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High-speed rail network boosts regional economic development

SUN WEIZENG and NIU DONGXIAO | 2022-08-25 | Hits:
Chinese Social Sciences Today

A high-speed train runs through a golden rice field in Songzhuang County, Lianyungang City, Jiangsu Province. Photo: CFP

As an important transmitter of the spatial flow of labor, capital, and technology, transportation infrastructure plays a key role in promoting economic growth, especially in the integration and coordinated development of regional resources. In recent years, China’s high-speed railway construction has accelerated, with a total operating mileage of 40,000 kilometers in 2021, accounting for 60% of the world’s total high-speed rail. The construction of a high-speed railway network has significantly improved accessibility between regions, enhanced the efficient flow of production factors such as information, labor, and capital, and served as a new driving force for high-quality regional economic development.
Increase of enterprises
Unlike other types of transportation, high-speed rail mainly serves passengers, so its connectivity will not create significant changes to non-labor production factors, nor will it reduce commodity transportation costs. Theoretically, the impact of high-speed rail on enterprise revenue and cost is mainly reflected in two aspects. 
First, the high-speed railway connects capital markets, commodity markets, and labor markets in different cities, which improves enterprises production efficiency by generating agglomerated economic benefits. At the same time, given the spatial-temporal compression effect brought by high-speed railway networks, communication time costs between cities are largely reduced, and market accessibility improves. 
Second, high-speed rail facilitates the flow of enterprises and labor forces, which increases the demand and price of land, and raises the labor force’s wages considering the rise of production efficiency and living costs. To maximize profits, enterprises will be faced with an efficiency vs cost trade-off.
Evidently, the attractiveness of high-speed rail to businesses will also vary according to industry and city endowments. On the one hand, from the perspective of industries, high-tech industries such as software development and biomedicine invest more capital and high-skilled labor than ordinary manufacturing industries, so their dependence on land is lower. Comparatively, low-end manufacturing is more reliant on building factories and hiring large quantities of low-skilled workers. Therefore, technology-intensive and information-intensive industries will benefit more from the agglomerated economy fueled by high-speed rail. 
On the other hand, as the main factor affecting enterprises choice of location, land prices are associated with urban land supply’s elasticity. When supply elasticity is relatively small (as when it is restricted by geographical factors or urban planning), the increase in real estate demand brought by the influx of enterprises and new labor force will lead to a spike in property prices. In this case, the dividends of agglomerated economic benefits are mostly reaped by real estate developers, which is not conducive to the development of enterprises and vice versa. 
For cities located at the edge of transportation networks, the rise in market potential may not offset the increase in cost brought by soaring property prices. Therefore, enterprises with a high degree of dependence on land cost factors will avoid edge cities when selecting sites along high-speed rail routes, as they have a limited market potential.
A study of industrial and commercial enterprise registration data for 280 cities in China, from 2000 to 2017, shows that the expansion of high-speed railways will increase the total number of newly registered enterprises per 10,000 people in the city by 1.76, but it will also lead to the withdrawal of about 0.32 enterprises, so the net increase of enterprises per 10,000 people is 1.44, equivalent to 6.26% of the net increase in urban enterprises in the same period.
Talent agglomeration
For China’s labor force, high-speed rail translates to transportation convenience, high wages, and high housing costs. High-speed rail can improve a city’s livability and enhance residents’ living utility. Moreover, by improving enterprises production efficiency, high-speed rail can drive up nominal wages and attract labor to relocate. However, the influx of labor migration could also boost housing demand, leading to higher housing prices, which in the end would result in increased living costs squeezing out part of the labor force. To maximize utility, individual workers need to trade off the above costs and benefits. 
From the perspective of labor skill differences, high-skilled labor would value the convenience of urban infrastructure more. The connectivity woven into the high-speed railway network can significantly improve high-tech enterprises’ production efficiency and nominal wages for high-skilled labor, which are conducive to the agglomeration of high-skilled labor in cities along the high-speed railways. 
In addition, urban housing supply’s elasticity will also affect the attractiveness of high-speed rail cities for workers. Low-skilled labor, whose nominal wages are less affected by the high-speed railway, may avoid cities with less elastic housing supply when choosing their places of residence.
Based on national college students’ employment surveys and dynamic data monitoring of the “floating” population in China, we found that expansion of the high-speed railway raised the proportion of college students in urban employment by a notable 0.08%, equivalent to 11.76% of the proportion of new urban employment during the same period. In the meantime, there was some decline in low-skilled labor. High-speed railway lines significantly increase the attractiveness of first- and second-tier cities for college graduates, whilst crowding out a percentage of low-skilled labor. In contrast, the labor force’s employment structure in third- and fourth-tier cities has not changed much. 
