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The microfoundations of business cycles: an evolutionary, multi-agent model

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  • Giovanni Dosi
  • Giorgio Fagiolo
  • Andrea Roventini

Abstract

This work presents an evolutionary model of output and investment dynamics yielding endogenous business cycles. The model describes an economy composed of firms and consumers/workers. Firms belong to two industries. The first one performs R&D and produces heterogeneous machine tools. Firms in the second industry invest in new machines and produce a homogenous consumption good. Consumers sell their labor and fully consume their income. In line with the empirical literature on investment patterns, we assume that firms’ investment decisions are lumpy and constrained by their financial structure. Simulation results show that the model is able to deliver self-sustaining patterns of growth characterized by the presence of endogenous business cycles. The model can also replicate the most important stylized facts concerning micro- and macro-economic dynamics.
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  • Giovanni Dosi & Giorgio Fagiolo & Andrea Roventini, 2008. "The microfoundations of business cycles: an evolutionary, multi-agent model," Journal of Evolutionary Economics, Springer, vol. 18(3), pages 413-432, August.
  • Handle: RePEc:spr:joevec:v:18:y:2008:i:3:p:413-432
    DOI: 10.1007/s00191-008-0094-8
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    1. Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2008. "Are output growth-rate distributions fat-tailed? some evidence from OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 639-669.
    2. A. Pyka & G. Fagiolo, 2007. "Agent-based Modelling: A Methodology for Neo-Schumpetarian Economics," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 29, Edward Elgar Publishing.
    3. Giovanni Dosi & Giorgio Fagiolo & Andrea Roventini, 2006. "An Evolutionary Model of Endogenous Business Cycles," Computational Economics, Springer;Society for Computational Economics, vol. 27(1), pages 3-34, February.
    4. Caballero, Ricardo J., 1999. "Aggregate investment," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 12, pages 813-862, Elsevier.
    5. Giovanni Dosi, 2008. "Statistical Regularities in the Evolution of Industries. A Guide through Some Evidence and Challenges for the Theory," L'industria, Società editrice il Mulino, issue 2, pages 185-220.
    6. King, Robert G. & Rebelo, Sergio T., 1999. "Resuscitating real business cycles," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 14, pages 927-1007, Elsevier.
    7. Giovanni Dosi & Giorgio Fagiolo & Andrea Roventini, 2005. "Animal Spirits, Lumpy Investment, and Endogenous Business Cycles," LEM Papers Series 2005/04, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Charolina CASTALDI & Giovanni Dosi, 2004. "Income Levels and Income Growth: Some New Cross-Country Evidence and some Interpretative Puzzles," DEGIT Conference Papers c009_038, DEGIT, Dynamics, Economic Growth, and International Trade.
    9. Mark Doms & Eric J. Bartelsman, 2000. "Understanding Productivity: Lessons from Longitudinal Microdata," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 569-594, September.
    10. Kirman, Alan, 1989. "The Intrinsic Limits of Modern Economic Theory: The Emperor Has No Clothes," Economic Journal, Royal Economic Society, vol. 99(395), pages 126-139, Supplemen.
    11. Mauro Napoletano & Andrea Roventini & Sandro Sapio, 2006. "Are Business Cycles All Alike? A Bandpass Filter Analysis of the Italian and US Cycles," Rivista italiana degli economisti, Società editrice il Mulino, issue 1, pages 87-118.
    12. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    13. Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 227-244, October.
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    More about this item

    Keywords

    Evolutionary dynamics; Agent-based computational economics; Lumpy investment; Output fluctuations; Endogenous business cycles; C15; C22; C49; E17; E22; E32;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • 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

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