Skip to main content
Log in

Drawing on different disciplines: macroeconomic agent-based models

  • Regular Article
  • Published:
Journal of Evolutionary Economics Aims and scope Submit manuscript

Abstract

Macroeconomic modelling has been under intense scrutiny since the Great Financial Crisis, when serious shortcomings were exposed in the methodology used to understand the economy as a whole. Criticism has been levelled at the assumptions employed in the dominant models, particularly that economic agents are homogenous and optimising and that the economy is equilibrating. In a related paper (Haldane and Turrell Oxford Rev Econ Polic 34(1–2):219–251 2018), we argue that an interdisciplinary approach to modelling in macroeconomics is beneficial. Here we focus on what one such approach - agent-based modelling, which has been extensively used across a wide range of disciplines - could do for macroeconomics. Agent-based models are complementary to existing approaches to macroeconomics and are particularly well-suited to answering questions where complexity, heterogeneity, networks, and heuristics play an important role.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. Every agent-based model is computable by a Turing machine, and every algorithm computable by a Turing machine may be expressed via sets of partial recursive functions.

References

  • Abel AB (1990) Asset prices under habit formation and catching up with the Joneses. Tech. rep., National Bureau of Economic Research

  • Aikman D, Galesic M, Gigerenzer G, Kapadia S, Katsikopoulos KV, Kothiyal A, Murphy E, Neumann T (2014) Taking uncertainty seriously: simplicity versus complexity in financial regulation. Bank of England Financial Stability Paper 28

  • Aiyagari SR (1994) Uninsured idiosyncratic risk and aggregate saving. Quart J Econ 109(3):659–684

    Google Scholar 

  • Alfarano S, Lux T, Wagner F (2005) Estimation of agent-based models: the case of an asymmetric herding model. Comput Econ 26(1):19–49

    Google Scholar 

  • Alfi V, Cristelli M, Pietronero L, Zaccaria A (2009) Minimal agent based model for financial markets I. Europ Phys J B 67(3):385–397

    Google Scholar 

  • Arber T, Bennett K, Brady C, Lawrence-Douglas A, Ramsay M, Sircombe N, Gillies P, Evans R, Schmitz H, Bell A et al (2015) Contemporary particle-in-cell approach to laser-plasma modelling. Plasma Phys Controll Fusion 57 (11):113,001

    Google Scholar 

  • Arthur WB (2006) Out-of-equilibrium economics and agent-based modeling. Handbook Comput Econ 2:1551–1564

    Google Scholar 

  • Ascari G, Fagiolo G, Roventini A (2015) Fat-tail distributions and business-cycle models. Macroecon Dyn 19(02):465–476

    Google Scholar 

  • Ashraf Q, Gershman B, Howitt P (2017) Banks, market organization, and macroeconomic performance: an agent-based computational analysis, vol 135

  • Assenza T, Gatti DD, Grazzini J (2015) Emergent dynamics of a macroeconomic agent based model with capital and credit. J Econ Dyn Control 50:5–28

    Google Scholar 

  • Assenza T, Gatti DD, Grazzini J, Ricchiuti G (2016) Heterogeneous firms and international trade: the role of productivity and financial fragility. CESifo Working Paper Series 5959, CESifo Group Munich

  • Assenza T, Brock WA, Hommes CH (2017) Animal spirits, heterogeneous expectations, and the amplification and duration of crises. Econ Inq 55(1):542–564

    Google Scholar 

  • Auclert A (2015) Monetary policy and the redistribution channel. 2015 Meeting Papers 381, Society for Economic Dynamics, http://EconPapers.repec.org/RePEc:red:sed015:381

  • Ausloos M, Miśkiewicz J, Sanglier M (2004) The durations of recession and prosperity: does their distribution follow a power or an exponential law? Physica Stat Mech Appl 339(3):548–558

    Google Scholar 

  • Bagehot W (1873) Lombard street: a description of the money market. Henry S. King and Co., London

