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Network Effects and Infrastructure Productivity in Developing Countries

Author

Listed:
  • Bertrand Candelon

    (Department of Economics, Maastricht University, The Netherlands)

  • Gilbert Colletaz

    (LEO, University of Orléans, France)

  • Christophe Hurlin

    (LEO, University of Orléans, France)

Abstract

This paper proposes to investigate the threshold effects of the productivity of infrastructure investment in developing countries within a panel data framework. Various specifications of an augmented production function that allow for endogenous thresholds are considered. The overwhelming outcome is the presence of strong threshold effects in the relationship between output and private and public inputs. Whatever the transition mechanism used, the testing procedures lead to strong rejection of the linearity of this relationship. In particular, the productivity of infrastructure investment generally exhibits some network effects. When the available stock of infrastructure is very low, investment in this sector has the same productivity as non-infrastructure investment. On the contrary, when a minimum network is available, the marginal productivity of infrastructure investment is generally largely greater than the productivity of other investments. Finally, when the main network is achieved, its marginal productivity becomes similar to the productivity of other investment.

Suggested Citation

  • Bertrand Candelon & Gilbert Colletaz & Christophe Hurlin, 2013. "Network Effects and Infrastructure Productivity in Developing Countries," NCID Working Papers 08/2013, Navarra Center for International Development, University of Navarra.
    • Handle: RePEc:nva:unnvaa:wp08-2013
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    Cited by:

    1. Pierre-Richard Agénor & Devrim Yilmaz, 2012. "Simple Dynamics of Public Debt with Productive Public Goods," Centre for Growth and Business Cycle Research Discussion Paper Series 165, Economics, The University of Manchester.
    2. Zhang, Yin-Fang & Ji, Shengbao, 2018. "Does infrastructure have a transitory or longer-term impact? Evidence from China," Economic Modelling, Elsevier, vol. 73(C), pages 195-207.
    3. Kalu Ojah & Stella Muhanji & Odongo Kodongo, 2022. "Infrastructure threshold and economic growth in Africa: do income level and geography matter?," Economic Change and Restructuring, Springer, vol. 55(3), pages 1587-1627, August.
    4. Hideaki Matsuoka, 2022. "Debt Intolerance: Threshold Level and Composition," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 894-932, August.
    5. Emilio Congregado & Antonio Golpe & André Stel, 2014. "The role of scale economies in determining firm size in modern economies," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 431-455, March.
    6. Hu, Zongyi & Tang, Liwei, 2013. "Exploring the relation between urbanization and residential CO2 emissions in China: a PTR approach," MPRA Paper 55379, University Library of Munich, Germany.
    7. Ogbaro, Eyitayo O., 2019. "Threshold Effects of Institutional Quality in the Infrastructure-Growth Nexus," Journal of Quantitative Methods, University of Management and Technology, Lahore, Pakistan, vol. 3(2), pages 45-61.
    8. Emmanuel Apergis & Nicholas Apergis, 2019. "“Sakura” has not grown in a day: infrastructure investment and economic growth in Japan under different tax regimes," Empirical Economics, Springer, vol. 57(2), pages 541-567, August.
    9. Bazoumana Ouattara & Yin-Fang Zhang, 2019. "Infrastructure and long-run economic growth: evidence from Chinese provinces," Empirical Economics, Springer, vol. 57(1), pages 263-284, July.
    10. José Santiago Gómez Medina, 2021. "Efecto de la banda ancha sobre el valor agregado en los municipios de Colombia," Documentos CEDE 19559, Universidad de los Andes, Facultad de Economía, CEDE.
    11. Jintao Zhan & Yubei Ma & Wuyang Hu & Chao Chen & Qinan Lu, 2022. "Enhancing rural income through public agricultural R&D: Spatial spillover and infrastructure thresholds," Review of Development Economics, Wiley Blackwell, vol. 26(2), pages 1083-1107, May.

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    More about this item

    Keywords

    Infrastructure; Threshold Panel Regression Models;

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory

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