311 research outputs found
Stochastic Trade Networks
This paper develops a simple network model to describe the dynamic of the intensive and extensive margin of international trade flows. The result is achieved by means of the combination of two mechanisms of proportional
growth: the first (discrete) determines the formation of trade links, the second (continuous) governs trade intensity. We show that our setup is able to simultaneously match a large number of empirical regularities, such as the
fraction of zero trade flows across pairs of countries or the high concentration of trade with respect to both products and destinations. Our findings suggest that stylized facts are strongly interconnected across different levels of aggregation of trade data , so that a unifying explanation is called for. By incorporating stochastic elements into standard trade models we can improve their ability to explain relevant facts about world trade
Technological Regimes and the Growth of Networks An Empirical Analysis
This paper shows how specific technological and relational regimes have shaped the growth of the network of R&D collaborative agreements in pharmaceuticals in the 1990s. Our analysis reveals the existence of a complex set of regimes of firm growth within the network, providing additional evidence supporting prediction that both growth and innovative activities of large and small firms respond, even within a given industry, to considerably different technological and economic factors. Moreover, the paper shows, in the context of a specific industry and by means of a series of preliminary and explorative empirical analyses, that information on the topological properties of a given industrial settings and on roles/positions of organizations within it can be used to disentangle some fundamental generative processes underlying observed processes of growth. This result contributes to the 'old' stochastic approach to firm growth, in the direction of building parsimonious and, at the same time, more realistic, representations of processes of industrial growth.-
Market Structure and Drug Innovation
An explosion of knowledge and a growing array of tools and technologies have transformed modern drug R&D, while its cost has risen by a sizable amount. At the same time, the unchecked increase in health care and prescription drug spending has spawned cost containment policies that are restricting the demand for drugs in all major markets. This Perspective explores the interplay between technological advances and regulatory policies and their likely impact on the dynamics of the pharmaceutical industry. Advances in the life sciences have profoundly transformed the drug research and development (R&D) process. That transformation has come at a price, boosting the cost of developing a new molecular entity (NME) to 802 million by 2000. More expensive R&D, combined with an aging population and better diagnostic techniques, has swelled drug spending in the United States, which reached 141 billion in 2001. These increases have in turn induced a spate of cost containment measures that are affecting demand for pharmaceuticals in all major markets. This Perspective considers the impact of the interplay between technological advances and health care policy on the future dynamics of the pharmaceutical industry.Pharmaceutical Industry, R&D Productivity, Health Care Policy
The Structure and Growth of International Trade
The paper develops a model of proportionate growth to describe the dynamics of international trade flows. We show that a large number of the empirical regularities characterizing international trade -such as the fraction of zero trade flows across pairs of countries, the positive relationship between inten- sive and extensive margins, the high concentration of trade with respect to both products and destinations, the core-periphery structure of exchanges- are well explained by this simple stochastic setup. This helps us to distinguish among economically relevant regularities and those simply resulting from the mechanical interactions among agents. Furthermore, our model can be used to describe the process of `self-discovery' that lie at the foundations of suc- cessful export-led growth and is thought to play a crucial role in the process of economic development. Our model correctly predicts that large export flows are rare events, as pointed out in the empirical literature: yet, countries char- acterized by large `discovery' efforts are much more likely to draw a `big hit' due to the (very skewed) shape of the distribution of bilateral export flows.international trade, development, weighted networks, proportionate growth, industrial policy
On Firm Growth in Networks
This paper is explorative in nature. Based on an empirical analysis of two different industrial settings (life sciences, LS; information and communication technologies, ICT), it investigates network growth and firm growth in networks. We find a remarkable correspondence between a few fundamental findings of the ‘old’ stochastic approach to the analysis of firm internal growth, and empirically observed patterns of firm external growth through collaborative agreements. We show that scale-free behavior in real-world industrial networks can be accounted for by a general and parsimonious model, originally developed by Herbert Simon in 1955, based on entry and proportional growth. However, relevant departures from the stochastic benchmark are revealed that cannot be ascribed to the effect of mergers and acquisitions (M&As) and growth autocorrelation. Moreover, different regimes of growth are found to be at work in the life sciences for originators versus developers of new business opportunities, reflecting the fact that growth is driven by specialization and division of labor in the processes of generation and attraction/development of technological opportunities.Firm growth; Network growth; Biotechnology; Information and communication technologies
Innovation and corporate dynamics: a theoretical framework
We provide a detailed analysis of a generalized proportional growth model (GPGM) of innovation and corporate dynamics that encompasses the Gibrat’s Law of Proportionate Effect and the Simon growth process as particular instances. The predictions of the model are derived in terms of (i) firm size distribution, (ii) the distribution of firm growth rates, and (iii-iv) the relationships between firm size and the mean and variance of firm growth rates. We test the model against data from the worldwide pharmaceutical industry and find its predictions to be in good agreement with empirical evidence on all four dimensions
Missing Links in Multiple Trade Networks
In this paper we develop a network model of international trade which is able to replicate the concentrated and sparse nature of trade data. Our model extends the preferential attachment (PA) growth model to the case of multiple networks. Countries trade a variety of goods of
different complexity. Every country progressively evolves from trading less sophisticated to high-tech goods. The probability to capture more trade opportunities at a given level of complexity and to start trading more complex goods are both proportional to the number of existing trade links. We provide a set of theoretical predictions and simulative results. A calibration exercise shows that our model replicates the same concentration level of world trade as well as the sparsity pattern of the trade matrix. Moreover, we find a lower bound for the share of genuine missing trade links. We also discuss a set of numerical
solutions to deal with large multiple networks
R&D, Within and Between Patent Competition in the Pharmaceutical Industry
We analyse the consequences of the increasing complexity of R&D on within- and between-patent competition in the pharmaceutical industry. The intensity of competition
is measured by jointly considering the timing from market launch to patent expiry, the strength of between-patent competition as well as competition introduced by generic
producers. A simple model is proposed that predicts the shrinking of product lifetimes in the presence of correlated parallel R&D projects and market portfolios. The model is tested using data on pharmaceutical products sold in Europe and in the US. Based on our model we are able to estimate the impact of R&D complexity and relatedness
among R&D portfolios on the value of innovative drugs
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