英文标题：
《Estimating the drivers of urban economic complexity and their connection
to economic performance》
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作者：
Andres Gomez-Lievano and Oscar Patterson-Lomba
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最新提交年份：
2021
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英文摘要：
Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated in the complexity and sophistication of urban activities, the knowhow of individual workers, and the city-wide collective knowhow. We derive a model that indicates how the value of these three quantities can be inferred from the probability that an individual in a city is employed in a given urban activity. We illustrate how to estimate empirically these variables using data on employment across industries and metropolitan statistical areas in the US. We then show how the functional form of the probability function derived from our theory is statistically superior when compared to competing alternative models, and that it explains well-known results in the urban scaling and economic complexity literature. Finally, we show how the quantities are associated with metrics of economic performance, suggesting our theory can provide testable implications for why some cities are more prosperous than others.
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中文摘要：
估计推动和制约城市地区经济发展的能力或生产投入仍然是一个具有挑战性的目标。我们认为，能力体现在城市活动的复杂性和复杂性、单个工人的专有技术和整个城市的集体专有技术中。我们推导了一个模型，该模型表明如何从城市中的个人受雇于给定城市活动的概率中推断出这三个量的值。我们举例说明如何使用美国各行业和大都市统计区的就业数据对这些变量进行经验估计。然后，我们展示了与竞争替代模型相比，从我们的理论推导出的概率函数的函数形式在统计上是如何优越的，并且它解释了城市规模和经济复杂性文献中的著名结果。最后，我们展示了数量是如何与经济绩效指标相关联的，这表明我们的理论可以为为什么一些城市比其他城市更繁荣提供可验证的含义。
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分类信息：

一级分类：Physics 物理学
二级分类：Physics and Society 物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Physics 物理学
二级分类：Adaptation and Self-Organizing Systems 自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
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一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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