    Google Scholar 

  • Baptista R, Farmer JD, Hinterschweiger M, Low K, Tang D, Uluc A (2016) Macroprudential policy in an agent-based model of the UK housing market. Staff Working Paper 619, Bank of England, http://EconPapers.repec.org/RePEc:boe:boeewp:0619

  • Bardoscia M, Battiston S, Caccioli F, Caldarelli G (2017) Pathways towards instability in financial networks. Nat Commun, 8

  • Bartelsman EJ, Doms M (2000) Understanding productivity: lessons from longitudinal microdata. J Econ Literat 38(3):569–594

    Google Scholar 

  • Battiston S, Gatti DD, Gallegati M, Greenwald B, Stiglitz JE (2007) Credit chains and bankruptcy propagation in production networks. J Econ Dyn Control 31(6):2061–2084

    Google Scholar 

  • Bernanke B (2004) The great moderation. Speech given at the Eastern Economic Association

  • Bjørnland HC, Gerdrup K, Jore AS, Smith C, Thorsrud LA (2012) Does forecast combination improve Norges Bank inflation forecasts? Oxf Bull Econ Stat 74(2):163–179

    Google Scholar 

  • Blanchard O (2017) On the need for (at least) five classes of macro models. https://piie.com/blogs/realtime-economic-issues-watch/need-least-five-classes-macro-models

  • Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci 99(suppl 3):7280–7287

    Google Scholar 

  • Bottazzi G, Secchi A (2003) Common properties and sectoral specificities in the dynamics of US manufacturing companies. Rev Indus Organ 23(3–4):217–232

    Google Scholar 

  • Bottazzi G, Secchi A (2006) Explaining the distribution of firm growth rates. RAND J Econ 37(2):235–256

    Google Scholar 

  • Braun-Munzinger K, Liu Z, Turrell AE (2016) An agent-based model of dynamics in corporate bond trading. Staff Working Paper 592, Bank of England, https://ideas.repec.org/p/boe/boeewp/0592.html

  • Brayton F, Tinsley PA (1996) A guide to FRB/US: a macroeconomic model of the United States. FEDS Paper 96-42, US Federal Reserve, https://ssrn.com/abstract=3553

  • Bulanov S, Khoroshkov V (2002) Feasibility of using laser ion accelerators in proton therapy. Plasma Phys Rep 28(5):453–456

    Google Scholar 

  • Burgess S, Fernandez-Corugedo E, Groth C, Harrison R, Monti F, Theodoridis K, Waldron M (2013) The Bank of England’s forecasting platform: COMPASS, MAPS, EASE and the suite of models. Staff Working Paper 471, Bank of England, https://ideas.repec.org/p/boe/boeewp/0471.html

  • Burns AF, Mitchell WC (1946) Measuring business cycles. National Bureau of Economic Research, Inc, http://EconPapers.repec.org/RePEc:nbr:nberbk:burn46-1

  • Caiani A, Godin A, Caverzasi E, Gallegati M, Kinsella S, Stiglitz JE (2016) Agent based-stock flow consistent macroeconomics: towards a benchmark model. J Econ Dyn Control 69:375–408

    Google Scholar 

  • Campbell JY, Mankiw N G (1989) Consumption, income, and interest rates: reinterpreting the time series evidence. NBER Macroecon Annual 4:185–216

    Google Scholar 

  • Carroll CD (1997) Buffer-stock saving and the life cycle/permanent income hypothesis. Quart J Econ 112(1):1–55

    Google Scholar 

  • Carroll CD (2001) The epidemiology of macroeconomic expectations. Tech. rep., National Bureau of Economic Research

  • Carroll CD (2009) Precautionary saving and the marginal propensity to consume out of permanent income. J Monet Econ 56(6):780–790

    Google Scholar 

  • Carroll CD, Kimball MS (1996) On the concavity of the consumption function. Econometrica 64(4):981–992

    Google Scholar 

  • Carter N, Levin S, Barlow A, Grimm V (2015) Modeling tiger population and territory dynamics using an agent-based approach. Ecol Model 312:347–362

