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The Debunking the Granular Origins of Aggregate Fluctuations: From Real Business Cycles back to Keynes

Author

Listed:
  • Giovanni Dosi

    (LEM - Laboratory of Economics and Management - SSSUP - Scuola Universitaria Superiore Sant'Anna = Sant'Anna School of Advanced Studies [Pisa])

  • Mauro Napoletano

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

  • Andrea Roventini

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

  • Tania Treibich

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

Abstract

In this work we study the granular origins of business cycles and their possible underlying drivers. As shown by Gabaix (2011), the skewed nature of firm size distributions implies that idiosyncratic (and independent) firm-level shocks may account for a significant portion of aggregate volatility. Yet, we question the original view grounded on "supply granularity", as proxied by productivity growth shocks – in line with the Real Business Cycle framework–, and we provide empirical evidence of a "demand granularity", based on investment growth shocks instead. The role of demand in explaining aggregate fluctuations is further corroborated by means of a macroeconomic Agent-Based Model of the "Schumpeter meeting Keynes" family (Dosi et al., 2015). Indeed, the investigation of the possible microfoundation of RBC has led us to the identification of a sort of microfounded Keynesian multiplier.

Suggested Citation

  • Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Tania Treibich, 2018. "The Debunking the Granular Origins of Aggregate Fluctuations: From Real Business Cycles back to Keynes," Working Papers hal-03443460, HAL.
    • Handle: RePEc:hal:wpaper:hal-03443460
    Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-03443460
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    2. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    3. Pier-Paolo Saviotti & Andreas Pyka¤ & Bogang Jun, 2020. "Diversification, structural change, and economic development," Journal of Evolutionary Economics, Springer, vol. 30(5), pages 1301-1335, November.
    4. Leon Esquierro & Sergio Da Silva, 2024. "Is the Brazilian labor market granular?," Economics Bulletin, AccessEcon, vol. 44(2), pages 576-585.
    5. Citera, Emanuele & Gouri Suresh, Shyam & Setterfield, Mark, 2023. "The network origins of aggregate fluctuations: A demand-side approach," Structural Change and Economic Dynamics, Elsevier, vol. 64(C), pages 111-123.
    6. Adriano Maia & Guilherme De Oliveira & Raul Matsushita & Sergio Da Silva, 2023. "Granular banks and corporate investment," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 586-599, September.
    7. Dosi, Giovanni & Roventini, Andrea & Russo, Emanuele, 2019. "Endogenous growth and global divergence in a multi-country agent-based model," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 101-129.
    8. Nicholas Apergis & Sayantan Ghosh Dastidar, 2022. "The determinants of aggregate fluctuations: The role of firm‐borrowing channels," Manchester School, University of Manchester, vol. 90(1), pages 20-34, January.
    9. Ichiro Takahashi, 2021. "Market Mechanism: Stabilizing or Destabilizing?," Springer Books, in: An Artificial Wicksell—Keynes Macroeconomy, chapter 0, pages 1-20, Springer.
    10. Papa, Javier, 2019. "What is behind aggregate productivity growth in Ireland? A granular approach," MPRA Paper 116676, University Library of Munich, Germany.
    11. Corrado Di Guilmi & Yoshi Fujiwara, 2020. "Does the supply network shape the firm size distribution? The Japanese case," CAMA Working Papers 2020-66, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    12. Francisco Louçã & Alexandre Abreu & Gonçalo Pessa Costa, 2021. "Disarray at the headquarters: Economists and Central bankers tested by the subprime and the COVID recessions [Forward guidance without common knowledge]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(2), pages 273-296.
    13. Ichiro Takahashi & Isamu Okada, 2020. "An artificial Wicksell–Keynes economy integrating short-run business cycle and long-term cumulative trend," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(4), pages 953-998, October.
    14. 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.
    15. Giovanni Dosi & Andrea Roventini, 2024. "Evolutionary Growth Theory," LEM Papers Series 2024/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    16. Summaira Malik & Ali Abbas & Malik Shahzad Shabbir & Carlos Samuel Ramos-Meza, 2024. "Business Cycle Fluctuations, Foreign Direct Investment, and Real Effective Exchange Rate Nexus Among Asian Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 5466-5479, June.
    17. Ichiro Takahashi, 2021. "An Artificial Wicksell—Keynes Macroeconomy," Springer Books, Springer, number 978-981-16-6839-5, January.
    18. Emanuele Russo, 2021. "Harrodian instability in decentralized economies: an agent-based approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 539-567, July.

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    More about this item

    Keywords

    Business cycles; Granular residual; Granularity hypothesis; Agent-based model; Firm dynamics; Productivity growth; Investment growth;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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