Does China’s housing supply-demand relationship impact urban innovation capability
Abstract
Unlike existing literature that explores the impact of house prices on urban innovation, this paper skillfully examines the relationship between the housing market and urban innovation from the perspective of the housing supply-demand (S-D) relationship. Utilizing panel data from 284 prefecture-level cities in China spanning from 2005 to 2020, this study investigates the respective impacts of housing supply, housing demand, and their interplay on urban innovation capacity (UIC). Our findings indicate that housing supply positively influences UIC, with a coefficient of 0.060; specifically, for every 1% increase in housing supply, UIC increases by 0.06%. Similarly, housing demand also significantly affects UIC, with a coefficient of 0.060, suggesting that a 1% increase in housing demand corresponds to a 0.060% rise in UIC. However, we observe a significant negative effect of the housing S-D relationship on UIC, with a coefficient of –0.049, indicating that an increase in the housing S-D ratio detrimentally impacts urban innovation. Furthermore, our analysis reveals that as the housing supply-demand ratio rises, house prices also tend to increase. Additionally, we identify heterogeneity in our results, indicating variations in the housing supply-demand ratio’s impact on the innovation capacity of cities across different regions.
Keyword : innovation, capability, housing market, supply and demand ratio, China
How to Cite
Zhang, J., Hao, N., Zhao, G., Li, L., Xiang, X., & Han, R. (2025). Does China’s housing supply-demand relationship impact urban innovation capability. International Journal of Strategic Property Management, 29(1), 1–15. https://doi.org/10.3846/ijspm.2025.23234
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Hu, C. G., Cai, D. C., & Wen, Y. Y. (2024). Does subway mileage affect urban housing prices? An economic growth perspective. Applied Economics, 56(50), 6158–6170. https://doi.org/10.1080/00036846.2023.2268323
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Audretsch, D. B., & Feldman, M. P. (1996). R&D spillovers and the geography of innovation and production. The American Economic Review, 86(3), 630–640.
Banerjee, R., & Roy, S. S. (2014). Human capital, technological progress and trade: What explains India’s long run growth? Journal of Asian Economics, 30, 15–31. https://doi.org/10.1016/j.asieco.2013.12.003
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Brown, J. R., Martinsson, G., & Petersen, B. C. (2012). Do financing constraints matter for R&D? European Economic Review, 56(8), 1512–1529. https://doi.org/10.1016/j.euroecorev.2012.07.007
Carayannis, E. G., Grigoroudis, E., & Goletsis, Y. (2016). A multilevel and multistage efficiency evaluation of innovation systems: A multiobjective DEA approach. Expert Systems with Applications, 62, 63–80. https://doi.org/10.1016/j.eswa.2016.06.017
Chaney, T., Sraer, D., & Thesmar, D. (2012). The collateral channel: How real estate shocks affect corporate investment. American Economic Review, 102(6), 2381–2409. https://doi.org/10.1257/aer.102.6.2381
Chen, F. A., Wu, J. R., Chen, X. H., & Nielsen, C. P. (2021). Disentangling the impacts of the built environment and residential self-selection on travel behavior: An empirical study in the context of diversified housing types. Cities, 116, Article 103285. https://doi.org/10.1016/j.cities.2021.103285
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Fan, X. L., & Li, Q. F. (2022). Urban innovation behavior, economic development and environmental pollution: Empirical analysis based on panel threshold model. Science & Technology Review, 40(4), 64–73.
