Estimating the economic benefits of high-speed rail in China: A new perspective from the connectivity improvement
Zhaohui Chong
Business School, Shantou University, Shantou, China
Chenglin Qin
School of Economics, Jinan University
Zhenhua Chen
City and Regional Planning, Knowlton School of Architecture, The Ohio State University, 275 West Woodruff Ave, Columbus, OH 43210, USA
DOI: https://doi.org/10.5198/jtlu.2019.1264
Keywords: Urban economic growth, Connectivity improvement, HSR network, Spillover effect
Abstract
This paper evaluates the economic benefits of high-speed rail (HSR) in China, with a focus on the connectivity change resulting from HSR development. The effect of HSR, measured in degree centrality, is assessed using a spatial econometric modeling technique based on a panel dataset that covers 268 Chinese cities from 2008-2015. To provide a robust assessment, statistical issues including heterogeneous effects, endogeneity, and spatial dependence are addressed simultaneously in the spatial panel modeling process. Our empirical results confirm that connectivity improvement brought by HSR plays a vital role in facilitating economic growth. Specifically, the contribution of HSR to urban economic growth is found to be 0.11, most of which comes from a local effect rather than a spillover effect. Overall, the research findings suggest that urban economic growth can benefit from the development of HSR.Author Biography
Chenglin Qin, School of Economics, Jinan University
Prof Qin's research concerns the economic influence of rail transit and high speed railway network, and he combines spatial econometric and social network analysis in empirical studies.References
Alstadt, B., Weisbrod, G., & Cutler, D. (2012). Relationship of transportation access and connectivity to local economic outcomes: Statistical analysis. Transportation Research Record, 2297, 154–162.
Ansar, A., Flyvbjerg, B., Budzier, A., & Lunn, D. (2016). Does infrastructure investment lead to economic growth or economic fragility? Evidence from China. Oxford Review of Economic Policy, 32(3), 360–390.
Aschauer, D. (1989). Is public expenditure productive? Journal of Monetary Economics, 23, 177–200.
Baltagi, B. H., & Pinnoi, N. (1995). Public capital stock and state productivity growth: Further evidence from an error components model. Empirical Economics, 20(2), 351–359.
Banister, D., & Berechman, Y. (2001). Transport investment and the promotion of economic growth. Journal of Transport Geography, 9(3), 209–218.
Baum-Snow, N. (2013). Urban transport expansions, employment decentralization, and the spatial scope of agglomeration economies (Working paper). Brown University, Providence, RI.
Baum-Snow, N., Brandt, L., Henderson, V. J., Turner, M. A., & Zhang, Q. (2014). Transport infrastructure, urban growth and market access in China (Working paper). Brown University, Providence, RI.
Beyzatlar, M. A., Karacal, M., & Yetkiner, H. (2014). Granger-causality between transportation and GDP: A panel data approach. Transportation Research Part A: Policy and Practice, 63, 43–55.
Blumenberg, E., & Pierce, G. (2014). A driving factor in mobility? Transportation’s role in connecting subsidized housing and employment outcomes in the Moving to Opportunity (MTO) program. Journal of the American Planning Association, 80(1), 52–66.
Bom, P. R. D., & Ligthart, J. E. (2014). What have we learned from three decades of research on the productivity of public capital? Journal of Economic Surveys, 28(5), 889–916.
Bottasso, A., Conti, M., Ferrari, C., & Tei, A. (2014). Ports and regional development: A spatial analysis on a panel of European regions. Transportation Research Part A: Policy and Practice, 65, 44–55.
Calderón, C., Moral-Benito, E., & Servén, L. (2015). Is infrastructure capital productive? A dynamic heterogeneous approach. Journal of Applied Econometrics, 30(2), 1–34.
Chatman, D. G. (2014). Estimating the effect of land use and transportation planning on travel patterns: Three problems in controlling for residential self-selection. Journal of Transport and Land Use, 7(3), 47–56.
Chen, Z., & Haynes, K. E. (2015). Public surface transportation and regional output: A spatial panel approach. Papers in Regional Science, 94(4), 727–751.
Chen, Z., & Haynes, K. E. (2017). Impact of high-speed rail on regional economic disparity in China. Journal of Transport Geography, 65, 80–91.
Chen, Z., Xue, J., Rose, A. Z., & Haynes, K. E. (2016). The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis. Transportation Research Part A: Policy and Practice, 92, 232–245.
DeLaurentis, D., Han, E. P., & Kotegawa, T. (2008). Network-theoretic approach for analyzing connectivity in air transportation networks. Journal of aircraft, 45(5), 1669–1679.
Donaldson, D., & Hornbeck, R. (2016). Railroads and American economic growth: A “market access” approach. The Quarterly Journal of Economics, 131(2), 799–858.
Duranton, G., & Turner, M. A. (2012). Urban growth and transportation. Review of Economic Studies, 79(4), 1407–1440.
