城市地价的影响因素众多且复杂,地价水平和地价变化趋势受到社会、经济、政策等多方面因素的共同影响。论文从城市土地供需和宏观政策角度选取房地产投资额、市辖区建设用地面积、耕地占用税等10 项影响因素,采用2008-2010 年全国105 个土地市场较发育城市分季度地价数据,建立地价水平值与地价增长率影响因素的多层线性模型,定量分析了不同行政层次下,各影响因素对城市土地价格和地价增长率的影响程度。研究结论显示,地价水平值与地价增长率的影响因素不尽相同,且主导因素差异显著：在市级地价影响因素中,房地产投资增长是地价上升的直接动力,而地价增长率则主要受城市建设用地面积、房地产投资额的影响较；省级耕地保护政策对平抑地价、控制地价涨速作用显著,其中新增建设用地土地有偿使用费和耕地占用税是省级层次影响最显著的两项政策指标。
宋佳楠, 金晓斌, 唐健, 张志宏, 丁宁, 赵婕, 周寅康
. 中国城市地价水平及变化影响因素分析[J]. 地理学报, 2011
, 66(8)
: 1045
-1054
.
DOI: 10.11821/xb201108004
There are many factors affecting the level of land price and its changing trends, and these factors may fluctuate from time to time according to social and economic development and people's demands. In this paper, hierarchical linear models were employed to quantitatively measure the influences and interactions of 10 factors which were chosen in three aspects of urban land supply and demand and farmland protection policy, including real estate investment, population density, urban construction land area, new area for land transfer, arable land occupation tax, new construction land use fee. The level-1 and level-2 models constitute an individual development model using quarterly land price data of 105 cities of China with well-developed land markets from 2008 to 2010 and municipal influencing factors data, aiming to explore the way these factors affect the urban land price and its growth rate. The level-2 and level-3 models constitute an organization model, intending to explore contribution degree of the provincial factors chosen in this paper to land price and its growth rate. The results showed that there are multi-level factors affecting urban land price and its growth rate, and the interclass correlation coefficient shows that 12.45% of the difference in urban land price comes from provincial "background effect". Influencing factors of urban land price and its growth rate are different, and their dominant influencing factors have significant difference. Six municipal influencing factors chosen in this paper explained 82.07% of the difference in urban land price altogether, while 62.75% of the difference in urban land price growth rate. This illustrates that changes in land price growth rate is more "rational" than those of land price. Real estate investment explained 79.90% of the difference in urban land price, being the biggest influencing factor of all the municipal factors, which is the direct driving force of land prices rising. Meanwhile, both urban construction land area and real estate investment have a significant influence on land price growth rate. Farmland protection policies have a significant effect on controlling the level of land price and its growth rate. Concretely, new construction land use fee and arable land occupation tax are two of the most notable land price influencing factors at the provincial level.
[1] Wu Liping. Mechanism of Urban Land Price. Beijing: Economic Science Press, 2007. [邬丽萍. 城市土地价格机制研究.北京: 经济科学出版社, 2007.]
[2] Wu F. China's recent urban development in the process of land and housing marketization and economic globalization.Habitat International, 2001, 25(3): 273-89.
[3] Wang Zhen, Guo Huicheng, He Chengjie et al. Driving force analysis of residential land price in Beijing Based onStatistical Methods. Acta Geographica Sinica, 2009, 64(10): 1214-1220. [王真, 郭怀成, 何成杰等. 基于统计学的北京城市居住用地价格驱动力分析. 地理学报, 2009, 64(10): 1214-1220.]
[4] Hua Wen, Fan Li, Wu Qun et al. Regression analysis of urban land value influencing factors: For Jiangsu Province.Economic Geography, 2005, 25(2): 203-205, 218. [华文, 范黎, 吴群等. 城市地价水平影响因素的相关分析: 以江苏省为例. 经济地理, 2005, 25(2): 203-205, 218.]
[5] Mostafa Morsi El Araby. The role of the state in managing urban land supply and prices in Egypt. Habitat International,2003, 27(3): 429-458.
[6] Min Hwang, John M Quigley. Economic fundamentals in local housing markets: Evidence from U.S. metropolitan regions.Journal of Regional Science, 2006, 46(3): 425-453.
[7] Ogawa K, Suzuki K. Land value and corporate investment: Evidence from Japanese Panel Data. Journal of the Japaneseand International Economies, 1998, 12(3): 232-249.
[8] Wu Wenjie, Liu Zhilin, Zhang Wenzhong. Determinants of residential land price: Structure equation model analysis usingland-leasing parcel data in Beijing. Acta Geographica Sinica, 2010, 65(6): 676-684. [武文杰, 刘志林, 张文忠. 基于结构方程模型的北京居住用地价格影响因素评价. 地理学报, 2010, 65(6): 676-684.]
