The Impacts of High-Speed Rail on Producer Service Industry Agglomeration: Evidence from China’s Yangtze River Delta Urban Agglomeration
Abstract
:1. Introduction
2. Theoretical Framework and Hypothesis
2.1. Sample Description
2.2. Model Specification and Data Description
2.2.1. Model Specification
- (1)
- Urban scale: A higher population density means a larger urban scale, which affects the market scale to some extent and thus affects the spatial layout of the producer service industry. Hence, the urban scale is measured by population density, as denoted by the population size per square kilometer.
- (2)
- Wage level: Higher wages can attract a labor force to create wealth for enterprises, thus improving the agglomeration degree. However, higher wages will also increase the production costs of enterprises, thus reducing the agglomeration degree. The wage level is represented by the workers’ average wage level.
- (3)
- Informatization level: The improvement in the urban informatization level affects the location choice of producer service industry enterprises. The informatization level is measured by the number of Internet broadband access users.
- (4)
- Knowledge-spillover level (teacher): Producer service industry enterprises tend to introduce knowledge-flow elements into the process of production, thereby forming market competitive advantages and finally improving the enterprises’ benefits. The knowledge-spillover level is represented by the number of full-time teachers in institutions of higher learning.
- (5)
- Openness: The improvement in the openness level can further meet the needs of diverse elements of the producer service industry enterprises and affect the spatial layout of the producer service industry. The openness is represented by the proportion of foreign direct investment (FDI) actually used in the GDP of the year.
2.2.2. Data Description
3. Results and Discussion
3.1. Baseline Regression
3.2. Subdivision Industry Regression
3.3. Further Analysis
3.3.1. Parallel-Trend Test
3.3.2. Robustness Test
3.3.3. Placebo Test
3.4. Limitations and Future Work
4. Concluding Remarks
- (1)
- The planning and construction of HSR lines should be closely integrated with the development of the producer service industry and the coordinated development of the regional economy. When planning HSR lines and setting up HSR stations, we should not only consider the regional transportation demand and regional development planning but also the regional resource endowment, industrial base, industrial agglomeration modes, and other factors in order to stimulate the development potential of the producer service industry as much as possible through the planning and construction of HSR lines and promote the coordinated development of the regional economy.
- (2)
- Differentiated industrial development strategies for different industries based on a reasonable evaluation of the HSR industrial effects should be formulated. When formulating development policies for different industries and selecting regional leading industries, the agglomeration or diffusion effects of the HSR on different industries should be fully considered in order to give full play to the comparative advantages of different industries, plan industrial layout reasonably, and maximize the benefits of industrial development.
- (3)
- Differentiated industrial development strategies for core and peripheral medium- and small-sized cities based on a reasonable evaluation of the HSR industrial effects should be formulated. Considering the different industrial effects of the HSR on core and peripheral medium- and small-sized cities, the government should encourage regions with advantageous location conditions to make full use of their own advantageous resources to build a spatial agglomeration highland of producer service industries and form an industrial development pattern of “point to area” in geographical spatial distribution.
