Effect of land prices on the spatial differentiation of housing prices: Evidence from cross-county analyses in China

doi:10.1007/s11442-018-1501-1

Abstract

Abstract:

This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014. Multiple theoretical perspectives on housing demand, supply, and market, are combined to establish a housing price model to explore the impact of land prices on housing prices. The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geographical detector technique. Finally, the influencing mechanism of land prices on housing prices is discussed. The main conclusions are as follows. (1) Housing prices have a pyramid-ranked distribution in China, where higher housing prices are linked to smaller urban populations. (2) Land prices are the primary driver of housing prices, and their impacts on housing prices vary over different administrative levels. To be specific, the effect of land prices is the strongest in the urban districts of provincial capital cities. (3) The internal influence mechanisms for land prices driving housing prices are: topographic factors, urban construction level, the agglomeration degree of high-quality public service resources, and the tertiary industrial development level. The urban land supply plan (supply policies) is the intrinsic driver that determines land prices in cities; through supply and demand, cost, and market mechanisms, land prices then impact housing prices.

Key words: housing prices, land prices, influencing factors, spatial differentiation, county unit, China

Shaojian WANG, Jieyu WANG, Yang WANG. Effect of land prices on the spatial differentiation of housing prices: Evidence from cross-county analyses in China[J].Journal of Geographical Sciences, 2018, 28(6): 725-740.

