IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i3p317-d520536.html
   My bibliography  Save this article

Spatio-Temporal Non-Stationarity and Its Influencing Factors of Commercial Land Price: A Case Study of Hangzhou, China

Author

Listed:
  • Zhuoma Garang

    (Land Academy for National Development, Zhejiang University, Hangzhou 310029, China)

  • Cifang Wu

    (Land Academy for National Development, Zhejiang University, Hangzhou 310029, China)

  • Guan Li

    (Law School, Ningbo University, Ningbo 315211, China)

  • Yuefei Zhuo

    (Law School, Ningbo University, Ningbo 315211, China)

  • Zhongguo Xu

    (Law School, Ningbo University, Ningbo 315211, China)

Abstract

Investigating the characteristics and mechanisms of the spatial and temporal variations of commercial land prices and its major subdivisions has great theoretical and practical significance in the study of urban economy and its spatial refinement management. Unlike general commodity prices, land prices are influenced by geographical location and tend to fluctuate over time. However, most scholars have not explored the influence mechanism of commercial land prices in both time and space. To help bridge this gap, this study takes the sample commercial land prices in the main urban area of Hangzhou from 2006 to 2015 as the empirical research object and investigates the spatiotemporal evolution mechanism of urban commercial land prices through a comparative analysis of the multiple regression analysis (MRA) with ordinary least squares (OLS), the geographically weighted regression (GWR), the temporally weighted regression (TWR), and the geographically and temporally weighted regression (GTWR) models. Results indicate that the land prices of land for financial facilities (Commercial Land Category 1) and commercial-business land (Commercial Land Category 2) in Hangzhou show different spatial and temporal evolutions and are influenced by the common factors of residential land price level (PL), maturity of living services (EN), and plot ratio (FRO) in the district. Meanwhile the main difference between the two influencing factors is the significant difference in sensitivity to locational centrality and industrial structure. Furthermore, we find that the spatial and temporal evolution of commercial land prices has three main mechanism: location selection, point-axis evolution, and function-promoting. Our findings will provide guidelines for scientifically guiding the coordinated development of urban land price and industrial economy and realizing the fine management and allocation of urban spatial resources.

