IDEAS home Printed from https://ideas.repec.org/p/unm/unumer/2022023.html
   My bibliography  Save this paper

Complexity research in economics: past, present and future

Author

Listed:
  • Nomaler, Önder

    (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn)

  • Verspagen, Bart

    (RS: GSBE MGSoG, RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn, RS: UNU-MERIT Theme 1)

Abstract

In this paper, we provide a brief overview of the field of complexity research in economics, and discuss directions of research that we consider to be promising in terms of solving open issues. We start the survey of the field with the research that emerged in the 1990s, when under the influence of earlier developments in the natural sciences (e.g., thermodynamics and chaos theory), the term complexity became in fashion to refer to theoretical ideas about how "ordered" patterns at an aggregate level can emerge from interaction between heterogenous agents at the microeconomic level. This gave rise to the notion of self-organization in dissipative systems, or "order at the edge of chaos" to describe economic dynamics. Because disequilibrium plays a large role in these theories, these ideas worked very well in combination with a Schumpeterian view of the economy, which also stresses disequilibrium. In the current literature, economic complexity is mainly used to refer to the application of quantitative methods based on networks that can be created on the basis of very fine-grained data on production or trade. These data are used to produce aggregate measures of development, as well as to describe how production structures may evolve over time. This literature developed largely disconnected to the earlier complexity literature. The new economic complexity paradigm is largely void of economic theory, and instead aims to provide a set of data reduction techniques that are used to characterize development. With regard to outlook for complexity research in (Schumpeterian) economics, on the one hand, we feel that the potential for analyzing the economy as a dissipative, out-of-equilibrium system has not been fully exploited yet. In particular, we propose that - in line with the field of "Big History" (which aims to describe and analyze a coarse history of the universe since the Big Bang) - there is work to be done on the larger issues in economics, in particular climate change and sustainability.

Suggested Citation

  • Nomaler, Önder & Verspagen, Bart, 2022. "Complexity research in economics: past, present and future," MERIT Working Papers 2022-023, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    • Handle: RePEc:unm:unumer:2022023
    as

