Borrowed sizes: A hedonic price approach to the value of network structure in public transport systems
Keywords:hedonic price model, network effect, centrality, labour market accessibility, commuter rail
Property prices are known to be higher in places with high accessibility, such as in proximity to train stations and especially to commuter rail, than in places without this access. This study provides a better understanding of how regional accessibility, through the structure of railway networks, can influence local agglomeration economies by providing accessibility to large labor markets. Previous literature has shown a positive impact of proximity to railway stations on housing prices, and our study adds to the literature by analyzing the impact of network structure. We argue that public transport systems can support the benefits of city networks in line with Alonso’s concept of borrowed sizes (1973). Using network theory to measure accessibility provided by the network, we show that stations that provide accessibility to large labor markets across the region are perceived as more attractive by households. Cities in proximity to other cities are strengthened through their public transport links, which allow agglomeration benefits to be exploited by residents.
Alonso, W. (1964). Location and Land Use. https://doi.org/10.4159/harvard.9780674730854
Alonso, W. (1973). Urban Zero Population Growth. Daedalus, 102(4), 191–206. Retrieved from https://www.jstor.org/stable/20024174
Berger, R. T., & Enflo, K. (2015). Locomotives of local growth: The short- and long-term impact of railroads in Sweden. Journal of Urban Economics, 98, 124–138. https://doi.org/10.1016/j.jue.2015.09.001
Blumenfeld-Lieberthal, E. (2009). The topology of transportation networks: A comparison between different economies. Networks and Spatial Economics, 9, 427–458. https://doi.org/10.1007/s11067-008-9067-6
Capello, R. (2000). The City Network Paradigm: Measuring Urban Network Externalities. Urban Studies, 37(11), 1925–1945. https://doi.org/10.1080/713707232
Chatman, D. G., & Noland, R. B. (2011). Do Public Transport Improvements Increase Agglomeration Economies? A Review of Literature and an Agenda for Research. Transport Reviews, 31(6), 725–742. https://doi.org/10.1080/01441647.2011.587908
Crucitti, P., Latora, V., & Porta, S. (2006). Centrality measures in spatial networks of urban streets. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 73(3), 036125. https://doi.org/10.1103/PhysRevE.73.036125
Curtis, C., & Scheurer, J. (2017). Performance measures for public transport accessibility: Learning from international practice. The Journal of Transport and Land Use, 10(1), 1–26. Retrieved from http://dx.doi.org/10.5198/jtlu.2016.683
Czembrowski, P., & Kronenberg, J. (2016). Hedonic pricing and different urban green space types and sizes: Insights into the discussion on valuing ecosystem services. Landscape and Urban Planning, 146, 11–19. https://doi.org/10.1016/j.landurbplan.2015.10.005
Debrezion, G., Pels, E., & Rietveld, P. (2007). The Impact of Railway Stations on Residential and Commercial Property Value: A Meta-analysis. J Real Estate Finan Econ, 35(2), 161–180. https://doi.org/10.1007/s11146-007-9032-z
Derrible, S. (2012). Network centrality of metro systems. PLoS ONE, 7(7). https://doi.org/10.1371/journal.pone.0040575
Freeman, L. C. (1977). A Set of Measures of Centrality Based on Betweenness. Sociometry, 40(1), 35–41. Retrieved from http://www.jstor.org/stable/3033543
Freeman, L. C. (1978). Centrality in Social Networks Conceptual Clarification. Social Networks, 179, 215–239. Retrieved from http://ac.els-cdn.com.proxy.mah.se/0378873378900217/1-s2.0-0378873378900217-main.pdf?_tid=db734c84-3724-11e7-80e8-00000aacb35f&acdnat=1494601890_0c78f99120345215804378c6436470f2
Gonçalves, J. A. M., Portugal, L. da S., & Nassi, C. D. (2009). Centrality indicators as an instrument to evaluate the integration of urban equipment in the area of influence of a rail corridor. Transportation Research Part A: Policy and Practice, 43, 13–25. https://doi.org/10.1016/j.tra.2008.06.010
Johansson, B., & Quigley, J. M. (2004). Agglomeration and networks in spatial economies. Papers in Regional Science, (83), 165–176. https://doi.org/10.1007/s10110-003-0181-z
Kelejian, H. H., & Prucha, I. R. (2010). Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances. Journal of Econometrics, 157(1), 53–67. https://doi.org/10.1016/j.jeconom.2009.10.025
Knudsen, M. A., & Rich, J. (2013). Ex post socio-economic assessment of the Öresund Bridge. Transport Policy, 27, 53–65.
