COVID-19 对家庭消费和贫困的社会经济影响。

Amory Martin, Maryia Markhvida, Stéphane Hallegatte, Brian Walsh
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摘要

COVID-19 大流行在全球范围内造成了巨大的经济冲击,原因是社会疏远措施导致业务中断和停产。为了评估 COVID-19 对个人的社会经济影响,我们建立了一个微观经济模型,以估算疏远措施对家庭收入、储蓄、消费和贫困的直接影响。该模型假设了两个时期:危机期,在此期间,一些人的收入会下降,他们可以使用储蓄来维持消费;恢复期,在此期间,家庭通过储蓄将耗尽的储蓄补充到危机前的水平。本文以旧金山湾区为案例,对封锁的影响进行了量化,并考虑了失业保险(UI)和《CARES 法案》联邦刺激措施的影响。假定原地避难时间为三个月,在没有社会保障的情况下,湾区的贫困率将从 17.1%暂时上升到 25.9%,相对而言,最低收入人群将遭受最严重的影响。如果全面实施 UI 和 CARES,则可将贫困率的增长保持在接近零的水平,并将收入损失者的平均恢复时间从 11.8 个月缩短至 6.7 个月。然而,经济影响的严重程度在空间上是异质的,某些社区受到的影响比平均水平更大,可能需要一年以上的时间才能恢复。总体而言,该模型是在区域范围内量化 COVID-19 家庭层面影响的第一步。这项研究可以扩展到探讨间接宏观经济效应的影响、不确定性在家庭决策中的作用以及同时发生的外源冲击(如自然灾害)的潜在影响。
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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Socio-Economic Impacts of COVID-19 on Household Consumption and Poverty.

The COVID-19 pandemic has caused a massive economic shock across the world due to business interruptions and shutdowns from social-distancing measures. To evaluate the socio-economic impact of COVID-19 on individuals, a micro-economic model is developed to estimate the direct impact of distancing on household income, savings, consumption, and poverty. The model assumes two periods: a crisis period during which some individuals experience a drop in income and can use their savings to maintain consumption; and a recovery period, when households save to replenish their depleted savings to pre-crisis level. The San Francisco Bay Area is used as a case study, and the impacts of a lockdown are quantified, accounting for the effects of unemployment insurance (UI) and the CARES Act federal stimulus. Assuming a shelter-in-place period of three months, the poverty rate would temporarily increase from 17.1% to 25.9% in the Bay Area in the absence of social protection, and the lowest income earners would suffer the most in relative terms. If fully implemented, the combination of UI and CARES could keep the increase in poverty close to zero, and reduce the average recovery time, for individuals who suffer an income loss, from 11.8 to 6.7 months. However, the severity of the economic impact is spatially heterogeneous, and certain communities are more affected than the average and could take more than a year to recover. Overall, this model is a first step in quantifying the household-level impacts of COVID-19 at a regional scale. This study can be extended to explore the impact of indirect macroeconomic effects, the role of uncertainty in households' decision-making and the potential effect of simultaneous exogenous shocks (e.g., natural disasters).

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