Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
The Annals of Regional Science
Published in: The Annals of Regional Science 1/2021

22-07-2020 | Original Paper

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

Authors: Sanwei He, Shan Yu, Lei Wang

Published in: The Annals of Regional Science | Issue 1/2021

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.
previous article Industry linkage, spatial correlation, and city exports: case study of the textile and clothing export industry in China
next article Location choice and costly product differentiation in a mixed duopoly

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Footnotes
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).
 
Literature
Akkemik KA, Göksal K (2012) Energy consumption-GDP nexus: heterogeneous panel causality analysis. Energy Econ 34:865–873
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
Aschauer DA (1989) Is public expenditure productive? J Monet Econ 23:177–200
Berndt ER, Hansson B (1991) Measuring the contribution of public infrastructure capital in Sweden. National Bureau of Economic Research, New York
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
Blum U (1982) Effects of transportation investments on regional growth: a theoretical and empirical investigation. Pap Reg Sci 49:169–184
Boarnet MG (1996) The direct and indirect economic effects of transportation infrastructure. University of California Transportation Center, New York
Boopen S (2006) Transport infrastructure and economic growth: evidence from Africa using dynamic panel estimates. Empir Econ Lett 5:37–52
Bose N, Haque ME (2005) Causality between public investment in transport and communication and economic growth. J Econ Dev 30:95–106
Bougheas S, Demetriades PO, Mamuneas TP (2000) Infrastructure, specialization, and economic growth. Can J Econ/Revue can d’écon 33:506–522
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
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
Crihfield JB, Panggabean MP (1995) Is public infrastructure productive? A metropolitan perspective using new capital stock estimates. Reg Sci Urban Econ 25:607–630
Cullison WE (1993) Public investment and economic growth. FRB Richmond Econ Q 79:19–33
Démurger S (2001) Infrastructure development and economic growth: an explanation for regional disparities in China? J Comp Econ 29:95–117
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
Esfahani HS, Ramı́rez MAT (2003) Institutions, infrastructure, and economic growth. J Dev Econ 70:443–477
Farhadi M (2015) Transport infrastructure and long-run economic growth in OECD countries. Transp Res Part A Policy Pract 74:73–90
Fedderke JW, Perkins P, Luiz JM (2006) Infrastructural investment in long-run economic growth: South Africa 1875–2001. World Dev 34:1037–1059
Fernald JG (1999) Roads to prosperity? Assessing the link between public capital and productivity. Am Econ Rev 89:619–638
Fernandes E, Pacheco RR (2010) The causal relationship between GDP and domestic air passenger traffic in Brazil. Transp Plan Technol 33:569–581
Fleisher BM, Chen J (1997) The coast–noncoast income gap, productivity, and regional economic policy in China. J Comp Econ 25:220–236
Fujita M, Krugman P (2004) The new economic geography: past, present and the future. Pap Reg Sci 83:139–164
Fujita M, Mori T (2005) Transport development and the evolution of economic geography. Port Econ J 4:129–156
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
Gregoriou A, Ghosh S (2009) The impact of government expenditure on growth: empirical evidence from a heterogeneous panel. Bull Econ Res 61:95–102
Groote P, Jacobs J, Sturm JE (1999) Output effects of transport infrastructure: the Netherlands, 1853–1913. Tijdschrift voor econ soc geogr 90:97–109
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
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
He S, Bayrak MM, Lin H (2017) A comparative analysis of multi-scalar regional inequality in China. Geoforum 78:1–11
Herranz-Loncán A (2007) Infrastructure investment and Spanish economic growth, 1850–1935. Explor Econ Hist 44:452–468
Holtz-Eakin D, Newey W, Rosen HS (1988) Estimating vector autoregressions with panel data. Econ J Econ Soc 56:1371–1395
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
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
Jiwattanakulpaisarn P, Noland RB, Graham DJ (2010) Causal linkages between highways and sector-level employment. Transp Res Part A Policy Pract 44:265–280
Kim E (2002) Determinants of optimal level of transportation infrastructure. J Urban Plan Dev 128:150–163
Lall SV (2007) Infrastructure and regional growth, growth dynamics and policy relevance for India. Ann Reg Sci 41:581–599
Lall SV, Shalizi Z, Deichmann U (2004) Agglomeration economies and productivity in Indian industry. J Dev Econ 73:643–673
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
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
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
Lütkepohl H (2005) New introduction to multiple time series analysis. Springer, London
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
Pesaran MH, Smith R (1995) Estimating long-run relationships from dynamic heterogeneous panels. J Econ 68:79–113
Pradhan RP (2019) Investigating the causal relationship between transportation infrastructure, financial penetration and economic growth in G-20 countries. Res Transp Econ 78:100766
Pradhan RP, Bagchi TP (2013) Effect of transportation infrastructure on economic growth in India: the VECM approach. Res Transp Econ 38:139–148
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
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
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
Seitz H (1993) A dual economic analysis of the benefits of the public road networks. Ann Reg Sci 27:223–239
Shi Y, Guo S, Sun P (2017) The role of infrastructure in China's regional economic growth. J Asian Econ 49:26–41
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
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
Sturm J, Jacobs J, Groote P (1999) Output effects of infrastructure investment in the Netherlands. J Macroecon 21(2):355–380
Tatom JA (1993) Paved with good intentions: the mythical national infrastructure crisis. Water supply 110(2):8
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
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
Vijverberg WPM, Vijverberg C-PC, Gamble JL (1997) Public Capital and Private Productivity. Rev Econ Stat 79(2):267–278
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
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
Zhang X, Fan S (2004) How productive is infrastructure? A new approach and evidence from rural India. Am J Agr Econ 86:492–501
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
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
Metadata
Title
The nexus of transport infrastructure and economic output in city-level China: a heterogeneous panel causality analysis
Authors
Sanwei He
Shan Yu
Lei Wang
Publication date
22-07-2020
Publisher
Springer Berlin Heidelberg
Published in
The Annals of Regional Science / Issue 1/2021
Print ISSN: 0570-1864
Electronic ISSN: 1432-0592
DOI
https://doi.org/10.1007/s00168-020-01012-3

Other articles of this Issue 1/2021

The Annals of Regional Science 1/2021 Go to the issue

Original Paper

Location choice and costly product differentiation in a mixed duopoly

Original Paper

Fighting the wrong battle: the effects of immigrant inflows on domestic migration of natives versus settled immigrants in the USA

Original Paper

Industry linkage, spatial correlation, and city exports: case study of the textile and clothing export industry in China

Correction

Correction to: Where do people spend their leisure time on dusty days? Application of spatiotemporal behavioral responses to particulate matter pollution

Original Paper

Merging macroeconomic and territorial determinants of regional growth: the MASST4 model

Original Paper

Efficient estimation of heteroscedastic mixed geographically weighted regression models