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Contagious disruptions and complexity traps in economic development

Abstract

Poor economies not only produce less; they typically produce things that involve fewer inputs and fewer intermediate steps. Yet the supply chains of poor countries face more frequent disruptions—delivery failures, faulty parts, delays, power outages, theft and government failures—that systematically thwart the production process. To understand how these disruptions affect economic development, we modelled an evolving input–output network in which disruptions spread contagiously among optimizing agents. The key finding was that a poverty trap can emerge: agents adapt to frequent disruptions by producing simpler, less valuable goods, yet disruptions persist. Growing out of poverty requires that agents invest in buffers to disruptions. These buffers rise and then fall as the economy produces more complex goods, a prediction consistent with global patterns of input inventories. Large jumps in economic complexity can backfire. This result suggests why ‘big push’ policies can fail and it underscores the importance of reliability and gradual increases in technological complexity.

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Fig. 1: Disruptions to the production process tend to be more frequent in poorer, less complex economies.
Fig. 2: Illustration of the model.
Fig. 3: Representative phase portrait showing the three phases of a model economy.
Fig. 4: Jumping to a more complex technology can backfire by causing dysfunction to rise, especially for emerging economies.
Fig. 5: Phase diagram of the sign of dF/dt.
Fig. 6: Qualitative match between empirical data on input inventories and the model’s prediction that buffers to supply-chain disruptions rise and then fall as economies develop.

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References

  1. Schumpeter, J. A. The Theory of Economic Development: An Inquiry Into Profits, Capital, Credit, Interest, and the Business Cycle (Transaction Books, New Brunswick, NJ, 1983).

    Google Scholar 

  2. Romer, P. M. Growth based on increasing returns due to specialization. Am. Econ. Rev. 77, 56–62 (1987).

    Google Scholar 

  3. Allcott, H., Collard-Wexler, A. & O’Connell, S. D. How do electricity shortages affect industry? Evidence from India. Am. Econ. Rev. 106, 587–624 (2016).

    Article  Google Scholar 

  4. World Bank Group Enterprise Surveys Data (accessed 15 October 2015); http://www.enterprisesurveys.org/data/

  5. Chaudhury, N., Hammer, J., Kremer, M., Muralidharan, K. & Rogers, F. H. Missing in action: teacher and health worker absence in developing countries. J. Econ. Perspect. 20, 91–116 (2006).

    Article  PubMed  Google Scholar 

  6. Caselli, F. in Handbook of Economic Growth vol. 1 (eds Aghion, P. & Durlauf, S. N.) 679–741 (Elsevier, 2005).

  7. Hidalgo, C. A., Klinger, B., Barabási, A. L. & Hausmann, R. The product space conditions the development of nations. Science 317, 482–487 (2007).

    Article  CAS  PubMed  Google Scholar 

  8. Hidalgo, C. A. & Hausmann, R. The building blocks of economic complexity. Proc. Natl Acad. Sci. USA 106, 10570–10575 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Powell, B. The global supply chain: so very fragile. Fortune (12 December 2011)

  10. Punter, A. Supply Chain Failures. A Study of the Nature, Causes and Complexity of Supply Chain Disruptions. (Airmic, London, 2013); https://www.riskmethods.net/resources/research/supply_chain_failures_2013_final_web.pdf

    Google Scholar 

  11. Ciccone, A. Input chains and industrialization. Rev. Econ. Stud. 69, 565–587 (2002).

    Article  Google Scholar 

  12. Jones, C. I. Intermediate goods and weak links in the theory of economic development. Am. Econ. J. Macroecon. 3, 1–28 (2011).

    Article  Google Scholar 

  13. Jones, C. I. Misallocation, Economic Growth, and Input–Output Economics in 10th World Congress of the Econometric Society (National Bureau of Economic Research, Cambridge, MA, 2011).

    Google Scholar 

  14. Acemoglu, D., Carvalho, V. M., Ozdaglar, A. & Tahbaz-Salehi, A. The network origins of aggregate fluctuations. Econometrica 80, 1977–2016 (2012).

