The future of agent-based modelling

In this paper, I elaborate on the role of agent-based (AB) modeling for macroeconomic research. My main tenet is that the full potential of the AB approach has not been realized yet. This potential lies in the modular nature of the models, which is bought by abandoning the straitjacket of rational expectations and embracing an evolutionary perspective. I envisage the foundation of a Modular Macroeconomic Science, where new models with heterogeneous interacting agents, endowed with partial information and limited computational ability, can be created by recombining and extending existing models in a unified computational framework.

[1]  R. Hertwig,et al.  Heuristics: The Foundations of Adaptive Behavior , 2015 .

[2]  F. Smets,et al.  An estimated dynamic stochastic general equilibrium model of the euro area. NBB Working Paper Nr. 35 , 2002 .

[3]  Matteo G. Richiardi.  Toward a Non-Equilibrium Unemployment Theory , 2006 .

[4]  David Colander,et al.  Post Walrasian Macroeconomics , 2006 .

[5]  Mauro Gallegati,et al.  Heterogeneous Interacting Agent Models for Understanding Monetary Economies , 2011 .

[6]  Robert L. Axtell,et al.  An agent-based model of the housing market bubble in metropolitan Washington, D.C. , 2014 .

[7]  Matteo G. Richiardi,et al.  The Missing Link: AB Models and Dynamic Microsimulation , 2014 .

[8]  D. Bradford.  Economics in Crisis , 2011 .

[9]  Frank Smets,et al.  An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area , 2002 .

[10]  Jonathan Heathcote,et al.  Quantitative Macroeconomics with Heterogeneous Households , 2009 .

[11]  Matteo G. Richiardi,et al.  Agent-based computational economics: a short introduction , 2012, The Knowledge Engineering Review.

[12]  M. Brzoza‐Brzezina,et al.  The Anatomy of Standard DSGE Models with Financial Frictions , 2011 .

[13]  Jason Allen.  An Estimated Dynamic Stochastic General Equilibrium Model , 2015 .

[14]  M. Wolfson,et al.  Exploring Contingent Inequalities: Building the Theoretical Health Inequality Model , 2017 .

[15]  M. Mobius,et al.  Social Learning in Economics , 2014 .

[16]  Herbert Gintis,et al.  The Dynamics of General Equilibrium , 2007 .

[17]  Joseph E. Stiglitz,et al.  RETHINKING MACROECONOMICS: WHAT FAILED, AND HOW TO REPAIR IT , 2011 .

[18]  T. Schelling.  Models of Segregation , 1969 .

[19]  Leigh Tesfatsion,et al.  Co-learning patterns as emergent market phenomena: An electricity market illustration , 2012 .

[20]  A. Markiewicz,et al.  Learning to Forecast the Exchange Rate: Two Competing Approaches , 2006, SSRN Electronic Journal.

[21]  Pablo A. Guerrón-Quintana,et al.  Fortune or Virtue: Time-Variant Volatilities Versus Parameter Drifting in U.S. Data , 2010 .

[22]  Ross Richardson,et al.  JAS-mine: A new platform for microsimulation and agent-based modelling , 2016 .

[23]  C. Hommes,et al.  Evolutionary selection of expectations in positive and negative feedback markets , 2010 .

[24]  G. Weisbuch,et al.  From production networks to geographical economics , 2007 .

[25]  G. Dosi,et al.  Income Distribution, Credit and Fiscal Policies in an Agent-Based Keynesian Model , 2012 .

[26]  M. Batty.  Generative social science: Studies in agent-based computational modeling , 2008 .

[27]  Paul De Grauwe,et al.  Booms and busts in economic activity: A behavioral explanation , 2012 .

[28]  Michael Wooldridge,et al.  Introduction to multiagent systems , 2001 .

[29]  Herbert Dawid,et al.  Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model , 2014 .

[30]  Joshua M. Epstein,et al.  Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity) , 2007 .

[31]  Nicolaas J. Vriend,et al.  An Illustration of the Essential Difference between Individual and Social Learning, and its Consequences for Computational Analyses , 1998 .

[32]  David C. Colander,et al.  Post Walrasian macroeconomics : beyond the dynamic stochastic general equilibrium model , 2006 .

[33]  W. Bagehot.  Lombard Street: A Description of the Money Market , 1873 .

[34]  A. Kirman.  The Economic Crisis is a Crisis for Economic Theory , 2010 .

[35]  Dhananjay K. Gode,et al.  Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality , 1993, Journal of Political Economy.

[36]  Nicolaas J. Vriend,et al.  An Illustration of the Essential Difference between Individual and Social Learning, and its Consequences for Computational Analyses , 1998 .

[37]  M. Raberto,et al.  THE IMPACT OF BANKS' CAPITAL ADEQUACY REGULATION ON THE ECONOMIC SYSTEM: AN AGENT-BASED APPROACH , 2012 .

[38]  W. Scherer,et al.  Effects of Limit Order Book Information Level on Market Stability Metrics , 2014 .

[39]  Matteo G. Richiardi,et al.  Estimation of ergodic agent-based models by simulated minimum distance , 2015 .

