Capitalizing on a crisis: a computational analysis of all five million British firms during the Covid-19 pandemic.

IF 2 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Journal of Computational Social Science Pub Date : 2025-01-01 Epub Date: 2025-02-07 DOI:10.1007/s42001-025-00360-4
Naomi Muggleton, Charles Rahal, Aaron Reeves
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引用次数: 0

Abstract

The Covid-19 pandemic brought unprecedented changes to business ownership in the UK which affects a generation of entrepreneurs and their employees. Nonetheless, the impact remains poorly understood. This is because research on capital accumulation has typically lacked high-quality, individualized, population-level data. We overcome these barriers to examine who benefits from economic crises through a computationally orientated lens of firm creation. Leveraging a comprehensive cache of administrative data on every UK firm and all nine million people running them, combined with probabilistic algorithms, we conduct individual-level analyzis to understand who became Covid entrepreneurs. Using these techniques, we explore characteristics of entrepreneurs-such as age, gender, region, business experience, and industry-which potentially predict Covid entrepreneurship. By employing an automated time series model selection procedure to generate counterfactuals, we show that Covid entrepreneurs were typically aged 35-49 (40.4%), men (73.1%), and had previously held roles in existing firms (59.4%). For most industries, growth was disproportionately concentrated around London. It was therefore existing corporate elites who were most able to capitalize on the Covid crisis and not, as some hypothesized, young entrepreneurs who were setting up their first businesses. In this respect, the pandemic will likely impact future wealth inequalities. Our work offers methodological guidance for future policymakers during economic crises and highlights the long-term consequences for capital and wealth inequality.

利用危机:对2019冠状病毒病大流行期间所有500万家英国公司的计算分析
新冠肺炎疫情给英国的企业所有制带来了前所未有的变化,影响了一代企业家及其员工。尽管如此,人们对其影响仍知之甚少。这是因为对资本积累的研究通常缺乏高质量的、个性化的、人口水平的数据。我们克服了这些障碍,通过以计算为导向的企业创建视角来考察谁从经济危机中受益。利用每家英国公司及其900万运营人员的综合管理数据缓存,结合概率算法,我们进行了个人层面的分析,以了解谁成为了新冠肺炎企业家。利用这些技术,我们探索了企业家的特征,如年龄、性别、地区、商业经验和行业,这些特征可能会预测新冠肺炎创业。通过采用自动时间序列模型选择程序生成反事实,我们发现Covid企业家通常年龄在35-49岁(40.4%),男性(73.1%),之前曾在现有公司担任过职务(59.4%)。对大多数行业来说,增长不成比例地集中在伦敦。因此,最有能力利用新冠危机的是现有的企业精英,而不是像一些人假设的那样,是那些第一次创业的年轻企业家。在这方面,疫情可能会影响未来的财富不平等。我们的工作为未来经济危机期间的政策制定者提供了方法论指导,并强调了资本和财富不平等的长期后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computational Social Science
Journal of Computational Social Science SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
6.20
自引率
6.20%
发文量
30
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