- (4)
- The development of the producer service industry is not only affected by the HSR but also by other factors such as highways, railways, and civil aviation. Based on the empirical results of this study, the government should also give full consideration to other factors affecting producer service industry agglomeration besides the HSR so as to effectively promote the development of the producer service industry.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Straszheim, M.R. Researching the role of transportation in regional development. Land Econ. 1972, 48, 212–219. [Google Scholar] [CrossRef]
- Duranton, G.; Turner, M.A. Urban growth and transportation. Rev. Econ. Stud. 2012, 79, 1407–1440. [Google Scholar] [CrossRef]
- Tierney, S. High-speed rail, the knowledge economy and the next growth wave. J. Transp. Geogr. 2012, 22, 285–287. [Google Scholar] [CrossRef]
- Ahlfeldt, G.M.; Feddersen, A. From periphery to core: Measuring agglomeration effects using high-speed rail. J. Econ. Geogr. 2018, 18, 355–390. [Google Scholar] [CrossRef]
- Jia, S.M.; Zhou, C.Y.; Qin, C.L. No difference in effect of high-speed rail on regional economic growth on match effect perspective? Transp. Res. Part A Policy Pract. 2017, 106, 144–157. [Google Scholar] [CrossRef]
- Monzón, A.; Ortega, E.; López, E. Efficiency and spatial equity impacts of high-speed rail extensions in urban areas. Cities 2013, 30, 18–30. [Google Scholar] [CrossRef] [Green Version]
- Wang, L. High-speed rail services development and regional accessibility restructuring in megaregions: A case of the Yangtze River Delta, China. Transp. Pol. 2018, 72, 34–44. [Google Scholar] [CrossRef]
- Yang, H.R.; Dobruszkes, F.; Wang, J.E.; Dijst, M.; Witte, P. Comparing China’s urban systems in high-speed railway and airline networks. J. Transp. Geogr. 2018, 68, 233–244. [Google Scholar] [CrossRef]
- Chen, Z.H.; Haynes, K.E. Impact of high-speed rail on regional economic disparity in China. J. Transp. Geogr. 2017, 65, 80–91. [Google Scholar] [CrossRef]
- Xu, W.; Huang, Y. The correlation between HSR construction and economic development-Empirical study of Chinese cities. Transp. Res. Part A Policy Pract. 2019, 126, 24–36. [Google Scholar]
- Shao, S.; Tian, Z.H.; Yang, L.L. High speed rail and urban service industry agglomeration: Evidence from China’s Yangtze River Delta region. J. Transp. Geogr. 2017, 64, 174–183. [Google Scholar] [CrossRef]
- Henderson, J.V.; Wang, H.G. Urbanization and city growth: The role of institutions. Reg. Sci. Urban Econ. 2007, 37, 283–313. [Google Scholar] [CrossRef]
- Tian, M.; Li, T.P.; Yang, S.W.; Wang, Y.W.; Fu, S.K. The Impact of High-speed rail on the service-sector agglomeration in China. Sustainability 2019, 11, 2128. [Google Scholar] [CrossRef] [Green Version]
- Faber, B. Trade integration, market size, and industrialization: Evidence from China’s national trunk highway system. Rev. Econ. Stud. 2014, 81, 1046–1070. [Google Scholar] [CrossRef] [Green Version]
- Givoni, M. Development and impact of the modern high-speed train: A review. Transp. Rev. 2006, 26, 593–611. [Google Scholar] [CrossRef]
- Verma, A.; Sudhira, H.S.; Rathi, S.; King, R.; Dash, N. Sustainable urbanization using high speed rail (HSR) in Karnataka, India. Res. Transp. Econ. 2013, 38, 67–77. [Google Scholar] [CrossRef]
- Myrdal, G. Economic Theory and Under-Developed Regions; Harper & Brothers Publishers: London, UK, 1957; pp. 115–116. [Google Scholar]
- Ezcurra, R.; Gil, C.; Pascual, P.; Rapun, M. Inequality, polarization and regional mobility in the European Union. Urban Stud. 2005, 42, 1057–1076. [Google Scholar] [CrossRef]
- Mallach, A. The uncoupling of the economic city: Increasing spatial and economic polarization in American older industrial cities. Urban Aff. Rev. 2015, 51, 443–473. [Google Scholar] [CrossRef]
- Levinson, D.M. Accessibility impacts of high-speed rail. J. Transp. Geogr. 2012, 22, 288–291. [Google Scholar] [CrossRef] [Green Version]
- Zhao, M.X.; Liu, X.J.; Derudder, B.; Zhong, Y.; Shen, W. Mapping producer services networks in mainland Chinese cities. Urban Stud. 2015, 52, 3018–3034. [Google Scholar] [CrossRef]
- Greenfield, I.H. Manpower and the Growth of Producer Services; Columbia University Press: New York, NY, USA, 1966. [Google Scholar]
- Browning, H.L.; Singelmann, J. The Emergence of a Service Society: Demographic and Sociological Aspects of the Sectoral Transformation of the Labor Force in the USA; National Technical Information Service: Springfield, OR, USA, 1975.
