Abstract
The economy as a whole and most of its constituent parts, like markets, government institutions, firms, or households, are inherently complex conceptual constructions. Micro-level diversity, decentralized interaction, self-organization, adaptation and learning, emergence, and evolution, are some of the fundamental features that the above entities share and that allow to classify them as being complex entities. In a complex economic system, existing structures of interaction are in constant mutation as individual agents contact and influence one another and, by doing so, reshape the macro environment in which socio-economic relations unfold. Notwithstanding the observed pervasiveness of complexity in economics, there are a few areas of economic thought where the discussion on the theme has gained an exceptional relevance. In this article, six of such areas are identified and their complex nature is highlighted and scrutinized. These pertain to: (i) Knowledge interactions and technological innovation; (ii) Corporate design and organizational learning; (iii) Public policies directed at market regulation; (iv) Banking and financial markets; (v) Environmental economics, sustainability, and climate change; and (vi) income inequality.
Similar content being viewed by others
References
Hodgson G M, Come back Marshall, all is forgiven? Complexity, evolution, mathematics and Marshallian exceptionalism, Eur. J. Hist. Econ. Thou., 2013, 20: 957–981.
Caldari K, Marshall and complexity: A necessary balance between process and order, Cambridge J. Econ., 2015, 39: 1071–1085.
Colander D and Kupers R, Complexity and the Art of Public Policy: Solving Society’s Problems from the Bottom Up, Princeton University Press, Princeton and Oxford, 2014.
Heise A, Whither economic complexity? A new heterodox economic paradigm or just another variation within the mainstream?, Int. J. Plural. Econ. Edu., 2017, 8: 115–129.
Faggini M and Parziale A, More than 20 years of chaos in economics, Mind & Society, 2016, 15: 53–69.
Odum E P and Barrett G W, Fundamentals of Ecology, 5th Edition, Thomson, Brooks/Cole, Belmont CA, 2005.
Allen P, Complexity, uncertainty and innovation, Econ. Innov. New Tech., 2013, 22: 702–725.
Bargigli L and Tedeschi G, Interaction in agent-based economics: A survey on the network approach, Physica A, 2014, 399: 1–15.
Cilliers P, Biggs H C, Blignaut S, et al., Complexity, modelling, and natural resource management, Ecol. Soc., 2013, 18(3): article 1.
Bruno B, Faggini M, and Parziali A, Complexity modelling in economics: The state of the art, Economic Thought, 2016, 5: 29–43.
Foster J and Metcalfe J S, Economic emergence: An evolutionary economic perspective, J. Econ. Behav. Organ., 2012, 82: 420–432.
Gallegati M and Kirman A, Reconstructing economics: Agent based models and complexity, Complexity Econ., 2012, 1: 5–31.
Rosser J B, Emergence and complexity in Austrian economics, J. Econ. Behav. Organ., 2012, 81: 122–128.
Kao Y F and Velupillai K V, Behavioural economics: Classical and modern, Eur. J. Hist. Econ. Thou., 2015, 22: 236–271.
Tesfastsion L S, Agent-based computational economics: Modeling economies as complex adaptive systems, Inf. Sci., 2003, 149: 263–269.
Frenken K, Technological innovation and complexity theory, Econ. Innov. New Tech., 2006, 15: 137–155.
Antonelli C, The economic complexity of technological change: Knowledge interaction and path dependence, Handbook on the Economic Complexity of Technological Change, ch.1: 3–59, Ed. by Antonelli C, Edward Elgar, Cheltenham, 2011.
Krafft J and Quatraro F, The dynamics of technological knowledge: From linearity to recombination, Handbook on the Economic Complexity of Technological Change, ch.7: 181–200, Ed. by Antonelli C, Edward Elgar, Cheltenham, 2011.
Antonelli C and Scellato G, Complexity and technological change: Knowledge interactions and firm level total factor productivity, J. Evol. Econ., 2013, 23: 77–96.
Maggitti P G, Smith K G, and Katila R, The complex search process of invention, Res. Policy, 2013, 42: 90–100.
Lane D A, Complexity and innovation dynamics, in Handbook on the Economic Complexity of Technological Change, ch.2: 63–80, Ed. by Antonelli C, Edward Elgar, Cheltenham, 2011.
Lane D A and Maxfield R, Ontological uncertainty and innovation, J. Evol. Econ., 2005, 15: 3–50.
Colombelli A and von Tunzelmann N, The persistence of innovation and path-dependence, Handbook on the Economic Complexity of Technological Change, ch.4: 105–119, Ed. by Antonelli C, Edward Elgar, Cheltenham, 2011.
Barabási A L and Albert R, Emergence of scaling in random networks, Science, 1999, 286: 509–512.
Cantner U and Graf H, Innovation networks: Formation, performance and dynamics, Handbook on the Economic Complexity of Technological Change, ch.15: 366–394, Ed. by Antonelli C, Edward Elgar, Cheltenham, 2011.