    Google Scholar 

  • Castaldi C, Dosi G (2009) The patterns of output growth of firms and countries: scale invariances and scale specificities. Empir Econ 37(3):475–495

    Google Scholar 

  • Chakraborty C, Joseph A (2017) Machine learning at central banks. Staff Working Paper 674, Bank of England, https://ideas.repec.org/p/boe/boeewp/0674.html

  • Chan C K, Steiglitz K (2008) An agent-based model of a minimal economy. Dept of Computer Science. Princeton University, Princeton

    Google Scholar 

  • Cincotti S, Raberto M, Teglio A (2010) Credit money and macroeconomic instability in the agent-based model and simulator Eurace. Economics Discussion Papers 2010-4, Kiel Institute for the World Economy (IfW), http://EconPapers.repec.org/RePEc:zbw:ifwedp:20104

  • Colander D, Goldberg M, Haas A, Juselius K, Kirman A, Lux T, Sloth B (2009) The financial crisis and the systemic failure of the economics profession. Critic Rev 21(2-3):249–267

    Google Scholar 

  • Cooper D, Dynan K (2014) Wealth effects and macroeconomic dynamics. J Econ Surv

  • Cutler DM, Poterba JM, Summers LH (1989) What moves stock prices? J Portfolio Manag 15(3):4–12

    Google Scholar 

  • Davis M, Efstathiou G, Frenk CS, White SD (1985) The evolution of large-scale structure in a universe dominated by cold dark matter. Astrophys J 292:371–394

    Google Scholar 

  • Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M (2012) The eurace@ unibi model: an agent-based macroeconomic model for economic policy analysis. Bielefeld Working Papers in Economics and Management

  • Dawid H, Harting P, Neugart M (2014) Economic convergence: policy implications from a heterogeneous agent model. J Econ Dyn Control 44:54–80

    Google Scholar 

  • De Grauwe P (2010) Top-down versus bottom-up macroeconomics. CESifo Econ Stud 56(4):465–497

    Google Scholar 

  • Degli Atti MLC, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, Furlanello C, Tomba GS, Iannelli M (2008) Mitigation measures for pandemic influenza in italy: an individual based model considering different scenarios. PloS one 3(3):e1790

    Google Scholar 

  • Di Guilmi C, Gallegati M, Ormerod P (2004) Scaling invariant distributions of firms’ exit in OECD countries. Physica Statist Mech Appl 334(1):267–273

    Google Scholar 

  • Doms M, Dunne T (1998) Capital adjustment patterns in manufacturing plants. Rev Econ Dyn 1(2):409–429

    Google Scholar 

  • Dosi G, Fagiolo G, Roventini A (2010) Schumpeter meeting keynes: a policy-friendly model of endogenous growth and business cycles. J Econ Dyn Control 34(9):1748–1767

    Google Scholar 

  • Dosi G, Fagiolo G, Napoletano M, Roventini A, Treibich T (2015) Fiscal and monetary policies in complex evolving economies. J Econ Dyn Control 52:166–189

    Google Scholar 

  • Dosi G et al (2007) Statistical regularities in the evolution of industries. a guide through some evidence and challenges for the theory. Perspect Innov, 1110–1121

  • Elmendorf DW et al (1996) The effect of interest-rate changes on household saving and consumption: a survey. Citeseer

  • Epstein JM (1999) Agent-based computational models and generative social science. Complexity 4(5):41–60

    Google Scholar 

  • Epstein JM (2006) Remarks on the foundations of agent-based generative social science. Handbook Comput Econ 2:1585–1604

    Google Scholar 

  • Erlingsson EJ, Teglio A, Cincotti S, Stefansson H, Sturluson JT, Raberto M (2014) Housing market bubbles and business cycles in an agent-based credit economy. Econ Open-Access, Open-Assessment E-J 8(2014-8), https://doi.org/10.5018/economics-ejournal.ja.2014-8

