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Genetic Algorithm Learning in a New Keynesian Macroeconomic Setup

Author

Listed:
  • Hommes, C.H.

    () (University of Amsterdam)

  • Makarewicz, T.A.

    () (University of Amsterdam)

  • Massaro, D.

    () (University of Amsterdam)

  • Smits, T.

    (SEO Economic Research)

Abstract

In order to understand heterogeneous behaviour amongst agents, empirical data from Learning-to-Forecast (LtF) experiments can be used to construct learning models. This paper follows up on Assenza et al. (2013) by using a genetic algorithms (GA) model to replicate the results from their LtF experiment. In this GA model individuals optimise an adaptive, a trend following and an anchor coefficient in a population of general prediction heuristics. We replicate experimental treatments in a New-Keynesian environment with increasing complexity and use Monte Carlo simulations to investigate how well the model explains the experimental data. We find that the model is able to replicate the three different types of behaviour in the treatments using one GA model. The research furthermore shows that heterogeneous behaviour can be explained by an adaptive, anchor and trend extrapolating component and therewith contributes to the existing literature in the way that GA can be used to explain heterogeneous behaviour in LtF experiments with different types of complexity.

Suggested Citation

  • Hommes, C.H. & Makarewicz, T.A. & Massaro, D. & Smits, T., 2015. "Genetic Algorithm Learning in a New Keynesian Macroeconomic Setup," CeNDEF Working Papers 15-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  • Handle: RePEc:ams:ndfwpp:15-01
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    References listed on IDEAS

    as
    1. Mikhail Anufriev & Cars Hommes, 2012. "Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments," American Economic Journal: Microeconomics, American Economic Association, vol. 4(4), pages 35-64, November.
    2. repec:sfu:sfudps:dp13-09 is not listed on IDEAS
    3. Jasmina Arifovic & James Bullard & Olena Kostyshyna, 2013. "Social Learning and Monetary Policy Rules," Economic Journal, Royal Economic Society, vol. 123(567), pages 38-76, March.
    4. Hommes, Cars & Lux, Thomas, 2013. "Individual Expectations And Aggregate Behavior In Learning-To-Forecast Experiments," Macroeconomic Dynamics, Cambridge University Press, vol. 17(02), pages 373-401, March.
    5. Heemeijer, Peter & Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan, 2009. "Price stability and volatility in markets with positive and negative expectations feedback: An experimental investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1052-1072, May.
    6. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    7. Pfajfar, Damjan & Žakelj, Blaž, 2014. "Experimental evidence on inflation expectation formation," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 147-168.
    8. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    9. repec:taf:jnlbes:v:37:y:2019:i:2:p:288-300 is not listed on IDEAS
    10. Assenza, T. & Heemeijer, P. & Hommes, C.H. & Massaro, D., 2011. "Individual Expectations and Aggregate Macro Behavior," CeNDEF Working Papers 11-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    11. Mikhail Anufriev & Cars Hommes & Tomasz Makarewicz, 2015. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," Working Paper Series 29, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    12. Branch, William A. & McGough, Bruce, 2009. "A New Keynesian model with heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1036-1051, May.
    13. Adriana Cornea-Madeira & Cars Hommes & Domenico Massaro, 2019. "Behavioral Heterogeneity in U.S. Inflation Dynamics," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 288-300, April.
    14. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    15. Oleksiy Kryvtsov & Luba Petersen, 2013. "Expectations and Monetary Policy: Experimental Evidence," Staff Working Papers 13-44, Bank of Canada.
    16. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    17. Marimon Ramon & Spear Stephen E. & Sunder Shyam, 1993. "Expectationally Driven Market Volatility: An Experimental Study," Journal of Economic Theory, Elsevier, vol. 61(1), pages 74-103, October.
    18. Massaro, Domenico, 2013. "Heterogeneous expectations in monetary DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 680-692.
    19. Cars Hommes & Joep Sonnemans & Jan Tuinstra & Henk van de Velden, 2005. "Coordination of Expectations in Asset Pricing Experiments," Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 955-980.
    20. Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
    21. Sargent, Thomas J., 1993. "Bounded Rationality in Macroeconomics: The Arne Ryde Memorial Lectures," OUP Catalogue, Oxford University Press, number 9780198288695.
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    Cited by:

    1. Hommes, Cars, 2018. "Behavioral & experimental macroeconomics and policy analysis: a complex systems approach," Working Paper Series 2201, European Central Bank.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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