Furman, J. L., Porter, M. E., & Stern, S. (2002). The determinants of national innovative capacity. Research Policy, 31(6), 899–933. https://doi.org/10.1016/S0048-7333(01)00152-4
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Gao, X. M. (2023). Modern design of rural green buildings based on big data technology. Cities, 141, Article 104387. https://doi.org/10.1016/j.cities.2023.104387
Glaeser, E. L., & Nathanson, C. G. (2017). An extrapolative model of house price dynamics. Journal of Financial Economics, 126(1), 147–170. https://doi.org/10.1016/j.jfineco.2017.06.012
Grimes, A., & Aitken, A. (2010). Housing supply, land costs and price adjustment. Real Estate Economics, 38(2), 325–353. https://doi.org/10.1111/j.1540-6229.2010.00269.x
Hamidi, S., Zandiatashbar, A., & Bonakdar, A. (2019). The relationship between regional compactness and regional innovation capacity (RIC): Empirical evidence from a national study. Technological Forecasting and Social Change, 142, 394–402. https://doi.org/10.1016/j.techfore.2018.07.026
He, S. H., Du, D. B., Jiao, M. Q., & Lin, Y. (2017). Spatial-temporal characteristics of urban innovation capability and impact factors analysis in China. Geography Science, 37(07), 1014–1022.
Hou, L. Q. (2022). Study on the impact of innovative city construction on urban innovation capacity. Innovation, 16(06), 40–53.
Hu, C. G., Cai, D. C., & Wen, Y. Y. (2024). Does subway mileage affect urban housing prices? An economic growth perspective. Applied Economics, 56(50), 6158–6170. https://doi.org/10.1080/00036846.2023.2268323
Jalali, D., MacDonald, H., Ahmadian Fard Fini, A., & Shi, S. (2022). Effects of planning regulations on housing and land markets: A system dynamics modeling approach. Cities, 126, Article 103670. https://doi.org/10.1016/j.cities.2022.103670
Komikado, H., Morikawa, S., Bhatt, A., & Kato, H. (2021). High-speed rail, inter-regional accessibility, and regional innovation: Evidence from Japan. Technological Forecasting and Social Change, 167, Article 120697. https://doi.org/10.1016/j.techfore.2021.120697
Kou, Z., & Liu, X. (2020). FIND report on city and industrial innovation in China (2020). Fudan Institute of Industrial Development, School of Economics, Fudan University. https://ride.fudan.edu.cn/info/1020/1274.htm
Kuang, W. D., & Yu, J. W. (2019). Homeownership and innovation: Evidence from China’s 69 large-and middle-sized cities. Journal of East China Normal University (Philosophy and Social Sciences), 51(05), 60–66+237.
Kurcheeva, G. I., & Klochkov, G. A. (2018). Comprehensive approach to smart urban development based on Big Data application. International Conference Information Technologies in Business and Industry, 1015, Article 042025. https://doi.org/10.1088/1742-6596/1015/4/042025
Lee, C. (2022). Forecasting spatially correlated targets: Simultaneous prediction of housing market activity across multiple areas. International Journal of Strategic Property Management, 26(2), 119–126. https://doi.org/10.3846/ijspm.2022.16786
Lee, C. (2024). Train stations and house prices: A local perspective. Transportation Planning and Technology, 47(1), 27–41. https://doi.org/10.1080/03081060.2023.2252397
Lee, C. F. (2013). Human resource development and innovation in China: State HRD policies, organizational practices, and research opportunities. Journal of Chinese Human Resource Management, 4(2), 144–150. https://doi.org/10.1108/JCHRM-05-2013-0016
Li, N., Li, R. Y. M., & Nuttapong, J. (2022). Factors affect the housing prices in China: A systematic review of papers indexed in Chinese Science Citation Database. Property Management, 40(5), 780–796. https://doi.org/10.1108/PM-11-2020-0078
Lin, X., Ren, T., Wu, H., & Xiao, Y. (2021). Housing price, talent movement, and innovation output: Evidence from Chinese cities. Review of Development Economics, 25(1), 76–103. https://doi.org/10.1111/rode.12705
Lopez-Carreiro, I., & Monzon, A. (2018). Evaluating sustainability and innovation of mobility patterns in Spanish cities. Analysis by size and urban typology. Sustainable Cities and Society, 38, 684–696. https://doi.org/10.1016/j.scs.2018.01.029
Lu, L. C., & Li, Y. (2010). A research on Chinese renovation urban system based on urban renovation function. Acta Geographica Sinica, 65(2), 177–190.
Luo, S. C., & Chen, W. M. (2019). House price rises, elements mismatch and development of innovative cities in China. Shanghai Journal of Economics, 3, 38–47.