    Article  Google Scholar 

  15. Kremer, M. The O-ring theory of economic development. Q. J. Econ. 108, 551–575 (1993).

    Article  Google Scholar 

  16. Battiston, S., Delli Gatti, D., Gallegati, M., Greenwald, B. & Stiglitz, J. E. Credit chains and bankruptcy propagation in production networks. J. Econ. Dyn. Control 31, 2061–2084 (2007).

    Article  Google Scholar 

  17. Weisbuch, G. & Battiston, S. From production networks to geographical economics. J. Econ. Behav. Organ. 64, 448–469 (2007).

    Article  Google Scholar 

  18. Mizgier, K. J., Wagner, S. M. & Holyst, J. A. Modeling defaults of companies in multi-stage supply chain networks. Int. J. Prod. Econ. 135, 14–23 (2012).

    Article  Google Scholar 

  19. Henriet, F., Hallegatte, S. & Tabourier, L. Firm-network characteristics and economic robustness to natural disasters. J. Econ. Dyn. Control 36, 150–167 (2012).

    Article  Google Scholar 

  20. Levine, D. K. Production chains. Rev. Econ. Dyn. 15, 271–282 (2012).

    Article  Google Scholar 

  21. Contreras, M. G. A. & Fagiolo, G. Propagation of economic shocks in input-output networks: a cross-country analysis. Phys. Rev. E 90, 062812 (2014).

    Article  Google Scholar 

  22. Hendricks, K. B. & Singhal, V. R. The effect of supply chain glitches on shareholder wealth. J. Oper. Manag. 21, 501–522 (2003).

    Article  Google Scholar 

  23. Hendricks, K. B. & Singhal, V. R. An empirical analysis of the effect of supply chain disruptions on long-run stock price performance and equity risk of the firm. Prod. Oper. Manag. 14, 35–52 (2005).

    Article  Google Scholar 

  24. Barrot, J.-N. & Sauvagnat, J. Input specificity and the propagation of idiosyncratic shocks in production networks. Quart. J. Econ. 131, 1543–1592 (2016).

  25. Wang, Y. I., Li, J. & Anupindi, R. Risky suppliers or risky supply chains? An empirical analysis of sub-tier supply network structure on firm performance in the high-tech sector. Ross School of Business Paper No. 1297 Preprint at http://www.ssrn.com/abstract=2705654 (2015).

  26. Aoki, M. & Yoshikawa, H. Reconstructing Macroeconomics: A Perspective from Statistical Physics and Combinatorial Stochastic Processes Ch. 4 (Cambridge Univ. Press, New York, NY, 2006).

    Book  Google Scholar 

  27. Carvalho, V. M. From micro to macro via production networks. J. Econ. Perspect. 28, 23–48 (2014).

    Article  Google Scholar 

  28. Duan, W.-Q. Modelling the evolution of national economies based on input–output networks. Comput. Econ. 39, 145–155 (2011).

    Article  Google Scholar 

  29. Oberfield, E. Business networks, production chains, and productivity: a theory of input–output architecture. FRB of Chicago Working Paper No. 2011-12 Preprint at http://ssrn.com/abstract=1967148 (2012).

  30. Carvalho, V. M. & Voigtländer, N. Input diffusion and the evolution of production networks. NBER Working Paper No. 20025 Preprint at http://www.nber.org/papers/w20025 (2014).

  31. Tomlin, B. On the value of mitigation and contingency strategies for managing supply chain disruption risks. Manag. Sci. 52, 639–657 (2006).

    Article  Google Scholar 

  32. Aydin, G., Babich, V., Beil, D. & Yang, Z. in The Handbook of Integrated Risk Management in Global Supply Chains 387–424 (John Wiley & Sons, Hoboken, NJ, 2011).

  33. Bimpikis, K., Fearing, D. & Tahbaz Salehi, A. Multi-sourcing and miscoordination in supply chain networks. Stanford Business School Working Paper No. 3100 Preprint at https://www.gsb.stanford.edu/faculty-research/working-papers/multi-sourcing-miscoordination-supply-chain-networks (2014).

  34. Ang, E., Iancu, D. A. & Swinney, R. Disruption risk and optimal sourcing in multi-tier supply networks. Manag. Sci. 63, 2397–2419 (2016).