  • Ernest N, Carroll D, Schumacher C, Clark M, Cohen K et al (2016) Genetic fuzzy based artificial intelligence for unmanned combat aerial vehicle control in simulated air combat missions. J Def Manag 6(144):2167–0374

    Google Scholar 

  • Estrella A, Fuhrer JC (2002) Dynamic inconsistencies: counterfactual implications of a class of rational-expectations models. Am Econ Rev 92(4):1013–1028

    Google Scholar 

  • Fagiolo G, Roventini A (2012) Macroeconomic policy in DSGE and agent-based models. Revue de l’OFCE 5(124):67–116. https://doi.org/10.18564/jasss.3280. http://jasss.soc.surrey.ac.uk/20/1/1.html

    Google Scholar 

  • Fagiolo G, Roventini A (2017) Macroeconomic policy in DSGE and agent-based models redux: new developments and challenges ahead. J Artif Soc Soc Simul 20(1):1. https://doi.org/10.18564/jasss.3280. http://jasss.soc.surrey.ac.uk/20/1/1.html

    Google Scholar 

  • Fagiolo G, Napoletano M, Roventini A (2008) Are output growth-rate distributions fat-tailed? Some evidence from OECD countries. J Appl Econometr 23 (5):639–669

    Google Scholar 

  • Fair RC (2012) Has macro progressed? J Macroecon 34(1):2–10

    Google Scholar 

  • Foos D, Norden L, Weber M (2010) Loan growth and riskiness of banks. J Bank Financ 34(12):2929–2940

    Google Scholar 

  • Franke R, Westerhoff F (2012) Structural stochastic volatility in asset pricing dynamics: estimation and model contest. J Econ Dyn Control 36(8):1193–1211

    Google Scholar 

  • Friedman M (1957) A Theory of the Consumption Function. Princeton University Press

  • Friedman J, Hastie T, Tibshirani R (2001) The elements of statistical learning, vol 1. Springer series in statistics, New York

    Google Scholar 

  • Fukac M, Pagan A (2006) Issues in adopting DSGE models for use in the policy process. Australian National University. Centre for Applied Macroeconomic Analysis. CAMA Working Paper 10

  • Gabaix X (2011) The granular origins of aggregate fluctuations. Econometrica 79(3):733–772

    Google Scholar 

  • Gabaix X (2016) Behavioral macroeconomics via sparse dynamic programming. Tech. rep., National Bureau of Economic Research

  • Gabaix X (2017) Behavioral inattention. Tech. rep., National Bureau of Economic Research

  • Gaffeo E, Di Guilmi C, Gallegati M, Russo A (2012) On the mean/variance relationship of the firm size distribution: evidence and some theory. Ecol Complex 11:109–117

    Google Scholar 

  • Gai P, Kapadia S (2010) Contagion in financial networks. In: Proceedings of the royal society of london a: mathematical, physical and engineering sciences https://doi.org/10.1098/rspa.2009.0410, http://rspa.royalsocietypublishing.org/content/early/2010/03/18/rspa.2009.0410

  • Gai P, Haldane A, Kapadia S (2011) Complexity, concentration and contagion. J Monet Econ 58(5):453–470

    Google Scholar 

  • Galí J (2015) Monetary policy, inflation, and the business cycle: an introduction to the new Keynesian framework and its applications. Princeton University Press

  • García-Schmidt M, Woodford M (2015) Are low interest rates deflationary? A paradox of perfect-foresight analysis. Tech. rep., National Bureau of Economic Research

  • Gatti DD, Desiderio S (2015) Monetary policy experiments in an agent-based model with financial frictions. J Econ Interac Coord 10(2):265–286

    Google Scholar 

  • Geanakoplos J, Axtell R, Farmer DJ, Howitt P, Conlee B, Goldstein J, Hendrey M, Palmer NM, Yang CY (2012) Getting at systemic risk via an agent-based model of the housing market. Am Econ Rev 102(3):53–58

    Google Scholar 

  • Ghironi F (2018) Macro needs micro. Oxf Rev Econ Policy 34(1–2):195–218

    Google Scholar 

  • Gibson B (2007) A multi-agent systems approach to microeconomic foundations of macro. Tech. rep. Working Paper. University of Massachusetts, Department of Economics