Mao, F. F., Zheng, F., & He, H. Z. (2019). Do housing policies of “Robbing people” improve urban innovation capabilities? Journal of Finance and Economics, 7, 109–121.
Marmolejo-Duarte, C., & Chen, A. (2022). The effect of energy performance ratings over residential prices or how an insufficient control of architectural-quality may render spurious conclusions. Cities, 126, Article 103674. https://doi.org/10.1016/j.cities.2022.103674
Medina, R. M., Byrne, K., Brewer, S., & Nicolosi, E. A. (2020). Housing inequalities: Eviction patterns in Salt Lake County, Utah. Cities, 107, Article 102804. https://doi.org/10.1016/j.cities.2020.102804
Murray, C. K. (2022). A housing supply absorption rate equation. Journal of Real Estate Finance and Economics, 64(2), 228–246. https://doi.org/10.1007/s11146-020-09815-z
Puglisi, V., & Celani, A. (2017). Market innovation, rational housing supply and urban quality at the neighborhood scale. Materials Science and Engineering, 245, Article 062050. https://doi.org/10.1088/1757-899X/245/6/062050
Ramzi, T., & Salah, A. B. (2018). The determinants of innovation capacity in the less innovative countries in the Euro-Mediterranean region. Journal of the Knowledge Economy, 9, 526–543. https://doi.org/10.1007/s13132-015-0347-3
Reed, R. R., & Ume, E. S. (2017). Housing and unemployment: The search for the “American Dream”. Journal of Macroeconomics, 48, 72–86. https://doi.org/10.1016/j.jmacro.2016.01.001
Sohn, S. Y., Kim, D. H., & Jeon, S. Y. (2016). Re-evaluation of global innovation index based on a structural equation model. Technology Analysis & Strategic Management, 28(4), 492–505. https://doi.org/10.1080/09537325.2015.1104412
Strange, W., Hejazi, W., & Tang, J. (2006). The uncertain city: Competitive instability, skills, innovation and the strategy of agglomeration. Journal of Urban Economics, 59(3), 331–351. https://doi.org/10.1016/j.jue.2005.10.006
Sun, Q. Z., Gao, Q. D., Wu, B., Huang, J. R., Guo, H. Z., & Jiang, C. M. (2024). Sellers and buyers with lower construal levels are more likely to reach second-hand transactions: The focus-separation effect between sellers and buyers. Acta Psychologica Sinica, 56(8), 1141–1156. https://doi.org/10.3724/SP.J.1041.2024.01141
Torab, E. S. (2018). A law or just a hypothesis? A critical review of supply and demand effect on the affordable residential markets in developing countries. Alexandria Engineering Journal, 57(4), 4081–4090. https://doi.org/10.1016/j.aej.2018.10.010
Wang, S. Y. (2011). State misallocation and housing prices: Theory and evidence from China. American Economic Review, 101(5), 2081–2107. https://doi.org/10.1257/aer.101.5.2081
Wang, W. C., & Rong, Z. (2014). A study of the impact of rising house prices on the inhibition of innovation in industrial firms. Economics, 13(02), 465–490. (in Chinese)
Wang, X., & Wen, Y. (2011). Can rising housing prices explain China’s high household saving rate? Federal Reserve Bank of St. Louis Review, 93(2), 67–87. https://doi.org/10.20955/r.93.67-88
Wang, X., Duan, Y., Liu, P., & Han, G. (2020). The influence of housing investment on urban innovation: An empirical analysis based on city-level panel data in China. Sustainability, 12(7), Article 2968. https://doi.org/10.3390/su12072968
Warren-Myers, G., & Heywood, C. (2018). A new demand-supply model to enable sustainability in new Australian housing. Sustainability, 10(2), Article 376. https://doi.org/10.3390/su10020376
Xue, B. Q. (2022). Spatio-temporal pattern of urban innovation capacity in the Yellow River Basin and influencing factors. Journal of Desert Research, 42(06), 116–124. (in Chinese)
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