    Download full text from publisher

    File URL: https://cris.maastrichtuniversity.nl/ws/files/106569199/wp2022_023.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    3. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
    4. Markus C. Becker & Thorbjørn Knudsen, 2002. "Schumpeter 1911: Farsighted Visions on Economic Development," American Journal of Economics and Sociology, Wiley Blackwell, vol. 61(2), pages 387-403, April.
    5. Alain Alcouffe & Thomas Kuhn, 2004. "Schumpeterian endogenous growth theory and evolutionary economics," Journal of Evolutionary Economics, Springer, vol. 14(2), pages 223-236, June.
    6. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    7. Koen Frenken, 2006. "Technological innovation and complexity theory," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 15(2), pages 137-155.
    8. Horst Hanusch & Andreas Pyka (ed.), 2007. "Elgar Companion to Neo-Schumpeterian Economics," Books, Edward Elgar Publishing, number 2973.
    9. Cesar A. Hidalgo & Ricardo Hausmann, 2009. "The Building Blocks of Economic Complexity," CID Working Papers 186, Center for International Development at Harvard University.
    10. Koen Frenken & Alessandro Nuvolari, 2004. "The early development of the steam engine: an evolutionary interpretation using complexity theory," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 13(2), pages 419-450, April.
    11. Silverberg, Gerald & Verspagen, Bart, 2005. "A percolation model of innovation in complex technology spaces," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 225-244, January.
    12. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    13. Kemp-Benedict, Eric, 2014. "An interpretation and critique of the Method of Reflections," MPRA Paper 60705, University Library of Munich, Germany.
    14. Gerald Silverberg & Giovanni Dosi & Luigi Orsenigo, 2000. "Innovation, Diversity and Diffusion: A Self-Organisation Model," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 14, pages 410-432, Edward Elgar Publishing.
    15. Daniel A. Levinthal, 1997. "Adaptation on Rugged Landscapes," Management Science, INFORMS, vol. 43(7), pages 934-950, July.
    16. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-371, May.
    17. Fagerberg, Jan & Srholec, Martin & Verspagen, Bart, 2010. "Innovation and Economic Development," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 833-872, Elsevier.
    18. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    19. Koen Frenken & Frank Van Oort & Thijs Verburg, 2007. "Related Variety, Unrelated Variety and Regional Economic Growth," Regional Studies, Taylor & Francis Journals, vol. 41(5), pages 685-697.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Silvia Rocchetta & Martina Iori & Andrea Mina & Robert Gillanders, 2023. "Technological diversification and the growth of regions in the short and long run," LEM Papers Series 2023/46, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pier-Paolo Saviotti & Andreas Pyka¤ & Bogang Jun, 2020. "Diversification, structural change, and economic development," Journal of Evolutionary Economics, Springer, vol. 30(5), pages 1301-1335, November.
    2. Dosi, Giovanni & Nelson, Richard R., 2010. "Technical Change and Industrial Dynamics as Evolutionary Processes," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 51-127, Elsevier.
    3. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    4. Dosi, Giovanni & Roventini, Andrea & Russo, Emanuele, 2019. "Endogenous growth and global divergence in a multi-country agent-based model," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 101-129.
    5. Aistleitner, Matthias & Gräbner, Claudius & Hornykewycz, Anna, 2021. "Theory and empirics of capability accumulation: Implications for macroeconomic modeling," Research Policy, Elsevier, vol. 50(6).
    6. Giovanni Dosi & Andrea Roventini, 2024. "Evolutionary Growth Theory," LEM Papers Series 2024/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Cristiano Antonelli, 2011. "The Economic Complexity of Technological Change: Knowledge Interaction and Path Dependence," Chapters, in: Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, chapter 1, Edward Elgar Publishing.
    8. Agnieszka Lipieta & Elżbieta Pliś, 2022. "Diversity and mechanisms of economic evolution," Journal of Evolutionary Economics, Springer, vol. 32(4), pages 1265-1286, September.
    9. Voxi Heinrich Amavilah & Antonio Rodríguez Andrés, 2024. "Knowledge Economy and the Economic Performance of African Countries: A Seemingly Unrelated and Recursive Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 110-143, March.
    10. Hidalgo, César A., 2023. "The policy implications of economic complexity," Research Policy, Elsevier, vol. 52(9).
    11. Stanislao Gualdi & Antoine Mandel, 2019. "Endogenous growth in production networks," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 91-117, March.
    12. repec:spo:wpmain:info:hdl:2441/46k9rkvut99i7qnn4vqm25t53b is not listed on IDEAS
    13. 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.
    14. Mariane Santos Françoso & Ron Boschma & Nicholas Vonortas, 2024. "Regional diversification in Brazil: The role of relatedness and complexity," Growth and Change, Wiley Blackwell, vol. 55(1), March.
    15. Heinrich, Torsten, 2015. "Growth Cycles, Network Effects, and Intersectoral Dependence: An Agent-Based Model and Simulation Analysis," MPRA Paper 79575, University Library of Munich, Germany, revised 08 Jun 2017.
    16. Andreas Reinstaller, 2014. "Technologiegeber Österreich. Österreichs Wettbewerbsfähigkeit in Schlüsseltechnologien und Enwicklungspotentiale als Technologiegeber," WIFO Studies, WIFO, number 47444, April.
    17. Giovanni Dosi & Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2012. "Economic policies with endogenous innovation and Keynesian demand management," Chapters, in: Robert M. Solow & Jean-Philippe Touffut (ed.), What’s Right with Macroeconomics?, chapter 5, pages 110-148, Edward Elgar Publishing.
    18. repec:spo:wpmain:info:hdl:2441/32ctbi8fbq8j5aom2j69qam6tf is not listed on IDEAS
    19. Ludovic Dibiaggio & Benjamin Montmartin & Lionel Nesta, 2018. "Regional Alignment and Productivity Growth," GREDEG Working Papers 2018-18, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    20. Fulvio Castellacci, 2007. "Evolutionary And New Growth Theories. Are They Converging?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(3), pages 585-627, July.
    21. Nicolas Petit & Thibault Schrepel, 2023. "Complexity-minded antitrust," Journal of Evolutionary Economics, Springer, vol. 33(2), pages 541-570, April.
    22. Antonelli, Cristiano & Crespi, Francesco & Quatraro, Francesco, 2022. "Knowledge complexity and the mechanisms of knowledge generation and exploitation: The European evidence," Research Policy, Elsevier, vol. 51(8).

    More about this item

    JEL classification:

    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:unm:unumer:2022023. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ad Notten (email available below). General contact details of provider: https://edirc.repec.org/data/meritnl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.