Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data
Abstract
Under the development pattern of the “double cycle”, optimizing urban economic resilience is tremendously meaningful to improving a city’s affordability and the adaptability of the economy and to promoting the Chinese economy to develop with high quality. Based on Baidu migration big data perspective, exploratory spatial data analysis (ESDA) and multi-scale geographical weighted regression (MGWR) model were used to analyze the spatial characteristics and driving factors of economic resilience in 287 Chinese cities in 2019. The results show that (1) the number of low-level economically resilient cities is the largest and distributed continuously, while the number of high-level economically resilient cities is the lowest and distributed in clusters and blocks; (2) compared with the Pearl River Delta and Yangtze River Delta, the population accumulation characteristic of the Beijing- Tianjin-Hebei region is relatively slow; (3) Both net inflow of population after spring festival and daily flow scale are significantly correlated with urban economic resilience, and the former will affect urban economic resilience; and (4) the spatial heterogeneity of each factor driving is significant, and they have different impact scales. The impact intensity is as follows: net population inflow > innovation ability > public financial expenditure > financial efficiency > urban size.
First published online 07 February 2023
Keyword : economic resilience, population mobility, spatial difference, Multi-scale Geographical Weighted Regression (MGWR)
How to Cite
Chen, Y., Li, K., & Zhou, Q. (2023). Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data. Technological and Economic Development of Economy, 29(2), 353–381. https://doi.org/10.3846/tede.2023.17869
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Boschma, R. (2015). Towards an evolutionary perspective on regional resilience. Regional Studies, 49(5), 733–751. https://doi.org/10.1080/00343404.2014.959481
Bristow, G., & Healy, A. (2018). Innovation and regional economic resilience: An exploratory analysis. The Annals of Regional Science, 60(2), 265–284. https://doi.org/10.1007/s00168-017-0841-6
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Chen, Y., Su, X., & Zhou, Q. (2021a). Study on the spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin. International Journal of Environmental Research and Public Health, 18(19), 10231. https://doi.org/10.3390/ijerph181910231
Chen, Y., Zhu, M., Zhou, Q., & Qiao, Y. (2021b). Research on spatiotemporal differentiation and influence mechanism of urban resilience in China based on MGWR model. International Journal of Environmental Research and Public Health, 18(3), 1056. https://doi.org/10.3390/ijerph18031056
Combes, P.-P., Duranton, G., & Gobillon, L. (2008). Spatial wage disparities: Sorting matters! Journal of Urban Economics, 63(2), 723–742. https://doi.org/10.1016/j.jue.2007.04.004
Crespo, J., Suire, R., & Vicente, J. (2014). Lock-in or lock-out? How structural properties of knowledge networks affect regional resilience. Journal of Economic Geography, 14(1), 199–219. https://doi.org/10.1093/jeg/lbt006
Dawley, S., Pike, A., & Tomaney, J. (2010). Towards the resilient region? Local Economy: The Journal of the Local Economy Policy Unit, 25(8), 650–667. https://doi.org/10.1080/02690942.2010.533424
Di Caro, P. (2017). Testing and explaining economic resilience with an application to Italian regions. Papers in Regional Science, 96(1), 93–113. https://doi.org/10.1111/pirs.12168
Diodato, D., & Weterings, A. (2012). The resilience of Dutch regions to economic shocks. Measuring the relevance of interactions among firms and workers. Papers in Evolutionary Economic Geography (PEEG), 1–42. https://www.researchgate.net/publication/254410056
Du, Y., & Yang, C. (2015). Demographic transition and labour market changes: Implications for economic development in China. In I. Claus & L. Oxley (Eds.), China’s economy: A collection of surveys (pp. 25–44). Wiley. https://doi.org/10.1002/9781118982433.ch3
Feng, X., Xiu, C., Bai, L., Zhong, Y., & Wei, Y. (2020). Comprehensive evaluation of urban resilience based on the perspective of landscape pattern: A case study of Shenyang city. Cities, 104, 102722. https://doi.org/10.1016/j.cities.2020.102722
Giannakis, E., & Bruggeman, A. (2017). Determinants of regional resilience to economic crisis: A European perspective. European Planning Studies, 25(8), 1394–1415. https://doi.org/10.1080/09654313.2017.1319464
Glaeser, E. (2011). Engines of innovation. Scientific American, 305(3), 50–55. https://www.jstor.org/stable/26002793
Glaeser, E. L., & Lu, M. (2018). Human-capital externalities in China (No. w24925). National Bureau of Economic Research. http://www.nber.org/papers/w24925
Goodchild, M. F. (2001). Models of scale and scales of modelling. In N. Tate & P. Atkinson (Eds.), Modelling scale in geographical information science (pp. 3–6). Wiley.
