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Technological Change and Information Networks
Invention and technological change drives economic growth, creates many of the comforts and luxuries of modern society. Technology also lies at the heart of many of society’s problems and environmental challenges. Where do new technologies come from? How does technology evolve? Most research on technological change agrees that recombination as one of the most important sources of technological novelty; however, there are instances in history when very novel inventions appear with virtually no antecedents. Contrary to popular belief, these highly novel, pioneering inventions do not necessarily yield great wealth for their inventors, but they do open new technological pathway and create new markets for goods and services driving long run economic productivity. The spatial concentration of these pioneering inventions is far more concentrated than inventions characterized by other types of inventive novelty. This fact is not obvious apriori, and ultimately derives from the characteristics of inventor teams, the cities they agglomerate in and the information networks they form. This presentation will discuss empirical work characterizing inventive novelty across 200 year of US data, describe its spatial characteristics and present the underlying theory of human capital networks, cooperation and migration that give rise to metropolitan areas with distinctive contributions to inventive novelty and knowledge creation.
Lunch will be served, please RSVP to firstname.lastname@example.org by Tuesday, March 22 at noon.
Deborah Strumsky is an assistant professor at Arizona State University (ASU) in Tempe, Arizona. She has longstanding interest in the study of technological change and its relationship to economic growth. Recently, her research has focused work for the US Department of Energy on performance curve forecasting. The goal of the project is to develop an empirically grounded theory and quantitative model of technological evolution in solar technologies that can be expanded to a broader set of technologies. The models will produce better forecasts of technological progress and provide quantitative methods that support better decision making in the allocation of technology research and development investments. Other recent research has empirically examined sources of inventive novelty and long run trends in technological change using over 220 years of data. She received her BS in economics from the University of Southern Maine and her Masters and PhD in Regional Science from Cornell University.