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

Chapter

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.

Keywords

Evolutionary dynamics Agent-based computational economics Lumpy investment Output fluctuations Endogenous business cycles 

JEL Classification

C15 C22 C49 E17 E22 E32 

References

  1. Bartelsman E, Doms M (2000) Understanding productivity: lessons from longitudinal microdata. J Econ Lit 38:569–594CrossRefGoogle Scholar
  2. Baxter M, King R (1999) Measuring business cycle: approximate band-pass filter for economic time series. Rev Econ Stat 81:575–593CrossRefGoogle Scholar
  3. Bottazzi G, Secchi A (2006) Explaining the distribution of firm growth rates. RAND J Econ 37:235–256CrossRefGoogle Scholar
  4. Brenner T, Werker C (2007) A taxonomy of inference in simulation models. Comput Econ 30:227–244CrossRefGoogle Scholar
  5. Caballero R (1999) Aggregate investment. In: Taylor J, Woodford M (eds) Handbook of macroeconomics. Elsevier Science, AmsterdamGoogle Scholar
  6. Castaldi C, Dosi G (2004) Income levels and income growth. Some new cross-country evidence and some interpretative puzzles. Working paper 2004/18, Laboratory of Economics and Management (LEM), Sant’Anna School of Advanced Studies, Pisa, ItalyGoogle Scholar
  7. Chiaromonte F, Dosi G (1993) Heterogeneity, competition, and macroeconomic dynamics. Struct Chang Econ Dyn 4:39–63CrossRefGoogle Scholar
  8. Dosi G (2005) Statistical regularities in the evolution of industries. A guide through some evidence and challenges for the theory. Working paper 2005/17, Laboratory of Economics and Management (LEM), Sant’Anna School of Advanced Studies, Pisa, ItalyGoogle Scholar
  9. Dosi G, Fabiani S, Aversi R, Meacci M (1994) The dynamics of international differentiation: a multi-country evolutionary model. Ind Corp Change 3:225–242CrossRefGoogle Scholar
  10. Dosi G, Fagiolo G, Roventini A (2005) Animal spirits, lumpy investment and endogenous business cycles. Working paper 2005/04, Laboratory of Economics and Management (LEM), Sant’Anna School of Advanced Studies, Pisa, ItalyGoogle Scholar
  11. Dosi G, Fagiolo G, Roventini A (2006) An evolutionary model of endogenous business cycles. Comput Econ 27:3–34CrossRefGoogle Scholar
  12. Dosi G, Freeman C, Fabiani S (1994) The process of economic development: introducing some stylized facts and theories on technologies, firms and institutions. Ind Corp Change 3:1–45CrossRefGoogle Scholar
  13. Fagiolo G, Moneta A, Windrum P (2007) A critical guide to empirical validation of agent-based models in economics: methodologies, procedures, and open problems. Comput Econ 30:195–226CrossRefGoogle Scholar
  14. Fagiolo G, Napoletano M, Roventini A (2008) Are output growth-rate distributions fat-tailed? Some evidence from OECD countries. J Appl Econ (in press)Google Scholar
  15. Hubbard R (1998) Capital-market imperfections and investment. J Econ Lit 36:193–225Google Scholar
  16. King R, Rebelo S (1999) Resuscitating real business cycles. In: Taylor J, Woodford M (eds) Handbook of macroeconomics. Elsevier Science, AmsterdamGoogle Scholar
  17. Kirman, A (1989) The intrinsic limits of modern economic theory: the emperor has no clothes. Econ J 99:126–139CrossRefGoogle Scholar
  18. Lane DA (1993) Artificial worlds and economics, part I and II. J Evol Econ 3:89–107 and 177–197CrossRefGoogle Scholar
  19. Mankiw GN, Romer D (eds) (1991) New Keynesian economics. MIT, CambridgeGoogle Scholar
  20. Napoletano M, Roventini A, Sapio S (2006) Are business cycles all alike? A bandpass filter analysis of the Italian and US cycles. Riv Ital Econ 1:87–118Google Scholar
  21. Nelson R, Winter S (1982) An evolutionary theory of economic change. The Belknap Press of Harvard University Press, CambridgeGoogle Scholar
  22. Pyka A, Fagiolo G (2007) Agent-based modelling: a methodology for neo-schumpeterian economics. In: Hanusch H, Pyka A (eds) The Elgar companion to neo-Schumpeterian economics. Edward Elgar, CheltenhamGoogle Scholar
  23. Stock J, Watson M (1999) Business cycle fluctuations in U.S. macroeconomic time series. In: Taylor J, Woodford M (eds) Handbook of macroeconomics. Elsevier Science, AmsterdamGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Giovanni Dosi
    • 1
  • Giorgio Fagiolo
    • 2
  • Andrea Roventini
    • 1
    • 3
  1. 1.Sant’Anna School of Advanced StudiesPisaItaly
  2. 2.Laboratory of Economics and ManagementSant’Anna School of Advanced Studies, Piazza Martiri della LibertàPisaItaly
  3. 3.University of Modena and Reggio EmiliaModenaItaly

Personalised recommendations