Laird, J. J., & Venables, A. J. (2017). Transport investment and economic performance: A framework for project appraisal. Transport Policy, 56, 1–11. https://doi.org/10.1016/j.tranpol.2017.02.006
Lancaster, K. J. (1966). A New Approach to Consumer Theory. Journal of Political Economy, 74(2), 132–157. Retrieved from http://www.jstor.org/stable/1828835
Li, Z., Xu, M., & Shi, Y. (2015). Centrality in global shipping network basing on worldwide shipping areas. GeoJournal, (80), 47–60. https://doi.org/10.1007/s10708-014-9524-3
McCann, P. (2012). ‘The Role of Industrial Clustering and Increasing Returns to Scale in Economic Development and Urban Growth’. In N. Brooks, K. Donaghy, & G.-J. Knaap (Eds.), The Oxford Handbook of Urban Economics and Planning. https://doi.org/10.1093/oxfordhb/9780195380620.013.0009
Meijers, E. J., Burger, M. J., & Hoogerbrugge, M. M. (2015). Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe. Papers in Regional Science, 95(1). https://doi.org/10.1111/pirs.12181
Melo, P. C., Graham, D. J., & Noland, R. B. (2009). Regional Science and Urban Economics A meta-analysis of estimates of urban agglomeration economies. Regional Science and Urban Economics, 39(3), 332–342. https://doi.org/10.1016/j.regsciurbeco.2008.12.002
Mohammad, S. I., Graham, D. J., Melo, P. C., & Anderson, R. J. (2013). A meta-analysis of the impact of rail projects on land and property values. Transportation Research Part A, 50, 158–170. https://doi.org/10.1016/j.tra.2013.01.013
Nelson, J. P. (2004). Meta-Analysis of Airport Noise and Hedonic Property Values: Problems and Prospects Meta-Analysis of Airport Noise and Hedonic Property Values Problems and Prospects. Journal of Transport Economics and Policy, 38(1), 1–28. Retrieved from http://www.jstor.org/stable/20173043
Nguyen-Hoang, P., & Yinger, J. (2011). The capitalization of school quality into house values: A review. Journal of Housing Economics, 20(1), 30–48. https://doi.org/10.1016/j.jhe.2011.02.001
Osland, L. (2010). An Application of Spatial Econometrics in Relation to Hedonic House Price Modeling. The Journal of Real Estate Research, 32(3), 289–320.
Osland, L., & Thorsen, I. (2008). Effects on housing prices of urban attraction and labor-market accessibility. Environment and Planning A, 40(10), 2490–2509. https://doi.org/10.1068/a39305
Rosen, S. (1974). Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition. Journal of Political Economy, 82(1), 34–55. Retrieved from http://www.jstor.org/stable/1830899
Straatemeier, T. (2008). How to plan for regional accessibility? Transport Policy, 15(2), 127–137. https://doi.org/10.1016/J.TRANPOL.2007.10.002
To, W. M. (2015). Centrality of an Urban Rail System. Urban Rail Transit, 1(4), 249–256. https://doi.org/10.1007/s40864-016-0031-3
van Meeteren, M., Neal, Z., & Berudder, B. (2015). Disentangling agglomeration and network externalities : A conceptual typology. Papers in Regional Science, 95(1). https://doi.org/10.1111/pirs.12214
Xiao, Y., Orford, S., & Webster, C. J. (2016). Urban configuration, accessibility, and property prices: a case study of Cardiff, Wales. Environment and Planning B: Planning and Design, 43(1), 108–129. https://doi.org/10.1177/0265813515600120
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