  • Gigerenzer G, Brighton H (2009) Homo heuristicus: why biased minds make better inferences. Topics Cogn Sci 1(1):107–143

    Google Scholar 

  • Gobbi A, Grazzini J (2017) A basic new keynesian dsge model with dispersed information. An agent-based approach. J Econ Behav Org

  • Gode DK, Sunder S (1993) Allocative efficiency of markets with zero-intelligence traders: market as a partial substitute for individual rationality. J Polit Econ 101(1):119–137

    Google Scholar 

  • Godley W, Lavoie M (2007) Monetary economics. Palgrave Macmillan, Hampshire

    Google Scholar 

  • Gualdi S, Tarzia M, Zamponi F, Bouchaud JP (2015) Tipping points in macroeconomic agent-based models. J Econ Dyn Control 50:29–61

    Google Scholar 

  • Guerini M, Moneta A (2017) A method for agent-based models validation. J Econ Dyn Control

  • Guerini M, Napoletano M, Roventini A (2016) No man is an island: The impact of heterogeneity and local interactions on macroeconomic dynamics. Sciences Po publications 2016-18, Sciences Po, http://EconPapers.repec.org/RePEc:spo:wpmain:info:hdl:2441/20d1ncsepb9ssq3b3v4s6nbc41

  • Guvenen F (2011) Macroeconomics with heterogeneity: a practical guide. Tech. rep., National Bureau of Economic Research

  • Haldane AG (2016) The Dappled World. Bank of England Speech, www.bankofengland.co.uk/publications/Documents/speeches/2016/speech937.pdf

  • Haldane AG, Madouros V (2012) The dog and the frisbee. Revista de Economí,a Institucional 14(27):13–56

    Google Scholar 

  • Haldane AG, Turrell AE (2018) An interdisciplinary model for macroeconomics. Oxf Rev Econ Policy 34(1–2):219–251

    Google Scholar 

  • Heathcote J (2005) Fiscal policy with heterogeneous agents and incomplete markets. Rev Econ Stud 72(1):161–188

    Google Scholar 

  • Heppenstall AJ, Crooks AT, See LM, Batty M (2011) Agent-based models of geographical systems. Springer Science & Business Media

  • Hills S, Thomas R, Dimsdale N (2016) Three centuries of data version 2.3. http://www.bankofengland.co.uk/research/Pages/onebank/threecenturies.aspx

  • Hommes CH (2006) Heterogeneous agent models in economics and finance. Handbook Comput Econ 2:1109–1186

    Google Scholar 

  • Hong H, Stein JC (1999) A unified theory of underreaction, momentum trading, and overreaction in asset markets. J Financ 54(6):2143–2184

    Google Scholar 

  • Ilut CL, Schneider M (2014) Ambiguous business cycles. Am Econ Rev 104(8):2368–2399

    Google Scholar 

  • Jaimovich N, Floetotto M (2008) Firm dynamics, markup variations, and the business cycle. J Monet Econ 55(7):1238–1252

    Google Scholar 

  • Jawadi F, Sousa RM (2014) The relationship between consumption and wealth: a quantile regression approach. Revue d’é,conomie politique 124(4):639–652

    Google Scholar 

  • Kaplan G, Moll B, Violante GL (2016) Monetary policy according to HANK. Tech. rep., National Bureau of Economic Research

  • Keynes JM (1936) General theory of employment, interest and money. Palgrave Macmillan

  • Kindleberger CP (2001) Manias, panics, and crashes: a history of financial crises. Wiley 32(2):379

    Google Scholar 

  • Kirman AP (1992) Whom or what does the representative individual represent?. J Econ Perspect 6(2):117–136. https://doi.org/10.1257/jep.6.2.117. http://www.aeaweb.org/articles?id=10.1257/jep.6.2.117

