Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-10T19:58:39.691Z Has data issue: false hasContentIssue false

Coevolution in Economic Systems

Published online by Cambridge University Press:  12 May 2021

Isabel Almudi
Affiliation:
Universidad de Zaragoza
Francisco Fatas-Villafranca
Affiliation:
Universidad de Zaragoza

Summary

Coevolution in economic systems plays a key role in the dynamics of contemporary societies. Coevolution operates when, considering several evolving realms within a socioeconomic system, these realms mutually shape their respective innovation, replication and/or selection processes. The processes that emerge from coevolution should be analyzed as being globally codetermined in dynamic terms. The notion of coevolution appears in the literature on modern innovation economics since the neo-Schumpeterian inception four decades ago. In this Element, these antecedents are drawn on to formally clarify and develop how the coevolution notion can expand the analytical and methodological scope of evolutionary economics, allowing for further unification and advance of evolutionary subfields.
Get access
Type
Element
Information
Online ISBN: 9781108767798
Publisher: Cambridge University Press
Print publication: 10 June 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Acemoglu, D. and Robinson, J. A. (2012). Why Nations Fail: The Origins of Power, Prosperity and Poverty. New York: Crown Publishing Group.Google Scholar
Adner, R. and Kapoor, R. (2010). Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations. Strategic Management Journal, 31(3), 306333.Google Scholar
Aghion, P. and Griffith, R. (2005). Competition and Growth. Cambridge, MA: MIT Press.Google Scholar
Aghion, P. and Howitt, P. (1998). Endogenous Growth Theory. Cambridge, MA: MIT Press.Google Scholar
Agrawal, R. (2018). Built: The Hidden Stories behind Our Structures. London: Bloomsbury Publishing.Google Scholar
Almudi, I. and Fatas-Villafranca, F. (2018). Promotion and co-evolutionary dynamics in contemporary capitalism. Journal of Economic Issues, 52(1), 80102.Google Scholar
Almudi, I., Fatas-Villafranca, F., Fernandez, C., Potts, J. and Vazquez, F. J. (2020). Absorptive capacity in a two-sector neo-Schumpeterian model: a new role for innovation policy. Industrial and Corporate Change, 29(2), 507531.Google Scholar
Almudi, I., Fatas-Villafranca, F. and Izquierdo, L. R. (2012). Innovation, catch-up and leadership in science-based industries. Industrial and Corporate Change, 21(2), 345375.Google Scholar
Almudi, I., Fatas-Villafranca, F. and Izquierdo, L. R. (2013). Industry dynamics, technological regimes and the role of demand. Journal of Evolutionary Economics, 23, 10731098.Google Scholar
Almudi, I., Fatas-Villafranca, F., Izquierdo, L. R. and Potts, J. (2017). The economics of utopia: A co-evolutionary model of ideas, citizenship and socio-political change. Journal of Evolutionary Economics, 27, 629662.Google Scholar
Almudi, I., Fatas-Villafranca, F., Jarne, G. and Sanchez, J. (2020). An evolutionary growth model with banking activity. Metroeconomica, 71(2), 392430.CrossRefGoogle Scholar
Almudi, I., Fatas-Villafranca, F., Potts, J. and Thomas, S. (2018). Absorptive capacity of demand in sports innovation. Economics of Innovation and New Technology, 27(3), 115.Google Scholar
Almudi, I., Fatas-Villafranca, F. and Sanchez, J. (2016). A formal discussion of the Sarewitz-Nelson rules. Economics of Innovation and New Technology, 25, 714730.Google Scholar
Arrow, K. J. (1962a). Economic welfare and the allocation of resources for invention. 609–626. In Nelson, Richard R. (ed.), The Rate and Direction of Inventive Activity. Princeton: Princeton University Press.Google Scholar
Arrow, K. J. (1962b). The economic implications of learning by doing. Review of Economic Studies, 29(1), 155173.Google Scholar
Bloch, H. and Metcalfe, J. S. (2018). Innovation, creative destruction and price theory. Industrial and Corporate Change, 27(1), 113.Google Scholar
Bush, V. (1945). Science the Endless Frontier. Washington, DC: US Government Printing Office.Google Scholar
Bushan, B. (2017). Springer Handbook of Nanotechnology. Berlin: Springer.Google Scholar
