论文标题
COVID-19对家庭消费和贫困的社会经济影响
Socio-Economic Impacts of COVID-19 on Household Consumption and Poverty
论文作者
论文摘要
由于业务中断和与社会持续的措施的关闭,共同的19日大流行造成了全世界的巨大经济冲击。为了评估Covid-19对个人的社会经济影响,开发了一个微观经济模型,以估计疏远对家庭收入,储蓄,消费和贫困的直接影响。该模型假设了两个时期:一个危机时期,在此期间,有些人的收入下降,可以利用其预防储蓄来维持消费;以及一个恢复期,当家庭储蓄以补充贫困的储蓄到危机前的水平时。旧金山湾区被用作案例研究,量化的影响是量化的,构成了失业保险(UI)(UI)的影响和《 Cares Act联邦刺激》的影响。假设在三个月内的庇护所期间,在没有社会保护的情况下,贫困率将从湾区暂时增加到25.9%,而收入最低的收入人士的损失最低。如果完全实施,则UI和CARES的组合可以使贫困的增加接近零,并减少遭受收入损失的个人的平均恢复时间,从11.8个月到6.7个月。但是,经济影响的严重程度在空间上是异质的,某些社区比平均水平更大,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的家庭水平影响的第一步。可以扩展这项研究以探索间接宏观经济影响的影响,不确定性在家庭决策中的作用以及同时外源性冲击的潜在影响(例如,自然灾害)。
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 precautionary 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).