The economy needs agent-based modelling

By J. Farmer, Duncan K. Foley. Nature, 2009

1,311 citations recorded by the source corpus.

The leaders of the world are flying the economy by the seat of their pants, say J. Doyne Farmer and Duncan Foley. There is, however, a better way to help guide financial policies.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/9230b3c0d79aeac2eef4742addaa5001f4842bde

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

Citations in the corpus

Econophysics: Empirical facts and agent-based models (2009, neutral): “Many scientists have expressed their views on this subject (e.g. Bouchaud (2008); Lux and Westerhoff (2009); Farmer and Foley (2009)) and we believe as well that agent-based models we have presented here will be at the core of future modelling.”
Speculation: a political economy of technologies of imagination (2020, background): “The long-term dream is to input real-time data of financial transactions into such models so that they become vast simulations that anticipate the future (Braun-Munzinger et al., 2016; Farmer & Foley, 2009).”
Complexity and the Economics of Climate Change: A Survey and a Look Forward (2017, neutral): “ABMs have so far mainly focused on how single policies affect the introduction and diffusion of climatefriendly technologies.”
Agent based-stock flow consistent macroeconomics: Towards a benchmark model (2016, methodology): “In this respect, Agent Based models, geared around the conception of the economy as a complex adaptive system, may greatly help to overcome many of these limitations.”
Tipping Points in Macroeconomic Agent-Based Models (2013, background): “In order to do this, numerical simulations turn out to be very helpful [14, 15]: aggregate behaviour usually quickly sets in, even for small sizes.”
Micro-price trading in an order-driven market (2014, background): “Policy analysis and the analysis of systemic risk in the financial sector are areas where agent-based modeling may provide insight [15]–[17].”
Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model (2018, neutral): “Agent-based models consider the real world as a complex evolving system (more on this in Farmer and Foley, 2009; Dosi, 2012; Dosi and Virgillito, 2016; Kirman, 2016), wherein the interaction of many heterogenous agents, possibly across different spatial and temporal scales, gives rise to the…”
Systems integration for global sustainability (2015, background): “Agent-basedmodels create virtual worlds thatmimic the real world, in contrast to traditional empirical statistical models (such as econometric models) that are fitted to past data and fail when the future differs from the past, and dynamic stochastic general equilibrium models that presume a perfect”
Energy systems modeling for twenty-first century energy challenges (2014, background): “Finally, complex systems research is developing methods to model multi-scale systems in areas ranging from finance (Farmer and Foley, 2009) to ecology (Levin, 1998).”