- Howells, J.; Green, A.E. Location, technology and industrial organization in UK services. Prog. Plann. 1986, 26, 83–183. [Google Scholar] [CrossRef]
- Marshall, J.N.; Damesick, P.; Wood, P. Under-standing the location and role of producer services in the United Kingdom. Environ. Plann. 1987, 19, 575–595. [Google Scholar] [CrossRef]
- Wei, G.; Li, X.; Yu, M.; Lu, G.; Chen, Z. The Impact of Land Transportation Integration on Service Agglomeration in Yangtze River Delta Urban Agglomeration. Sustainability 2022, 14, 12580. [Google Scholar] [CrossRef]
- Hu, M.; Xu, J. How Does High-Speed Rail Impact the Industry Structure? Evidence from China. Urban Rail Transit. 2022, 8, 296–317. [Google Scholar] [CrossRef]
- Wang, Y.; Cao, G.; Yang, Y.; Wang, J.; Zhong, T. High-speed rail to prosperity? Assessing the role of transportation improvement in the urban economy. Econ. Res.-Ekon. Istraz. 2021, 35, 1500–1525. [Google Scholar]
- Géza, T.; Lóránt, D.; Zoltán, B. A hazai folyók által érintett települések társadalmi-gazdasági vizsgálata. Földr. Közl. 2010, 134, 189–202. [Google Scholar]
- Priatmoko, S.; Kabil, M.; Purwoko, Y.; David, L. Rethinking Sustainable Community-Based Tourism: A Villager’s Point of View and Case Study in Pampang Village, Indonesia. Sustainability 2021, 13, 3245. [Google Scholar] [CrossRef]
- Sharav, N.; Givoni, M.; Shiftan, Y. What transit service does the periphery need? A case study of Israel’s rural country. Transp. Res. Part A Policy Pract. 2019, 125, 320–333. [Google Scholar] [CrossRef]
- Zhang, G.; Zheng, D.; Wu, H.; Wang, J.; Li, S. Assessing the role of high-speed rail in shaping the spatial patterns of urban and rural development: A case of the Middle Reaches of the Yangtze River, China. Sci. Total Environ. 2020, 704, 135399. [Google Scholar] [CrossRef]
- Tsai, Y.; Guan, J.; Chung, Y. Multilevel spatial impact analysis of high-speed rail and station placement: A short-term empirical study of the Taiwan HSR. J. Transp. Land Use 2020, 13, 317–341. [Google Scholar] [CrossRef]
- Masson, S.; Petiot, R. Can the high-speed rail reinforce tourism attractiveness? The case of the high-speed rail between Perpignan (France) and Barcelona (Spain). Technovation 2009, 29, 611–617. [Google Scholar] [CrossRef]
- Goe, W.R. Factors associated with the development of non-metropolitan growth nodes in producer services industries. Rural Sociol. 2009, 67, 416–441. [Google Scholar] [CrossRef]
- Andersson, D.E.; Shyr, O.F.; Fu, J. Does high-speed rail accessibility influence residential property prices? Hedonic estimates from southern Taiwan. J. Transp. Geogr. 2010, 18, 166–174. [Google Scholar] [CrossRef]
- Hiramatsu, T. Job and population location choices and economic scale as effects of high-speed rail: Simulation analysis of Shinkansen in Kyushu, Japan. Res. Transp. Econ. 2018, 72, 15–26. [Google Scholar] [CrossRef]
- Wang, L.; Yuan, F.; Duan, X.J. How high-speed rail service development influenced commercial land market dynamics: A case study of Jiangsu Province, China. J. Transp. Geogr. 2018, 72, 248–257. [Google Scholar] [CrossRef]
