Acta Geographica Sinica ›› 2010, Vol. 65 ›› Issue (6): 676-684.doi: 10.11821/xb201006005

Previous Articles     Next Articles

Determinants of Residential Land Price: Structure Equation Model Analysis Using Land-leasing Parcel Data in Beijing

WU Wen-jie1, 2,3, LIU Zhi-lin4, ZHANG Wen-zhong1,2   

  1. 1. Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing, 100101, China;
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    3. Graduate University of Chinese Academy of Sciences, Beijing 100049, China;
    4. Public Administration School, Tsinghua University, Beijing 100084, China
  • Received:2009-04-23 Revised:2010-02-25 Online:2010-06-25 Published:2010-06-25
  • Supported by:

    Key Project of National Natural Science Foundation of China, No.40971077; National Natural Science Foundation of China, No.40571048; Peking University-Lincoln Institute of Urban Development and Land Policy Research Center Dissertation Fellowship


Since the 1980s Chinese cities have experienced dramatic transformation of its land use system from free allocation toward a leasehold system. Recent literatures have paid attention to spatial features and determinants of land price in transitional Chinese cities, in comparison to its counterparts in advanced market economies. Recently, many scholars have adopted the hedonic model to examine influences of urban spatial structure and local public goods on residential land leasing price. Nonetheless, research on this issue has been limited by the lack of systematic data - especially spatial data - on land leasing parcels as well as other related data sources, and by the limitation of the hedonic model in establishing the complex causal relationship between land price and its determinants. In this paper, we establish a PLS-based structural equation model to quantitatively measure the influences of accessibility to job centers and key local public services on the leasing prices of residential land parcels in transitional urban Beijing. We use Beijing as our case city, and we are particularly interested in four latent variables, i.e. distance to job centers of Beijing, public transportation connectivity, accessibility to public services, and accessibility to amenities, on residential land price during 2004-2008, the period when the land leasing market has largely been established. Based on the analysis, we found that residential land price has obvious relevance with its location to the four latent variables and influential powers of these four latent variables on the residential land price are varied. We believe our research would enrich the existing knowledge of the emerging urban land market in transitional China, and provide information for further land and housing policy making.

Key words: residential land price, public service facilities, PLS, structural equation model, Beijing