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Endogenous Innovation

Cristiano Antonelli
Edward Elgar Publishing: Cheltenham, 2017

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Reviewed by Paola D'Orazio
Ruhr University Bochum

Cover of book In this book, Antonelli presents a comprehensive framework for studying and analysing the process of endogenous innovation, and in particular economics of knowledge and technological change, in the light of the complex adaptive systems approach (Holland, 1988).

In the last decades, many researchers have started to adopt the complexity framework in the economics field (D’Orazio, 2017), and many have started to use it to conduct research in innovation dynamics (Nelson and Winter, 2002; Frenken, 2006; Foster, 2005; Fontana, 2014, among others). Antonelli largely contributed to this strand of research in the past ten years, starting from Antonelli, 2009 (For further investigation of the author’s contributions, I refer the interested reader to the references cited in the book).

The book starts with a presentation of the Schumpeterian contribution to the understanding of the role of innovation in the economic dynamics and growth, and defines innovation as an emergent property of the economic system. The introductory chapter is particularly important in that it stresses the difference and limitations of the two main approaches available in the economic literature to study innovation, namely the new growth theory and the evolutionary approach. After the assessment of the pros and cons of each approach, the author suggests that the Marshallian legacy can be used as the theoretical foundation over which to build a more comprehensive Schumpeterian approach to innovation.

The following sections draw upon the theoretical underpinnings discussed in the first part of the book and present the link between the Schumpeterian approach and evolutionary complexity. In particular, in Section 3, the author sustains that the “Schumpeterian legacy accommodates the basic tools of complexity economics: feedback, emergence, organized complexity and knowledge connectivity, endogenous variety and path dependence” (p. 51).

In the central sections of the book, Antonelli focuses on the new frontiers in the economics of knowledge. The author offers an introduction to the historical evolution of the field, as well as a detailed discussion about the implications of the appropriability trade-off and the role of pecuniary knowledge externalities. In doing so, he provides also a simplified theoretical framework with which to carry out the analysis and understand the role of a knowledge generation function. By stressing the differences with the new growth theory, the central part of the book emphasizes the importance of the environment heterogeneity and the notion that innovation is “a form of creative reaction supported and actually made possible by the actual availability of internal and external knowledge, as determined by the knowledge governance mechanism that copes with the structural conditions of the system” (p. 138). Furthermore, it is highlighted that “[t]he search for external knowledge [...] is a contingent process that takes place only when firms are in out-of-equilibrium conditions” (p. 139). Showing that knowledge is an intrinsic system character and that innovation is an emerging system property, which can actually take place when the economy is out-of-equilibrium (Arthur, 2006), the author calls the attention to the link with the “complexity view” to model innovation dynamics. By pointing out these features, the content of the book relates to research on the use of the agent-based approach to study innovation and technological change that has been blossoming in the past decades (see Lane (1993a,b) for an introduction and Dawid (2006) for a review).

Finally, in the last part of the book, the author presents a simple analytical model of Schumpeterian growth based on the interplay between knowledge externalities deriving from knowledge generation and the increasing supply of technological knowledge, to show the dynamics of the creative response. The model is used to stress the importance of the “role of the laws of accumulation of the stock of public knowledge and of the conditions of technological knowledge that cannot be fully appropriated by its investors” (p. 200). The presented theoretical setup allows the researcher to understand the economic shift that characterized advanced economies, namely the transition from a capital-intense manufacturing industry to knowledge economies distinguished by the presence of “large out- put elasticity of knowledge and strong knowledge intensity” (p. 200).

Overall, the book contributes to the exploration of the intertwining of innovation economics with the complexity approach and provides an interesting and concise presentation of the main linkages. Because of these features, I think it could be a useful reading for researchers that look for a condensed, yet detailed, introduction into evolutionary approaches of endogenous innovation. Furthermore, I see a lot of potential for this book in a master course, or seminar, on growth theory, the economics of innovation and evolutionary economics. The simple analytical models developed and presented in the book could indeed be used to confront students with the most important theoretical contributions of the Schumpeterian (evolutionary) approaches to innovation.

* References

ANTONELLI, C. (2009). The economics of innovation: from the classical legacies to the economics of complexity. Economics of Innovation and New Technology 18(7), pp. 611–646.

ARTHUR, W. B. (2006). Chapter 32 out-of-equilibrium economics and agent- based modeling. In: Volume 2 of Handbook of Computational Economics, Elsevier, pp. 1551 – 1564.

DAWID, H. (2006). Chapter 25 agent-based models of innovation and techno- logical change. In: Volume 2 of Handbook of Computational Economics, Elsevier pp. 1235 – 1272.

D’ORAZIO, P. (2017). Big data and complexity: Is macroeconomics heading toward a new paradigm? Journal of Economic Methodology 24(4), pp. 410– 429.

FONTANA, M. (2014). Pluralism(s) in economics: lessons from complexity and innovation. A review paper. Journal of Evolutionary Economics 24 (1), pp. 189–204.

FOSTER, J. (2005). From simplistic to complex systems in economics. Cambridge Journal of Economics 29(6), pp. 873–892.

FRENKEN, K. (2006). Technological innovation and complexity theory. Economics of Innovation and New Technology 15(2), pp. 137–155.

HOLLAND, J. H. (1988). The global economy as an adaptive process. The economy as an evolving complex system. Taylor & Francis, CRC Press.

LANE, D. A. (1993a). Artificial worlds and economics, Part I. Journal of evolutionary economics 3(2), pp. 89–107.

LANE, D. A. (1993b). Artificial worlds and economics, Part II. Journal of Evolutionary Economics 3(3), pp. 177–197.

NELSON, R. R. and S. G. Winter (2002). Evolutionary theorizing in economics. Journal of Economic Perspectives 16(2), 23–46.


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