1976-1989年美国生物技术企业人口动态和地理分布的基本原理

L. Zucker, M. Darby, Yusheng Peng
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引用次数: 13

摘要

人口生态学模型形式优雅,在描述总体数据方面也很充分,但在讲述故事和预测增长地点方面却很差。基础模型强调资源调动的核心变量,例如智力人力资本,可以预测生物技术企业出现和聚集的地点和时间。密度依赖性和先前的建立依赖性代表了许多潜在的过程;合法性和竞争的解释更多的是推测而不是经验站得住脚。我们论证并证明了基于资源再分配和动员相关基本原理的生物技术替代模型为探索产业形成提供了更强有力的框架。在种群生态学模型的估计中,基本模型优于种群生态学模型,而由基本驱动但包含弱种群动态的组合模型的估计效果最好。在重复动态模拟中,种群生态模型预测结果与生物技术进入各年份和区域面板数据基本不相关,而组合模型的相关系数平均在0.8以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fundamentals or Population Dynamics and the Geographic Distribution of U.S. Biotechnology Enterprises, 1976-1989
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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