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References 55

[1]	Bischoff O, 2012. Explaining regional variation in equilibrium real estate prices and income.Journal of Housing Economics, 21(1): 1-15. doi: 10.1016/j.jhe.2011.11.002
[2]	Bramley G, 1993. The impact of land use planning and tax subsidies on the supply and price of housing in Britain.Urban Studies, 30(1): 5-30. doi: 10.1080/00420989320080011
[3]	Caplin A, Leahy J, 2011. Trading frictions and house price dynamics.Journal of Money, Credit and Banking, 43(Suppl.2): 283-303. doi: 10.1111/j.1538-4616.2011.00436.x
[4]	Capozza D R, Schwann G M, 1989. The asset approach to pricing urban land: Empirical evidence.Real Estate Economics, 17(2): 161-174. doi: 10.1111/reec.1989.17.issue-2
[5]	Chen J, Guo F, Wu Y, 2011. One decade of urban housing reform in China: Urban housing price dynamics and the role of migration and urbanization, 1995-2005.Habitat International, 35(1): 1-8. doi: 10.1016/j.habitatint.2010.02.003
[6]	Chen Y, Wang H, 2011. Construction and application of bipartite recursive algorithm based on kernel density estimation: A new non-parametric method to measure the given income population scale.Statistics & Information Forum, 26(9): 3-8. (in Chinese)
[7]	Cohen J P, Ioannides Y M, Thanapisitikul W, 2015. Spatial effects and house price dynamics in the U.S.A.Journal of Housing Economics, 31(1): 1-13. doi: 10.1016/j.jhe.2015.10.006
[8]	Fortura P, Kushner J, 1986. Canadian inter-city house price differentials.Real Estate Economics, 14(4): 525-536. doi: 10.1111/1540-6229.00401
[9]	Gao Y, Zhao R, Shan A.et al, 2010. SOFM-based classification for land price of city in China.Acta Scientiarum Naturalium Universitatis Pekinensis, 46(4): 655-660. (In Chinese)
[10]	Glaeser E L, Gyourko J, Saks R, 2005. Why is Manhattan so expensive? Regulation and the rise in housing prices.Journal of Law & Economics, 48(2): 331-369. doi: 10.1086/429979
[11]	Green K P, Filipowicz J, Lafleur S.et al, 2016. The impact of land-use regulation on housing supply in Canada. Accessed September, 28.
[12]	Han L, Lu M, 2017. Housing prices and investment: An assessment of China’s inland-favoring land supply policies.Journal of the Asia Pacific Economy, 22(1): 106-121. doi: 10.1080/13547860.2016.1261452
[13]	Holly S, Pesaran M H, Yamagata T, 2010. A spatio-temporal model of house prices in the USA.Journal of Econometrics, 158(1): 160-173. doi: 10.1016/j.jeconom.2010.03.040
[14]	Holmes M J, Otero J, Panagiotidis T, 2011. Investigating regional house price convergence in the United States: Evidence from a pair-wise approach.Economic Modelling, 28(6): 2369-2376. doi: 10.1016/j.econmod.2011.06.015
[15]	Hu Y, Wang J, Li X.et al, 2011. Geographical detector-based risk assessment of the under-five mortality in the 2008 Wenchuan earthquake, China.PLoS One, 6(6): e21427. doi: 10.1371/journal.pone.0021427 pmid: 3124508
[16]	Hwang M, Quigley J M, 2006. Economic fundamentals in local housing markets: Evidence from US metropolitan regions.Journal of Regional Science, 46(3): 425-453. doi: 10.1111/j.1467-9787.2006.00480.x
[17]	Ihlanfeldt K R, 2007. The effect of land use regulation on housing and land prices.Journal of Urban Economics, 61(3): 420-435. doi: 10.1016/j.jue.2006.09.003
[18]	Kim S W, Bhattacharya R, 2009. Regional housing prices in the USA: An empirical investigation of nonlinearity.The Journal of Real Estate Finance and Economics, 38(4): 443-460. doi: 10.1007/s11146-007-9094-y
[19]	Kuethe T H, Pede V O, 2011. Regional housing price cycles: A spatio-temporal analysis using US state-level data.Regional Studies, 45(5): 563-574. doi: 10.1080/00343400903497897
[20]	Li Q, Chand S, 2013. House prices and market fundamentals in urban China.Habitat International, 40(7): 148-153. doi: 10.1016/j.habitatint.2013.04.002
[21]	Liang W, Lu M, Zhang H, 2016. Housing prices raise wages: Estimating the unexpected effects of land supply regulation in China.Journal of Housing Economics, 33: 70-81. doi: 10.1016/j.jhe.2016.07.002
[22]	Malpezzi S, 1996. Housing prices, externalities, and regulation in U.S. metropolitan areas.Journal of Housing Research, 7(2): 209-241. doi: 10.1023/A:1012216124122
[23]	Mankiw N G, Weil D N, 1989. The baby boom, the baby bust, and the housing market.Regional Science and Urban Economics, 19(2): 235-258. doi: 10.1016/0166-0462(89)90005-7 pmid: 12283640
[24]	Ortalomagné F, Rady S, 2001. Housing market dynamics: On the contribution of income shocks and credit constraints.Review of Economic Studies, 73(2): 459-485. doi: 10.1111/j.1467-937X.2006.383_1.x
[25]	Peng R, Wheaton W C, 1994. Effects of restrictive land supply on housing in Hong Kong: An econometric analysis.Journal of Housing Research, 5(2): 263-291.
[26]	Potepan M J, 1996. Explaining intermetropolitan variation in housing prices, rents and land prices.Real Estate Economics, 24(2): 219-245. doi: 10.1111/1540-6229.00688
[27]	Quigley J M, Rosenthal L A, 2s005. The effects of land use regulation on the price of housing: What do we know? What can we learn? Cityscape, 8(1): 69-137.
[28]	Quigley J M, Swoboda A M, 2010. Land use regulation with durable capital.Journal of Economic Geography, 10(1): 9-26. doi: 10.1093/jeg/lbp039
[29]	Qin Y, Zhu H, Zhu R, 2016. Changes in the distribution of land prices in urban China during 2007-2012.Regional Science and Urban Economics, 57: 77-90. doi: 10.1016/j.regsciurbeco.2016.02.002
[30]	Rubin Z, Felsenstein D, 2017. Supply side constraints in the Israeli housing market: The impact of state owned land.Land Use Policy, 65: 266-276. doi: 10.1016/j.landusepol.2017.04.002
[31]	Shen Y, Liu H, 2004. Housing prices and economic fundamentals: A cross city analysis of China for 1995-2002.Economic Research Journal, 6: 78-86.
[32]	Shih Y N, Li H C, Qin B, 2014. Housing price bubbles and inter-provincial spillover: Evidence from China.Habitat International, 43(4): 142-151. doi: 10.1016/j.habitatint.2014.02.008
[33]	Smith L B, 1974. The Postwar Canadian Housing and Residential Mortgage Markets and the Role of Government. Toronto: University of Toronto Press.
[34]	Song J, Jin X, Tang J.et al, 2011. Analysis of influencing factors for urban land price and its changing trend in China in recent years.Acta Geographica Sinica, 66(8): 1045-1054. (in Chinese) doi: 10.1007/s12182-011-0124-2
[35]	Wang J F, Li X H, Christakos G.et al, 2010. Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region, China.International Journal of Geographical Information Science, 24(1): 107-127. doi: 10.1080/13658810802443457
[36]	Wang S J, Fang C L, Guan X L.et al, 2014a. Urbanization, energy consumption, and CO2 emissions in China: A panel data analysis of China’s province.Applied Energy, 136: 738-749. doi: 10.1016/j.apenergy.2014.09.059
[37]	Wang S J, Fang C L, Ma H T.et al, 2014b. Spatial differences and multi-mechanism of carbon footprint based on GWR model in provincial China.Journal of Geographical Sciences, 24(4): 804-822. doi: 10.1007/s11442-014-1109-z
[38]	Wang S J, Fang C L, Wang Y.et al, 2015. Quantifying the relationship between urban development intensity and carbon dioxide emissions using a panel data analysis.Ecological Indicators, 49: 121-131. doi: 10.1016/j.ecolind.2014.10.004
[39]	Wang S J, Fang C L, Wang Y, 2016a. Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data.Renewable & Sustainable Energy Reviews, 55: 505-515. doi: 10.1016/j.rser.2015.10.140
[40]	Wang S J, Li Q Y, Fang C L.et al, 2016b. The relationship between economic growth, energy consumption, and CO2 emissions: Empirical evidence from China.Science of the Total Environment, 542: 360-371. doi: 10.1016/j.scitotenv.2015.10.027 pmid: 26520261
[41]	Wang S J, Liu X P, Zhou C S.et al, 2017. Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities.Applied Energy, 185: 189-200. doi: 10.1016/j.apenergy.2016.10.052
[42]	Wang Y, Fang C L, Sheng C Y, 2013. Spatial differentiation and model evolution of housing prices in Yangzhou.Acta Geographica Sinica, 68(8): 1082-1096. (in Chinese)
[43]	Wang Y, Fang C L, Xiu C L.et al, 2012. A new approach to measurement of regional inequality in particular directions.Chinese Geographical Science, 22(6): 705-717. doi: 10.1007/s11769-012-0556-7
[44]	Wang Y, Li Q, Wang S J.et al, 2014. Determinants and dynamics of spatial differentiation of housing price in Yangzhou.Progress in Geography, 33(3): 375-388. (in Chinese) doi: 10.11820/dlkxjz.2014.03.009
[45]	Wang Y, Wang D L, Liu X L.et al, 2015. Spatial differentiation of urban housing prices and its impacts on land market in China.China Land Sciences, 29(6): 33-40. (in Chinese)
[46]	Wang Y, Wang D L, Wang S J, 2013. Spatial differentiation patterns and impact factors of housing prices of China’s cities. Scientia Geographica Sinica, 33(10): 1157-1165. (in Chinese)
[47]	Wang Y, Wang S J, Li G D .et al , 2017. Identifying the determinants of housing prices in China using spatial regression and the geographical detector technique.Applied Geography, 79: 26-36. doi: 10.1016/j.apgeog.2016.12.003
[48]	Wen H, Goodman A C, 2013. Relationship between urban land price and housing price: Evidence from 21 provincial capitals in China.Habitat International, 40: 9-17. doi: 10.1016/j.habitatint.2013.01.004
[49]	Wheaton W C, 1996. Urban Economics and Real Estate Markets. Englewood Cliff: Prentice Hall.
[50]	Zabel J, Dalton M, 2011. The impact of minimum lot size regulations on house prices in Eastern Massachusetts.Regional Science & Urban Economics, 41: 571-583. doi: 10.1016/j.regsciurbeco.2011.06.002
[51]	Zang B, Lv P, Warren C M J, 2015. Housing prices, rural-urban migrants’ settlement decisions and their regional differences in China. Habitat International, 50: 149-159. doi: 10.1016/j.habitatint.2015.08.003
[52]	Zeng G, Zhang H, 2013. Test on the relationship between price of urban land and commercial residential houses.Contemporary Economic Research, (6): 19-25. (in Chinese)
[53]	Zhang H, 2008. Effects of urban land supply policy on real estate in China: An econometric analysis.Journal of Real Estate Literature, 16(1): 55-72.
[54]	Zhang L, Hui C M, Wen H, 2015. Housing price-volume dynamics under the regulation policy: Difference between Chinese coastal and inland cities.Habitat International, 47: 29-40. doi: 10.1016/j.habitatint.2015.01.003
[55]	Zhang L, Hui E C, Wen H, 2017. The regional house prices in China: Ripple effect or differentiation.Habitat International, 67: 118-128. doi: 10.1016/j.habitatint.2017.07.006

