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E&F Chaos: A User Friendly Software Package for Nonlinear Economic Dynamics

Author

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  • Cees Diks
  • Cars Hommes
  • Valentyn Panchenko
  • Roy Weide

Abstract

The use of nonlinear dynamic models in economics and finance has expanded rapidly in the last two decades. Numerical simulation is crucial in the investigation of nonlinear systems. E&F Chaos is an easy-to-use and freely available software package for simulation of nonlinear dynamic models to investigate stability of steady states and the presence of periodic orbits and chaos by standard numerical simulation techniques such as time series, phase plots, bifurcation diagrams, Lyapunov exponent plots, basin boundary plots and graphical analysis. The package contains many well-known nonlinear models, including applications in economics and finance, and is easy to use for non-specialists. New models and extensions or variations are easy to implement within the software package without the use of a compiler or other software. The software is demonstrated by investigating the dynamical behavior of some simple examples of the familiar cobweb model, including an extension with heterogeneous agents and asynchronous updating of strategies. Simulations with the E&F chaos software quickly provide information about local and global dynamics and easily lead to challenging questions for further mathematical analysis.
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Suggested Citation

  • Cees Diks & Cars Hommes & Valentyn Panchenko & Roy Weide, 2008. "E&F Chaos: A User Friendly Software Package for Nonlinear Economic Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 221-244, September.
    • Handle: RePEc:kap:compec:v:32:y:2008:i:1:p:221-244
    DOI: 10.1007/s10614-008-9130-x
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    Cited by:

    1. Cars Hommes & Robert Calvert Jump & Paul Levine, 2017. "Internal rationalityuyuyuy, heterogeneity and complexity in the New Keynesian model," Working Papers 20171706, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    2. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2021. "(Ir)rational explorers in the financial jungle," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1157-1188, September.
    3. Charpe, Matthieu & Flaschel, Peter & Hartmann, Florian & Malikane, Christopher, 2014. "Segmented Labor Markets and the Distributive Cycle: A Roadmap towards Inclusive Growth," MPRA Paper 62832, University Library of Munich, Germany.
    4. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    5. Airaudo, Marco, 2016. "Endogenous Stock Price Fluctuations with Dynamic Self-Control Preferences," School of Economics Working Paper Series 2016-2, LeBow College of Business, Drexel University.
    6. Matthieu Charpe & Peter Flaschel & Hans-Martin Krolzig & Christian Proaño & Willi Semmler & Daniele Tavani, 2015. "Credit-driven investment, heterogeneous labor markets and macroeconomic dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 163-181, April.
    7. repec:zbw:bofrdp:2007_019 is not listed on IDEAS
    8. Bask, Mikael, 2007. "Long swings and chaos in the exchange rate in a DSGE model with a Taylor rule," Bank of Finland Research Discussion Papers 19/2007, Bank of Finland.
    9. Klaus Prettner, 2012. "Public education, technological change and economic prosperity: semi-endogenous growth revisited," PGDA Working Papers 9012, Program on the Global Demography of Aging.
    10. Calvert Jump, Robert & Hommes, Cars & Levine, Paul, 2019. "Learning, heterogeneity, and complexity in the New Keynesian model," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 446-470.
    11. Xin, Baogui & Chen, Tong, 2011. "On a master-slave Bertrand game model," Economic Modelling, Elsevier, vol. 28(4), pages 1864-1870, July.
    12. Mikhail Anufriev & Davide Radi & Fabio Tramontana, 2018. "Some reflections on past and future of nonlinear dynamics in economics and finance," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 91-118, November.
    13. Panchenko, Valentyn & Gerasymchuk, Sergiy & Pavlov, Oleg V., 2013. "Asset price dynamics with heterogeneous beliefs and local network interactions," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2623-2642.
    14. Bask, Mikael, 2007. "Long swings and chaos in the exchange rate in a DSGE model with a Taylor rule," Research Discussion Papers 19/2007, Bank of Finland.
    15. Peter Flaschel & Florian Hartmann & Christopher Malikane & Christian Proaño, 2015. "A Behavioral Macroeconomic Model of Exchange Rate Fluctuations with Complex Market Expectations Formation," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 669-691, April.
    16. Luis-Felipe Zanna & Mr. Marco Airaudo, 2012. "Interest Rate Rules, Endogenous Cycles, and Chaotic Dynamics in Open Economies," IMF Working Papers 2012/121, International Monetary Fund.
    17. Florian Hartmann & Matthieu Charpe & Peter Flaschel & Roberto Veneziani, 2016. "A Basic Model of Real-Financial Market Interactions with Heterogeneous Opinion Dynamics," IEER Working Papers 104, Institute of Empirical Economic Research, Osnabrueck University, revised 26 May 2016.
    18. Fabio Lamantia & Anghel Negriu & Jan Tuinstra, 2018. "Technology choice in an evolutionary oligopoly game," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 335-356, November.
    19. P. Luizi & F. Cruz & J. Graaf, 2010. "Assessing the Quality of Pseudo-Random Number Generators," Computational Economics, Springer;Society for Computational Economics, vol. 36(1), pages 57-67, June.
    20. Gilberto Tadeu Lima & Jaylson Jair Silveira, 2021. "Evolutionary microdynamics of employee profit sharing as productivity-enhancing device," Journal of Evolutionary Economics, Springer, vol. 31(2), pages 417-449, April.
    21. Guo Feng & Liu Chong & Shi Qingling, 2019. "Smart or stupid depends on who is your counterpart: a cobweb model with heterogeneous expectations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(5), pages 1-17, December.
    22. Choudhary, M. Ali & Michael Orszag, J., 2008. "A cobweb model with local externalities," Journal of Economic Dynamics and Control, Elsevier, vol. 32(3), pages 821-847, March.
    23. Prettner, Klaus, 2012. "Public education and economic prosperity: Semi-endogenous growth revisited," ECON WPS - Working Papers in Economic Theory and Policy 02/2012, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit.
    24. Lamantia, F. & Negriu, A. & Tuinstra, J., 2016. "Evolutionary Cournot competition with endogenous technology choice: (in)stability and optimal policy," CeNDEF Working Papers 16-08, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    25. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2020. "(Ir)rational explorers in the financial jungle: modelling Minsky with heterogeneous agents," Department of Economics University of Siena 819, Department of Economics, University of Siena.

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    More about this item

    Keywords

    Nonlinear dynamics; Simulation software; Heterogeneous agents; C60; E37; G10;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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