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The nexus of transport infrastructure and economic output in city-level China: a heterogeneous panel causality analysis

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Abstract

The nexus between transport infrastructure and economic output has been subject to heated debates. Existing studies investigating their nexus between transportation and economic growth tend to focus on macroscales and utilize panel data but assume homogeneity across individual units. This paper aims to handle the problem of geographic heterogeneity and panel heterogeneity embedded in Granger causality between transportation and economic growth in China. According to a panel data of 216 cities from 1999 to 2014, heterogeneous Granger non-causality model at the nation level and region-specific heterogeneous Granger non-causality models are established. Results show that the heterogeneity of their mutual causality across cities cannot be neglected. In the direction from transport infrastructure to economic output, this paper finds homogeneous causality in all geographic regions except central China and it proves that the pulling effect of transportation on economic growth is positive in China but relatively marginal in eastern and western regions. In the reverse direction, heterogeneous causality can be found in all geographic regions. However, western region finds negative impact of economic growth on transportation. Overall, bidirectional causality is observed in 53.24% of the cities (115 out of 216) in the panel. Unidirectional causality is observed in about 39.35% (85 out of 216) and no causality in 7.41% (16 out of 216). This paper concludes with some main findings and region-specific policy implications.

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Notes

  1. The data source is from http://www.chinanews.com/cj/2015/04-30/7245191.shtml.

  2. The eastern region encompasses the economically developed areas along the coast, including three provincial-level municipalities (Beijing, Tianjin and Shanghai) and seven provinces (Hebei, Jiangsu, Zhejiang, Shandong, Fujian, Guangdong, and Hainan). The other regions are inland areas with relatively lagging economies. The central region includes six provinces (Shanxi, Anhui, Jiangxi, Henan, Hubei and Hunan). The western region includes one provincial-level municipality (Chongqing) and eleven provinces (Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, Guangxi and Inner Mongolia). The northeastern region includes three provinces (Liaoning, Jilin and Heilongjiang).

  3. The p values corresponding to these three elasticity coefficients are 0.38, 0.39 and 0.05. Therefore, only the elasticity coefficient in northeastern region is significant in statistics.

  4. A total investment of 854 billion yuan is completed in central China during the 11th 5-year plan (2006–2010).

References

  • Akkemik KA, Göksal K (2012) Energy consumption-GDP nexus: heterogeneous panel causality analysis. Energy Econ 34:865–873

    Google Scholar 

  • Arvin MB, Pradhan RP, Norman NR (2015) Transportation intensity, urbanization, economic growth, and CO2 emissions in the G-20 countries. Util Policy 35:50–66

    Google Scholar 

  • Aschauer DA (1989) Is public expenditure productive? J Monet Econ 23:177–200

    Google Scholar 

  • Berndt ER, Hansson B (1991) Measuring the contribution of public infrastructure capital in Sweden. National Bureau of Economic Research, New York

    Google Scholar 

  • Beyzatlar MA, Karacal M, Yetkiner H (2014) Granger-causality between transportation and GDP: a panel data approach. Transp Res Part A Policy Pract 63:43–55

    Google Scholar 

  • Blum U (1982) Effects of transportation investments on regional growth: a theoretical and empirical investigation. Pap Reg Sci 49:169–184

    Google Scholar 

  • Boarnet MG (1996) The direct and indirect economic effects of transportation infrastructure. University of California Transportation Center, New York

    Google Scholar 

  • Boopen S (2006) Transport infrastructure and economic growth: evidence from Africa using dynamic panel estimates. Empir Econ Lett 5:37–52

    Google Scholar 

  • Bose N, Haque ME (2005) Causality between public investment in transport and communication and economic growth. J Econ Dev 30:95–106

    Google Scholar 

  • Bougheas S, Demetriades PO, Mamuneas TP (2000) Infrastructure, specialization, and economic growth. Can J Econ/Revue can d’écon 33:506–522

    Google Scholar 

  • Chatman DG, Noland RB (2011) Do public transport improvements increase agglomeration economies? A review of literature and an agenda for research. Transp Rev 31:725–742