Gu, S., & Jian, X. (1996). The dual function of and counter-measures for rural population migration. Chinese Journal of Population Science, 8(1), 59–68. https://pubmed.ncbi.nlm.nih.gov/12291454/
Hauser, C., Tappeiner, G., & Walde, J. (2010). The learning region: The impact of social capital and weak ties on innovation. Regional Studies, 41(1), 75–88. https://doi.org/10.1080/00343400600928368
Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4(1), 1–23. https://www.jstor.org/stable/2096802
Hu, M. M., Zhang, J. M., & Huang, J. L. (2018). Assessing social-ecological system resilience in mainland China. Polish Journal of Environmental Studies, 27(3), 1085–1096. https://doi.org/10.15244/pjoes/76242
Hudson, R. (2010). Resilient regions in an uncertain world: Wishful thinking or a practical reality? Cambridge Journal of Regions, Economy and Society, 3(1), 11–25. https://doi.org/10.1093/cjres/rsp026
Jiang, D. Y., Wang, X. Y., & Zhao, R. (2022). Analysis on the economic recovery in the post COVID-19 era: Evidence from China. Frontiers in Public Health, 9, 787190. https://doi.org/10.3389/fpubh.2021.787190
Kirdar, M., & Saracoglu, S. (2008). Migration and regional convergence: An empirical investigation for Turkey. Papers in Regional Science, 87(4), 545–566. https://doi.org/10.1111/j.1435-5957.2008.00178.x
Klimanov, V. V., Mikhaylova, A. A., & Kazakova, S. M. (2018). Regional resilience: Theoretical basics of the question. Ekonomicheskaya politika, 13(6), 164–187. https://repec.ranepa.ru/rnp/ecopol/ep1853.pdf
Liu, X. L., Li, S. J., Xu, X., & Luo, J. S. (2021). Integrated natural disasters urban resilience evaluation: The case of China. Natural Hazards, 107(3), 2105–2122. https://doi.org/10.1007/s11069-020-04478-8
Martin, P., Mayer, T., & Mayneris, F. (2013). Are clusters more resilient in crises? Evidence from French exporters in 2008–2009 (CEPR Discussion Papers, No. DP9667). https://ssrn.com/abstract=2333585
Martin, R. (2012). Regional economic resilience, hysteresis and recessionary shocks. Journal of Economic Geography, 12(1), 1–32. https://doi.org/10.1093/jeg/lbr019
Masik, G. (2016). Economic resilience: The case of Poland and certain European regions. Geographia Polonica, 89(4), 457–471. https://doi.org/10.7163/GPol.0068
McMaster, R. B., & Sheppard, E. (2004). Introduction: Scale and geographic inquiry. In E. Sheppard & R. B. McMaster (Eds.), Scale and geographic inquiry: Nature, society, and method (pp. 1–22). Blackwell Publishing Ltd. https://doi.org/10.1002/9780470999141.ch1
Niu, X., Liu, S., & Zhu, Y. (2021). Spatial characteristics of urbanization in China from the perspective of inter-regional mobility. Urban Planning Forum, 1, 82–89.