Camprubi, L. (2014). Engineers and the Making of the Francoist Regime. Cambridge, MA: MIT Press.Google Scholar
Cantner, U., Savin, I. and Vannuccini, S. (2019). Replicator dynamics in value chains: Explaining some puzzles of market selection. Industrial and Corporate Change, 28(3), 589611.CrossRefGoogle Scholar
Chai, A. and Baum, C. (eds.) (2019). Demand, Complexity and Long-Run Economic Evolution. Cham: Springer Nature.Google Scholar
Ciarli, T., Lorentz, A., Valente, M. and Savona, M. (2019). Structural changes and growth regimes. Journal of Evolutionary Economics, 29(1), 119176.Google Scholar
Cohen, W. M. and Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128152.Google Scholar
Davidson, S., De Filippi, P. and Potts, J. (2018). Blockchains and the economic institutions of capitalism. Journal of Institutional Economics, 14(4), 639658.CrossRefGoogle Scholar
Delli Gatti, D., Fagiolo, G., Gallegati, M., Richiardi, M. and Russo, A. (2018). Agent-Based Models in Economics. New York: Cambridge University Press.Google Scholar
Denzau, A. T. and North, D. C. (2000). Shared mental models: Ideologies and institutions. 23–46. In Lupia, A., McCubbins, M. and Popkin, S. L. (eds.), Elements of Reason. New York. Cambridge University Press.Google Scholar
Dewey, J. (1927). The Public and Its Problems. Athens, OH: Swallow Press.Google Scholar
Dollimore, D. and Hodgson, G. M. (2014). Four essays on economic evolution: An introduction. Journal of Institutional Economics, 24(1), 110.Google Scholar
Dopfer, K. (ed.) (2005). The Evolutionary Foundations of Economics. Cambridge: Cambridge University Press.Google Scholar
Dopfer, K. and Potts, J. (2008). The General Theory of Economic Evolution. London: Routledge.Google Scholar
Dosi, G. and Orsenigo, L. (1988). Coordination and transformation: An overview of structures, behaviours and change in evolutionary environments. In Dosi, G., Freeman, C., Nelson, R. R., Silverberg, G. and Soete, L. (eds.), Technical Change and Economic Theory, 1337. London: Pinter.Google Scholar
Dosi, G., Fagiolo, G., Napoletano, M. and Roventini, A. (2013). Income distribution, credit and fiscal policies in an agent-based Keynesian model. Journal of Economic Dynamics and Control, 37(8), 15981625.CrossRefGoogle Scholar
Dosi, G., Freeman, C., Nelson, R. R., Silverberg, G. and Soete, L. (eds.) (1988). Technical Change and Economic Theory. London: Pinter.Google Scholar
Dosi, G. and Grazzi, M. (2010). On the nature of technologies. Cambridge Journal of Economics, 34(1), 173184.Google Scholar
Dosi, G., Marengo, L. and Fagiolo, G. (2005). Learning in evolutionary environments. In Dopfer, K. (ed.), The Evolutionary Foundations of Economics, 255338. Cambridge: Cambridge University Press.Google Scholar
Dosi, G. and Nelson, R. R. (2010). Technical change and industrial dynamics as an evolutionary processes. In Hall, B. H. and Rosenberg, N. (ed.), Handbook of the Economics of Innovation, 51–127. Amsterdam: Elsevier.Google Scholar
Dosi, G. and Nuvolari, A. (2020). Introduction: Chris Freeman’s History, Coevolution and economic growth. An affectionate reappraisal. Industrial and Corporate Change, 29(4), 10211034.CrossRefGoogle Scholar
Dosi, G., Pereira, M. and Virgillito, M. E. (2017). The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics. Industrial and Corporate Change, 26(2), 187210.Google Scholar
Dosi, G. and Roventini, A. (2019). More is different and complex! The case for agent-based macroeconomics. Journal of Evolutionary Economics, 29(1), 137.Google Scholar
Earl, P. and Potts, J. (2013). The creative instability hypothesis. Journal of Cultural Economics, 37(2), 153173.CrossRefGoogle Scholar
Earl, P. and Potts, J. (2016). The management of creative vision and the economics of creative cycles. Management and Decision Economics, 37(7), 474484.Google Scholar
Fatas-Villafranca, F., Férnández-Márquez, C. M. and Vázquez, F. J. (2019). Consumer social learning and industrial dynamics. Economics of Innovation and New Technology, 28(2), 119141.Google Scholar
