Summary:
The construction of transportation infrastructure is a leading factor in economic development. In the last 10 years, China has made considerable progress in developing the infrastructure for its high-speed railway, which is now the world‘s largest and fastest rail network. The network characteristics of transport infrastructure can improve spatial accessibility by reducing the transportation costs. Transport infrastructure can also increase the free flow of innovation and lead to innovation spillover across regions (Krugman, 1991). In general, if transportation infrastructure leads to a one-way flow of innovation factors, it can be seen to have had an agglomeration effect on regional innovation and a negative spillover effect in terms of space. If it leads to the two-way flow of innovation factors, it can be seen to have had an innovation diffusion effect and a positive spillover effect in terms of space (Cantos et al., 2005). Although the literature has mostly focused on the macro-economic effects of high-speed rail, a few studies have focused on high-speed rail from the perspective of heterogeneous firm theory and analyzed the mechanism of the innovation incentives for firms. The extension of the high-speed rail network has improved the accessibility of the major cities in China, and had innovation “spillover effects” on the cities along the lines. In addition, the extension of the high-speed railway has strengthened the foundations for innovation in the central cities through economic agglomeration, and thus had a “siphon effect” in transferring high-end economic factors from the cities along the line to the central cities. In this paper, we use the firms in cities that joined the high-speed rail network in 2008-2012 as our research object for conducting quasi-natural experiments to determine the effects of high-speed rail on the innovative performance of firms along the lines. First, our results show that in general, the number of patent applications and the average annual patent citations of the treatment firms are significantly higher than those of the control group of firms without access to high-speed rail. Specifically, there is a significant positive effect on the number of patent applications for inventions, utility models, and designs, with the increase in the number of patent applications for utility models being greater than that for the others. Second, gaining access to high-speed rail has a dynamic effect on firm innovation, showing positive innovation effects within one to three years. Notably, the amount of patent applications reaches a local peak after one year, and the average patent citations reach a local peak after three years. Third, the distance from the innovation center has a partial “U”-shaped relationship with the effect on innovation, such that the positive effect is greater for cities within 100 km of a railway line than those 200-300 km away from a line. Fourth, our analysis of the intermediary mechanism shows that firm-level variables such as the degree of competition, entry and exit, change in profit, and change in human capital, and city-industry level variables such as the industry concentration, transportation volume, investment volume, and market potential can explain the changes in firms' innovation behavior. Fifth, in cities closer to the technological frontier, the more competitive industries can achieve greater positive innovation. This paper makes the following contributions. (1) The literature has mainly explored the effects of transport infrastructure at the macro level, and we thus lack information on the micro-level effects of transport infrastructure on firm behavior. Our findings address this gap by revealing the micro-mechanism of the impact of high-speed rail on firm innovation in cities on the network. (2) Existing studies on the micro effects of transport have potential endogeneity issues (Li and Tang, 2015; Zhang et al., 2018). In this paper, these endogeneity issues are resolved by using the high-speed railway network as a quasi-natural experiment. (3) We provide empirical evidence of the positive impact of transport infrastructure on economic growth. Specifically, we show that infrastructure construction, including high-speed rail, can achieve the dual goals of upgrading the innovation “hardware” and “software.” Our findings have a number of policy implications. First, the government should accelerate the supply side of the structural reform of transport infrastructure to improve the level of economic development. In this regard, a possible implementation path would be to increase the supply of high-quality infrastructure and the construction of transportation infrastructure, especially in relatively backward areas. Second, the government should accelerate the development of an innovative economy and focus on the factors that drive innovation in the central cities. Improving the quality of the railway infrastructure in underdeveloped cities can also help narrow the development gap between different regions. Third, the government should accelerate the transformation of the modes of innovation, and seek to improve the quality and the level of application of innovation. Rather than directly stipulating the number and speed of patent applications, the government should pay more attention to the dynamic monitoring of the quality of innovation and the level of application. Overall, enhancing the effectiveness of the industrial policies will promote innovation and economic development.
诸竹君, 黄先海, 王煌. 交通基础设施改善促进了企业创新吗?——基于高铁开通的准自然实验[J]. 金融研究, 2019, 473(11): 153-169.
ZHU Zhujun, HUANG Xianhai, WANG Huang. Does Traffic Infrastructure Promote Innovation?A Quasi-natural Experiment Based on the Expansion of the High-Speed Railway Network in China. Journal of Financial Research, 2019, 473(11): 153-169.