    Google Scholar 

  • Knight FH (2012) Risk, uncertainty and profit. Courier Corporation

  • Krugman P (2011) The profession and the crisis. Eastern Econ J 37(3):307–312. https://doi.org/10.1057/eej.2011.8

    Google Scholar 

  • Kumhof M, Rancière R, Winant P (2015) Inequality, leverage, and crises. Am Econ Rev 105(3):1217–1245

    Google Scholar 

  • Kuznets S, Murphy JT (1966) Modern economic growth: rate, structure, and spread, vol 2. Yale University Press, New Haven

    Google Scholar 

  • Kydland FE, Prescott EC (1982) Time to build and aggregate fluctuations. Econometrica: J Econometr Soc 1345–1370

  • Laeven L, Valencia F (2013) Systemic banking crises database. IMF Econ Rev 61(2):225–270

    Google Scholar 

  • Lamperti F, Dosi G, Napoletano M, Roventini A, Sapio A (2017a) Faraway, so close: coupled climate and economic dynamics in an agent-based integrated assessment model. Sciences Po OFCE Working Paper 10, Sciences Po

  • Lamperti F, Roventini A, Sani A (2017b) Agent-based model calibration using machine learning surrogates. Papers 1703.10639, arXiv.org, https://ideas.repec.org/p/arx/papers/1703.10639.html

  • Leary M T (2009) Bank loan supply, lender choice, and corporate capital structure. J Financ 64(3):1143–1185

    Google Scholar 

  • Leibo JZ, Zambaldi V, Lanctot M, Marecki J, Graepel T (2017) Multi-agent reinforcement learning in sequential social dilemmas. Working paper, DeepMind, https://storage.googleapis.com/deepmind-media/papers/multi-agent-rl-in-ssd.pdf

  • Leijonhufvud A (2000) Macroeconomic instability and coordination: selected essays. Edward Elgar, Cheltenham

    Google Scholar 

  • Lengnick M (2013) Agent-based macroeconomics: a baseline model. J Econ Behav Org 86:102–120

    Google Scholar 

  • Leombruni R, Richiardi M (2005) Why are economists sceptical about agent-based simulations? Physica Statist Mech Appl 355(1):103–109

    Google Scholar 

  • Lindé J, Smets F, Wouters R (2016) Challenges for central banks’ macro models. Handb Macroecon 2:2185–2262

    Google Scholar 

  • Lindl JD, Amendt P, Berger RL, Glendinning SG, Glenzer SH, Haan SW, Kauffman RL, Landen OL, Suter LJ (2004) The physics basis for ignition using indirect-drive targets on the National Ignition Facility. Phys Plasmas 11(2):339–491

    Google Scholar 

  • Lown C, Morgan D P (2006) The credit cycle and the business cycle: new findings using the loan officer opinion survey. J Money Credit Bank 1575–1597

  • Lucas RE (1972) Expectations and the neutrality of money. J Econ Theory 4(2):103–124

    Google Scholar 

  • Lucas RE (1976) Econometric policy evaluation: a critique. In: Carnegie-Rochester conference series on public policy, vol 1. Elsevier, pp 19-46

  • Lucas RE (1987) Models of business cycles, vol 26. Basil Blackwell, Oxford

    Google Scholar 

  • Lucas RE, Sargent TJ (1979) After Keynesian macroeconomics. Quart Rev 3(Spr), https://ideas.repec.org/a/fip/fedmqr/y1979isprnv.3no.2.html

  • Lux T, Marchesi M (1999) Scaling and criticality in a stochastic multi-agent model of a financial market. Nature 397(6719):498–500

    Google Scholar 

  • Mendoza EG, Terrones ME (2012) An anatomy of credit booms and their demise. Tech. rep., National Bureau of Economic Research

  • Metroplis N (1987) The beginning of the Monte Carlo method. Los Alamos Sci 15(548):125–130

    Google Scholar 

  • Metropolis N, Ulam S (1949) The Monte Carlo method. J Amer Statist Assoc 44(247):335–341

