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Measuring the impact of large‐scale transportation projects on land price using spatial statistical models

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  • Morito Tsutsumi
  • Hajime Seya

Abstract

. Large‐scale transportation projects such as the construction of a commuter railway accessible to metropolises have a significant regional impact. This study attempts to measure this impact using spatial statistical models and land price data. First, dynamic changes in the land price are analysed and the so‐called announcement effect is presented using the spatial interpolation techniques. Second, various types of land price models are constructed by employing the existing methods of spatial econometrics and geostatistics; their estimates and project benefits are compared and discussed, particularly from the viewpoint of policy implications. Resumen. Los proyectos de transporte de gran escala tales como la construcción de un tren suburbano de acceso a una metrópolis tienen un impacto regional significativo. Este estudio intenta medir este impacto utilizando modelos estadísticos espaciales y datos del precio del suelo. Primero, se analizan cambios dinámicos en el precio del suelo y se presenta el llamado efecto de anuncio utilizando técnicas de interpolación espacial. Segundo, se construyen varios tipos de modelos de precio del suelo mediante el empleo de métodos existentes de econometría espacial y geoestadística; se comparan y discuten sus estimaciones y los beneficios del proyecto, en particular desde el punto de vista de sus implicaciones políticas.

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  • Morito Tsutsumi & Hajime Seya, 2008. "Measuring the impact of large‐scale transportation projects on land price using spatial statistical models," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 385-401, August.
    • Handle: RePEc:bla:presci:v:87:y:2008:i:3:p:385-401
    DOI: 10.1111/j.1435-5957.2008.00192.x
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    Cited by:

    1. Seya, Hajime & Tsutsumi, Morito & Yamagata, Yoshiki, 2012. "Income convergence in Japan: A Bayesian spatial Durbin model approach," Economic Modelling, Elsevier, vol. 29(1), pages 60-71.
    2. Seya, Hajime & Yamagata, Yoshiki & Tsutsumi, Morito, 2013. "Automatic selection of a spatial weight matrix in spatial econometrics: Application to a spatial hedonic approach," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 429-444.
    3. Arthur Grimes & Chris Young, 2010. "Anticipatory Effects of Rail Upgrades: Auckland’s Western Line," Working Papers 10_11, Motu Economic and Public Policy Research.
    4. Rodrigo García Arancibia & Pamela Llop & Mariel Lovatto, 2023. "Nonparametric prediction for univariate spatial data: Methods and applications," Papers in Regional Science, Wiley Blackwell, vol. 102(3), pages 635-672, June.
    5. Melser, Daniel, 2020. "Estimating the housing capitalization effects of new infrastructure: Should we be using rents instead of prices?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 402-421.
    6. Grimes, Arthur & Young, Chris, 2013. "Spatial effects of urban rail upgrades," Journal of Transport Geography, Elsevier, vol. 30(C), pages 1-6.
    7. White, Karen, 2010. "Measuring Livability in Transportation Infrastructure Investments," 51st Annual Transportation Research Forum, Arlington, Virginia, March 11-13, 2010 207267, Transportation Research Forum.
    8. Seya, Hajime & Yoshida, Takahiro & Tsutsumi, Morito, 2016. "Ex-post identification of geographical extent of benefited area by a transportation project: Functional data analysis method," Journal of Transport Geography, Elsevier, vol. 55(C), pages 1-10.
    9. Zhiheng Yang & Chenxi Li & Yongheng Fang, 2020. "Driving Factors of the Industrial Land Transfer Price Based on a Geographically Weighted Regression Model: Evidence from a Rural Land System Reform Pilot in China," Land, MDPI, vol. 9(1), pages 1-21, January.
    10. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    11. Jorge Chica-Olmo & Rafael Cano-Guervos & Mario Chica-Rivas, 2019. "Estimation of Housing Price Variations Using Spatio-Temporal Data," Sustainability, MDPI, vol. 11(6), pages 1-21, March.

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