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Policy Design from a Network Perspective: Targeting a Sector, Cascade of Links, Network Resilience

Author

Listed:
  • Temel, Tugrul
  • Phumpiu, Paul

Abstract

Drawing on input-output data, a computational methodology is proposed to: (i) characterize the upstream and/or downstream network of a targeted (or prioritized) sector i, (ii) uncover the cascade of layers of links in the network constructed, and (iii) measure the degree of network resilience using edge betweenness centrality measure of edges between communities. These objectives are accomplished through three complementary algorithms. The implementation of the algorithms is illustrated using Turkiye’s 2018 input-output production network. Ways to design policies are discussed from a network perspective. The key findings are three-fold. First, in network-based policy design, it is highly critical to consider the interdependencies of regulated and seemingly competitive sectors. Efficiencies gained in liberalized markets via pro-competitive PMR can easily be wasted before final consumers benefit from them as regulated industries may exercise their market power to confiscate part of the efficiency gain created in competitive markets. Improved competition in a single market may not generate the desired outcome even if competition policies perfectly support that market because benefits from competition may not spread over the rest of the network due to disruptions in the cascade of interdependencies concerned. Second, a network-based policy design should start with the identification of the “dominant” source and the “subordinate” sink sector(s), and those in between. The source−sink structure of Turkiye’s manufacturing network illustrates that the manufacturing sector is the most dominant, whereas telecommunications and transport, energy and construction sectors are the potential sinks where large chunk of input flow ends up. Agriculture, finance and oil extraction-mining seem to be interactive sectors. Third, the cascade of three layers of links are identified, and the upstream network of the manufacturing sector is found to have a mediocre level of resilience against the complete disruption of the intermediate layer of the network.

Suggested Citation

  • Temel, Tugrul & Phumpiu, Paul, 2023. "Policy Design from a Network Perspective: Targeting a Sector, Cascade of Links, Network Resilience," MPRA Paper 118389, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:118389
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    References listed on IDEAS

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    1. Enghin Atalay, 2017. "How Important Are Sectoral Shocks?," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 254-280, October.
    2. Vasco M. Carvalho, 2014. "From Micro to Macro via Production Networks," Journal of Economic Perspectives, American Economic Association, vol. 28(4), pages 23-48, Fall.
    3. Pol Antras & Davin Chor & Thibault Fally & Russell Hillberry, 2012. "Measuring the Upstreamness of Production and Trade Flows," American Economic Review, American Economic Association, vol. 102(3), pages 412-416, May.
    4. Peter N. Gal & Alexander Hijzen, 2016. "The Short-Term Impact of Product Market Reforms: A cross-country firm-level analysis," IMF Working Papers 2016/116, International Monetary Fund.
    5. Renaud Bourlès & Gilbert Cette & Jimmy Lopez & Jacques Mairesse & Giuseppe Nicoletti, 2013. "Do Product Market Regulations In Upstream Sectors Curb Productivity Growth? Panel Data Evidence For OECD Countries," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1750-1768, December.
    6. Vasco M. Carvalho, 2014. "From Micro to Macro via Production Networks," Working Papers 793, Barcelona School of Economics.
    7. Saki Bigio & Jennifer La’O, 2020. "Distortions in Production Networks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 2187-2253.
    8. Steiner, Bodo E. & Ali, Jolene, 2009. "Regional Food Clusters and Government Support for Clustering: Evidence for a ‘Dynamic Food Innovation Cluster’ in Alberta, Canada?," Staff Paper Series 99705, University of Alberta, Department of Resource Economics and Environmental Sociology.
    9. Paolo Buccirossi & Lorenzo Ciari & Tomaso Duso & Giancarlo Spagnolo & Cristiana Vitale, 2013. "Competition Policy and Productivity Growth: An Empirical Assessment," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1324-1336, October.
    10. Boyan Jovanovic, 1987. "Micro Shocks and Aggregate Risk," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 395-409.
    11. Philippe Aghion & Mark Schankerman, 2004. "On the welfare effects and political economy of competition-enhancing policies," Economic Journal, Royal Economic Society, vol. 114(498), pages 800-824, October.
    12. Ernest Liu, 2019. "Industrial Policies in Production Networks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(4), pages 1883-1948.
    13. Guglielmo Barone & Federico Cingano, 2011. "Service Regulation and Growth: Evidence from OECD Countries," Economic Journal, Royal Economic Society, vol. 121(555), pages 931-957, September.
    14. Romain Bouis & Mr. Romain A Duval & Johannes Eugster, 2016. "Product Market Deregulation and Growth: New Country-Industry-Level Evidence," IMF Working Papers 2016/114, International Monetary Fund.
    15. Pichler, Anton & Pangallo, Marco & del Rio-Chanona, R. Maria & Lafond, François & Farmer, J. Doyne, 2022. "Forecasting the propagation of pandemic shocks with a dynamic input-output model," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    16. Vasco Carvalho, 2007. "Aggregate fluctuations and the network structure of intersectoral trade," Economics Working Papers 1206, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2010.
    17. Hao Xiao & Tianyang Sun & Bo Meng & Lihong Cheng, 2017. "Complex Network Analysis for Characterizing Global Value Chains in Equipment Manufacturing," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-22, January.
    18. Nihat Ay & Daniel Polani, 2008. "Information Flows In Causal Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 17-41.
    19. Vladimír Holý & Karel Šafr, 2023. "Disaggregating input–output tables by the multidimensional RAS method: a case study of the Czech Republic," Economic Systems Research, Taylor & Francis Journals, vol. 35(1), pages 95-117, January.
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    More about this item

    Keywords

    graph theory; input-output production network; network resilience; systemic risk; policy plan- ning; technological change;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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