The Impact of COVID–19 on the Level and Structure of Employment in European Union Countries

IF 0.7 Q3 ECONOMICS
M. Markowska, A. Sokołowski
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引用次数: 0

Abstract

The paper proposes methods that can be used to evaluate the changes in one year of any measurable phenomenon based on how it performed in previous years. The following economic sections are considered: Agriculture, forestry and fishing/Industry/Construction/Wholesale and retail trade, transport, accommodation and food services/Information and communication/Financial and insurance activities/Real estate activities/Professional, scientific and technical activities, including administrative and support services/Public administration, defence, education, human health and social work/Arts, entertainment and recreation; other service activities; activities of household and extra‑territorial organisations and bodies. The paper proposes a new method – called The Triple 2 Rule – to identify changes in employment time series. Trends and autoregressive models are estimated for the period 2008–2019, and 2020 forecasts are calculated. The difference between the forecasted and observed values for 2020 is treated as a measure of the impact of COVID–19. Dynamic cluster analysis based on 2008–2020 data is the second approach. The characteristics and changes in the composition of dynamic clusters give a picture of the impact of 2020. These changes can be considered to have been caused – at least partially – by the COVID–19 pandemic.
2019冠状病毒病对欧盟国家就业水平和结构的影响
这篇论文提出了一些方法,可以根据前几年的表现来评估任何可测量现象在一年内的变化。考虑以下经济部门:农业、林业和渔业/工业/建筑/批发和零售贸易、运输、住宿和食品服务/信息和通信/金融和保险活动/房地产活动/专业、科学和技术活动,包括行政和支助服务/公共管理、国防、教育、人类健康和社会工作/艺术、娱乐和休闲;其他服务活动;家庭和域外组织和机构的活动。这篇论文提出了一种新的方法——被称为“三2规则”——来识别就业时间序列的变化。估计了2008-2019年期间的趋势和自回归模型,并计算了2020年的预测。2020年的预测值与实测值之间的差异被视为衡量COVID-19影响的指标。基于2008-2020年数据的动态聚类分析是第二种方法。动态集群的组成特征和变化为2020年的影响提供了一幅图景。可以认为,这些变化至少部分是由COVID-19大流行造成的。
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
CiteScore
1.30
自引率
0.00%
发文量
26
审稿时长
16 weeks
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