- Kandampully, J. The dynamics of service industry agglomerations: A phenomenon for further study. Manag. Serv. Qual. 2001, 11, 11–15. [Google Scholar]
- Wei, G.; Li, X.; Yu, M.; Lu, G.; Chen, Z. Influence Mechanism of Transportation Integration on Industrial Agglomeration in Urban Agglomeration Theory—Taking the Yangtze River Delta Urban Agglomeration as an Example. Appl. Sci. 2022, 12, 8369. [Google Scholar] [CrossRef]
- Liang, P.; Cui, X.; Lin, M.; Yang, T.; Wu, B. High-speed rail effects on station area-level business commercial agglomeration: Evidence from 110 stations in China. Front. Environ. Sci. 2022, 10, 1045959. [Google Scholar] [CrossRef]
- Yin, M.; Bertolini, L.; Duan, J. The effects of the high-speed railway on urban development: International experience and potential implications for China. Prog. Plann. 2015, 98, 1–52. [Google Scholar] [CrossRef] [Green Version]
- Arrow, K.J. The economic implications of learning by doing. Rev. Econ. Stud. 1962, 29, 155–173. [Google Scholar] [CrossRef]
- Romer, P.M. Endogenous technological-change. Trimest. Econ. 1991, 58, 441–480. [Google Scholar]
- Glaeser, E.L.; Kallal, H.D.; Scheinkman, J.A.; Shleifer, A. Growth in cities. J. Polit. Econ. 1992, 100, 1126–1152. [Google Scholar] [CrossRef]
- Martin, P.; Mayer, T.; Mayneris, F. Spatial concentration and plant-level productivity in France. J. Urban Econ. 2011, 69, 182–195. [Google Scholar] [CrossRef] [Green Version]
- Hall, P. Magic carpets and seamless webs: Opportunities and constraints for highspeed trains in Europe. Built Environ. 2009, 35, 59–69. [Google Scholar] [CrossRef]
- Chen, C.L. Reshaping Chinese space-economy through high-speed trains: Opportunities and challenges. J. Transp. Geogr. 2012, 22, 312–316. [Google Scholar] [CrossRef]
- Liu, Y.; Tang, D.; Bu, T.; Wang, Y. The spatial employment effect of high-speed railway: Quasi-natural experimental evidence from China. Ann. Reg. Sci. 2022, 69, 333–359. [Google Scholar] [CrossRef]
- Xuan, Y.; Lu, J.; Yu, Y. The impact of HSR opening on the spatial agglomeration of high-end service industry. Financ. Trade Econ. 2019, 40, 117–131. [Google Scholar]
- Wang, F.; Wei, X.; Liu, J.; He, L.; Gao, M. Impact of high-speed rail on population mobility and urbanisation: A case study on Yangtze River Delta urban agglomeration, China. Transp. Res. Part A Policy Pract. 2019, 127, 99–114. [Google Scholar] [CrossRef]
- Freeman, A. London’s Creative Sector: 2007 Update; Greater London Authority: London, UK, 2007.
- Murakami, J.; Cervero, R. High-speed rail and economic development: Business agglomerations and policy implications. In Transportation Center Working Paper No. UCTC-FR-2012-10; University of California: Berkeley, CA, USA, 2012. [Google Scholar]
- Tian, M.; Li, T.; Ye, X.; Zhao, H.; Meng, X. The impact of high-speed rail on service industry agglomeration in peripheral cities. Transp. Res. Part D Transp. Environ. 2021, 93, 102745. [Google Scholar] [CrossRef]
Variable | Indicator | Definition | Mean | Standard Deviation | Mini Mum | Maxi Mum |
---|---|---|---|---|---|---|
Dependent variable | sag | Specialized index, see Equation (2) | 0.807 | 0.318 | 0.269 | 2.153 |