Ormerod P, Rosewell B, and Wiltshire G, Network models of innovation process and policy implications, Handbook on the Economic Complexity of Technological Change, ch.19: 492–532 Ed. by Antonelli C, Edward Elgar, Cheltenham, 2011.
Saviotti P P, Knowledge, complexity and networks, Handbook on the Economic Complexity of Technological Change, ch.6: 141–180, Ed. by Antonelli C, Edward Elgar, Cheltenham, 2011.
Chiva R, Ghauri P, and Alegre J, Organizational learning, innovation and internationalization: A complex system model, Brit. J. Manage., 2014, 25: 687–705.
Dosi G and Marengo L, The dynamics of organizational structures and performances under diverging distributions of knowledge and different power structures, J. I. Econ., 2015, 11: 535–559.
Dosi G and Virgillito M E, In order to stand up you must keep cycling: Change and coordination in complex evolving economies, Struct. Change Econ. D., 2017, in press.
Chang M H and Harrington Jr J E, Agent-based models of organizations, Handbook of Computational Economics, Eds. by Tesfastsion L and Judd K L, 2006, 2: 1273–1337.
Anderson P, Complexity theory and organization science, Organ. Sci., 1999, 10: 216–232.
Dosi G, Faillo M, Manara V C, et al., The formalization of organizational capabilities and learning: Results and challenges, LEM Papers Series 2017/08, Sant’Anna School of Advanced Studies, Pisa, Italy, 2017.
Schneider M and Somers M, Organizations as complex adaptive systems: Implications of complexity theory for leadership research, Leadership Quart., 2006, 17: 351–365.
Uhl-Bion M, Marion R, and McKelvey B, Comlpexity leadership theory: Shifting leadership from the industrial age to the knowledge era, Leadership Quart., 2007, 18: 298–318.
Dosi G, Marengo L, and Nuvolari A, Institutions are neither autistic maximizers nor flocks of birds: Self-organization, power, and learning in human organizations, LEM Papers Series 2016/38, Sant’Anna School of Advanced Studies, Pisa, Italy, 2016.
David P, Path dependence and predictability in dynamic systems with local externalities: A paradigm for historical economics, Technology and the Wealth of Nations, Eds. by Foray D and Freeman C, Pinter, London, 1992, 208–231.
Ioannides Y M, Complexity and organizational architecture, Math. Soc. Sci., 2012, 64: 193–202.
Elsner W, Hocker G, and Schwardt H, Simplistic vs complex organizations: Markets, hierarchies, and networks in an organizational triangle — A simple heuristic to analyze real-world organizational forms, J. Econ. Issues, 2010, 44: 1–30.
Durlauf S N, Complexity, economics and public policy, Polit., Philos. Econ., 2012, 11: 45–75.
Durlauf S N, Complexity and empirical economics, Econ. J., 2005, 115: 225–243.
Elsner W, Policy and state in complexity economics, A Modern Guide to State Intervention, Eds. by Karagiannis N and King J E, Edward Elgar Publishing, Cheltenham, 2019, 13–48.
Velupillai K V, The impossibility of an effective theory of policy in a complex economy, Complexity Hints for Economic Policy, Eds. by Salzano M and Colander D, Springer, Milan, 2007, 273–290.
Kirman A, Complexity and economic policy: A paradigm shift or a change in perspective? A review essay on David Colander and Roland Kupers’s complexity and the art of public policy, J. Econ. Lit., 2016, 54: 534–572.
Dawid H, Gemkow S, Harting P, et al., Labor market integration policies and the convergence of regions: The role of skills and technology diffusion, J. Evol. Econ., 2012, 22: 543–562.
Dosi G, Fagiolo G, Napoletano M, et al., Income distribution, credit and fiscal policies in an agent-based Keynesian model, J. Econ. Dyn. Control, 2013, 37: 1598–1625.
Furtado B A and Eberhardt I D R, A simple agent-based spatial model of the economy: Tools for policy, J. Artif. Societies Soc. Simul., 2016, 19(4).
Tabak B M, Cajueiro D O, and Serra T R, Topological properties of bank networks: The case of Brazil, Int. J. Mod. Phys. C, 2009, 20: 1121–1143.
Grilli R, Tedeschi G, and Gallegati M, Markets connectivity and financial contagion, J. Econ. Interact. Coor., 2015, 10: 287–304.
Russo A, Riccetti L, and Gallegati M, Increasing inequality, consumer credit and financial fragility in an agent based macroeconomic model, J. Evol. Econ., 2016, 26: 25–47.
Kenett D and Havlin S, Network science: A useful tool in economics and finance, Mind & Society, 2015, 14: 155–167.
Cetorelli N and Goldberg L S, Organizational complexity and balance sheet management in global banks, NBER Working Paper, 22169, 2016.
