Breaking the waves: a Poisson regression approach to Schumpeterian clustering of basic innovations.
Breaking the waves: a Poisson regression approach to Schumpeterian clustering of basic innovations.
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破浪：熊彼特基本创新聚类的泊松回归方法。
DOI：
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发表时间：
2000
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通讯作者：
B. Verspagen
中科院分区：
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作者：
G. Silverberg;B. Verspagen
熊彼特的长波理论引发了一场关于基本创新集群存在的激烈辩论。Silverberg和Lehnert在几个方法论上批评了这篇文献中的经验部分。在这篇文章中，我们提出了泊松回归的方法论，作为纳入这一批评的逻辑方式。我们构造了一个新的基本创新时间序列(基于以前使用的时间序列)，并用它来检验基本创新在时间上聚集的假设。在进行统计检验之前，我们以各种精确的方式定义了聚类的概念。我们发现的证据只支持我们的集群假说中最弱的一个，即数据表现出过度分散。因此，我们得出的结论是，那些认为经济生活中的一波长浪潮是由一系列基本创新推动的作者，夸大了统计证据。版权所有2003，牛津大学出版社。
The Schumpeterian theory of long waves has given rise to an intense debate on the existence of clusters of basic innovations. Silverberg and Lehnert have criticised the empirical part of this literature on several methodological accounts. In this paper, we propose the methodology of Poisson regression as a logical way of incorporating this criticism. We construct a new time series for basic innovations (based on previously used time series), and use this to test the hypothesis that basic innovations cluster in time. We define the concept of clustering in various precise ways before undertaking the statistical tests. The evidence we find supports only the 'weakest' of our clustering hypotheses, i.e., that the data display overdispersion. We thus conclude that the authors who have argued that a long wave in economic life is driven by clusters of basic innovations have stretched the statistical evidence too far. Copyright 2003, Oxford University Press.