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What makes Input-Output Tables of Trade of Raw Material Goods Peculiar Networks? The World and Mexican Cases

Author

Listed:
  • Katya Pérez-Guzmán

    (International Institute for Applied Systems Analysis, Austria)

  • Isela-Elizabeth Téllez-León

    (International Institute for Applied Systems Analysis, Austria)

  • Ali Kharrazi

    (The University of Tokyo, Japan)

  • Brian Fath

    (Towson University, USA)

  • Francisco Venegas-Martínez

    (Instituto Politécnico Nacional, Mexico)

Abstract
Objetivo: se examinan varias peculiaridades de las tablas de input-output (IOT) del comercio de materias primas cuando se tratan como redes. Metodología: dos IOTs de comercio de materias primas (mundial y México) se comparan con una red con distribución de escala y organización jerárquica (una base de datos de correos electrónicos) utilizando distintas centralidades y estadísticas de la teoría de grafos. Resultados: las IOTs son un tipo de gráfico muy particular debido a su idiosincrasia, para las cuales las medidas de estándar de gráficas no proporcionan resultados satisfactorios, y que deben adaptarse para dar un retrato fragmentado de toda la red. Recomendaciones: las herramientas analíticas de redes aplicadas a las IOTs mejoran la comprensión del comercio de materias primas, a nivel nacional como mundial, lo cual es útil en el diseño de la política comercial. Limitaciones: no se incluye la centralidad de caminata aleatoria ni cambios de régimen por shocks externos. Originalidad: es una contribución novedosa que resalta particularidades de las IOTs, vistas como redes, para México. Conclusiones: se encuentran importantes particularidades de las IOTs al compararlas con otras redes.

Suggested Citation

  • Katya Pérez-Guzmán & Isela-Elizabeth Téllez-León & Ali Kharrazi & Brian Fath & Francisco Venegas-Martínez, 2018. "What makes Input-Output Tables of Trade of Raw Material Goods Peculiar Networks? The World and Mexican Cases," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 13(4), pages 483-505, Octubre-D.
    • Handle: RePEc:imx:journl:v:13:y:2018:i:4:p:483-505
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    File URL: http://www.remef.org.mx/index.php/remef/article/view/334
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    References listed on IDEAS

    as
    1. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2015. "Systemic Risk and Stability in Financial Networks," American Economic Review, American Economic Association, vol. 105(2), pages 564-608, February.
    3. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    4. Freixas, Xavier & Parigi, Bruno M & Rochet, Jean-Charles, 2000. "Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(3), pages 611-638, August.
    5. Yann Bramoull? & Rachel Kranton & Martin D'Amours, 2014. "Strategic Interaction and Networks," American Economic Review, American Economic Association, vol. 104(3), pages 898-930, March.
    6. Ana Salome Garcia Muniz & Antonio Morillas Raya & Carmen Ramos Carvajal, 2008. "Key Sectors: A New Proposal from Network Theory," Regional Studies, Taylor & Francis Journals, vol. 42(7), pages 1013-1030.
    7. , D. & Tessone, Claudio J. & ,, 2014. "Nestedness in networks: A theoretical model and some applications," Theoretical Economics, Econometric Society, vol. 9(3), September.
    8. Dirk Helbing, 2013. "Globally networked risks and how to respond," Nature, Nature, vol. 497(7447), pages 51-59, May.
    9. McNerney, James & Fath, Brian D. & Silverberg, Gerald, 2013. "Network structure of inter-industry flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6427-6441.
    10. Marcel P. Timmer & Erik Dietzenbacher & Bart Los & Robert Stehrer & Gaaitzen J. Vries, 2015. "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 575-605, August.
    11. Stefan Pauliuk & Guillaume Majeau-Bettez & Daniel B. Müller, 2015. "A General System Structure and Accounting Framework for Socioeconomic Metabolism," Journal of Industrial Ecology, Yale University, vol. 19(5), pages 728-741, October.
    12. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    13. Ana Salomé García Muñiz & Antonio Morillas Raya & Carmen Ramos Carvajal, 2011. "Core periphery valued models in input‐output field: A scope from network theory," Papers in Regional Science, Wiley Blackwell, vol. 90(1), pages 111-121, March.
    14. Tolga Kaya, 2017. "Unraveling the Energy use Network of Construction Sector in Turkey using Structural Path Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 31-43.
    15. Christina Prell & Laixiang Sun & Kuishuang Feng & Tyler W Myroniuk, 2015. "Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position, Economic Wealth, Pollution and Mortality," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-18, December.
    16. S. L. Hakimi, 1964. "Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph," Operations Research, INFORMS, vol. 12(3), pages 450-459, June.
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    More about this item

    Keywords

    Network analysis; network topology; graph theory; input-output tables; extractivism; raw material trade;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • F10 - International Economics - - Trade - - - General

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