Applied Evolutionary Economics

Applied Evolutionary Economics

New Empirical Methods and Simulation Techniques

Edited by Pier Paolo Saviotti

The expert contributors to this book examine recent developments in empirical methods and applied simulation in evolutionary economics. Using examples of innovation and technology in industry, it is the first book to address the following questions in a systematic manner: Can evolutionary economics use the same empirical methods as other research traditions in economics?; Is there a need for empirical methods appropriate to the subject matter chosen?; What is the relationship between appreciative theorising, case studies and more structured empirical methods?; and What is the relationship of modelling and simulation to empirical analysis?

Chapter 8: An Evolutionary View on Persistence in Innovation: An Empirical Application of Duration Models

C. Le Bas, A. Cabagnols and C. Gay

Subjects: economics and finance, evolutionary economics

Extract

1 C. Le Bas, A. Cabagnols and C. Gay OPENING ANOTHER BLACK BOX: THE DETERMINANTS OF THE CONTINUITY OF FIRMS’ INNOVATING BEHAVIOUR Many contributions to the economics of technological innovation explain why firms in a specific context innovate during one period of time and why others do not. These contributions are concerned with analysing the determinants of innovating behaviour (see for instance Cohen, 1995; Geroski, 1994; Malerba and Orsenigo, 1996; Nelson and Winter, 1982; Patel and Pavitt, 1995; Tirole, 1988). Once it is acknowledged that some firms innovate over a long time period and others fail to do so, what keeps a firm innovative over time? What are the factors explaining why firms innovate persistently? Economic theory has not paid much attention to this question, whereas empirical studies are more numerous. Geroski et al. (1997), with patent and direct innovation data concerning UK firms show that very few firms are persistently innovative. Malerba, Orsenigo and Peretto (1997) build a Schumpeterian framework in which persistence in innovation is related to technological cumulativeness, ‘learning to learn’ and new research opportunities. Associated to industrial heterogeneity these phenomena produce concentration, stability in the ranking of innovators and low turnover in the population of innovators. All these are characteristics of the ‘routinized’ regime (Winter, 1984). Cefis (1999) with a sample of UK firms suggests the firms which are systematic innovators and earn profits above the average have a high profitability. Two other analyses on French industrial firms using the innovation surveys...

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