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Agent-Based Model Calibration using Machine Learning Surrogates

Listed author(s):
  • Francesco Lamperti

    (Université Panthéon-Sorbonne - Paris 1 (UP1))

  • Andrea Roventini

    (Laboratory of Economics and Management)

  • Amir Sani

    (Université Paris 1 Panthéon-Sorbonne (UP1))

Taking agent-based models (ABM) closer to the data is an open challenge. This paper explicitly tackles parameter space exploration and calibration of ABMs combining supervised machine-learning and intelligent sampling to build a surrogate meta-model. The proposed approach provides a fast and accurate approximation of model behaviour, dramatically reducing computation time. In that, our machine-learning surrogate facilitates large scale explorations of the parameter-space, while providing a powerful filter to gain insights into the complex functioning of agent-based models. The algorithm introduced in this paper merges model simulation and output analysis into a surrogate meta-model, which substantially ease ABM calibration. We successfully apply our approach to the Brock and Hommes (1998) asset pricing model and to the “Island” endogenous growth model (Fagiolo and Dosi, 2003). Performance is evaluated against a relatively large outof-sample set of parameter combinations, while employing different user-defined statistical tests for output analysis. The results demonstrate the capacity of machine learning surrogates to facilitate fast and precise exploration of agent-based models’ behaviour over their often rugged parameter spaces.

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Paper provided by Sciences Po in its series Sciences Po publications with number 2017-09.

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Date of creation: Mar 2017
Handle: RePEc:spo:wpmain:info:hdl:2441/20hflp7eqn97boh50no50tv67n
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  1. G. Fagiolo & C. Birchenhall & P. Windrum, 2007. "Empirical Validation in Agent-based Models: Introduction to the Special Issue," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 189-194, October.
  2. 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.
  3. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
  4. Dosi, G. & Pereira, M.C. & Roventini, A. & Virgillito, M.E., 2017. "When more flexibility yields more fragility: The microfoundations of Keynesian aggregate unemployment," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 162-186.
  5. Archer, Kellie J. & Kimes, Ryan V., 2008. "Empirical characterization of random forest variable importance measures," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2249-2260, January.
  6. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
  7. Guus ten Broeke & George van Voorn & Arend Ligtenberg, 2016. "Which Sensitivity Analysis Method Should I Use for My Agent-Based Model?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-5.
  8. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
  9. Isabelle Salle & Murat Yıldızoğlu, 2014. "Efficient Sampling and Meta-Modeling for Computational Economic Models," Computational Economics, Springer;Society for Computational Economics, vol. 44(4), pages 507-536, December.
  10. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
  11. Dosi, Giovanni & Fagiolo, Giorgio & Napoletano, Mauro & Roventini, Andrea & Treibich, Tania, 2015. "Fiscal and monetary policies in complex evolving economies," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 166-189.
  12. Dosi, G. & Pereira, M. C. & Roventini, A. & Virgillito, M. E., 2017. "Causes and Consequences of Hysteresis: Aggregate Demand, Productivity and Employment," GLO Discussion Paper Series 64, Global Labor Organization (GLO).
  13. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
  14. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
  15. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2015. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 1-25.
  16. Caiani, Alessandro & Godin, Antoine & Caverzasi, Eugenio & Gallegati, Mauro & Kinsella, Stephen & Stiglitz, Joseph E., 2016. "Agent based-stock flow consistent macroeconomics: Towards a benchmark model," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 375-408.
  17. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
  18. Giulio Bottazzi & Angelo Secchi, 2006. "Explaining the distribution of firm growth rates," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 235-256, June.
  19. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An objective function for simulation based inference on exchange rate data," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(2), pages 125-145, December.
  20. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
  21. Fagiolo, Giorgio & Dosi, Giovanni, 2003. "Exploitation, exploration and innovation in a model of endogenous growth with locally interacting agents," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 237-273, September.
  22. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
  23. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2006. "Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 38-42.
  24. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
  25. Jan C. Thiele & Winfried Kurth & Volker Grimm, 2014. "Facilitating Parameter Estimation and Sensitivity Analysis of Agent-Based Models: A Cookbook Using NetLogo and 'R'," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(3), pages 1-11.
  26. Dosi, Giovanni & Fagiolo, Giorgio & Napoletano, Mauro & Roventini, Andrea, 2013. "Income distribution, credit and fiscal policies in an agent-based Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1598-1625.
  27. Guerini, Mattia & Moneta, Alessio, 2017. "A method for agent-based models validation," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 125-141.
  28. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
  29. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
  30. Sylvain Barde, 2015. "A Practical, Universal, Information Criterion over Nth Order Markov Processes," Studies in Economics 1504, School of Economics, University of Kent.
  31. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  32. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
  33. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
  34. Chiarella, Carl & Iori, Giulia, 2009. "The impact of heterogeneous trading rules on the limit order book and order flows," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 525-537.
  35. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
  36. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
  37. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
  38. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  39. Carolina Castaldi & Giovanni Dosi, 2009. "The patterns of output growth of firms and countries: Scale invariances and scale specificities," Empirical Economics, Springer, vol. 37(3), pages 475-495, December.
  40. Francesco Lamperti & Clara Elisabetta Mattei, 2016. "Going Up and Down: Rethinking the Empirics of Growth in the Developing and Newly Industrialized World," LEM Papers Series 2016/01, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  41. Dawid, H. & Harting, P. & Neugart, M., 2014. "Economic convergence: Policy implications from a heterogeneous agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 54-80.
  42. repec:spo:wpecon:info:hdl:2441/f6h8764enu2lskk9p4oq9ig8k is not listed on IDEAS
  43. Giovanni Dosi & Marcelo C. Pereira & Andrea Roventini & Maria Enrica Virgillito, 2016. "The Effects of Labour Market Reforms upon Unemployment and Income Inequalities: an Agent Based Model," Sciences Po publications 2016-24, Sciences Po.
  44. Franke, Reiner, 2009. "Applying the method of simulated moments to estimate a small agent-based asset pricing model," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 804-815, December.
  45. Assenza, Tiziana & Delli Gatti, Domenico & Grazzini, Jakob, 2015. "Emergent dynamics of a macroeconomic agent based model with capital and credit," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 5-28.
  46. Ju-Sung Lee & Tatiana Filatova & Arika Ligmann-Zielinska & Behrooz Hassani-Mahmooei & Forrest Stonedahl & Iris Lorscheid & Alexey Voinov & J. Gary Polhill & Zhanli Sun & Dawn C. Parker, 2015. "The Complexities of Agent-Based Modeling Output Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(4), pages 1-4.
  47. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
  48. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.
  49. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
  50. Francesco Lamperti, 2015. "An Information Theoretic Criterion for Empirical Validation of Time Series Models," LEM Papers Series 2015/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  51. Dosi, Giovanni, 1988. "Sources, Procedures, and Microeconomic Effects of Innovation," Journal of Economic Literature, American Economic Association, vol. 26(3), pages 1120-1171, September.
  52. Giovanni Dosi & Marcelo C. Pereira & Maria Enrica Virgillito, 2016. "On the robustness of the fat-tailed distribution of firm growth rates: a global sensitivity analysis," LEM Papers Series 2016/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  53. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
  54. Jakob Grazzini, 2012. "Analysis of the Emergent Properties: Stationarity and Ergodicity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-7.
  55. Weeks, Melvyn, 1995. "Circumventing the Curse of Dimensionality in Applied Work Using Computer Intensive Methods," Economic Journal, Royal Economic Society, vol. 105(429), pages 520-530, March.
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