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On the robustness of the fat-tailed distribution of firm growth rates: a global sensitivity analysis

Author

Listed:
  • G. Dosi

    () (Scuola Superiore Sant’Anna)

  • M. C. Pereira

    () (Scuola Superiore Sant’Anna
    University of Campinas)

  • M. E. Virgillito

    () (Scuola Superiore Sant’Anna
    Istituto di Politica Economica, Universita’ Cattolica del Sacro Cuore)

Abstract

Abstract Firms grow and decline by relatively lumpy jumps which cannot be accounted by the cumulation of small, “atom-less”, independent shocks. Rather “big” episodes of expansion and contraction are relatively frequent. More technically, this is revealed by the fat-tailed distributions of growth rates. This applies across different levels of sectoral disaggregation, across countries, over different historical periods for which there are available data. What determines such property? In Dosi et al. (The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics. Industrial and corporate change. Oxford University Press, Oxford, 2016) we implemented a simple multi-firm evolutionary simulation model, built upon the coupling of a replicator dynamic and an idiosyncratic learning process, which turns out to be able to robustly reproduce such a stylized fact. Here, we investigate, by means of a Kriging meta-model, how robust such “ubiquitousness” feature is with regard to a global exploration of the parameters space. The exercise confirms the high level of generality of the results in a statistically robust global sensitivity analysis framework.

Suggested Citation

  • G. Dosi & M. C. Pereira & M. E. Virgillito, 2018. "On the robustness of the fat-tailed distribution of firm growth rates: a global sensitivity analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 173-193, April.
  • Handle: RePEc:spr:jeicoo:v:13:y:2018:i:1:d:10.1007_s11403-017-0193-4
    DOI: 10.1007/s11403-017-0193-4
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    2. Giovanni Dosi & Marcelo C. Pereira & Andrea Roventini & Maria Enrica Virgillito, 2018. "What if supply-side policies are not enough ? The perverse interaction of flexibility and austerity," Sciences Po publications 2018-04, Sciences Po.
    3. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    4. G Dosi & M C Pereira & A Roventini & M E Virgillito, 2018. "Causes and consequences of hysteresis: aggregate demand, productivity, and employment," Industrial and Corporate Change, Oxford University Press, vol. 27(6), pages 1015-1044.
    5. Sylvain Barde & Sander van der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," Studies in Economics 1712, School of Economics, University of Kent.
    6. Dosi, Giovanni & Pereira, Marcelo C. & Roventini, Andrea & Virgillito, Maria Enrica, 2018. "The labour-augmented K+S model: a laboratory for the analysis of institutional and policy regimes," GLO Discussion Paper Series 241, Global Labor Organization (GLO).
    7. Giovanni Dosi & Marcelo C. Pereira & Andrea Roventini & Maria Enrica Virgillito, 2016. "The Effects of Labour Market Reforms upon Unemployment and Income Inequalities: an Agent Based Model," Sciences Po publications 2016-24, Sciences Po.
    8. Sylvain Barde & Sander Van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," Sciences Po publications 17/12, Sciences Po.
    9. repec:spr:joevec:v:29:y:2019:i:1:d:10.1007_s00191-019-00609-y is not listed on IDEAS
    10. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Giovanni Dosi & Marcelo C. Pereira & Andrea Roventini & Maria Enrica Virgillito, 2018. "Causes et consequences of hysteresis : aggregate demand, productivity and employment," Sciences Po publications info:hdl:2441/4h9cnu4n2k8, Sciences Po.
    12. Chen, Siyan & Desiderio, Saul, 2018. "Computational evidence on the distributive properties of monetary policy," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 12, pages 1-32.
    13. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    14. Emanuele Brancati & Raffaele Brancati & Dario Guarascio & Andrea Maresca & Manuel Romagnoli & Antonello Zanfei, 2018. "Firm-level Drivers of Export Performance and External Competitiveness in Italy," European Economy - Discussion Papers 2015 - 087, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

    More about this item

    Keywords

    Fat-tailed distributions; Kriging meta-modeling; Near-orthogonal latin hypercubes; Variance-based sensitivity analysis; ABMs validation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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