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Journal of Transport and Land Use

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Published

2010-09-23

Issue

Vol. 3 No. 2 (2010)

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Articles

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Authors who publish with JTLU agree to the following terms: 1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution-Noncommercial License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. 2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. 3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

How to Cite

Löchl, M., & Axhausen, K. W. (2010). Modelling hedonic residential rents for land use and transport simulation while considering spatial effects. Journal of Transport and Land Use, 3(2). https://doi.org/10.5198/jtlu.v3i2.117

Modelling hedonic residential rents for land use and transport simulation while considering spatial effects

Michael Löchl

IVT, ETH Zürich

Kay W. Axhausen

DOI: https://doi.org/10.5198/jtlu.v3i2.117

Abstract

The application of UrbanSim requires land or real estate price data for the study area. These can be difficult to obtain, particularly when tax assessor data and data from commercial sources are unavailable. The article discusses an alternative method of data acquisition and applies hedonic modeling techniques in order to generate the required data. Many studies have highlighted that ordinary least square (OLS) regression approaches lack the ability to consider spatial dependency and spatial heterogeneity, consequently leading to biased and inefficient estimations. Therefore, a comprehensive data set is used for modeling residential asking rents by applying and comparing OLS, spatial autoregressive, and geographically weighted regression (GWR) techniques. The latter technique performed best with regard to model fit, but the issue of correlated coefficients favored a spatial simultaneous autoregressive model. Overall, the article reveals that when housing markets are a particular concern in UrbanSim applications, significant efforts are needed for the price data generation and modeling. The study concludes with further development potentials for UrbanSim.

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The Journal of Transport and Land Use is published and sponsored by the University of Minnesota Center for Transportation Studies and is the official journal of the World Society for Transport and Land Use (WSTLUR).

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