It’s worth noting that in cities with greater housing supply elasticity, opening a high-speed railway station will attract more high-skilled labor, while the crowding out effect on low-skilled labor will also be smaller. On the contrary, cities with less flexible housing supply may face a sharp rise in housing prices after the arrival of high-speed rail, which causes some low-skilled labor to leave.
Industrial upgrade
High-speed railway not only facilitates non-business trips such as tourism and family visits, but also lowers business travel’s time cost and encourages population flow between cities. According to statistics from the China Railway Corporation, high-speed rail passenger traffic reached 2.29 billion in 2019, accounting for 62.6% of China’s total rail passenger traffic, about six times more than that of 2010. The increase in passenger traffic inspires significant increases in consumer demand, which promotes the development of other industries in the region, especially the service industry. In addition, the decrease of transportation costs also helps investors explore the market and seek cross-regional cooperation opportunities, which has an impact on the industrial structure of cities.
Overall, there are great differences in terms of the impact of high-speed railway on the industrial structure of each city, which can be grouped into the following three phenomena. 
First, the division of labor effect. High-speed railway systems allow connected cities to develop industries based on their comparative advantages and achieve mutual growth through trade. Regions with relatively underdeveloped industrial structures can take advantage of their comparative advantages to undertake some industries from other cities, or further strengthen the development of advantageous industries through knowledge spillover and technological exchange. In this case, high-speed rail accelerates the division of labor and specialization between regions, enables the two cities to expand the scale of their respective leading industries, and their industrial structure trends toward short-term polarization. 
Second, the convergence effect. Being incorporated into the high-speed railway network brings cities face-to-face with larger factor and product markets, and the degree of market convergence between different cities goes up. In order to compete for high-quality resources and make full use of market potential, cities may develop similar industrial structures. With convenient travel, people can relocate to other cities, where new demand rises. In order to meet this new demand, there will be new supply side investment, which will cause industrial structure convergence between cities where the migrants are living and cities they come from. 
Third, we are witnessing a learning effect. Cities can achieve coordinated development through information exchange and mutual learning, thus improving urban production efficiency. The more developed cities set an example for others to follow. Enterprises are eager to learn advanced production technologies of other enterprises through technical personnel exchanges, field visits, and patent citations, to raise technological levels and optimize factor input structures, which transforms and upgrades the overall industry.
A study of the panel data from 280 prefecture-level and above cities in China, from 2005 to 2019, revealed that opening high-speed railway stations significantly improved urban industrial structures, and the rail’s impact accounted for 3.75%-4.84% of overall structural change. A heterogeneity analysis showed that when the initial industrial structure of connected cities is different, but the economic development level is similar, the division of labor effect plays a dominant role, leading to differentiated industrial structures among cities. When there are differences in industrial structures and development levels between connected cities, the convergence effect is dominant, leading to similar industrial structures. Under the influence of “structural deceleration” in the transition period, the learning effect was more prominent in cases of cities with a high industrial structure index, who were economically weak, learning from those with a low industrial structure index.
Future suggestions
Going forward, when making an innovation-driven development strategy, it is necessary to fully consider and make use of the economic law of enterprise location choice decision in the high-speed railway era, to improve the quality of government services, provide supporting industrial policies, stabilize the market order, and enhance comprehensive environmental competitiveness. For third- and fourth-tier cities where the agglomeration effect is weak, local governments should supplement other policies to create a good business environment.
The convenience brought by the high-speed railway network could be better used to strengthen infrastructure support within the region, improve the living environment, attract highly skilled personnel, which coupled with the labor force’s complementary skills, will promote the high-quality development of the city. Small and medium-sized cities should give full play to their comparative advantages to introduce differentiated and individualized plans to attract talent in today’s era when core cities in the high-speed railway network are often haunted by high production costs and suffer from low-skill labor saturation. 
A comprehensive evaluation of the dynamic effects of high-speed rail on the redistribution of enterprises and labor forces in an open urban system is needed to scientifically and effectively promote the systematic layout of high-speed railways and regional development strategies. By reasonably dividing the scope of urban agglomerations, to coordinate development and make use of structural differences and comparative advantages among cities, we could promote the effective integration of resources in urban agglomerations or metropolitan areas, optimize resource allocations and socioeconomic structures, and accelerate cooperation between cities, to realize high-speed rail’s traction in a wider range.
Sun Weizeng is an associate professor from the School of Economics at Central University of Finance and Economics; Niu Dongxiao is from the Department of Construction Management under the School of Civil Engineering at Tsinghua University. 



Edited by YANG XUE