    Google Scholar 

  • Chinahighway.com (2011) The twelfth transportation plan [交通运输“十二五”发展规划]

  • Crescenzi R, Rodríguez-Pose A (2012) An ‘integrated’ framework for the comparative analysis of the territorial innovation dynamics of developed and emerging countries. J Econ Surv 26(3):517–533

    Google Scholar 

  • Crihfield JB, Panggabean MP (1995) Is public infrastructure productive? A metropolitan perspective using new capital stock estimates. Reg Sci Urban Econ 25:607–630

    Google Scholar 

  • Cullison WE (1993) Public investment and economic growth. FRB Richmond Econ Q 79:19–33

    Google Scholar 

  • Démurger S (2001) Infrastructure development and economic growth: an explanation for regional disparities in China? J Comp Econ 29:95–117

    Google Scholar 

  • Erdil E, Yetkiner IH (2004) A panel data approach for income-health causality. The Economics of Health Reforms. Athens, Greece: Athens Institute for Education and Research, pp 701–724

  • Erdil E, Yetkiner IH (2009) The Granger-causality between health care expenditure and output: a panel data approach. Appl Econ 41:511–518

    Google Scholar 

  • Esfahani HS, Ramı́rez MAT (2003) Institutions, infrastructure, and economic growth. J Dev Econ 70:443–477

    Google Scholar 

  • Farhadi M (2015) Transport infrastructure and long-run economic growth in OECD countries. Transp Res Part A Policy Pract 74:73–90

    Google Scholar 

  • Fedderke JW, Perkins P, Luiz JM (2006) Infrastructural investment in long-run economic growth: South Africa 1875–2001. World Dev 34:1037–1059

    Google Scholar 

  • Fernald JG (1999) Roads to prosperity? Assessing the link between public capital and productivity. Am Econ Rev 89:619–638

    Google Scholar 

  • Fernandes E, Pacheco RR (2010) The causal relationship between GDP and domestic air passenger traffic in Brazil. Transp Plan Technol 33:569–581

    Google Scholar 

  • Fleisher BM, Chen J (1997) The coast–noncoast income gap, productivity, and regional economic policy in China. J Comp Econ 25:220–236

    Google Scholar 

  • Fujita M, Krugman P (2004) The new economic geography: past, present and the future. Pap Reg Sci 83:139–164

    Google Scholar 

  • Fujita M, Mori T (2005) Transport development and the evolution of economic geography. Port Econ J 4:129–156

    Google Scholar 

  • Garcia-Mila T, McGuire TJ, Porter RH (1996) The effect of public capital in state-level production functions reconsidered. Rev Econ Stat 78:177–180

    Google Scholar 

  • Gregoriou A, Ghosh S (2009) The impact of government expenditure on growth: empirical evidence from a heterogeneous panel. Bull Econ Res 61:95–102

    Google Scholar 

  • Groote P, Jacobs J, Sturm JE (1999) Output effects of transport infrastructure: the Netherlands, 1853–1913. Tijdschrift voor econ soc geogr 90:97–109

    Google Scholar 

  • Haque ME, Kim DH (2003) Public investment in transportation and communication and growth: a dynamic panel approach: University of Manchester, Center for Growth and Business Cycle Research Discussion Paper Series, p 31

  • Hart T (1993) Transport investment and disadvantaged regions: UK and European policies since the 1950s. Urban Stud 30:417–436

    Google Scholar 

  • He D, Zhang W (2010) How dependent is the Chinese economy on exports and in what sense has its growth been export-led? J Asian Econ 21:87–104

    Google Scholar 

  • He S, Bayrak MM, Lin H (2017) A comparative analysis of multi-scalar regional inequality in China. Geoforum 78:1–11

    Google Scholar 

  • Herranz-Loncán A (2007) Infrastructure investment and Spanish economic growth, 1850–1935. Explor Econ Hist 44:452–468

    Google Scholar 

  • Holtz-Eakin D, Newey W, Rosen HS (1988) Estimating vector autoregressions with panel data. Econ J Econ Soc 56:1371–1395

