Department of Economics and Statistics, University of Siena, Siena, Italy.
Institute for Complex Systems, UOS Sapienza, Rome, Italy.
Sci Rep. 2022 Dec 22;12(1):22141. doi: 10.1038/s41598-022-25940-6.
We study the empirical relationship between green technologies and industrial production at very fine-grained levels by employing Economic Complexity techniques. Firstly, we use patent data on green technology domains as a proxy for competitive green innovation and data on exported products as a proxy for competitive industrial production. Secondly, with the aim of observing how green technological development trickles down into industrial production, we build a bipartite directed network linking single green technologies at time [Formula: see text] to single products at time [Formula: see text] on the basis of their time-lagged co-occurrences in the technological and industrial specialization profiles of countries. Thirdly, we filter the links in the network by employing a maximum entropy null-model. Our results emphasize a strong connection between green technologies and the export of products related to the processing of raw materials, notably crucial for the development of climate change mitigation and adaptation technologies. Furthermore, by looking at the evolution of the network over time, we observe a growing presence of more complex green technologies and high-tech products among the significant links, suggesting an increase in their importance in the network.
我们通过采用经济复杂度技术,在非常细粒度的水平上研究绿色技术和工业生产之间的经验关系。首先,我们使用绿色技术领域的专利数据作为竞争绿色创新的代理,使用出口产品数据作为竞争工业生产的代理。其次,为了观察绿色技术发展如何渗透到工业生产中,我们基于各国技术和产业专业化档案中绿色技术和产品在时间上的滞后共现,构建了一个将单个绿色技术在时间 t 与单个产品在时间 t 联系起来的二分有向网络。第三,我们通过使用最大熵零模型来过滤网络中的链接。我们的结果强调了绿色技术与与原材料加工相关的产品出口之间的紧密联系,这对减缓气候变化和适应技术的发展至关重要。此外,通过观察网络随时间的演变,我们观察到在重要链接中出现了越来越多的复杂绿色技术和高科技产品,这表明它们在网络中的重要性不断增加。