[9] Ahlfeldt G, Maennig W. Impact of sports arenas on land values: Evidence from Berlin. The Annals of Regional Science,2010, 44(2): 205-227.
[10] Gao Yanna, Zhu Daolin. Influence factors of rural land price for compulsory acquisition by hedonic price model.Geomatics and Information Science of Wuhan University, 2008, 33(11): 1198-1201. [高延娜, 朱道林. 基于特征价格模型的农村土地征收价格影响因素研究. 武汉大学学报: 信息科学版, 2008, 33(11): 1198-1201.]
[11] Raimond M, Martin P, Steffen S. Hedonic price indices for the Paris housing market. Allgemeines Statistisches Archiv,2004, 88: 303-326.
[12] Zhou Ganghua. Micro influence factors of urban land price and its case study [D]. Hangzhou: Zhejiang University, 2004.[周刚华. 城市土地价格的微观影响因素及其实证研究[D]. 杭州: 浙江大学, 2004.]
[13] Bryk A S, Raudenbush S W. On heterogeneity of variance in experimental studies: A challenge to conventionalinterpretations. Psychological Bulletin, 1988, 104(3): 396-404.
[14] Rogosa D R, Brand D, Zimowski M. A growth curve approach to the measurement of change. Psychological Bulletin,1982, 90: 726-748.
[15] Song Jianan, Jin Xiaobin, Zhou Yinkang. A study on the contribution rate of agricultural land use intensity to grainproductivity based on hierarchical linear models: A case study on the Inner Mongolia. Resources Science, 2010, 32(6):1161-1168. [宋佳楠, 金晓斌, 周寅康. 基于多层线性模型的耕地集约利用对粮食生产力贡献度分析. 资源科学, 2010,32(6): 1161-1168.]
[16] Raudenbush S W, Bryk A S. Guo Zhigang et al. trans. Hierarchical Linear Models: Applications and Data AnalysisMethods. Beijing: Social Sciences Academic Press, 2007: 3-6. [郭志刚等译. 多层线性模型: 应用与数据分析方法. 北京: 社会科学文献出版社, 2007: 3-6.]
[17] Dempster A P, Laird N M, Rubin D B. Maximum likelihood from incomplete data via the EM algorithm. Journal of theRoyal Statistics Society, 1977, 39: 1-8.
[18] Dempster A P, Rubin D B, Tsutakawa R K. Estimation in covariance components models. Journal of American StatisticalAssociation, 1981, 76: 341-353.
[19] Goldstein H. Multilevel mixed linear model analysis using iterative generalized least squares. Biometrika, 1986, 73: 46-56.
[20] Longford N T. A fast scoring algorithm for maximum likelihood estimation in unbalance models with nested randomeffects. Biometrika, 1987, 74(4): 817-827.
[21] Chinese National Standards GB/T.18507-2001. Beijing: Standard Press of China, 2001: 2-3. [中华人民共和国国家标准GB/T.18507-2001. 北京: 中国标准出版社, 2001: 2-3.]
[22] Yan Xing, Lin Zengjie. Urban Property Assessment. Beijing: China Renmin University Press, 1999: 38-53. [严星, 林增杰.城市地产评估. 北京: 中国人民大学出版社, 1999: 38-53.]
[23] Ke Shanzi, He Ming. Urban land prices driven by market forces and government actions: An empirical study of Chinesecities. Modern Economic Science, 2008, 30(2): 25-32. [柯善咨, 何鸣. 市场和政府共同作用下的城市地价: 中国城市的实证研究. 当代经济科学, 2008, 30(2): 25-32.]
[24] Xie Q, Parsa A R G, Redding B. The emergence of the urban land market in China: Evolution, structure, constraints andperspectives. Urban Studies, 2002, 39(8): 1375-1398.
[25] Raudenbush S W, Liu X. Statistical power and optimal design for multisite randomized trials. Psychological Methods,2000, 5(2): 199-213.
[26] Ding Jianhong. Response of residential land market to the reform of land supply policy in Beijing. China Land Science,2007, 21(3): 11-18. [丁洪建. 土地供应规则的变化对北京市住宅用地市场的影响. 中国土地科学, 2007, 21(3): 11-18.]
[27] Zou Pingzuo. Main characteristics and causes of changes in current land prices. China Finance, 2005, (2): 19-20. [邹平座.当前土地价格变动的主要特征与成因分析. 中国金融, 2005, (2): 19-20.]
