org/0000-0002-1964-1495
Benjamin Biesinger AIT Austrian Institute of Technology, Vienna Author https://orcid.org/0000-0001-6276-8339
Ivo Hindriks Panteia, Zoetermeer Author

DOI:

https://doi.org/10.5604/01.3001.0015.9928

Keywords:

transportation planning, decision-making, economic impacts, social impact, environmental impacts

Abstract

Transportation appraisal has a potential important role in prioritization of transportation investment projects and other transportation measures. Appraisal practices vary much over countries and time, but these differences are not fully known. More knowledge on the variation in practices may contribute to smoother knowledge exchange between countries and more informed choices in the further development of each national practice. In this paper, we present both an updated mapping and a meta-analysis of impact coverage in national appraisal guidelines for transportation measures and spatial measures more generally. Our updated mapping of impact coverage covers 18 national and regional guideline sets and 44 sorts of impact. It shows rather similar overall impact coverage in the reviewed guidelines for economic, social and environmental impacts. The most advanced appraisal practices are found in Northern and Western Europe and Oceania. We find that supplementary quantitative analyses are most common for economic impacts, while multi-criteria analyses are most common for environmental impacts. Our meta-analysis covers ours and 15 earlier impact mappings, jointly covering 42 countries and regions. In this examination, we show how impact coverage in appraisal practices has improved over time, particularly for environmental, user and wider economic impacts. The meta-analysis also reveals that Western and Northern European and Oceanian countries and dependencies have had the widest impact coverage from 1998 to 2020, both in CB and overall. To examine what characterize countries with broad and narrow impact coverage, we have applied econometric regression models that are linear (i.e. linear least squares), quasi-linear (i.e. Tobit) and fractional response-based (i.e. fractional probit and fractional logit). In these regression analyses, we control for study-specific characteristics and clustering the standard errors on countries. Our results show that the CB impact coverage tends to increase with economic wealth, equality and population size in developed countries, while we find no such patterns for overall impact coverage.

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