    Google Scholar 

  • Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21 (6):1087–1092

    Google Scholar 

  • Minsky HP (2008) Stabilizing an unstable economy, vol 1. McGraw Hill, New York

    Google Scholar 

  • Muellbauer J, Murata K (2009) Consumption, land prices and the monetary transmission mechanism in japan. Columbia University Academic Commons

  • Muth JF (1961) Rational expectations and the theory of price movements. Econometrica: J Econometr Soc, 315–335

  • Napoletano M, Roventini A, Sapio S (2006) Are business cycles all alike? A bandpass filter analysis of the Italian and US cycles. Rivista Italiana degli Economisti 11(1):87–118

    Google Scholar 

  • Popoyan L, Napoletano M, Roventini A (2016) Taming macroeconomic instability: monetary and macro prudential policy interactions in an agent-based model. J Econ Behav Org

  • Ravn M, Sterk V (2016) Macroeconomic fluctuations with HANK & SAM: an analytical approach. Discussion Papers 1633, Centre for Macroeconomics (CFM), http://EconPapers.repec.org/RePEc:cfm:wpaper:1633

  • Reinhart CM, Rogoff KS (2009) The aftermath of financial crises. Tech. rep., National Bureau of Economic Research

  • Romer P (2016) The trouble with macroeconomics. September, forthcoming in The American Economist

  • Rubiano J, Florido R, Bowen C, Lee R, Ralchenko Y (2007) Review of the 4th nlte code comparison workshop. High Energy Dens Phys 3(1):225–232

    Google Scholar 

  • Salle I, Yıldızoğlu M, Sénégas MA (2013) Inflation targeting in a learning economy: an ABM perspective. Econ Modell 34:114–128

    Google Scholar 

  • Shaikh A (2016) Capitalism: competition, conflict, crises. Oxford University Press

  • Sherlock M, Hill E, Evans R, Rose S, Rozmus W (2014) In-depth plasma-wave heating of dense plasma irradiated by short laser pulses. Phys Rev Lett 113(25):255,001

    Google Scholar 

  • Shiller RJ (2017) Narrative economics. Working Paper 23075, National Bureau of Economic Research, https://doi.org/10.3386/w23075, http://www.nber.org/papers/w23075

  • Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, Hubert T, Baker L, Lai M, Bolton A et al (2017) Mastering the game of go without human knowledge. Nature 550(7676):354

    Google Scholar 

  • Silver N (2012) The signal and the noise: the art and science of prediction. Penguin UK

  • Simon HA (1959) Theories of decision-making in economics and behavioral science. Amer Econ Rev 49(3):253–283

    Google Scholar 

  • Sinitskaya E, Tesfatsion L (2015) Macroeconomies as constructively rational games. J Econ Dyn Control 61:152–182

    Google Scholar 

  • Smets F, Wouters R (2003) An estimated dynamic stochastic general equilibrium model of the euro area. J Eur Econ Assoc 1(5):1123–1175

    Google Scholar 

  • Smith N (2014) Wall street skips economics class. Bloomberg View; https://www.bloomberg.com/view/articles/2014-07-23/wall-street-skips-economics-class

  • Solow R (2008) The state of macroeconomics. J Econ Perspect 22(1):243–246

    Google Scholar 

  • Sornette D (2014) Physics and financial economics (1776–2014): puzzles, Ising and agent-based models. Rep Progress Phys 77(6):062,001

    Google Scholar 

  • Souleles NS (1999) The response of household consumption to income tax refunds. Am Econ Rev 89(4):947–958

    Google Scholar 

  • Spears BK, Munro DH, Sepke S, Caggiano J, Clark D, Hatarik R, Kritcher A, Sayre D, Yeamans C, Knauer J et al (2015) Three-dimensional simulations of national ignition facility implosions: insight into experimental observables a). Phys Plasmas 22(5):056,317

    Google Scholar 

  • Stern N (2016) Economics: current climate models are grossly misleading. Nature 530(7591):407–409

    Google Scholar 

  • Stern NH (2007) The economics of climate change: the Stern review. Cambridge University Press

