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Fundamentals or Population Dynamics and the Geographic Distribution of U.S. Biotechnology Enterprises, 1976-1989 / Lynne G. Zucker, Michael R. Darby, Yusheng Peng.

By: Contributor(s): Material type: TextTextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w6414.Publication details: Cambridge, Mass. National Bureau of Economic Research 1998.Description: 1 online resource: illustrations (black and white)Subject(s): Online resources: Available additional physical forms:
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Abstract: Population ecology models are elegant in form and adequate in describing aggregate data, but poor in telling stories and predicting the location of growth. Fundamentals models emphasizing the variables central to resource mobilization, such as intellectual human capital, can predict where and when biotechnology enterprises emerge and agglomerate. Density dependence and previous founding dependence proxy many underlying processes; the legitimation and competition interpretation is more conjectural than empirically tenable. We argue and demonstrate for biotechnology that an alternative model based on the fundamentals related to resource reallocation and mobilization provides a stronger frame to explore industry formation. Fundamentals models outperform population ecology models in the estimations, while a combined model driven by fundamentals but incorporating weak population dynamics does best. In repeated dynamic simulations, the population ecology model predictions are essentially uncorrelated with the panel data on biotechnology entry by year and region while the combined model has correlation coefficients averaging above 0.8.
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February 1998.

Population ecology models are elegant in form and adequate in describing aggregate data, but poor in telling stories and predicting the location of growth. Fundamentals models emphasizing the variables central to resource mobilization, such as intellectual human capital, can predict where and when biotechnology enterprises emerge and agglomerate. Density dependence and previous founding dependence proxy many underlying processes; the legitimation and competition interpretation is more conjectural than empirically tenable. We argue and demonstrate for biotechnology that an alternative model based on the fundamentals related to resource reallocation and mobilization provides a stronger frame to explore industry formation. Fundamentals models outperform population ecology models in the estimations, while a combined model driven by fundamentals but incorporating weak population dynamics does best. In repeated dynamic simulations, the population ecology model predictions are essentially uncorrelated with the panel data on biotechnology entry by year and region while the combined model has correlation coefficients averaging above 0.8.

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