劳动力网络的模块化结构揭示了技能基础
Modular structure in labour networks reveals skill basins
摘要：
文献中正在形成一种共识，即当地固有的能力和工业专门知识是增长和多样化进程的关键决定因素。为了将这些动态模拟为一个分支过程，即行业根据相关或相关技能的可用性而增长，通常采用行业网络。这些网络有时被称为产业空间，描述了产业对之间的能力或技能重叠的复杂结构，这里通过产业间劳动力流动来衡量。现有模式通常采用当地或“最近邻”办法，以确定相关部门中某一行业可利用的劳动力储备规模。然而，这种方法忽略了网络中更高阶的相互作用，以及表现出高度内部技能重叠的产业集群或产业群的存在。我们认为，这些集群代表的技能盆地，工人流通和扩散知识，并划定了规模的熟练劳动力提供给一个行业。通过将多尺度社区检测算法应用于这个网络的流量，我们确定了一系列规模的产业集群，从许多小集群到几个大集团。我们构建了一个新的变量，集群就业，它捕获的劳动力提供给一个行业在自己的集群。使用英国的数据，我们表明，这个变量是预测的工业城市就业增长，并利用检测到的产业集群的多尺度性质，提出了一种方法来揭示劳动力集中运作的最佳规模。
英文摘要：
There is an emerging consensus in the literature that locally embedded capabilities and industrial know-how are key determinants of growth and diversification processes. In order to model these dynamics as a branching process, whereby industries grow as a function of the availability of related or relevant skills, industry networks are typically employed. These networks, sometimes referred to as industry spaces, describe the complex structure of the capability or skill overlap between industry pairs, measured here via inter-industry labour flows. Existing models typically deploy a local or 'nearest neighbour' approach to capture the size of the labour pool available to an industry in related sectors. This approach, however, ignores higher order interactions in the network, and the presence of industry clusters or groups of industries which exhibit high internal skill overlap. We argue that these clusters represent skill basins in which workers circulate and diffuse knowledge, and delineate the size of the skilled labour force available to an industry. By applying a multi-scale community detection algorithm to this network of flows, we identify industry clusters on a range of scales, from many small clusters to few large groupings. We construct a new variable, cluster employment, which captures the workforce available to an industry within its own cluster. Using UK data we show that this variable is predictive of industry-city employment growth and, exploiting the multi-scale nature of the industrial clusters detected, propose a methodology to uncover the optimal scale at which labour pooling operates.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
