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The universal shape of economic recession and recovery after a shock

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  • Damien Challet
  • Sorin Solomon
  • Gur Yaari

Abstract

We show that a simple and intuitive three-parameter equation fits remarkably well the evolution of the gross domestic product (GDP) in current and constant dollars of many countries during times of recession and recovery. We then argue that this equation is the response function of the economy to isolated shocks, hence that it can be used to detect large and small shocks, including those which do not lead to a recession; we also discuss its predictive power. Finally, a two-sector toy model of recession and recovery illustrates how the severity and length of recession depends on the dynamics of transfer rate between the growing and failing parts of the economy.

Suggested Citation

  • Damien Challet & Sorin Solomon & Gur Yaari, 2008. "The universal shape of economic recession and recovery after a shock," Papers 0802.2004, arXiv.org, revised Aug 2009.
    • Handle: RePEc:arx:papers:0802.2004
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    References listed on IDEAS

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    1. Kolodko, Grzegorz W., 2000. "From Shock to Therapy: The Political Economy of Postsocialist Transformation," OUP Catalogue, Oxford University Press, number 9780198297437.
    2. Vladimir Popov, 2006. "Shock Therapy Versus Gradualism Reconsidered: Lessons From Transition Economies After 15 Years Of Reforms," Working Papers w0068, New Economic School (NES).
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    6. Vladimir Popov, 2007. "Shock Therapy versus Gradualism Reconsidered: Lessons from Transition Economies after 15 Years of Reforms1," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 49(1), pages 1-31, March.
    7. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
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    Cited by:

    1. Popov, Vladimir, 2020. "How to Deal with a Coronavirus Economic Recession?," MPRA Paper 100485, University Library of Munich, Germany.
    2. Sorin Solomon & Nataša Golo, 2015. "Microeconomic structure determines macroeconomic dynamics: Aoki defeats the representative agent," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 5-30, April.
    3. dos Santos, Renato Vieira & da Silva, Linaena Méricy, 2015. "Discreteness induced extinction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 17-25.
    4. Priscila Silva & Mariana Hidalgo & Mindy Hotchkiss & Lasitha Dharmasena & Igor Linkov & Lance Fiondella, 2024. "Predictive Resilience Modeling Using Statistical Regression Methods," Mathematics, MDPI, vol. 12(15), pages 1-30, July.
    5. Betarelli Junior, Admir Antonio & Faria, Weslem Rodrigues & Proque, Andressa Lemes & Perobelli, Fernando Salgueiro & de Almeida Vale, Vinicius, 2021. "COVID-19, public agglomerations and economic effects: Assessing the recovery time of passenger transport services in Brazil," Transport Policy, Elsevier, vol. 110(C), pages 254-272.
    6. Natasa Golo & Guy Kelman & David S. Bree & Leanne Usher & Marco Lamieri & Sorin Solomon, 2015. "Many-to-one contagion of economic growth rate across trade credit network of firms," Papers 1506.01734, arXiv.org.

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    More about this item

    JEL classification:

    • O23 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Fiscal and Monetary Policy in Development
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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