Industrial leadership in science-based industries: A co-evolution model

Abstract

In this paper, we seek to analyse the role of national university systems in combination with technological and market factors as sources of industrial leadership and industry growth in sciencebased industries. We propose a model in which national university systems and their respective national firms and industries are considered as co-evolving. National firms compete on a worldwide level and they rely on the progress of science and the availability of scientists to innovate. As the global industry develops, firms try to mold their national university systems, but they achieve different degrees of success. Apart from highlighting the role of institutional responsiveness as a source of competitive advantage, our model points to the access to essential inputs for production, the technological and strategic characteristics of firms, the international diffusion of knowledge, and the initial distribution of market demand as key sources of leadership and industry growth. The international mobility of scientists seems to foster the emergence of industrial leadership shifts.

An evolutionary growth model with banking activity

“…Likewise, we have set market reactivity coefficients that maintain the orders of magnitude. Notice also that capital, a bank's initial net worth, and deposits are of compatible size, and can be assimilated to similar values in Delli Gatti et al, ; Fatas‐Villafranca et al, , ; Assenza et al, . Moreover, Baseline scenario I seeks to be a useful departure point to run simulations in which we can study the following issues: virtuous growth paths, in Section 4.1; potential problems in highly innovative economies with uneven firm costs, Section 4.2; the role of institutional conditions underlying production–banking interactions in growth, Section 4.3; prices and growth, Section 4.4; and, in Section 4.5, highly stylized representations of what Schumpeter () called creative destruction processes, exploring the links in the model between uneven innovation rates in the productive sector and banking aspects, as well as the possible roles of these links in large contractions with structural effects in long‐run growth.…”

“…Furthermore, we suppose that firms innovate following an innovation equation (Almudi, Fatas‐Villafranca, & Izquierdo, ; Fatas‐Villafranca, Jarne, & Sanchez‐Choliz, , ; Nelson, ), where is R&D spending (which differs among firms), and is R&D productivity: …”

“…In Baseline scenario I , we have tried to delineate a setting that, at least in a qualitative way, may resemble real conditions. Note that R&D to sales ratios, operating cost rates, proportions of profits to be shared out, rates of debt devolution, minimum interest rates, and reserve ratios all have plausible values (see the simulations in Almudi et al, ; Delli Gatti et al, ; Dosi et al, , ; Fatas‐Villafranca et al, ; Fatas‐Villafranca et al, ; Winter, ). Likewise, we have set market reactivity coefficients that maintain the orders of magnitude.…”

“…They hire skilled workers to innovate, and they do so by devoting a specific share i ∈ (0,1) of their sales to R&D (Dosi & Nelson, 2010). That is, Furthermore, we suppose that firms innovate following an innovation equation (Almudi, Fatas-Villafranca, & Izquierdo, 2013;Fatas-Villafranca, Jarne, & Sanchez-Choliz, 2009, 2014Nelson, 1982), where R i,t is R&D spending (which differs among firms), and z i,t is R&D productivity:…”

Rethinking Macroeconomic Policy within a Simple Dynamic Model

“…Even so, the model leads to a system of six difference equations. In other works we have endogenized technical change (Fatas‐Villafranca et al ., , 2012; Almudi et al ., ).…”