连接经济结构变化的短期和长期动态
Bridging the short-term and long-term dynamics of economic structural change
摘要：
经济转型-经济生产的变化-是发展和提高生活水平的基础。我们对这一过程的理解最近受到经济复杂性领域两个分支工作的推动，一个研究经济如何多样化，另一个研究经济的复杂性如何在其产出构成中表现出来。然而，这些分支之间的联系并没有得到很好的理解，也没有它们如何与结构转型的经典理解相关联。在这里，我们提出了一个简单的动态建模框架，统一了这些领域的工作，基于广泛的观察，经济多样化的优先活动，他们已经做的。我们展示了如何程式化的长期结构变化的事实，以及复杂性指标，都可以自然地从这一个观察。然而，复杂性指标有了新的含义，它描述了经济体经历的长期变化，而不是复杂性本身。这表明相关性和复杂性度量是以一种迄今为止被忽视的方式联系在一起的：两者都描述了不同时间尺度上的结构变化。相关性在短时间尺度上探索变革，而复杂性度量则捕捉长期变化。
英文摘要：
Economic transformation -- change in what an economy produces -- is foundational to development and rising standards of living. Our understanding of this process has been propelled recently by two branches of work in the field of economic complexity, one studying how economies diversify, the other how the complexity of an economy is expressed in the makeup of its output. However, the connection between these branches is not well understood, nor how they relate to a classic understanding of structural transformation. Here, we present a simple dynamical modeling framework that unifies these areas of work, based on the widespread observation that economies diversify preferentially into activities that are related to ones they do already. We show how stylized facts of long-run structural change, as well as complexity metrics, can both emerge naturally from this one observation. However, complexity metrics take on new meanings, as descriptions of the long-term changes an economy experiences rather than measures of complexity per se. This suggests relatedness and complexity metrics are connected, in a hitherto overlooked way: Both describe structural change, on different time scales. Whereas relatedness probes transformation on short time scales, complexity metrics capture long-term change.
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