  • Stock J, Watson M (1999) Business cycle fluctuations in us macroeconomic time series. In: Taylor JB, Woodford M (eds) Handbook of macroeconomics. 1st edn. chap 01, vol 1, Part A. Elsevier, pp 3–64. http://EconPapers.repec.org/RePEc:eee:macchp:1-01

  • Stock JH, Watson M (2011) Dynamic factor models. Oxford Handbook on Economic Forecasting

  • Stock JH, Watson MW (2006) Forecasting with many predictors. Handbook Econ Forecast 1:515–554

    Google Scholar 

  • Summers LH (2002) Some skeptical observations on real business cycle theory. Macroecon Reader, 389

  • Tesfatsion L (2002) Agent-based computational economics: growing economies from the bottom up. Artif Life 8(1):55–82

    Google Scholar 

  • Timmermann A (2006) Forecast combinations. Handbook Econ Forecast 1:135–196

    Google Scholar 

  • Turrell A (2016) Agent-based models: understanding the economy from the bottom up. Bank Of England Quarterly Bulletin Series 2016Q4, https://ssrn.com/abstract=2898740

  • Turrell A, Sherlock M, Rose S (2015a) Self-consistent inclusion of classical large-angle Coulomb collisions in plasma Monte Carlo simulations. J Comput Phys

  • Turrell A, Sherlock M, Rose S (2015b) Ultrafast collisional ion heating by electrostatic shocks. Nat Commun 6

  • Tversky A, Kahneman D (1975) Judgment under uncertainty: Heuristics and biases. In: Utility, probability, and human decision making. Springer, pp 141–162

  • Wälde K, Woitek U (2004) R&D expenditure in G7 countries and the implications for endogenous fluctuations and growth. Econ Lett 82(1):91–97

    Google Scholar 

  • Watts DJ (2002) A simple model of global cascades on random networks. Proc Natl Acad Sci 99(9):5766–5771

    Google Scholar 

  • Welfe W (2013) Macroeconometric models, vol 47. Springer Science & Business Media

  • Wren-Lewis S (2016a) More on stock-flow consistent models. https://mainlymacro.blogspot.co.uk/2016/09/more-on-stock-flow-consistent-models.html

  • Wren-Lewis S (2016b) Unravelling the new classical counter revolution. Rev Keynesian Econ 4(1):20–35

    Google Scholar 

  • Wright I (2005) The duration of recessions follows an exponential not a power law. Physica Statist Mech Appl 345(3):608–610

    Google Scholar 

  • Yellen J L et al (2016) Macroeconomic research after the crisis: a speech at the elusive ‘great’ recovery: causes and implications for future business cycle dynamics. In: 60th annual economic conference sponsored by the Federal Reserve Bank of Boston. Boston, Massachusetts, October 14, 2016. Tech. rep., United States Federal Reserve

  • Zarnowitz V (1985) Recent work on business cycles in historical perspective: a review of theories and evidence. J Econ Lit 23(2):523–580

    Google Scholar 

Download references

Acknowledgements

We are grateful to attendees of a seminar at the University of Oxford, to an anonymous referee, and to John Barrdear, James Barker, David Bholat, Shiv Chowla, Giovanni Dosi, Jeremy Franklin, Simon Hayes, Sujit Kapadia, Francesca Monti, Mauro Napoletano, Paul Robinson and Andrea Roventini for their help and comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Arthur E. Turrell.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

The views expressed in this paper are solely those of the authors, and do not necessarily represent those of the Bank of England or its policy committees and should not be reported as such. This paper was initially prepared for a special edition of The Oxford Review of Economic Policy. A modified version is reproduced here with an additional section which examines the barriers to the more widespread adoption of macroeconomic agent-based models.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Haldane, A.G., Turrell, A.E. Drawing on different disciplines: macroeconomic agent-based models. J Evol Econ 29, 39–66 (2019). https://doi.org/10.1007/s00191-018-0557-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00191-018-0557-5

Keywords

JEL Classification

Navigation