Fatas-Villafranca, F., Jarne, G. and Sanchez, J. (2009). Industrial leadership in science-based industries: A co-evolution model. Journal of Economic Behavior and Organization, 72(1), 390407.Google Scholar
Fatas-Villafranca, F., Jarne, G. and Sanchez, J. (2012). Innovation, cycles and growth. Journal of Evolutionary Economics, 22(2), 207233.Google Scholar
Fatas-Villafranca, F., Jarne, G. and Sanchez, J. (2014). Stock and mobility of researchers and industrial leadership. Metroeconomica, 65(1), 95122.CrossRefGoogle Scholar
Fatas-Villafranca, F., Sanchez, J. and Jarne, G. (2008). Modeling the co-evolution of national industries and institutions. Industrial and Corporate Change, 17(1), 65108.CrossRefGoogle Scholar
Fatas-Villafranca, F., Saura, D. and Vazquez, F. J. (2007). Emulation, prevention and social interaction in consumption dynamics. Metroeconomica, 58(4), 582608.Google Scholar
Fatas-Villafranca, F., Saura, D. and Vazquez, F. J. (2009). Diversity, persistence and chaos in consumption patterns. Journal of Bioeconomics, 11(1), 4363.Google Scholar
Fatas-Villafranca, F., Saura, D. and Vazquez, F. J. (2011). A dynamic model of public opinion formation. Journal of Public Economic Theory, 13(3), 417441.Google Scholar
Fernández-Márquez, C. M., Fatas-Villafranca, F. and Vázquez, F. J. (2017a). Endogenous demand and demanding consumers: A computational approach. Computational Economics, 49(2), 307323.CrossRefGoogle Scholar
Fernández-Márquez, C. M., Fatas-Villafranca, F. and Vázquez, F. J. (2017b). A computational consumer-driven market model: statistical properties and the underlying industry dynamics. Computational and Mathematical Organization Theory, 23(3), 319346.Google Scholar
Foray, D., David, P. and Hall, B. (2009). Smart specialization: The concept. In Knowledge for Growth. Brussels: European Commission.Google Scholar
Foster, J. and Metcalfe, J. S. (eds.) (2001). Frontiers of Evolutionary Economics. Cheltenham: Edward Elgar.Google Scholar
Freeman, C. (1987). Technology Policy and Economic Performance: Lessons from Japan. London: Pinter.Google Scholar
Freeman, C. (1988). Introduction. In Dosi, G., Freeman, C., Nelson, R. R., Silverberg, G. and Soete, L. (eds.), Technical Change and Economic Theory, 18. London: Pinter.Google Scholar
Gilboa, I. (ed.) (2004). Uncertainty in Economic Theory. London: Routledge.Google Scholar
Gordon, R. (2012). Is US economic growth over? Faltering innovation confronts the six headwinds. NBER Working Paper No. 18315.Google Scholar
Haldane, A. G. and Turrell, A. E. (2019). Drawing in different disciplines: Macroeconomic agent-based models. Journal of Evolutionary Economics, 29(1), 3966.Google Scholar
Hodgson, G. M. (2015). Conceptualizing Capitalism. Chicago. University of Chicago Press.Google Scholar
Hodgson, G. M. (2019). Evolutionary Economics: Its Nature and Future. Elements in Evolutionary Economics. Cambridge: Cambridge University Press.Google Scholar
Hodgson, G. M. and Knudsen, T. (2010). Darwin’s Conjecture. Chicago: University of Chicago Press.Google Scholar
Hofbauer, J. and Sigmund, K. (1998). Evolutionary Games and Population Dynamics. Cambridge: Cambridge University Press.Google Scholar
Jacobides, M. G., Cennamo, C. and Gawer, A. (2018). Toward a theory of ecosystems. Strategic Management Journal, 39(8), 22552276.Google Scholar
Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. American Economic Review, 93, 14491475.CrossRefGoogle Scholar
Lippmann, W. (1922). Public Opinion. New York: Simon & Schuster.Google Scholar
Lipsey, R. G. (2018). A Reconsideration of the Theory of Non-linear Scale Effects. Elements in Evolutionary Economics. Cambridge: Cambridge University Press.Google Scholar
Lundvall, B. A. (1992). National Systems of Innovation: Toward a Theory of Innovation and Interactive Learning. London: Pinter.Google Scholar
Luppia, A., McCubbins, M. and Popkin, S. (eds.) (2000). Elements of Reason: Cognition, Choice and the Bounds of Rationality. New York: Cambridge University Press.Google Scholar
Malerba, F., Edquist, C. and Steinmueller, E. (eds.) (2004). Sectoral Systems of Innovation. New York: Cambridge University Press.Google Scholar
