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Transportation, Economic Growth and Spillover Effects: The Conclusion Based on the Spatial Econometric Model

Author

Listed:
  • Angang Hu

    (Center for China Study, School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Shenglong Liu

    (Center for China Study, School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

Abstract

This paper tests the external spillover effects of the transportation on China’s economic growth from the theoretical and the empirical perspectives. Based on a logarithm production model, this study first proves the existence of the positive externality in the transportation. After that, the authors collect the data of the 28 provinces in China from 1985 to 2006, and use a relatively advanced spatial econometric method to test the positive externality. After constructing a spatial econometric model, the authors use the Maximum Likelihood (ML) method to estimate this model. According to the theoretical model and the empirical results, this article reaches the following conclusion: (1) The positive externalities in the transportation do exist; (2) From 1985 to 2006, the transportation contributed 24.8 billion yuan to China's GDP every year: in this 24.8 billion yuan, 19.6 billion comes from the direct contribution and the rest 5.2 billion comes from the external spillover effects; (3) The summation of the direct contribution and the external spillover effects to the economic growth is on average 13.8% every year.

Suggested Citation

  • Angang Hu & Shenglong Liu, 2010. "Transportation, Economic Growth and Spillover Effects: The Conclusion Based on the Spatial Econometric Model," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 5(2), pages 169-186, June.
    • Handle: RePEc:fec:journl:v:5:y:2010:i:2:p:169-186
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    File URL: http://journal.hep.com.cn/fec/EN/10.1007/s11459-010-0009-0
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    Citations

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    Cited by:

    1. Ya Lin & Quanwu Zhao & Peisen Liu & Qinhong Zhang, 2020. "Do Transportation Infrastructure Investments Reduce Inventory Levels in the Manufacturing Sector in China?," International Regional Science Review, , vol. 43(4), pages 397-420, July.
    2. Sinem Kilic Celik & M. Ayhan Kose & Franziska Ohnsorge, 2023. "Potential Growth Prospects: Risks, Rewards and Policies," CAMA Working Papers 2023-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Tong, Tingting & Yu, T. Edward, 2018. "Transportation and economic growth in China: A heterogeneous panel cointegration and causality analysis," Journal of Transport Geography, Elsevier, vol. 73(C), pages 120-130.
    4. Ştefan Cristian Gherghina & Mihaela Onofrei & Georgeta Vintilă & Daniel Ştefan Armeanu, 2018. "Empirical Evidence from EU-28 Countries on Resilient Transport Infrastructure Systems and Sustainable Economic Growth," Sustainability, MDPI, vol. 10(8), pages 1-34, August.
    5. Konno, Akio & Kato, Hironori & Takeuchi, Wataru & Kiguchi, Riku, 2021. "Global evidence on productivity effects of road infrastructure incorporating spatial spillover effects," Transport Policy, Elsevier, vol. 103(C), pages 167-182.
    6. Lei Kang & Li Ma, 2021. "Expansion of Industrial Parks in the Beijing–Tianjin–Hebei Urban Agglomeration: A Spatial Analysis," Land, MDPI, vol. 10(11), pages 1-18, October.
    7. Elena Cigu & Daniela Tatiana Agheorghiesei & Anca Florentina Gavriluță (Vatamanu) & Elena Toader, 2018. "Transport Infrastructure Development, Public Performance and Long-Run Economic Growth: A Case Study for the Eu-28 Countries," Sustainability, MDPI, vol. 11(1), pages 1-22, December.
    8. Hosein Mohammadi & Samira Shayanmehr & Juan D. Borrero, 2022. "Does Freedom Matter for Sustainable Economic Development? New Evidence from Spatial Econometric Analysis," Mathematics, MDPI, vol. 11(1), pages 1-19, December.
    9. Nawaz, Saima & Mangla, Inayat Ullah, 2021. "The economic geography of infrastructure in Asia: The role of institutions and regional integration," Research in Transportation Economics, Elsevier, vol. 88(C).

    More about this item

    Keywords

    transportation; spillover effects; spatial autoregressive model; spatial moving average model; maximum likelihood estimation;
    All these keywords.

    JEL classification:

    • L90 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - General
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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