    Google Scholar 

  • Hurlin C (2004a) A note on causality tests in panel data models with random coefficients. Miméo, University of Orléans

  • Hurlin C (2004b) Testing Granger causality in heterogeneous panel data models with fixed coefficients. Miméo, University of Orléans

  • Iacono M, Levinson D (2016) Mutual causality in road network growth and economic development. Trans Policy 45:209–217

    Google Scholar 

  • Jiang X, He X, Zhang L, Qin H, Shao F (2017) Multimodal transportation infrastructure investment and regional economic development: a structural equation modeling empirical analysis in China from 1986 to 2011. Transp Policy 54:43–52

    Google Scholar 

  • Jiwattanakulpaisarn P, Noland RB, Graham DJ (2010) Causal linkages between highways and sector-level employment. Transp Res Part A Policy Pract 44:265–280

    Google Scholar 

  • Kim E (2002) Determinants of optimal level of transportation infrastructure. J Urban Plan Dev 128:150–163

    Google Scholar 

  • Lall SV (2007) Infrastructure and regional growth, growth dynamics and policy relevance for India. Ann Reg Sci 41:581–599

    Google Scholar 

  • Lall SV, Shalizi Z, Deichmann U (2004) Agglomeration economies and productivity in Indian industry. J Dev Econ 73:643–673

    Google Scholar 

  • Leightner JE, Inoue T (2012) Solving the omitted variables problem of regression analysis using the relative vertical position of observations. Adv Decis Sci 2012:353

    Google Scholar 

  • Levin A, Lin C-F, Chu C-SJ (2002) Unit root tests in panel data: asymptotic and finite-sample properties. J Econ 108:1–24

    Google Scholar 

  • Liddle B, Lung S (2013) The long-run causal relationship between transport energy consumption and GDP: evidence from heterogeneous panel methods robust to cross-sectional dependence. Econ Lett 121:524–527

    Google Scholar 

  • Lütkepohl H (2005) New introduction to multiple time series analysis. Springer, London

    Google Scholar 

  • Maddison D, Rehdanz K (2008) Carbon emissions and economic growth: homogeneous causality in heterogeneous panels. Working paper no. 1437. Kiel Institute for the World Economy, Kiel

  • Martinsons MG (2008) Relationship-based e-commerce: theory and evidence from China. Inf Syst J 18(4):331–356

    Google Scholar 

  • Pesaran MH, Smith R (1995) Estimating long-run relationships from dynamic heterogeneous panels. J Econ 68:79–113

    Google Scholar 

  • Pradhan RP (2019) Investigating the causal relationship between transportation infrastructure, financial penetration and economic growth in G-20 countries. Res Transp Econ 78:100766

    Google Scholar 

  • Pradhan RP, Bagchi TP (2013) Effect of transportation infrastructure on economic growth in India: the VECM approach. Res Transp Econ 38:139–148

    Google Scholar 

  • Pradhan RP, Norman NR, Badir Y, Samadhan B (2013) Transport infrastructure, foreign direct investment and economic growth interactions in India: the ARDL bounds testing approach. Proc Soc Behav Sci 104:914–921

    Google Scholar 

  • Qin D, Cagas MA, Quising P, He X-H (2006) How much does investment drive economic growth in China? J Policy Model 28:751–774

    Google Scholar 

  • Randolph S, Bogetic Z, Heffley DR (1996) Determinants of public expenditure on infrastructure: transportation and communication. World Bank policy research working paper

  • Rietveld P, Nijkamp P (1992) Transport and regional development. Research Memorandum, p 50

  • Sahoo P, Dash RK, Nataraj G (2010) Infrastructure development and economic growth in China. The Institute of Development Economics discussion paper no.261

  • Saidi S, Hammami S (2017) Modeling the causal linkages between transport, economic growth and environmental degradation for 75 countries. Transp Res Part D: Transp Environ 53:415–427

    Google Scholar 

  • Seitz H (1993) A dual economic analysis of the benefits of the public road networks. Ann Reg Sci 27:223–239

    Google Scholar 

  • Shi Y, Guo S, Sun P (2017) The role of infrastructure in China's regional economic growth. J Asian Econ 49:26–41