  35. Bakshi, N. & Mohan, S. Mitigating disruption cascades in supply networks. Preprint at http://faculty.london.edu/nbakshi/Nw.pdf (2015).

  36. Murphy, K. M., Shleifer, A. & Vishny, R. W. Industrialization and the big push. J. Polit. Econ. 97, 1003 (1989).

    Article  Google Scholar 

  37. Garb, Y. & Friedlander, L. From transfer to translation: using systemic understandings of technology to understand drip irrigation uptake. Agric. Sys. 128, 13–24 (2014).

    Article  Google Scholar 

  38. Bold, T., Kaizzi, K., Svensson, J. & Yanagizawa-Drott, D. Low quality, low returns, low adoption: evidence from the market for fertilizer and hybrid seed in uganda. CEPR Discussion Papers 10743 Preprint at http://EconPapers.repec.org/RePEc:cpr:ceprdp:10743 (2015).

  39. Sanjay, A. K. & Gupta, V. Gyandoot: trying to improve government services for rural citizens in India. Tech. Rep. 11, eGovernment for Development Preprint at http://www.egov4dev.org/transparency/case/gyandoot.shtml (2003).

  40. Johnson, N. & Kotz, S. Urn Models and Their Application: An Approach to Modern Discrete Probability Theory (Wiley, 1977).

  41. Woodbury, M. A. On a probability distribution. Ann. Math. Stat. 20, 311–313 (1949).

    Article  Google Scholar 

  42. Toral, R. & Colet, P. in Stochastic Numerical Methods 235–260 (Wiley-VCH, Weinheim, Germany, 2014).

  43. Helbing, D. Quantitative Sociodynamics: Stochastic Methods and Models of Social Interaction Processes 2nd edn (Springer-Verlag, Berlin, Germany, 2010).

    Book  Google Scholar 

  44. Aoki, M. New Approaches to Macroeconomic Modeling: Evolutionary Stochastic Dynamics, Multiple Equilibria, and Externalities as Field Effects. (Cambridge Univ. Press, 1998).

  45. Aoki, M. Modeling Aggregate Behavior and Fluctuations in Economics. (Cambridge Univ. Press, New York, NY, 2004).

    Google Scholar 

  46. Granovetter, M. Threshold models of collective behavior. Am. J. Sociol. 83, 1420–1443 (1978).

    Article  Google Scholar 

  47. Watts, D. J. A simple model of global cascades on random networks. Proc. Natl Acad. Sci. USA 99, 5766–5771 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Jackson, M. O. & Yariv, L. Diffusion of behavior and equilibrium properties in network games. Am. Econ. Rev. 97, 92–98 (2007).

    Article  Google Scholar 

  49. Ethier, W. J. National and international returns to scale in the modern theory of international trade. Am. Econ. Rev. 72, 389–405 (1982).

    Google Scholar 

  50. Romer, P. M. Endogenous technological change. J. Polit. Econ. 98, S71–S102 (1990).

    Article  Google Scholar 

  51. Proviti. Managing Supply Chain Disruption Risk (2011); https://www.protiviti.com/US-en/insights/managing-supply-chain-disruption-risk

  52. Simchi-Levi, D., Schmidt, W. & Wei, Y. From Superstorms to Factory Fires: Managing Unpredictable Supply-Chain Disruptions (Harvard Business Review, 2014); https://hbr.org/2014/01/from-superstorms-to-factory-fires-managing-unpredictable-supply-chain-disruptions

  53. Tang, C. S. Robust strategies for mitigating supply chain disruptions. Int. J. Logist. Res. Appl. 9, 33–45 (2006).

    Article  Google Scholar 

  54. Bak, P., Chen, K., Scheinkman, J. & Woodford, M. Aggregate fluctuations from independent sectoral shocks: self-organized criticality in a model of production and inventory dynamics. Res. Econom. 47, 3–30 (1993).

    Google Scholar 

  55. Gabaix, X. The granular origins of aggregate fluctuations. Econometrica 79, 733–772 (2011).

    Article  Google Scholar 

  56. Burlon, L. How do aggregate fluctuations depend on the network structure of the economy? SSRN Electronic Journal Preprint at http://www.ssrn.com/abstract=2028093 (2012).