Suggested Citation

  • Zhuoma Garang & Cifang Wu & Guan Li & Yuefei Zhuo & Zhongguo Xu, 2021. "Spatio-Temporal Non-Stationarity and Its Influencing Factors of Commercial Land Price: A Case Study of Hangzhou, China," Land, MDPI, vol. 10(3), pages 1-27, March.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:317-:d:520536
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/3/317/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/3/317/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tian, Li & Liang, Yinlong & Zhang, Bo, 2017. "Measuring residential and industrial land use mix in the peri-urban areas of China," Land Use Policy, Elsevier, vol. 69(C), pages 427-438.
    2. 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.
    3. Davis, Morris A., 2009. "The price and quantity of land by legal form of organization in the United States," Regional Science and Urban Economics, Elsevier, vol. 39(3), pages 350-359, May.
    4. Cheng, Jing, 2021. "Analysis of commercial land leasing of the district governments of Beijing in China," Land Use Policy, Elsevier, vol. 100(C).
    5. McDonald, John F. & Osuji, Clifford I., 1995. "The effect of anticipated transportation improvement on residential land values," Regional Science and Urban Economics, Elsevier, vol. 25(3), pages 261-278, June.
    6. Yizhou Wu & Peilei Fan & Heyuan You, 2018. "Spatial Evolution of Producer Service Sectors and Its Influencing Factors in Cities: A Case Study of Hangzhou, China," Sustainability, MDPI, vol. 10(4), pages 1-23, March.
    7. Yanjing Zhang & Zhengguo Su & Guan Li & Yuefei Zhuo & Zhongguo Xu, 2018. "Spatial-Temporal Evolution of Sustainable Urbanization Development: A Perspective of the Coupling Coordination Development Based on Population, Industry, and Built-Up Land Spatial Agglomeration," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    8. Mathur, Shishir, 2020. "Impact of transit stations on house prices across entire price spectrum: A quantile regression approach," Land Use Policy, Elsevier, vol. 99(C).
    9. Qin, Yu & Zhu, Hongjia & Zhu, Rong, 2016. "Changes in the distribution of land prices in urban China during 2007–2012," Regional Science and Urban Economics, Elsevier, vol. 57(C), pages 77-90.
    10. Timothy J. Fik & David C. Ling & Gordon F. Mulligan, 2003. "Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(4), pages 623-646, December.
    11. Atack, Jeremy & Margo, Robert A, 1998. ""Location, Location, Location!" The Price Gradient for Vacant Urban Land: New York, 1835 to 1900," The Journal of Real Estate Finance and Economics, Springer, vol. 16(2), pages 151-172, March.
    12. J F McDonald & D P McMillen, 1990. "Employment Subcenters and Land Values in a Polycentric Urban Area: The Case of Chicago," Environment and Planning A, , vol. 22(12), pages 1561-1574, December.
    13. Nichols, Joseph B. & Oliner, Stephen D. & Mulhall, Michael R., 2013. "Swings in commercial and residential land prices in the United States," Journal of Urban Economics, Elsevier, vol. 73(1), pages 57-76.
    14. Robert W. Paterson & Kevin J. Boyle, 2002. "Out of Sight, Out of Mind? Using GIS to Incorporate Visibility in Hedonic Property Value Models," Land Economics, University of Wisconsin Press, vol. 78(3), pages 417-425.
    15. Chamblee, John F. & Dehring, Carolyn A. & Depken, Craig A., 2009. "Watershed development restrictions and land prices: Empirical evidence from southern Appalachia," Regional Science and Urban Economics, Elsevier, vol. 39(3), pages 287-296, May.
    16. Haizhen Wen & Zaiyuan Gui & Chuanhao Tian & Yue Xiao & Li Fang, 2018. "Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou, China," Sustainability, MDPI, vol. 10(7), pages 1-23, June.
    17. Han, M.Y. & Chen, G.Q. & Dunford, M., 2019. "Land use balance for urban economy: A multi-scale and multi-type perspective," Land Use Policy, Elsevier, vol. 83(C), pages 323-333.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tianyu Li & Yizheng Zhao & Xiang Kong, 2022. "Spatio-Temporal Characteristics and Influencing Factors of Basic Public Service Levels in the Yangtze River Delta Region, China," Land, MDPI, vol. 11(9), pages 1-23, September.
    2. Luhui Qi & Liqi Jia & Yubin Luo & Yuanyi Chen & Minggang Peng, 2022. "The External Characteristics and Mechanism of Urban Road Corridors to Agglomeration: Case Study for Guangzhou, China," Land, MDPI, vol. 11(7), pages 1-17, July.
    3. Hao Xi & Lin Tang & Changchun Feng, 2022. "Research on the Measurement Method of Benchmark Price of Rental Housing," Land, MDPI, vol. 11(5), pages 1-15, May.
    4. Qing Wang & Yuhang Xiao, 2022. "Has Urban Construction Land Achieved Low-Carbon Sustainable Development? A Case Study of North China Plain, China," Sustainability, MDPI, vol. 14(15), pages 1-29, August.
    5. Zengzheng Wang & Fuhao Zhang & Yangyang Zhao, 2023. "Exploring the Spatial Discrete Heterogeneity of Housing Prices in Beijing, China, Based on Regionally Geographically Weighted Regression Affected by Education," Land, MDPI, vol. 12(1), pages 1-24, January.
    6. Xia, Fangzhou & Lu, Pingzhen, 2023. "Can mixed land use promote social integration? Multiple mediator analysis based on spatiotemporal big data in Beijing," Land Use Policy, Elsevier, vol. 132(C).
    7. Wanfu Jin & Chunshan Zhou, 2022. "Effect of Land Marketization Level and Land Prices on Foreign Direct Investment in China," Land, MDPI, vol. 11(9), pages 1-20, August.