[1]董艳梅和朱英明,2016,《高铁建设能否重塑中国的经济空间布局——基于就业,工资和经济增长的区域异质性视角》,《中国工业经济》第10期,第92~108页。 [2]冯长春、丰学兵和刘思君,2013,《高速铁路对中国省际可达性的影响》,《地理科学进展》第8期,第1187~1194页。 [3]黄先海和宋学印,2017,《准前沿经济体的技术进步路径及动力转换——从“追赶导向”到“竞争导向”》,《中国社会科学》第6期,第60~79页。 [4]黄先海、诸竹君和宋学印,2016,《中国中间品进口企业“低加成率之谜”》,《管理世界》第7期,第23~35页。 [5]刘秉镰、武鹏和刘玉海,2010,《交通基础设施与中国全要素生产率增长——基于省域数据的空间面板计量分析》,《中国工业经济》第3期,第54~64页。 [6]刘勇政和李岩,2017,《中国的高速铁路建设与城市经济增长》,《金融研究》第11期,第18~33页。 [7]龙玉、赵海龙、张新德和李曜,2017,《时空压缩下的风险投资——高铁通车与风险投资区域变化》,《经济研究》第4期,第195~208页。 [8]施震凯、邵军和浦正宁,2018,《交通基础设施改善与生产率增长:来自铁路大提速的证据》,《世界经济》第6期,第127~151页。 [9]张学良,2012,《中国交通基础设施促进了区域经济增长吗——兼论交通基础设施的空间溢出效应》,《中国社会科学》第3期,第60~77页。 [10]张克中和陶东杰,2016,《交通基础设施的经济分布效应——来自高铁开通的证据》,《经济学动态》第6期,第62~73页。 [11]Acemoglu, D., P. Aghion and F. Zilibotti, 2006, “Distance to Frontier, Selection, and Economic Growth,” Journal of the European Economic Association, 4 (1), pp.37~74. [12]Aghion, P., N. Bloom and R. Blundell, et al., 2005, “Competition and Innovation: an Inverted-U Relationship,” Quarterly Journal of Economics, 120 (2), pp.701~728. [13]Aghion, P., R. Blundell and R. Griffith, et al., 2009, “The Effects of Entry on Incumbent Innovation and Productivity,” Review of Economics and Statistics, 91 (1), pp.20~32. [14]Albalate, D. and A. Tomer, 2012, “High-speed Rail: Lessons for Policy Makers from Experiences Abroad,” Public Administration Review, 72 (3), pp.336~349. [15]Audretsch, D. B. and M. P. Feldman, 1996, “R&D Spillovers and the Geography of Innovation and Production,” American Economic Review, 86 (3), pp.630~640. [16]Cantos, P., M. Gumbau-Albert and J. Maudos, 2005, “Transport Infrastructures, Spillover Effects and Regional Growth: Evidence of the Spanish Case,” Transport Reviews, 25 (1), pp.25~50. [17]Chandra, A. and E. Thompson, 2000, “Does Public Infrastructure Affect Economic Activity? Evidence from the Rural Interstate Highway System,” Regional Science and Urban Economics, 30 (4), pp.457~490. [18]Cornaggia, J., Y. Mao and X. Tian. et al., 2015,“Does Banking Competition Affect Innovation?” Journal of Financial Economics, 115 (1), pp.189~209. [19]Donaldson, D. and R. Hornbeck, 2016, “Railroads and American Economic Growth: a ‘Market Access' Approach,” Quarterly Journal of Economics, 131, pp.799~858. [20]Grillitsch, M. and M. Nilsson, 2015, “Innovation in Peripheral Regions: Do Collaborations Compensate for a Lack of Local Knowledge Spillovers?” The Annals of Regional Science, 54 (1), pp.299~321. [21]Hall, P., 2009, “Magic Carpets and Seamless Webs: Opportunities and Constraints for High-Speed Trains in Europe,” Built Environment, 35 (1), pp.59~69. [22]Heckman, J. J. and P. Todd, 1998, “Matching as an Econometric Evaluation Estimator,” Review of Economic Studies, 65 (2), pp.261~294. [23]Ju, J., Y. J. Lin and Y. Wang, 2015, “Endowment Structures, Industrial Dynamics, and Economic Growth,” Journal of Monetary Economics, 76, pp.244~263. [24]Kaiser, U., H. C. Kongsted and T. Rønde, 2015, “Does the Mobility of R&D Labor Increase Innovation?” Journal of Economic Behavior & Organization, 110, pp.91~105. [25]Krugman, P., 1991, “Increasing Returns and Economic Geography,” Journal of Political Economy, 99 (3), pp.483~499. [26]Li, Y., H. Guo and Y. Liu, 2010, “Incentive Mechanisms, Entrepreneurial Orientation, and Technology Commercialization: Evidence from China's Transitional Economy,” Journal of Product Innovation Management, 25 (1), pp.63~78. [27]Liu, Z., 2008, “Foreign Direct Investment and Technology Spillovers: Theory and Evidence,”Journal of Development Economics, 85 (1), pp.176~193. [28]Mouzon, O. D., P. Dubois and F. S. Morton, et al., 2015, “Market Size and Pharmaceutical Innovation,” Rand Journal of Economics, 46 (4), pp.844~871. [29]Schumpeter, J. A., 1942, Capitalism, Socialism and Democracy, Published by Harper and Brothers Press. [30]Thompson, P. and M. Fox-Kean, 2005, “Patent Citations and the Geography of Knowledge Spillovers: A Reassessment,” American Economic Review, 95 (1), pp.450~460. [31]Venables, A. J., 2010, “Productivity in Cities: Self-Selection and Sorting,” Journal of Economic Geography, 11 (2), pp.241~251.