Technical Change and Industrial Dynamics as Evolutionary Processes

This work prepared for B. Hall and N. Rosenberg (eds.) Handbook of Innovation, Elsevier (2010), lays out the basic premises of this research and review and integrate much of what has been learned on the processes of technological evolution, their main features and their effects on the evolution of industries. First, we map and integrate the various pieces of evidence concerning the nature and structure of technological knowledge the sources of novel opportunities, the dynamics through which they are tapped and the revealed outcomes in terms of advances in production techniques and product characteristics. Explicit recognition of the evolutionary manners through which technological change proceed has also profound implications for the way economists theorize about and analyze a number of topics central to the discipline. One is the theory of the firm in industries where technological and organizational innovation is important. Indeed a large literature has grown up on this topic, addressing the nature of the technological and organizational capabilities which business firms embody and the ways they evolve over time. Another domain concerns the nature of competition in such industries, wherein innovation and diffusion affect growth and survival probabilities of heterogeneous firms, and, relatedly, the determinants of industrial structure. The processes of knowledge accumulation and diffusion involve winners and losers, changing distributions of competitive abilities across different firms, and, with that, changing industrial structures. Both the sector-specific characteristics of technologies and their degrees of maturity over their life cycles influence the patterns of industrial organization ? including of course size distributions, degrees of concentration, relative importance of incumbents and entrants, etc. This is the second set of topics which we address. Finally, in the conclusions, we briefly flag some fundamental aspects of economic growth and development as an innovation driven evolutionary process.Innovation, Technological paradigms, Technological regimes and trajectories, Evolution, Learning, Capability-based theories of the firm, Selection, Industrial dynamics, Emergent properties, Endogenous growth

Density and Strength of Ties in Innovation Networks: An Analysis of Multi-Media and Biotechnology

In this article we provide an empirical illustration of hypotheses, developed in the literature, on the role of density and strength of ties in innovation networks.We study both exploration and exploitation networks in the Dutch multimedia and pharmaceutical biotechnology industry.We find support for most of our hypotheses but not all.These findings, in line with the mixed results in the literature, seem to indicate that the distinction between exploration versus exploitation, albeit useful, is still too general.There may be a stronger sectoral effect in how exploration and exploitation settle in network structural properties than anticipated thus far.innovation;networks;density;strength of ties;governance;biotechnology;multimedia

Economic Development from the Perspective of Evolutionary Economic Theory

The purpose of the article is to discuss the differences between the evolutionary economic theory and the neoclassical theory from the appreciative viewpoint that aims to capture the basics of what actually is going on, leaving aside formal mathematical modeling in the two theories. As the result, evolutionary theory sees the economy as always in the process of change that involves economic actors taking actions that break from previous behavior, and an environment in continuing flux because of the innovation. While neoclassical theory sees the economy as at rest, or undergoing well anticipated change it has nothing to say about these kinds of conditions. Therefore the author believes the processes of economic catch-up have to proceed under the implicit or explicit guidance of an evolutionary economic theory.

Accounting for Calibration Uncertainties in X-ray Analysis: Effective Areas in Spectral Fitting

While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a proper interpretation of analysis results because instrumental calibration uncertainty is a form of systematic uncertainty. Ignoring it can underestimate error bars and introduce bias into the fitted values of model parameters. Accounting for such uncertainties currently requires extensive case-specific simulations if using existing analysis packages. Here we present general statistical methods that incorporate calibration uncertainties into spectral analysis of high-energy data. We first present a method based on multiple imputation that can be applied with any fitting method, but is necessarily approximate. We then describe a more exact Bayesian approach that works in conjunction with a Markov chain Monte Carlo based fitting. We explore methods for improving computational efficiency, and in particular detail a method of summarizing calibration uncertainties with a principal component analysis of samples of plausible calibration files. This method is implemented using recently codified Chandra effective area uncertainties for low-resolution spectral analysis and is verified using both simulated and actual Chandra data. Our procedure for incorporating effective area uncertainty is easily generalized to other types of calibration uncertainties.Comment: 61 pages double spaced, 8 figures, accepted for publication in Ap

Securitization and Post-Crisis Financial Regulation

There are few types of securities as internationally traded as those issued in securitization (also spelled securitisation) transactions. The post-financial crisis regulatory responses to securitization in the United States and Europe are, at least in part, political and ad hoc. To achieve a more systematic regulatory framework, this article examines how existing regulation should be supplemented by identifying the market failures that apply distinctively to securitization and analyzing how those market failures could be corrected. Among other things, the article argues that Europe’s regulatory framework for simple, transparent, and standardised (“STS”) securitizations goes a long way towards addressing complexity as a market failure, and that the United States should consider a similar regulatory approach