Variables	Definition	Expected direction	Min	Max	Mean	S.D.
Land price	Cost of land (10⁴ yuan/ha)	+	27.76	6127.08	783.02	829.99
Proportion of renters	Proportion of renters (%)	+	0.00	84.94	9.50	10.45
Floating population	Urban floating population (10⁴ person)	+	0.00	243.41	10.58	15.79
Wage level	Average wage of urban employees (yuan)	+	5128.74	125949.00	30286.80	9161.17
Housing market	Proportion of the population working in the real-estate industry (%)	+	0.00	8.06	0.56	0.89

Variables	Non-standardized coefficient	Standard error	Standardized coefficient	t-value	Significance	Model parameters
Coefficient (α₀)	-1103.623	178.337	-	-6.188	0.000	R = 0.855 R²= 0.732 Aj-R²= 0.731 F = 1502.289 Sig. = 0.000 df = 5
Land price	2.702	0.068	0.488	39.482	0.000
Proportion of renters	28.680	6.657	0.065	4.308	0.000
Floating population	0.001	0.000	0.033	2.882	0.007
Wage level	0.089	0.007	0.178	12.947	0.000
Housing market	1448.468	72.222	0.281	20.056	0.000

	Land prices	Proportion of renters	Floating population	Wage level	Housing market
Nation	0.3837	0.3291	0.1664	0.2816	0.3214
Urban district of provincial capital city	0.9070	0.9069	0.6452	0.8307	0.9244
Urban district of prefecture-level city	0.7141	0.8790	0.0095	0.9108	0.8166
County	0.7022	0.7844	0.7382	0.2829	0.7489