dag | Diversified index, see Equation (3) | 0.229 | 0.103 | 0.064 | 0.655 | |
Group dummy variable | city | If the city is in the treatment group, then city = 1, and 0 otherwise. | 0.769 | 0.422 | 0 | 1 |
Time dummy variable | year | If HSR service exists in the city at year then when , year = 1, and 0 otherwise. | 0.398 | 0.490 | 0 | 1 |
Control variable | urban scale | The population size per square kilometer | 6.408 | 0.484 | 5.242 | 7.743 |
wage level | The workers’ average wage level | 10.702 | 0.482 | 9.407 | 11.870 | |
informatization level | The number of Internet broadband access users | 4.249 | 1.205 | 0.900 | 8.551 | |
teacher | The number of full-time teachers in institutions of higher learning | 0.804 | 1.179 | 0.010 | 5.253 | |
openness | The proportion of FDI actually used in the GDP of the year | 3.688 | 2.110 | 0.204 | 11.674 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Sag | Sag | Dag | Dag | |
0.051 ** | 0.042 * | −0.027 *** | −0.029 *** | |
(0.022) | (0.022) | (0.010) | (0.010) | |
urban scale | 0.091 | −0.067 | ||
(0.134) | (0.064) | |||
wage level | 0.134 | −0.135 *** | ||
(0.087) | (0.042) | |||
informatization level | −0.090 *** | 0.013 | ||
(0.022) | (0.010) | |||
teacher | 0.017 | −0.027 | ||
(0.038) | (0.018) | |||
openness | 0.020 *** | −0.005 ** | ||
(0.004) | (0.002) | |||
_cons | 0.820 *** | −0.902 | 0.220 *** | 1.985 *** |
(0.023) | (1.126) | (0.011) | (0.540) | |
city-fixed effect | yes | yes | yes | yes |
time-fixed effect | yes | yes | yes | yes |
N | 364 | 364 | 364 | 364 |
R-squared | 0.076 | 0.183 | 0.225 | 0.276 |
(1) | (2) | (3) | (4) | (5) | |
---|---|---|---|---|---|
Sagtra | Saginf | Sagfin | Sagren | Sagsci | |
0.029 | −0.027 | 0.145 *** | 0.032 | 0.011 | |
(0.031) | (0.050) | (0.036) | (0.049) | (0.033) | |
urban scale | 0.124 | 0.454 | 0.061 | −0.737 ** | 0.170 |
(0.192) | (0.308) | (0.222) | (0.300) | (0.201) | |
wage level | 0.100 | −0.384 * | −0.150 | 0.593 *** | 0.455 *** |
(0.124) | (0.199) | (0.144) | (0.194) | (0.130) | |
Informatization level | −0.080 ** | −0.153 *** | −0.065 * | −0.175 *** | 0.038 |
(0.031) | (0.050) | (0.036) | (0.049) | (0.033) | |
teacher | −0.171 *** | 0.564 *** | −0.140 ** | 0.167 * | −0.114 ** |
(0.055) | (0.088) | (0.063) | (0.086) | (0.057) | |
openness | 0.021 *** | 0.027 *** | 0.056 *** | −0.005 | 0.005 |
(0.006) | (0.010) | (0.007) | (0.010) | (0.006) | |
_cons | −0.708 | 1.870 | 2.176 | −0.088 | −4.935 *** |
(1.609) | (2.580) | (1.861) | (2.513) | (1.686) | |
city-fixed effect | yes | yes | yes | yes | yes |
time-fixed effect | yes | yes | yes | yes | yes |
N | 364 | 364 | 364 | 364 | 364 |
R-squared | 0.093 | 0.344 | 0.232 | 0.140 | 0.173 |
(1) | (2) | (3) | (4) | (5) | |
---|---|---|---|---|---|
Dagtra | Daginf | Dagfin | Dagren | Dagsci | |
−0.011 *** | −0.004 *** | −0.003 | −0.008 *** | −0.004 *** | |
(0.004) | (0.001) | (0.010) | (0.003) | (0.001) | |
urban scale | −0.009 | 0.014 * | 0.034 | −0.095 *** | −0.011 |
(0.024) | (0.008) | (0.059) | (0.018) | (0.009) | |
wage level | 0.003 | −0.005 | −0.195 *** | 0.038 *** | 0.024 *** |