Elhorst, J. P., & Oosterhaven, J. (2008). Integral cost-benefit analysis of Maglev Rail projects under market imperfections. Journal of Transport and Land Use, 1(1), 65–87.
Faber, B. (2014). Trade integration, market size, and industrialization: Evidence from China's National Trunk Highway System. The Review of Economic Studies, 81(3), 1046–1070.
Fujita, M., & Thisse, J. F. (2003). Does geographical agglomeration foster economic growth? And who gains and loses from it? The Japanese Economic Review, 54(2), 121–145.
Ghani, E., Goswami, A. G., & Kerr, W. R. (2016). Highways and spatial location within cities: Evidence from India. The World Bank Economic Review, 30(S1), S97–S108.
Giacinto, V. D., Micucci, G., & Montanaro, P. (2010). Dynamic macroeconomic effects of public capital: Evidence from regional Italian data. Giornale Degli Economisti E Annali Di Economia, 69(1), 29–66.
Gibbons, S., & Overman, H. G. (2012). Mostly pointless spatial econometrics? Journal of Regional Science, 52(2), 172–191.
Graham, D. J., & Dender, K. V. (2011). Estimating the agglomeration benefits of transport investments: Some tests for stability. Transportation, 38(3), 409–426.
Handy, S., Cao, X., & Mokhtarian, P. (2005). Correlation or causality between the built environment and travel behavior? Evidence from Northern California. Transportation Research Part D Transport & Environment, 10(6), 427–444.
Holtz-Eakin, D., & Schwartz, A. E. (1995). Infrastructure in a structural model of economic growth. Regional Science and Urban Economics, 25(2), 131–151.
Jia, S., Zhou, C., & Qin, C. (2017). No difference in effect of high-speed rail on regional economic growth based on match effect perspective? Transportation Research Part A: Policy and Practice, 106, 144–157.
Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3), 483–499.
Lesage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. Boca Raton, FL: CRC Press.
Lin, Y. (2017). Travel costs and urban specialization patterns: Evidence from china’s high-speed railway system. Journal of Urban Economics, 98(C), 98–123.
Michaels, G., Rauch, F., & Redding, S. J. (2012). Urbanization and structural transformation. The Quarterly Journal of Economics, 127(2), 535–586.
Mishra, S., Welch, T. F., & Jha, M. K. (2012). Performance indicators for public transit connectivity in multi-modal transportation networks. Transportation Research Part A: Policy and Practice, 46(7), 1066–1085.
Morten, M., & Oliveira, J. (2016). Paving the way to development: Costly migration and labor market integration (NBER working paper, No. 22158). National Bureau of Economic Research, Cambridge, MA.
Ottaviano, G. I. P., & Thisse, J. F. (2002). Integration, agglomeration and the political economics of factor mobility. Journal of Public Economics, 83(3), 429–456.
Parthasarathi, P. (2014). Network structure and metropolitan mobility. Journal of Transport and Land Use, 7(2), 153–170.
Patuelli, R., Reggiani, A., Nijkamp, P., & Bade, F. J. (2010). The evolution of the commuting network in Germany: Spatial and connectivity patterns. Journal of Transport and Land Use, 2(3/4), 5–37.
Qin, Y. (2017). No county left behind? The distributional impact of high-speed rail upgrades in China. Journal of Economic Geography, 17(3), 489–520.
Rodríguez-Pose, A., & Peralta, E. M. V. (2015). Innovation and regional growth in Mexico: 2000–2010. Growth & Change, 46(2), 172–195.
Roland-Holst, D. (2009). Infrastructure as a catalyst for regional integration, growth, and economic convergence: Scenario analysis for Asia. From growth to convergence. London: Palgrave Macmillan.
Tikoudis, I., Sundberg, M., & Karlström, A. (2012). The effects of transport infrastructure on regional economic development: A simulated spatial overlapping generations model with heterogenous skill. Journal of Transport and Land Use, 5(2), 77–101.
Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240.
Tong, T., Yu, T. H. E., Cho, S. H., Jensen, K., & Ugarte, D. D. L. T. (2013). Evaluating the spatial spillover effects of transportation infrastructure on agricultural output across the united states. Journal of Transport Geography, 30(3), 47–55.
Wang, H., Song, Z., & Wen, R. (2018). Modeling air traffic situation complexity with a dynamic weighted network approach. Journal of Advanced Transportation, Article ID 5254289.
Zhang, L., Hong, J. H., Nasri, A., & Shen, Q. (2012). How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in U.S. cities. Journal of Transport and Land Use, 5(3), 40–52.
Zhang, W. B. (2013). The impact of transport, land and fiscal policy on housing and economic geography in a small, open growth model. Journal of Transport and Land Use, 6(1), 89–100.
Zheng, S., & Kahn, M. E. (2013). China’s bullet trains facilitate market integration and mitigate the cost of megacity growth. Proceedings of the National Academy of Sciences, 110(14), E1248–E1253.
