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The Network Origins of Large Economic Downturns

Author

Listed:
  • Daron Acemoglu
  • Asuman E. Ozdaglar
  • Alireza Tahbaz-Salehi

Abstract

This paper shows that large economic downturns may result from the propagation of microeconomic shocks over the input-output linkages across different firms or sectors within the economy. Building on the framework of Acemoglu et al. (2012), we argue that the economy's input-output structure can fundamentally reshape the distribution of aggregate output, increasing the likelihood of large downturns from infinitesimal to substantial. More specifically, we show that an economy with non-trivial intersectoral input-output linkages that is subject to thin-tailed productivity shocks may exhibit deep recessions as frequently as economies that are subject to heavy-tailed shocks. Moreover, we show that in the presence of input-output linkages, aggregate volatility is not necessarily a sufficient statistic for the likelihood of large downturns. Rather, depending on the shape of the distribution of the idiosyncratic shocks, different features of the economy's input-output network may be of first-order importance. Finally, our results establish that the effects of the economy's input-output structure and the nature of the idiosyncratic firm-level shocks on aggregate output are not separable, in the sense that the likelihood of large economic downturns is determined by the interplay between the two.
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Suggested Citation

  • Daron Acemoglu & Asuman E. Ozdaglar & Alireza Tahbaz-Salehi, 2014. "The Network Origins of Large Economic Downturns," Levine's Working Paper Archive 786969000000000944, David K. Levine.
  • Handle: RePEc:cla:levarc:786969000000000944
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    References listed on IDEAS

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    4. Nino Antulov-Fantulin & Dijana Tolic & Matija Piskorec & Zhang Ce & Irena Vodenska, 2018. "Inferring short-term volatility indicators from Bitcoin blockchain," Papers 1809.07856, arXiv.org.
    5. Mr. Alexei P Kireyev & Andrei Leonidov, 2016. "A Network Model of Multilaterally Equilibrium Exchange Rates," IMF Working Papers 2016/130, International Monetary Fund.
    6. Mizuno, Takayuki & Souma, Wataru & Watanabe, Tsutomu, 2014. "The Structure and Evolution of Buyer-Supplier Networks," Working Paper Series 27, Center for Interfirm Network, Institute of Economic Research, Hitotsubashi University.
    7. Li, Nan & Martin, Vance L., 2019. "Real sectoral spillovers: A dynamic factor analysis of the great recession," Journal of Monetary Economics, Elsevier, vol. 107(C), pages 77-95.
    8. Mr. Alexei P Kireyev & Andrei Leonidov, 2015. "Network Effects of International Shocks and Spillovers," IMF Working Papers 2015/149, International Monetary Fund.
    9. Mr. Alexei P Kireyev & Andrei Leonidov, 2016. "China’s Imports Slowdown: Spillovers, Spillins, and Spillbacks," IMF Working Papers 2016/051, International Monetary Fund.
    10. Thesmar , David & Landier , Augustin, 2014. "Instabilities in Large Economies: Aggregate Volatility Without Idiosyncratic Shocks," HEC Research Papers Series 1052, HEC Paris.
    11. Martina Sartori & Stefano Schiavo, 2014. "Virtual Water Trade and Country Vulnerability: A network perspective," IEFE Working Papers 73, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    12. Julio César Leal Ordoñez, 2017. "Equivalence between input-output and value-added economies," Working Papers 2017-13, Banco de México.
    13. Fagiolo, Giorgio & Santoni, Gianluca, 2015. "Human-mobility networks, country income, and labor productivity," Network Science, Cambridge University Press, vol. 3(3), pages 377-407, September.
    14. Takayuki Mizuno & Wataru Souma & Tsutomu Watanabe, 2014. "The Structure and Evolution of Buyer-Supplier Networks," CARF F-Series CARF-F-339, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    15. Dror Y. Kenett & Sary Levy-Carciente & Adam Avakian & H. Eugene Stanley & Shlomo Havlin, 2015. "Dynamical Macroprudential Stress Testing Using Network Theory," Working Papers 15-12, Office of Financial Research, US Department of the Treasury.
    16. Levy-Carciente, Sary & Kenett, Dror Y. & Avakian, Adam & Stanley, H. Eugene & Havlin, Shlomo, 2015. "Dynamical macroprudential stress testing using network theory," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 164-181.

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    More about this item

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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