(0.016) | (0.005) | (0.038) | (0.012) | (0.006) | |
Informatization level | 0.007 * | 0.000 | 0.008 | −0.004 | 0.001 |
(0.004) | (0.001) | (0.010) | (0.003) | (0.001) | |
teacher | −0.008 | 0.014 *** | −0.035 ** | 0.002 | 0.001 |
(0.007) | (0.002) | (0.017) | (0.005) | (0.003) | |
openness | −0.004 *** | −0.000 * | 0.006 *** | −0.004 *** | −0.002 *** |
(0.001) | (0.000) | (0.002) | (0.001) | (0.000) | |
_cons | 0.087 | −0.028 | 1.781 *** | 0.285 * | −0.140 * |
(0.201) | (0.069) | (0.494) | (0.152) | (0.076) | |
city-fixed effect | yes | yes | yes | yes | yes |
time-fixed effect | yes | yes | yes | yes | yes |
N | 364 | 364 | 364 | 364 | 364 |
R-squared | 0.218 | 0.278 | 0.177 | 0.316 | 0.298 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Sag | Sag | Dag | Dag | |
0.064 *** | 0.072 *** | −0.033 *** | −0.041 *** | |
(0.021) | (0.021) | (0.012) | (0.012) | |
urban scale | −0.158 | −0.025 | ||
(0.127) | (0.072) | |||
wage level | 0.170 ** | −0.145 *** | ||
(0.081) | (0.046) | |||
informatization level | −0.078 *** | 0.008 | ||
(0.028) | (0.016) | |||
teacher | 0.378 *** | −0.231 *** | ||
(0.137) | (0.078) | |||
openness | 0.022 *** | −0.006 *** | ||
(0.004) | (0.002) | |||
_cons | 0.736 *** | 0.100 | 0.237 *** | 1.882 *** |
(0.022) | (1.026) | (0.012) | (0.581) | |
city-fixed effect | yes | yes | yes | yes |
time-fixed effect | yes | yes | yes | yes |
N | 308 | 308 | 308 | 308 |
R-squared | 0.166 | 0.289 | 0.260 | 0.325 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Sag | Dag | Sag | Dag | |
PHSR | 0.028 | −0.021 | 0.003 | −0.013 |
(0.033) | (0.016) | (0.030) | (0.017) | |
urban scale | 0.147 | −0.108 * | −0.088 | −0.073 |
(0.136) | (0.065) | (0.129) | (0.073) | |
wage level | 0.103 | −0.113 *** | 0.116 | −0.115 ** |
(0.085) | (0.041) | (0.081) | (0.046) | |
Informatization level | −0.096 *** | 0.017 | −0.093 *** | 0.018 |
(0.022) | (0.011) | (0.029) | (0.016) | |
teacher | 0.030 | −0.036 * | 0.379 *** | −0.228 *** |
(0.039) | (0.019) | (0.141) | (0.079) | |
openness | 0.020 *** | −0.004 ** | 0.022 *** | −0.006 ** |
(0.004) | (0.002) | (0.004) | (0.002) | |
_cons | −0.947 | 2.023 *** | 0.230 | 1.871 *** |
(1.144) | (0.551) | (1.061) | (0.600) | |
city-fixed effect | yes | yes | yes | yes |
time-fixed effect | yes | yes | yes | yes |
N | 364 | 364 | 308 | 308 |
R-squared | 0.175 | 0.262 | 0.258 | 0.297 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Jin, Y.; Ou, G. The Impacts of High-Speed Rail on Producer Service Industry Agglomeration: Evidence from China’s Yangtze River Delta Urban Agglomeration. Sustainability 2023, 15, 3581. https://doi.org/10.3390/su15043581
Jin Y, Ou G. The Impacts of High-Speed Rail on Producer Service Industry Agglomeration: Evidence from China’s Yangtze River Delta Urban Agglomeration. Sustainability. 2023; 15(4):3581. https://doi.org/10.3390/su15043581
Chicago/Turabian StyleJin, Yanan, and Guoli Ou. 2023. "The Impacts of High-Speed Rail on Producer Service Industry Agglomeration: Evidence from China’s Yangtze River Delta Urban Agglomeration" Sustainability 15, no. 4: 3581. https://doi.org/10.3390/su15043581