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Effects of Road Infrastructure on Employment, Productivity and Growth: An Empirical Analysis at Country Level

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  • Leopoldo Laborda
  • Daniel Sotelsek

Abstract

This article estimates the effect of transport infrastructure at country level, on employment, productivity (total factor productivity (TFP), and their components technical efficiency–pure and the scale—and technological change) and economic growth, using a dynamic panel approach. We focus on two broad categories of transport infrastructure: (1) road density and (2) road paved. Using dynamic panel GMM system estimation, we find positive effects of road density and road paved on total factor productivity (TFP) in countries with middle low and low income (using parametric and non-parametric estimations). On the other hand, and taking into account the Deng’s hypothesis of a nonlinearity relationship between transport infrastructure and economic growth (Deng, 2013, Transport Reviews 33(6): 686–99), we found empirical evidence about a Kuznets curve when we consider the percentage of roads paved. In countries with middle low and low income, we also found a Kuznets curve between road density and unemployment. JEL Classification: H54, R42, O47, O4, C23

Suggested Citation

  • Leopoldo Laborda & Daniel Sotelsek, 2019. "Effects of Road Infrastructure on Employment, Productivity and Growth: An Empirical Analysis at Country Level," Journal of Infrastructure Development, India Development Foundation, vol. 11(1-2), pages 81-120, June.
    • Handle: RePEc:sae:jouinf:v:11:y:2019:i:1-2:p:81-120
    DOI: 10.1177/0974930619879573
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    Cited by:

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    2. Saima Nawaz & Saba Anwar & Nasir Iqbal, 2021. "The Spatial Effects of Road Infrastructure on Employment in Pakistan: Quantifying the Role of Complementary Factors," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 60(3), pages 309-330.
    3. Acheampong, Alex O. & Dzator, Janet & Dzator, Michael & Salim, Ruhul, 2022. "Unveiling the effect of transport infrastructure and technological innovation on economic growth, energy consumption and CO2 emissions," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    4. Korrakot Phomsoda & Nattapong Puttanapong & Mongkut Piantanakulchai, 2021. "Assessing Economic Impacts of Thailand’s Fiscal Reallocation between Biofuel Subsidy and Transportation Investment: Application of Recursive Dynamic General Equilibrium Model," Energies, MDPI, vol. 14(14), pages 1-32, July.
    5. Jajati Keshari Parida & Shiba Shankar Pattayat & Sher Verick, 2023. "Why is the size of discouraged labour force increasing in India?," Economic Change and Restructuring, Springer, vol. 56(5), pages 3601-3630, October.
    6. Arsène Aurelien Njamen Kengdo & Tii N. Nchofoung & Philemon Bonaventure Ntang, 2020. "Effect of external debt on the level of infrastructure in Africa," Economics Bulletin, AccessEcon, vol. 40(4), pages 3349-3366.
    7. Zheng, Qing Yuan & Law, Teik Hua & Wong, Shaw Voon & Ng, Choy Peng, 2024. "Relative improvements between roads and railways and economic performance: A panel data analysis," Transport Policy, Elsevier, vol. 153(C), pages 87-96.

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    More about this item

    Keywords

    Transport infrastructure; employment; productivity; growth; panel data; dynamic models;
    All these keywords.

    JEL classification:

    • H54 - Public Economics - - National Government Expenditures and Related Policies - - - Infrastructures
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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