    8. Sisman, S. & Aydinoglu, A.C., 2022. "Improving performance of mass real estate valuation through application of the dataset optimization and Spatially Constrained Multivariate Clustering Analysis," Land Use Policy, Elsevier, vol. 119(C).
    9. Ping Zhang & Xiaojuan Yang & Hua Chen & Sidong Zhao, 2023. "Matching Relationship between Urban Service Industry Land Expansion and Economy Growth in China," Land, MDPI, vol. 12(6), pages 1-29, May.
    10. Haocong Wang & Kening Wu & Zhe Feng & Huafu Zhao & Hua Ai & Chao Meng, 2023. "Evaluation of Urban Commercial Land Use Intensification Based on Land Parcels: Taking Wuxi City as an Example," Land, MDPI, vol. 12(8), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tideman, Nicolaus & Plassmann, Florenz, 2018. "The effects of changes in land value on the value of buildings," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 69-76.
    2. Kheir, Nasr & Portnov, Boris A., 2024. "Land market segmentation along ethnic lines: Four urban localities in Israel as a case study," Land Use Policy, Elsevier, vol. 136(C).
    3. J. Scott Davis & Kevin X. D. Huang & Ayse Sapci, 2020. "Imperfect substitution in real estate markets and the effect of housing demand on corporate investment," Vanderbilt University Department of Economics Working Papers 20-00002, Vanderbilt University Department of Economics.
    4. Davis, J. Scott & Huang, Kevin X.D. & Sapci, Ayse, 2022. "Land price dynamics and macroeconomic fluctuations with imperfect substitution in real estate markets," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    5. William Larson, 2015. "New Estimates of Value of Land of the United States," BEA Working Papers 0120, Bureau of Economic Analysis.
    6. Chun-Chang Lee & Chi-Ming Liang & Hui-Chuan Hong, 2020. "The Impact of a Mass Rapid Transit System on Neighborhood Housing Prices: An Application of Difference-In-Difference and Spatial Econometrics," Real Estate Management and Valuation, Sciendo, vol. 28(1), pages 28-40, March.
    7. d’Amato, Maurizio & Zrobek, Sabina & Renigier Bilozor, Malgorzata & Walacik, Marek & Mercadante, Giuseppe, 2019. "Valuing the effect of the change of zoning on underdeveloped land using fuzzy real option approach," Land Use Policy, Elsevier, vol. 86(C), pages 365-374.
    8. Yuan, Feng & Wei, Yehua Dennis & Xiao, Weiye, 2019. "Land marketization, fiscal decentralization, and the dynamics of urban land prices in transitional China," Land Use Policy, Elsevier, vol. 89(C).
    9. Michael Iacono & David Levinson, 2017. "Accessibility dynamics and location premia: Do land values follow accessibility changes?," Urban Studies, Urban Studies Journal Limited, vol. 54(2), pages 364-381, February.
    10. repec:bea:wpaper:0209 is not listed on IDEAS
    11. Wentland, Scott A. & Ancona, Zachary H. & Bagstad, Kenneth J. & Boyd, James & Hass, Julie L. & Gindelsky, Marina & Moulton, Jeremy G., 2020. "Accounting for land in the United States: Integrating physical land cover, land use, and monetary valuation," Ecosystem Services, Elsevier, vol. 46(C).
    12. Ping Zhang & Xiaojuan Yang & Hua Chen & Sidong Zhao, 2023. "Matching Relationship between Urban Service Industry Land Expansion and Economy Growth in China," Land, MDPI, vol. 12(6), pages 1-29, May.
    13. Cheng, Jing, 2022. "Analysis of the factors influencing industrial land leasing in Beijing of China based on the district-level data," Land Use Policy, Elsevier, vol. 122(C).
    14. Konstantinos Vasilopoulos & William Tayler, 2021. "Real Estate and Construction Sector Dynamics Over the Business Cycle," Working Papers 326919291, Lancaster University Management School, Economics Department.
    15. Joseph Hiebert & Karen Allen, 2019. "Valuing Environmental Amenities across Space: A Geographically Weighted Regression of Housing Preferences in Greenville County, SC," Land, MDPI, vol. 8(10), pages 1-16, October.
    16. Ahlfeldt, Gabriel M. & Wendland, Nicolai, 2011. "Fifty years of urban accessibility: The impact of the urban railway network on the land gradient in Berlin 1890-1936," Regional Science and Urban Economics, Elsevier, vol. 41(2), pages 77-88, March.
    17. Scott Wentland & Gary Cornwall & Jeremy G. Moulton, 2023. "For What It's Worth: Measuring Land Value in the Era of Big Data and Machine Learning," BEA Papers 0115, Bureau of Economic Analysis.
    18. Can Li & Yu Meng & Yingkui Li & Jingfeng Ge & Chaoran Zhao, 2019. "Inter-Metropolitan Land-Price Characteristics and Patterns in the Beijing-Tianjin-Hebei Urban Agglomeration in China," Sustainability, MDPI, vol. 11(17), pages 1-29, August.
    19. Gao, Qishuo & Shi, Vivien & Pettit, Christopher & Han, Hoon, 2022. "Property valuation using machine learning algorithms on statistical areas in Greater Sydney, Australia," Land Use Policy, Elsevier, vol. 123(C).
    20. Bo Qin & Sun Sheng Han, 2013. "Emerging Polycentricity in Beijing: Evidence from Housing Price Variations, 2001–05," Urban Studies, Urban Studies Journal Limited, vol. 50(10), pages 2006-2023, August.
    21. Pengyu Ren & Zhaoji Li & Weiguang Cai & Lina Ran & Lei Gan, 2021. "Heterogeneity Analysis of Urban Rail Transit on Housing with Different Price Levels: A Case Study of Chengdu, China," Land, MDPI, vol. 10(12), pages 1-15, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:317-:d:520536. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.