    Google Scholar 

  • SinaLiaoning (2016) Solving the difficulties and problems of developing northeastern China (解决东北地区发展的困难和问题)

  • Soja EW (2009) Regional planning and development theories A2—Kitchin, Rob. In: Thrift N (ed) International encyclopedia of human geography. Elsevier, Oxford, pp 259–270

    Google Scholar 

  • Song L, van Geenhuizen M (2014) Port infrastructure investment and regional economic growth in China: panel evidence in port regions and provinces. Transp Policy 36:173–183

    Google Scholar 

  • Sturm J, Jacobs J, Groote P (1999) Output effects of infrastructure investment in the Netherlands. J Macroecon 21(2):355–380

    Google Scholar 

  • Tatom JA (1993) Paved with good intentions: the mythical national infrastructure crisis. Water supply 110(2):8

    Google Scholar 

  • Tong T, Yu T-HE, Cho S-H, Jensen K, Ugarte DDLT (2013) Evaluating the spatial spillover effects of transportation infrastructure on agricultural output across the United States. J Transp Geogr 30(30):47–55

    Google Scholar 

  • Venet B, Hurlin C (2001) Granger causality tests in panel data models with fixed coefficients. Eurisco working paper no. 2001-09. University of Paris-Dauphine

  • Vickerman R, Spiekermann K, Wegener M (1999) Accessibility and economic development in Europe. Reg Stud 33:1–15

    Google Scholar 

  • Vijverberg WPM, Vijverberg C-PC, Gamble JL (1997) Public Capital and Private Productivity. Rev Econ Stat 79(2):267–278

    Google Scholar 

  • Wang W, Bengler K, Wets G, Shen Y, Jiang X, Gao Y, Zhang Y, Li H, Peng T, Hao S (2016) Green intelligent transportation system and safety study on the relationship between comprehensive transportation freight index and GDP in China. Proc Eng 137:571–580

    Google Scholar 

  • Xinhuanet (2015) Transportation infrastructure investment this year will exceed 2.5 trillion RMB; railway investment will exceed 800 billion RMB

  • Yu N, De Jong M, Storm S, Mi J (2012) The growth impact of transport infrastructure investment: a regional analysis for China (1978–2008). Policy Soc 31:25–38

    Google Scholar 

  • Zhang X, Fan S (2004) How productive is infrastructure? A new approach and evidence from rural India. Am J Agr Econ 86:492–501

    Google Scholar 

  • Zhang J, Gao Y, Fu Y, Zhang H (2007) Why does China enjoy so much better physical infrastructure? (中国为什么拥有了良好的基础设施?). Econ Res J 3:4–19

    Google Scholar 

  • Zhao J, Guo D, Wang J, Yang Z, Zhang H (2018) Examining the Association of Economic Development with Intercity Multimodal Transport Demand in China: A Focus on Spatial Autoregressive Analysis. ISPRS Int J Geo-Inf 7(2):56–73

    Google Scholar 

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Acknowledgements

This research is funded by National Natural Science Foundation of China (41601162). The Open Project Grant from Institute of Wuhan Studies (IWHS20182024).

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Authors and Affiliations

  1. School of Public Administration, Zhongnan University of Economics and Law, Wuhan, 430073, China

    Sanwei He

  2. School of Urban and Regional Science, East China Normal University, Shanghai, 200062, China

    Shan Yu

  3. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, China

    Lei Wang

  4. Department of Planning and Environmental Management, The University of Manchester, Manchester, UK

    Lei Wang

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  1. Sanwei He
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Contributions

According to the contribution of each author during the revision stage, after all authors agreed, we added two new authors because of their substantial contributions. SY mainly contributed to data processing and data analysis and LW restructured the full paper and revised the discussion section greatly. SH drafted the full paper and revised the result analysis greatly.

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Correspondence to Sanwei He.

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He, S., Yu, S. & Wang, L. The nexus of transport infrastructure and economic output in city-level China: a heterogeneous panel causality analysis. Ann Reg Sci 66, 113–135 (2021). https://doi.org/10.1007/s00168-020-01012-3

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