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Urban Vibrancy: An Emerging Factor that Spatially Influences the Real Estate Market

Author

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  • Alice Barreca

    (Architecture and Design Department, Politecnico di Torino, Castello del Valentino, Viale Mattioli 39, 10125 Torino, Italy)

  • Rocco Curto

    (Architecture and Design Department, Politecnico di Torino, Castello del Valentino, Viale Mattioli 39, 10125 Torino, Italy)

  • Diana Rolando

    (Architecture and Design Department, Politecnico di Torino, Castello del Valentino, Viale Mattioli 39, 10125 Torino, Italy)

Abstract

Urban vibrancy is defined and measured differently in the literature. Originally, it was described as the number of people in and around streets or neighborhoods. Now, it is commonly associated with activity intensity, the diversity of land-use configurations, and the accessibility of a place. The aim of this paper is to study urban vibrancy, its relationship with neighborhood services, and the real estate market. Firstly, it is used a set of neighborhood service variables, and a Principal Component Analysis is performed in order to create a Neighborhood Services Index (NeSI) that is able to identify the most and least vibrant urban areas of a city. Secondly, the influence of urban vibrancy on the listing prices of existing housing is analyzed by performing spatial analyses. To achieve this, the presence of spatial autocorrelation is investigated and spatial clusters are identified. Therefore, spatial autoregressive models are applied to manage spatial effects and to identify the variables that significantly influence the process of housing price determination. The results confirm that housing prices are spatially autocorrelated and highlight that housing prices and NeSI are statistically associated with each other. The identification of the urban areas characterized by different levels of vibrancy and housing prices can effectively support the revision of the urban development plan and its regulatory act, as well as strategic urban policies and actions. Such data analyses support a deep knowledge of the current status quo, which is necessary to drive important changes to develop more efficient, sustainable, and competitive cities.

Suggested Citation

  • Alice Barreca & Rocco Curto & Diana Rolando, 2020. "Urban Vibrancy: An Emerging Factor that Spatially Influences the Real Estate Market," Sustainability, MDPI, vol. 12(1), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:1:p:346-:d:304127
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    References listed on IDEAS

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    1. Alice Barreca & Rocco Curto & Diana Rolando, 2018. "Housing Vulnerability and Property Prices: Spatial Analyses in the Turin Real Estate Market," Sustainability, MDPI, vol. 10(9), pages 1-20, August.
    2. Rocco Curto & Elena Fregonara & Patrizia Semeraro, 2015. "Listing behaviour in the Italian real estate market," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 8(1), pages 97-117, March.
    3. Yuan, Feng & Wu, Jiawei & Wei, Yehua Dennis & Wang, Lei, 2018. "Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China," Land Use Policy, Elsevier, vol. 75(C), pages 225-236.
    4. Isaac F. Megbolugbe & Marja C. Hoek-Smit & Peter D. Linneman, 1996. "Understanding Neighbourhood Dynamics: A Review of the Contributions of William G. Grigsby," Urban Studies, Urban Studies Journal Limited, vol. 33(10), pages 1779-1795, December.
    5. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    6. Harry Haupt & Joachim Schnurbus & Rolf Tschernig, 2010. "On nonparametric estimation of a hedonic price function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 894-901.
    7. Charlotta Mellander & José Lobo & Kevin Stolarick & Zara Matheson, 2015. "Night-Time Light Data: A Good Proxy Measure for Economic Activity?," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-18, October.
    8. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    9. Steven C. Bourassa & Eva Cantoni & Martin Hoesli, 2010. "Predicting House Prices with Spatial Dependence: A Comparison of Alternative Methods," Journal of Real Estate Research, American Real Estate Society, vol. 32(2), pages 139-160.
    10. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    11. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    12. Steven Bourassa & Eva Cantoni & Martin Hoesli, 2007. "Spatial Dependence, Housing Submarkets, and House Price Prediction," The Journal of Real Estate Finance and Economics, Springer, vol. 35(2), pages 143-160, August.
    13. Leopoldo Catania & Anna Gloria Billé, 2017. "Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1178-1196, September.
    14. Yong Tu & Hua Sun & Shi-Ming Yu, 2007. "Spatial Autocorrelations and Urban Housing Market Segmentation," The Journal of Real Estate Finance and Economics, Springer, vol. 34(3), pages 385-406, April.
    15. Luc Anselin & Arthur Getis, 2010. "Spatial Statistical Analysis and Geographic Information Systems," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 35-47, Springer.
    16. Gillen, Kevin & Thibodeau, Thomas & Wachter, Susan, 2001. "Anisotropic Autocorrelation in House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 23(1), pages 5-30, July.
    17. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    18. Lynne Seymour, 2005. "Spatial Data Analysis: Theory and Practice. Robert Haining," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 353-354, March.
    19. Mathew C. Schmidtlein & Roland C. Deutsch & Walter W. Piegorsch & Susan L. Cutter, 2008. "A Sensitivity Analysis of the Social Vulnerability Index," Risk Analysis, John Wiley & Sons, vol. 28(4), pages 1099-1114, August.
    20. Craig A Watkins, 2001. "The Definition and Identification of Housing Submarkets," Environment and Planning A, , vol. 33(12), pages 2235-2253, December.
    21. Charles C. Cartern & William J. Haloupek, 2000. "Spatial Autocorrelation in a Retail Context," International Real Estate Review, Global Social Science Institute, vol. 3(1), pages 34-48.
    22. Basu, Sabyasachi & Thibodeau, Thomas G, 1998. "Analysis of Spatial Autocorrelation in House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 61-85, July.
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    7. Shoaib Khalid & Fariha Zameer, 2023. "Revisiting Urban Immovable Property Valuation: An Appraisal of Spatial Heterogeneities in Punjab Using Big Data (Article)," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 62(4), pages 493-520.
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    9. Sijia Li & Chao Wu & Yu Lin & Zhengyang Li & Qingyun Du, 2020. "Urban Morphology Promotes Urban Vibrancy from the Spatiotemporal and Synergetic Perspectives: A Case Study Using Multisource Data in Shenzhen, China," Sustainability, MDPI, vol. 12(12), pages 1-24, June.
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