Population Density and Its Impact on Local Economy Pre and Post COVID-19

Despoina Balouktsi
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Abstract

How new jobs requiring high skill can be notably beneficial for the overall employment of a local economy has been a long discussed topic in economic literature. Nevertheless, given the post COVID-19 breakout trend for increasing remote work, especially in the case of high-skilled workers, the beneficial effects may not be the same. This paper presents a two-sector spatial equilibrium search model that explains skill premium differences together with the pre and post COVID-19 unemployment rate patterns for high and low population density locations. This is accomplished through an idea exchange environment that draws highly paid workers, who, as their wage increases, consume more of the local goods and services, together. Post COVID-19, this situation changes to a degree, explaining the pattern reversal in unemployment rate, namely that unemployment is now greater in high population density locations.
疫情前后人口密度及其对地方经济的影响
需要高技能的新工作如何对当地经济的整体就业显著有益,一直是经济文献中讨论已久的话题。然而,鉴于2019冠状病毒病爆发后远程工作增加的趋势,特别是对高技能工人而言,其有益效果可能不尽相同。本文提出了一个双部门空间均衡搜索模型,该模型解释了高人口密度和低人口密度地区的技能溢价差异以及疫情前后的失业率模式。这是通过一个吸引高薪工人的思想交流环境来实现的,随着他们工资的增加,他们会消费更多的当地商品和服务。2019冠状病毒病后,这种情况在一定程度上发生了变化,这解释了失业率模式的逆转,即现在人口密度高的地区失业率更高。
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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