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The impact of land use effects in infrastructure appraisal
Linköping University, Sweden.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, System Analysis and Economics.ORCID iD: 0000-0003-1360-4906
2020 (English)In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, E-ISSN 1879-2375, Vol. 141, p. 262-276Article in journal (Refereed) Published
Abstract [en]

When benefits of proposed infrastructure investments are forecasted, residential location is usually treated as fixed, since very few operational transport models are able to forecast residential relocation. It has been argued that this may constitute a source of serious error or bias when evaluating and comparing the benefits of proposed infrastructure investments. We use a stylized simulation model of a metropolitan region to compare calculated benefits for a large number of infrastructure investments with and without taking changes in residential location into account. In particular, we explore the changes in project selection when assembling an optimal project portfolio under a budget constraint. The simulation model includes endogenous land prices and demand for residential land, heterogeneous preferences and wage offers across residents, and spillover mechanisms which affect wage rates in zones. The model is calibrated to generate realistic travel patterns and demand elasticities. Our results indicate that ignoring residential relocation has a small but appreciable effect on the selected project portfolio, but only a very small effect on achieved total benefits.

Place, publisher, year, edition, pages
Elsevier Ltd , 2020. Vol. 141, p. 262-276
Keywords [en]
Cost-benefit analysis, Land use, Land use/transport interaction models, Wider impacts, Budget control, Employment, Housing, Relocation, Wages, Budget constraint, Demand elasticities, Infrastructure investment, Metropolitan regions, Project portfolio, Project selection, Residential locations, Spillover mechanisms, Investments, investment, model, residential location, spillover effect, transportation infrastructure
National Category
Transport Systems and Logistics Economics
Identifiers
URN: urn:nbn:se:kth:diva-287945DOI: 10.1016/j.tra.2020.09.026ISI: 000587811600016Scopus ID: 2-s2.0-85091923464OAI: oai:DiVA.org:kth-287945DiVA, id: diva2:1512034
Note

QC 20201221

Available from: 2020-12-21 Created: 2020-12-21 Last updated: 2022-06-25Bibliographically approved

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Savemark, ChristianFranklin, Joel P.

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CiteExportLink to record
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  • apa
  • ieee
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  • de-DE
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