Kitt R, Economic decision making: Application of the theory of complex systems, Chaos Theory in Politics, Eds. by Banerjee S, Ercetin S S, and Tekin A, Springer, Amsterdam, 2014, 51–73.
Hommes C H, Interacting agents in finance, The New Palgrave Dictionary of Economics, Eds. by Durlauf S N and Blume L E, 2nd Edition, Palgrave MacMillan, Basingstoke, 2006, 4: 402–406.
Gaffeo E and Tamborini R, If the financial system is complex, how can we regulate it?, Int. J. Polit. Eco., 2011, 40: 79–97.
Cruz J and Lind P, The dynamics of financial stability in complex networks, Eur. Phys. J. B, 2012, 85: 1–9.
Giocoli N, Network efficiency and the banking system, Int. Rev. Econ., 2014, 61: 203–218.
Ramanauskas T, Agent-based financial modelling: A promosing alternative to the standard representative agent approach, Bank of Lithuania Working Paper, 2009, 3.
Bookstaber R, Using agent-based models for analyzing threats to financial stability, US Department of the Treasury, Working Paper, 2012, 12–03.
Gubareva M and Gomes O, On the edge of climate change: In a search of an adequate agent-based methodology to model environmental dynamics, Eds. by Sequeira T and Reis L, Climate Change and Global Development, Contributions to Economics, 2019, 37–57. https://doi.org/10.1007/978-3-030-02662-2.3.
Balint T, Lamperti F, Mandel A, et al., Complexity and the economics of climate change: A survey and a look forward, Ecol. Econ., 2017, 138: 252–265.
Farmer J D, Hepburn C, Mealy P, et al., A third wave in the economics of climate change, Environ. Res. Econ., 2015, 62: 329–357.
Farmer J D and Hepburn C, Less precision, more truth: uncertainty in climate economics and macroprudential policy, Bank of England Interdisciplinary Workshop on the Role of Uncertainty in Central Bank Policy, 2014.
Foxon T J, Kohler J, Michie J, et al., Towards a new complexity economics for sustainability, Cambridge J. Econ., 2013, 37: 187–208.
Mercure J F, Pollitt H, Bassi A M, et al., Modelling complex systems of heterogeneous agents to better design sustainability transitions policy, Global Environ. Chang., 2016, 37: 102–115.
Berger T and Troost C, Agent-based modelling of climate adaptation and mitigation options in agriculture, J. Agr. Econ., 2014, 65: 323–348.
Hassani-Mahmooei B and Parris B W, Why might climate change not cause conflict? An agent-based computational response, MPRA Paper, 2012, 44918.
Hassani-Mahmooei B and Parris B W, Resource scarcity, effort allocation and environmental security: An agent-based theoretical approach, Econ. Model., 2013, 30: 183–192.
Markey-Towler B and Foster J, Understanding the causes of income inequality in complex economic systems, University of Queensland Discussion Paper, 2013, 478.
Desiderio S and Chen S, Why the rich become richer: Insights from an agent-based model, Int. J. Comput. Econ. Econometrics, 2016, 6: 258–275.
Cardaci A and Saraceno F, Inequality, financialisation and economic crises: An agent-based model, Sciences-Po Publications, 2015, 2015–27.
Palagi E, Napoletano M, Roventini A, et al., Inequality, redistributive policies and multiplier dynamics in an agent-based model with credit rationing, Sciences Po publications, 2017, 2017–06.
Caiani A, Russo A, and Gallegati M, Does inequality hamper innovation and growth? An ABSFC analysis, J. Evol. Econ., 2019, 29: 177–228.
Dosi G, Pereira, M C, Roventini A, et al., The effects of labour market reforms upon unemployment and income inequalities: An agent based model, Socio-Econ. Rev., 2018, 16: 687–720.
Dawid H, Harting P, and Neugart M, Cohesion policy and inequality dynamics: Insights from a heterogeneous agents macroeconomic model, J. Econ. Behav. Organ., 2018, 150: 220–255.
Hartmann D, Guevara M R, Jara-Figueroa C, et al., Linking economic complexity, institutions and income inequality, World Development, 2015, 93: 75–93.
Sbardella A, Pugliese E, and Pietronero L, Economic development and inequality: A complex system analysis, PLoS ONE, 2017, 12(9): e0182774.
Author information
Authors and Affiliations
Corresponding author
Additional information
This research was supported by the Portuguese National Funding Agency for Science, Research and Technology (FCT), under the Project UID/SOC/04521/2020, and by the Instituto Politécnico de Lisboa as a part of the IPL/2019/MacroVirtu/ISCAL and IPL/2020/MacroRates/ISCAL Projects.
This paper was recommended for publication by Editor TANG Xijin.
Rights and permissions
About this article
Cite this article
Gomes, O., Gubareva, M. Complex Systems in Economics and Where to Find Them. J Syst Sci Complex 34, 314–338 (2021). https://doi.org/10.1007/s11424-020-9149-1
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11424-020-9149-1