[40]  Martin Eichenbaum,et al.  NBER WORKING PAPER SERIES UNDERSTANDING THE GREAT RECESSION , 2014 .

[41]  Olivier J. Blanchard.  The State of Macro , 2008 .

[42]  P. Krugman,et al.  The Profession and the Crisis , 2011 .

[43]  J. Geanakoplos,et al.  Leverage-induced systemic risk under Basle II and other credit risk policies , 2013, 1301.6114.

[44]  Michael Wickens,et al.  How Did We Get to Where We are Now? Reflections on 50 Years of Macroeconomic and Financial Econometrics , 2014 .

[45]  Leigh Tesfatsion,et al.  Macroeconomies as Constructively Rational Games , 2015 .

[46]  David C. Colander,et al.  The future of economics: the appropriately educated in pursuit of the knowable , 2005 .

[47]  Matteo G. Richiardi,et al.  Agent-Based Computational Demography and Microsimulation Using JAS-mine , 2017 .

[48]  Gérard Ballot,et al.  Training policies and economic growth in an evolutionary world , 2001 .

[49]  Nelson Minar,et al.  The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations , 1996 .

[50]  Ricardo J. Caballero,et al.  Macroeconomics after the Crisis: Time to Deal with the Pretense-of-Knowledge Syndrome , 2010 .

[51]  Mauro Gallegati,et al.  The financial accelerator in an evolving credit network , 2010 .

[52]  C. Hommes,et al.  Innovate or Imitate? Behavioural Technological Change , 2013 .

[53]  Roberto Leombruni,et al.  A Common Protocol for Agent-Based Social Simulation , 2006, J. Artif. Soc. Soc. Simul..

[54]  Barbara Messing,et al.  An Introduction to MultiAgent Systems , 2002, Künstliche Intell..

[55]  G. Dosi,et al.  Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles , 2010 .

[56]  Vadim Khramov,et al.  Solving and Estimating Indeterminate DSGE Models , 2013, SSRN Electronic Journal.

[57]  D. Gatti,et al.  A new approach to business fluctuations: heterogeneous interacting agents, scaling laws and financial fragility , 2003, cond-mat/0312096.

[58]  Pablo A. Guerrón-Quintana,et al.  Fortune or Virtue: Time-Variant Volatilities Versus Parameter Drifting , 2010 .

[59]  Morris Altman,et al.  Handbook of Contemporary Behavioral Economics: Foundations and Developments , 2006 .

[60]  Leigh Tesfatsion,et al.  Agent-based Modeling and Institutional Design , 2011 .

[61]  Moses Abramovitz,et al.  Resources and Output Trends in the United States since 1870. , 1957 .

[62]  C. Hommes,et al.  Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems , 2013 .

[63]  Ricardo L. Viana,et al.  Structural Change and Economic Dynamics , 2011 .

[64]  Richard B. Freeman,et al.  War of the models: Which labour market institutions for the 21st century? 1 This is the text of the , 1998 .

[65]  Dudley D. Dillard.  Can “It” Happen Again? Essays on Instability and Finance , 1984 .

[66]  E. Phelps,et al.  Rethinking Expectations: The Way Forward for Macroeconomics , 2013 .

[67]  Herbert Dawid,et al.  Economic convergence : policy implications from a heterogeneous agent model , 2014 .

[68]  W. Lewis,et al.  Manias, Panics and Crashes: A History of Financial Crises , 1979 .

[69]  Matteo Richiardi,et al.  Consistent Estimation of Agent-Based Models by Simulated Minimum Distance , 2013 .

[70]  Blake LeBaron,et al.  Modeling Macroeconomies As Open-Ended Dynamic Systems of Interacting Agents , 2008 .

[71]  Seppo Honkapohja,et al.  Learning as a Rational Foundation for Macroeconomics and Finance , 2011, SSRN Electronic Journal.

[72]  G. Fagiolo,et al.  Working Paper Series Department of Economics University of Verona Fat-Tail Distributions and Business-Cycle Models , 2012 .

[73]  P. Todd,et al.  Ecological Rationality: Intelligence in the World , 2012 .

[74]  Alan Kirman,et al.  Learning in Agent-based Models , 2011 .

[75]  H. Minsky.  Stabilizing an Unstable Economy , 1986 .

[76]  R. Leombruni,et al.  Why are economists sceptical about agent-based simulations? , 2005 .

[77]  S. Battiston,et al.  Credit Chains and Bankruptcy Propagation in Production Networks , 2007 .

[78]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[79]  G. Evans,et al.  Learning and Macroeconomics , 2009 .

[80]  Michael Woodford,et al.  Macroeconomic Analysis Without the Rational Expectations Hypothesis , 2013 .

[81]  Stefano Battiston,et al.  Default Cascades: When Does Risk Diversification Increase Stability? , 2011 .

[82]  David Colander,et al.  Beyond DSGE Models: Toward an Empirically Based Macroeconomics , 2008 .

[83]  Marco Del Negro,et al.  Inflation in the Great Recession and New Keynesian Models , 2013 .

[84]  D. Foley,et al.  The economy needs agent-based modelling , 2009, Nature.

[85]  William A. Brock,et al.  A rational route to randomness , 1997 .