IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i10p4283-d1397622.html

Driving Economic Growth through Transportation Infrastructure: An In-Depth Spatial Econometric Analysis

Author

Listed:
  • Jianwei Shi

    (School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China)

  • Tongyuan Bai

    (Faculty of Science and Technology, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai 519087, China)

  • Zhihong Zhao

    (School of Applied Science and Civil Engineering, Beijing Institute of Technology (Zhuhai), Zhuhai 519085, China)

  • Huachun Tan

    (Advanced Research Institute of Multidisciplineary Sciences, Beijing Institute of Technology, Beijing 100081, China)

Abstract

This research investigates the crucial role of transportation infrastructure in influencing economic activity, thus employing advanced econometric methods including Moran’s I index, LM, Hausman, and LR tests to ensure analytical accuracy and select the appropriate spatial model. Our findings reveal that freight volumes across road, waterway, and civil aviation significantly enhance economic activity by bolstering domestic trade, industrial production, and supply chains. Conversely, the impact of passenger turnover is comparatively minor, although it still contributes to labor mobility and urban accessibility. This study highlights the need for strategic investment in transportation infrastructure and efficient public transport systems to foster economic growth and sustainable development. We recommend that policymakers focus on optimizing transportation networks and integrating intelligent transport technologies to boost economic competitiveness and societal well-being. This analysis not only sheds light on the direct economic impacts of transportation but also underscores the broader social implications, thus advocating for a holistic approach to transportation planning and policymaking.

Suggested Citation

  • Jianwei Shi & Tongyuan Bai & Zhihong Zhao & Huachun Tan, 2024. "Driving Economic Growth through Transportation Infrastructure: An In-Depth Spatial Econometric Analysis," Sustainability, MDPI, vol. 16(10), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4283-:d:1397622
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/10/4283/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/10/4283/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Engle, Robert F., 1984. "Wald, likelihood ratio, and Lagrange multiplier tests in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 13, pages 775-826, Elsevier.
    2. Saidi, Samir & Shahbaz, Muhammad & Akhtar, Pervaiz, 2018. "The long-run relationships between transport energy consumption, transport infrastructure, and economic growth in MENA countries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 78-95.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Forouhar, Amir & Chapple, Karen & Pokharel, Ramesh & Allen, Jeff, 2025. "Transit-driven resilience: Unraveling post-COVID-19 urban recovery dynamics," Journal of Transport Geography, Elsevier, vol. 128(C).
    2. Fan Yang & Yunlan Tang & Suwen Xiong & Chuntian Gu & Yadan Xiao, 2024. "Development of Highway Construction Route Selection Based on Ecological Sensitivity Evaluation and Intervention Optimization Strategy Research," Land, MDPI, vol. 13(11), pages 1-24, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Udi Joshua & Festus V. Bekun & Samuel A. Sarkodie, 2020. "New Insight into the Causal Linkage between Economic Expansion, FDI, Coal consumption, Pollutant emissions and Urbanization in South Africa," Working Papers 20/011, European Xtramile Centre of African Studies (EXCAS).
    2. Eryilmaz, Unal, 2021. "Enflasyonist Koşullarda Türkiye Ekonomisine İlişkin Bir Para Arzı Tahmini [Money Supply Forecast for the Turkish Economy in Inflationary Conditions]," MPRA Paper 111685, University Library of Munich, Germany.
    3. Campbell, John Y., 2001. "Why long horizons? A study of power against persistent alternatives," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 459-491, December.
    4. Urbain, Jean-Pierre, 1995. "Partial versus full system modelling of cointegrated systems an empirical illustration," Journal of Econometrics, Elsevier, vol. 69(1), pages 177-210, September.
    5. Urzua, Carlos M., 2000. "A simple and efficient test for Zipf's law," Economics Letters, Elsevier, vol. 66(3), pages 257-260, March.
    6. Gökçe Esenduran & James A. Hill & In Joon Noh, 2020. "Understanding the Choice of Online Resale Channel for Used Electronics," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1188-1211, May.
    7. Yash P. Mehra, 1995. "Some key empirical determinants of short-term nominal interest rates," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 33-51.
    8. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 0000. "Dynamic Factor Models with Smooth Loadings for Analyzing the Term Structure of Interest Rates," Tinbergen Institute Discussion Papers 09-041/4, Tinbergen Institute, revised 17 Sep 2010.
    9. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    10. He, Jiaxiu & Wang, Xin (Shane) & Curry, David J., 2017. "Mediation analysis: A new test when all or some variables are categorical," International Journal of Research in Marketing, Elsevier, vol. 34(4), pages 780-798.
    11. Onur Ozsoy, 2008. "Defence Spending And The Macroeconomy: The Case Of Turkey," Defence and Peace Economics, Taylor & Francis Journals, vol. 19(3), pages 195-208.
    12. Steel, M.F.J., 1989. "Weak exogeneity in misspecified sequential models," Discussion Paper 1989-42, Tilburg University, Center for Economic Research.
    13. Zhang, Yijia & Cheng, Lu, 2023. "The role of transport infrastructure in economic growth: Empirical evidence in the UK," Transport Policy, Elsevier, vol. 133(C), pages 223-233.
    14. Steven T. Yen & Ernest M. Zampelli, 2023. "A Bivariate Probit Model of Attitudes Toward the Preferential Hiring and Promotion of Women and Black People," Journal of Economics, Race, and Policy, Springer, vol. 6(2), pages 82-101, June.
    15. Saidi, Samir & Mani, Venkatesh & Mefteh, Haifa & Shahbaz, Muhammad & Akhtar, Pervaiz, 2020. "Dynamic linkages between transport, logistics, foreign direct Investment, and economic growth: Empirical evidence from developing countries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 277-293.
    16. Ke-Hai Yuan & Peter Bentler, 2006. "Mean Comparison: Manifest Variable Versus Latent Variable," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 139-159, March.
    17. Efstathios Polyzos & Costas Siriopoulos, 2024. "Autoregressive Random Forests: Machine Learning and Lag Selection for Financial Research," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 225-262, July.
    18. Valter Di Giacinto, 2003. "Differential Regional Effects of Monetary Policy: A Geographical SVAR Approach," International Regional Science Review, , vol. 26(3), pages 313-341, July.
    19. Ravi Kashyap, 2016. "The Perfect Marriage and Much More: Combining Dimension Reduction, Distance Measures and Covariance," Papers 1603.09060, arXiv.org, revised Jul 2019.
    20. Queralt, Magaly & Witte, Ann D., 1999. "Childcare regulations: A method to pursue social welfare goals?," Children and Youth Services Review, Elsevier, vol. 21(2), pages 111-146, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4283-:d:1397622. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.