Pike, A., Dawley, S., & Tomaney, J. (2010). Resilience, adaptation and adaptability. Cambridge Journal of Regions, Economy and Society, 3(1), 59–70. https://doi.org/10.1093/cjres/rsq001
Rose, A., & Liao, S. Y. (2005). Modeling regional economic resilience to disasters: A computable general equilibrium analysis of water service disruptions. Journal of Regional Science, 45(1), 75–112. https://doi.org/10.1111/j.0022-4146.2005.00365.x
Shaw, K., & Maythorne, L. (2013). Managing for local resilience: Towards a strategic approach. Public Policy and Administration, 28(1), 43–65. https://doi.org/10.1177/0952076711432578
Shi, T., Qiao, Y., & Zhou, Q. (2021). Spatiotemporal evolution and spatial relevance of urban resilience: Evidence from cities of China. Growth and Change, 52(4), 2364–2390. https://doi.org/10.1111/grow.12554
Shi, T., Qiao, Y., Zhou, Q., & Zhang, J. (2022). The regional differences and random convergence of urban resilience in China. Technological and Economic Development of Economy, 28(4), 979–1002. https://doi.org/10.3846/tede.2022.16721
Smirnov, S., Kondrashov, N., & Petronevich, A. (2015). Dating turning points of the Russian economic cycle, 1981–2015. Ekonomicheskii zhurnal Vysshei shkoly ekonomiki, 19(4), 534–553.
Storper, M., & Scott, A. J. (2009). Rethinking human capital, creativity and urban growth. Journal of Economic Geography, 9(2), 147–167. https://doi.org/10.1093/jeg/lbn052
Tong, Y., Ma, Y., & Liu, H. (2020). Short-term impact of COVID-19 on urban migration in China and evaluation of urban resilience. Journal of Geographical, 75(11), 2505–2520.
Walker, B., Gunderson, L., Kinzig, A., Folke, C., Carpenter, S., & Schultz, L. (2006). A handful of heuristics and some propositions for understanding resilience in social-ecological systems. Ecology and Society, 11(1), 13. https://www.jstor.org/stable/26267801
Website of central Government of the People’s Republic of China. (2020). Proposal of the Central Committee of the Communist Party of China on formulating the 14th Five-Year Plan for National Economic and Social Development and the Long-range objective for the year 2035. Retrieved July 2, 2021, from http://www.gov.cn/zhengce/2020-11/03/content_5556991.htm
Yan, X. D., Shi, X. R., & Fang, X. (2022). The internal dynamics and regional differences of China’s marine economic evolution based on comprehensive evaluation. Alexandria Engineering Journal, 61(10), 7571–7583. https://doi.org/10.1016/j.aej.2022.01.016
You, H., Jin, C., & Sun, W. (2020). Spatiotemporal evolution of population in Northeast China during 2012–2017: A nighttime light approach. Complexity, 2020, 3646145. https://doi.org/10.1155/2020/3646145
Yu, H. C., Fotheringham, A. S., Li, Z. Q., Oshan, T., Kang, W., & Wolf, L. J. (2020). Inference in multiscale geographically weighted regression. Geographical Analysis, 52(1), 87–106. https://doi.org/10.1111/gean.12189
Zheng, Y., Xie, X. L., Lin, C. Z., Wang, M., & He, X. J. (2018). Development as adaptation: Framing and measuring urban resilience in Beijing. Advances in Climate Change Research, 9(4), 234–242. https://doi.org/10.1016/j.accre.2018.12.002
Zhou, Q., Qiao, Y., Zhang, H., & Zhou, S. (2022). How does college scale affect urban resilience? Spatiotemporal evidence from China. Sustainable Cities and Society, 85, 104084. https://doi.org/10.1016/j.scs.2022.104084
Zhou, Q., Zhu, M. K., Qiao, Y. R., Zhang, X. L., & Chen, J. (2021). Achieving resilience through smart cities? Evidence from China. Habitat International, 111, 102348. https://doi.org/10.1016/j.habitatint.2021.102348