Malerba, F., Nelson, R. R., Orsenigo, L. and Winter, S. G. (2016). Innovation and the Evolution of Industries: History-Friendly Models. Cambridge: Cambridge University Press.Google Scholar
Markey-Towler, B. (2016). Law of the jungle: Firm survival and price dynamics in evolutionary markets. Journal of Evolutionary Economics, 26(3), 655696.Google Scholar
Markey-Towler, B. (2019). The competition and evolution of ideas in the market sphere: A new foundations for institutional theory. Journal of Institutional Economics, 15(1), 2748.CrossRefGoogle Scholar
Martin, S. and Scott, J. (2000). The nature of innovation market failure and the design of public support for private innovation. Research Policy, 29(4), 437447.Google Scholar
Metcalfe, J. S. (1998). Evolutionary Economics and Creative Destruction. London: Routledge.Google Scholar
Metcalfe, J. S. (2010). Technology and economic theory. Cambridge Journal of Economics, 34(1), 153171.Google Scholar
Metcalfe, J. S., Foster, J. and Ramlogan, R. (2006). Adaptive economic growth. Cambridge Journal of Economics, 30(1), 732.Google Scholar
Montgomery, S. and Chirot, D. (2015). The Shape of the New. Princeton: Princeton University Press.Google Scholar
Muñoz, F. F., Encinar, M. I. and Cañibano, C. (2011). On the role of intentionality in evolutionary economic change. Structural Change and Economic Dynamics, 22(3), 193203.Google Scholar
Murmann, J. P. (2003). Knowledge and Competitive Advantage: The Coevolution of Firms, Technology and National Institutions. New York: Cambridge University Press.Google Scholar
Nelson, R. R. (1959). The simple economics of basic scientific research. Journal of Political Economy, 77, 297306.Google Scholar
Nelson, R. R. (ed.) (1962). The Rate and Direction of Inventive Activity. Princeton: Princeton University Press.Google Scholar
Nelson, R. R. (1982). The role of knowledge in R&D efficiency. Quarterly Journal of Economics, 97(3), 453470.Google Scholar
Nelson, R. R. (ed.) (1993). National Innovation Systems. Oxford: Oxford University Press.CrossRefGoogle Scholar
Nelson, R. R. (1995). Recent evolutionary theorizing about economic change. Journal of Economic Literature, 33, 4890.Google Scholar
Nelson, R. R. (1988). Institutions supporting technical change in the United States. In Dosi, G., Freeman, C., Nelson, R. R., Silverberg, G. and Soete, L. (eds.), Technical Change and Economic Theory, 312–239. London: Pinter.Google Scholar
Nelson, R. R. (2008). Economic development from the perspective of evolutionary economic theory. Oxford Development Studies, 36(1), 921.CrossRefGoogle Scholar
Nelson, R. R. (2012). Some features of research by economists foreshadowed by “The Rate and Direction of Inventive Activity.” In Lerner, J. and Stern, S. (eds.), The Rate and Direction of Inventive Activity Revisited, 3542. Chicago: University of Chicago Press.Google Scholar
Nelson, R. R. (2018). Modern Evolutionary Economics: An Overview. New York: Cambridge University Press.Google Scholar
Nelson, R. R. and Sampat, B. (2001). Making sense of institutions as a factor shaping economic performance. Journal of Economic Behavior and Organization, 44(1), 3154.Google Scholar
Nelson, R. R. and Winter, S. G. (1982). An Evolutionary Theory of Economic Change. Cambridge, MA: Harvard University Press.Google Scholar
North, D. C. (2005). Understanding the Process of Economic Change. Princeton: Princeton University Press.Google Scholar
Novak, M. (2018). Inequality: An Entangled Political Economy Perspective. London: Palgrave Macmillan.Google Scholar
Nowak, M. (2006). Evolutionary Dynamics. Cambridge, MA: Belknap Press.CrossRefGoogle Scholar
Page, B. and Shapiro, R. Y. (1992). The Rational Public. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Potts, J. (2000). The New Evolutionary Microeconomics. Cheltenham: Edward Elgar.Google Scholar
Pretel, D. and Camprubi, L. (eds.) (2018). Technology and Globalization. Palgrave Studies in Economic History. London: Macmillan.Google Scholar
Pyka, A. (2017). Dedicated innovation systems to support the transformation towards sustainability. Journal of Open Innovation: Technology, Market, Complexity, 3(1), 27.Google Scholar