  57. Baqaee, D. R. Cascading failures in production networks. SSRN Electronic Journal Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2909868 (2015).

  58. Francois, P. & Zabojnik, J. Trust, social captial, and economic development. J. Eur. Econ. Assoc. 3, 51–94 (2005).

    Article  Google Scholar 

  59. Humphreys, B. R., Maccini, L. J. & Schuh, S. Input and output inventories.J. Monetary Econ. 47, 347–375 (2001).

    Article  Google Scholar 

  60. Iacoviello, M., Schiantarelli, F. & Schuh, S. Input and output inventories in general equilibrium. Int. Econ. Rev. 52, 1179–1213 (2011).

    Article  Google Scholar 

  61. Khan, A. & Thomas, J. K. Inventories and the business cycle: an equilibrium analysis of (S, s) policies. Am. Econ. Rev. 97, 1165–1188 (2007).

    Article  Google Scholar 

  62. Wen, Y. Input and output inventory dynamics. Am. Econ. J. Macroeconom. 3, 181–212 (2011).

    Article  Google Scholar 

  63. Atlas of Economic Complexity. Economic Complexity Index (accessed 8 November 2015); http://atlas.cid.harvard.edu/rankings/country/download/

  64. Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M. & Simoes, A. The Atlas of Economic Complexity: Mapping Paths to Prosperity (MIT Press, Cambridge, MA, 2014).

    Google Scholar 

  65. McArthur, J. et al. Ending Africa’s poverty trap. Brookings Pap. Econ. Act. 1, 117–240 (2004).

    Google Scholar 

  66. Azariadis, C. & Stachurski, J. in Handbook of Economic Growth (eds Aghion, P. & Durlauf, S.) 295–384 (Elsevier, 2005).

  67. Barrett, C. B., Garg, T. & McBride, L. Well-being dynamics and poverty traps. Annu. Rev. Res. Econ. 8, 303–327 (2016).

    Article  Google Scholar 

  68. Easterly, W. Reliving the 1950s: the big push, poverty traps, and takeoffs in economic development. J. Econ. Growth 11, 289–318 (2006).

    Article  Google Scholar 

  69. Gershenson, C. & Helbing, D. When slower is faster. Complexity 21, 9–15 (2015).

    Article  Google Scholar 

  70. North, D. C. Institutions, Institutional Change and Economic Performance. (Cambridge Univ. Press, Cambridge, UK, 1990).

  71. Acemoglu, D., Johnson, S. & Robinson, J. A. in Handbook of Economic Growth (eds Aghion, P. & Durlauf, S. N.) 386–414 (Elsevier, 2005).

  72. Morduch, J. Poverty and vulnerability. Am. Econ. Rev. 84, 221–225 (1994).

    Google Scholar 

  73. Haushofer, J. & Fehr, E. On the psychology of poverty. Science 344, 862–867 (2014).

    Article  CAS  PubMed  Google Scholar 

  74. The World Bank. GDP Per Capita (in Current US$) (accessed 15 February 2016); http://data.worldbank.org/indicator/NY.GDP.PCAP.CD

  75. Hilft, B. E. in Worldriskreport 2014. 64–66 (United Nations University Institute for Environment and Human Security, accessed 11 February 2016); http://i.unu.edu/media/ehs.unu.edu/news/4070/11895.pdf.

  76. World Health Organization. Adult Mortality Data by Country (accessed 15 February 2016); http://apps.who.int/gho/data/node.main.11?lang=en

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Acknowledgements

C.D.B. and M.H.B. acknowledge funding from the James S. McDonnell Foundation for the Postdoctoral Award and the Scholar Award (respectively) in Complex Systems. P.P. and F.V.-R. acknowledge funding from the Italian Ministry of Education Progetti di Rilevante Interesse Nazionale grant 2015592CTH. No funders had any role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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All authors designed and performed the research and wrote the paper. C.D.B. and K.H. analysed the data.

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Brummitt, C.D., Huremović, K., Pin, P. et al. Contagious disruptions and complexity traps in economic development. Nat Hum Behav 1, 665–672 (2017). https://doi.org/10.1038/s41562-017-0190-6

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