Generalized barriers to entry and economic development

In this paper we are going to analyze the dynamics of barriers to entry at the international level. In our model economic development takes place and continues in the long run due to the emergence of new sectors, which can compensate for the diminishing ability of mature sectors to create employment and growth. Each new sector is created by a pervasive innovation, which creates a new market and into and out of which there are entry and exit of firms. Depending on the inter-temporal coordination of the maturation of older sectors and of the maturation of new ones our model can give rise to development paths with growth rates ranging from high to negative, to fluctuations, to bubbles and to chaos. In the construction of our model we found inspiration in a number of growth models, both endogenous and evolutionary as well as on empirical work on structural change. The model also bears some similarity of style to history friendly models. Its unique feature is that it gives rise to an endogenously variable number of sectors. Unless new sectors are exact substitutes of older ones the model gives rise to growing variety. In fact, the main objective for which the model was initially constructed was to test some propositions implying that variety growth is a necessary requirement for long term economic development. Within our model the ability to create new sectors at the right times is the crucial determinant of the growth potential of an economic system. Thus, inter country differences in the barriers to entry into new sectors can be expected to give rise to different rates of growth and in the end to increasingly skewed world income distribution. --Technological Change,Economic Development,Economic Variety,Entry Barriers

Economic Development, variety and employment

This paper studies qualitative change taking place during economic development. In the model presented qualitative change is created by the mergence of new sectors, each of which produces an output that is different from other sectors. A system with a variable number of sectors is simulated. The model predicts that under given conditions the evolution of a sector tends to follow a life cycle in both the number of firms and in terms of employment. The cyclical behavior is determined by the balance between the increasing intensity of competition, saturating demand and increasing retuns to adoption. In its present form the model is a simplified representation of the economic system, but several improvements can be introduced in order to increase its degree of realism.economic development, employment, multisectoral model

Innovation Networks in the Biotechnology-Based Sectors

The basic theme underlying this paper is qualitative change taking place during economic development. These changes in the composition of the economic system should become one of the most important variables in models of economic growth and development. Our knowledge of the relationship between economic development and qualitative change, however, is still very limited. This paper attempts to shed light on some important aspects of the role played by qualitative change in economic development, by laying the foundations of a model in which changes in the composition of the economic system are endogenously generated by the evolution of the system itself and, in turn, affect its future development. To put it shortly, we can say that economic development is a process in which new activities emerge, old ones disappear, the weight of all economic activities and their patterns of interaction change.economic development, qualitative change, Neo-Schumpeterian-Economics

Innovation Networks in the Biotechnology-Based Sectors

Technological progress in the biological sciences is now advancing across such a wide range and at such a pace, that, irrespective of size, no firm can hope to keep up in all the different areas. Participating in innovation networks, bundling of competencies and capabilities, therefore, offers an alternative to extremely expensive go-it-alone strategies, whether carried out by acquisition and mergers or by isolated R&D. This imbalance between the rate of growth of the biotechnology knowledge base and the capability of individual firms to access it can explain the persistence of cooperative R&D in the biotechnology-based sectors at the end of the 90s. Such imbalance is not due any more only to the lack of absorptive capacity of existing firms, because the large pharmaceutical firms have meanwhile developed considerable competencies in that field. This previous competence-gap was considered to be the reason for cooperative behaviour in the early phases of these industries in the end of the 70s and early 80s. To the extent that this was considered to be the only knowledge gap innovation networks were considered as a temporary phenomenon, which could not persist beyond the period required by large firms to catch up with the new technology. We are then proposing that a new role, that of explorers scanning parts of the knowledge space that LDFs (Large Diversified Firms) are capable of exploring but unwilling to commit themselves in an irreversible way, can be played by DBFs (Dedicated Biotechnology Firms) in innovation networks. Our simulation approach attempts to represent the emergence of these two roles as endogenous changes in the motivation for participating in innovation networks, allowing them to become an important and long-lasting organizational device for industrial R&D. Drawing on a history friendly modeling approach the decisive mechanisms responsible for the emergence of innovation networks in these industries are figured out and compared to real developments.entrepreneurship, human capital, venture capital, social networks, evolutionary economics, swarms of innovations

Intangible Assests and Market Value: Evidence from Biotechnology Firms

We examine the relationship between the characteristics of the firms' knowledge base in terms of knowledge capital and knowledge integration and the stock market value of 99 firms active in biotechnology during the nineties. Panel data regression models show that our measure of knowledge integration better explains the variance of a firm's market value than the more conventional variable of knowledge capital. This econometric relationship becomes stronger as the technology cycle reaches more mature phases. Meanwhile, profitable and research-intensive firms reach higher levels of market value.Knowledge integration; intangible assets; market value; biotechnology; GMM.

The Knowledge Base Evolution in Biotechnology: A Social Network Analysis.