Pyrgidis, C. N. (2018). Railway Transportation Systems: Design, Construction and Operation. London: Taylor & Francis.Google Scholar
Rodrik, D. (2004). Industrial policy for the 21st century. Harvard University Working Paper No. RWP04-047.Google Scholar
Sandholm, W. (2010). Population Games and Evolutionary Dynamics. Cambridge, MA: MIT Press.Google Scholar
Sarewitz, D. and Nelson, R. R. (2008a). Three rules for technological fixes. Nature, 456, 871872.CrossRefGoogle ScholarPubMed
Sarewitz, D. and Nelson, R. R. (2008b). Progress in know-how: Its origins and limits. Innovations: Technology, Governance, Globalization, 3(1), 101117.Google Scholar
Saviotti, P. P. and Pyka, A. (2004). Economic development by the creation of new sectors. Journal of Evolutionary Economics, 14(1), 135.Google Scholar
Saviotti, P. P. and Pyka, A. (2013). The coevolution of innovation, demand and growth. Economics of Innovation and New Technology, 22(5), 461482.Google Scholar
Schumpeter, J. A. (1942). Capitalism, Socialism and Democracy. New York: Harper & Row.Google Scholar
Shapiro, R. Y. and Jacobs, L. R. (1989). The relationship between public opinion and public policy. In Long, S. and (eds.), Political Behavior Annual, 1–50 . Boulder, CO: Westview.Google Scholar
Silverberg, G. and Soete, L. (eds.) (1994). The Economics of Growth and Technical Change. Aldershot: Edward Elgar.Google Scholar
Simon, H. (1955). A behavioural model of rational choice. Quarterly Journal of Economics, 69(1), 99118.Google Scholar
Simon, H. (1957). Models of Man. New York: Wiley.Google Scholar
Simon, H. (1991). Bounded rationality and organizational learning. Organization Science, 2(1), 125134.CrossRefGoogle Scholar
Stachurski, J. (2016). A Primer in Econometric Theory. Cambridge, MA: MIT Press.Google Scholar
Stimson, J. A. (1991). Public Opinion in America: Moods, Cycles and Swings. Boulder, CO: Westview.Google Scholar
Trajtenberg, M. (2012). Can the Nelson-Arrow paradigm still be the beacon of innovation policy? In Lerner, J. and Stern, S. (eds.), The Rate and Direction of Inventive Activity Revisited, 679684. Chicago: University of Chicago Press.Google Scholar
Trevelyan, J. (1992). Robots for Shearing Sheep: Shear Magic. Oxford: Oxford University Press.Google Scholar
Urmetzer, S., Schlaile, M., Bogner, K., Muller, M. and Pyka, A. (2018). Exploring the dedicated knowledge base of a transformation towards a sustainable bioeconomy. Sustainability, 10(6), 1694.Google Scholar
Van den Bergh, J., Savin, I. and Drews, S. (2019). Evolution of opinions in the growth-vs-environment debate: Extended replicator dynamics. Futures, 109, 84100.Google Scholar
Vega-Redondo, F. (2007). Complex Social Networks. Cambridge: Cambridge University Press.Google Scholar
Weibull, J. W. (1995). Evolutionary Game Theory. Cambridge, MA: MIT Press.Google Scholar
Weidlich, W. (2006). Sociodynamics: A Systematic Approach to Mathematical Modeling in the Social Sciences. Mineola, NY: Dover Publications.Google Scholar
Wilson, D. S. and Kirman, A. (eds.) (2016). Complexity and Evolution. Cambridge, MA: MIT Press.Google Scholar
Winter, S. G. (1984). Schumpeterian competition in alternative technological regimes. Journal of Economic Behavior and Organization, 5(3), 287320.Google Scholar
Winter, S. G. (2014). The future of evolutionary economics: Can we break out from the beach headed? Journal of Institutional Economics, 10(4), 613644.Google Scholar
Witt, U. (2009). Novelty and the bounds of unknowledge in economics. Journal of Economic Methodology, 16(4), 361375.Google Scholar
Witt, U. (2014). The future of evolutionary economics: Why the modalities of explanation matter? Journal of Institutional Economics, 10(4), 645664.Google Scholar
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(1), 333353.Google Scholar

Save element to Kindle

To save this element to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Coevolution in Economic Systems
Available formats
×

Save element to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Coevolution in Economic Systems
Available formats
×

Save element to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Coevolution in Economic Systems
Available formats
×