This paper applies the methodological tools typical of social network analysis (SNA) within an evolutionary framework, to investigate the knowledge base dynamics of the biotechnology sector. Knowledge is here considered a collective good represented as a co-relational and a retrieval-interpretative structure. The internal structure of knowledge is described as a network the nodes of which are small units within traces of knowledge, such as patent documents, connected by links determined by their joint utilisation. We used measures referring to the network, like density, and to its nodes, like degree, closeness and betweenness centrality, to provide a synthetic description of the structure of the knowledge base and of its evolution over time. Eventually, we compared such measures with more established properties of the knowledge base calculated on the basis of co-occurrences of technological classes within patent documents. Empirical results show the existence of interesting and meaningful relationships across the different measures, providing support for the use of SNA to study the evolution of the knowledge bases of industrial sectors and their lifecycles.Knowledge Base, Social Network Analysis, Variety, Coherence, Industry lifecycles; exploration/exploitation

Generalized barriers to entry and economic development

In this paper we are going to analyze the dynamics of barriers to entry at the international level. In our model economic development takes place and continues in the long run due to the emergence of new sectors, which can compensate for the diminishing ability of mature sectors to create employment and growth. Each new sector is created by a pervasive innovation, which creates a new market and into and out of which there are entry and exit of firms. Depending on the inter-temporal coordination of the maturation of older sectors and of the maturation of new ones our model can give rise to development paths with growth rates ranging from high to negative, to fluctuations, to bubbles and to chaos. In the construction of our model we found inspiration in a number of growth models, both endogenous and evolutionary as well as on empirical work on structural change. The model also bears some similarity of style to history friendly models. Its unique feature is that it gives rise to an endogenously variable number of sectors. Unless new sectors are exact substitutes of older ones the model gives rise to growing variety. In fact, the main objective for which the model was initially constructed was to test some propositions implying that variety growth is a necessary requirement for long term economic development. Within our model the ability to create new sectors at the right times is the crucial determinant of the growth potential of an economic system. Thus, inter country differences in the barriers to entry into new sectors can be expected to give rise to different rates of growth and in the end to increasingly skewed world income distribution

Variety and the evolution of refinery processing

Dans ce papier, les auteurs proposent une méthode générique permettant de mesurer la variété au sein d'une famille de technologies. Cette méthode de mesure de la variété est appliquée aux technologies du raffinage. Les résultats font apparaître des comportements classiques de spécialisation qui peuvent s'interpréter dans le cadre de la théorie des niches.progrès technologique,raffinage, pétrole, mesure de Weitzman, variété

Evolution of the knowledge base in knowledge intensive sectors

In a knowledge based society the creation and utilisation of knowledge become the key factors determining the competitiveness of firms, regions and countries. In this perspective a considerable effort is today dedicated to characterise the knowledge base of different sectors in the economy and to detect its impact on firm performance and on industrial organization (Breschi, Lissoni, and Malerba, 2003; Krafft, 2004; Nesta and Saviotti, 2005). Although all sectors in modern economies are affected by a growing knowledge intensity, some sectors are influenced more than the average. We call these Knowledge Intensive Sectors (KISs). In this paper we map the dynamics of knowledge generation within three KISs: biotechnology, telecommunications and electronics. The first question which is addressed is how to characterize a KIS. Typically we would expect KISs to have a high R&D intensity, to produce more patents and publications than less knowledge intensive sectors and to have a greater impact of knowledge production on firm performance and on sectoral growth. A further and important aspect of KISs is the presence of discontinuity in knowledge. Not that such discontinuities are present only in KISs: other sectors are going to be affected, although often less directly, by these discontinuities. However, KISs are likely to be the first ones to start exploring new forms of knowledge and to move them towards exploitation. Thus, we can expect the dynamics of knowledge generation and utilization in KISs to be affected by both (i) the rate of knowledge creation and (ii) the presence of discontinuities in new knowledge. It follows that in order to be able to link the dynamics of knowledge creation and utilization to firm performance and to industrial organization we need to detect a number of properties of the knowledge base (KB) of KISs. Properties such as the diversity/variety of the KB, its coherence and its cognitive distance (or conversely its similarity) between different KBs have already been shown to be potential determinants of firm performance. The aim of this paper is to contribute to this new literature by characterizing the evolution of the KB in three KISs, namely biotechnology, telecommunications and electronics. We use data from the European Patent Office database (EPO database) to see whether we can find common trends in the evolution of the KB of these three KISs.

Introduction to the Journal of Evolutionary Economics special issue: the product characteristics approach to innovation studies

International audience; This special issue collects a selection of papers that were originally presented at the workshop on 'Demand, Product Characteristics and Innovation' organized at the Friedrich Schiller University in Jena in October 2007. The workshop was funded by the DIME (Dynamics of Innovation and Markets) Network of Excellence of the European Commission. All these papers are empirical investigations of the dynamics of innovation in particular industries, based on the 'twin characteristics' approach pioneered by Saviotti and Metcalfe (1984) exactly 25 years ago. Altogether, the papers contained in this special issue provide a good illustration of the variety of approaches that can be employed in detailed studies of product characteristics. They also provide a good overview of the riches of insights that can be gained using this approach. As the availability of datasets and information on product prices and technical characteristics is likely to increase in the near future, empirical studies based on product characteristics seem to represent a research trajectory that is worthwhile pursuing, especially by younger generations of researchers