paper-with-me

Papers

Socio-Economic Impacts of COVID-19 on Household Consumption and Poverty

2020-05-12

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).

📄 PDF Abstract BibTeX arXiv:2005.05945

Code (0)

등록된 구현이 없습니다.

Tasks

Decision Making

Similar Papers 제목 키워드 기반

Analyzing Impact of Socio-Economic Factors on COVID-19 Mortality Prediction Using SHAP Value

2023-02-27 · Redoan Rahman, Jooyeong Kang, Justin F Rousseau, Ying Ding

This paper applies multiple machine learning (ML) algorithms to a dataset of de-identified COVID-19 patients provided by the COVID-19 Research Database. The dataset consists of 20,878 COVID-positive patients, among which…

Mortality PredictionPrediction

Grid tariff designs coping with the challenges of electrification and their socio-economic impacts

2022-10-07 · Philipp Andreas Gunkel, Claire-Marie Bergaentzlé, Dogan Keles, Fabian Scheller 외

This paper investigates volumetric grid tariff designs under consideration of different pricing mechanisms and resulting cost allocation across socio-techno-economic consumer categories. In a case study of 1.56 million D…

Assessing Fiscal Policy Effectiveness on Household Savings in Hungary, Slovenia, and the Czech Republic during the COVID-19 Crisis: A Markov Switching VAR Approach

2025-03-19 · Tuhin G M Al Mamun

The COVID-19 pandemic significantly disrupted household consumption, savings, and income across Europe, particularly affecting countries like Hungary, Slovenia, and the Czech Republic. This study investigates the effecti…

Twitter and Census Data Analytics to Explore Socioeconomic Factors for Post-COVID-19 Reopening Sentiment

2020-06-30 · Md. Mokhlesur Rahman, G. G. Md. Nawaz Ali, Xue Jun Li, Kamal Chandra Paul 외

Investigating and classifying sentiments of social media users towards an item, situation, and system are very popular among the researchers. However, they rarely discuss the underlying socioeconomic factor associations …

Characterizing Residential Load Patterns by Household Demographic and Socioeconomic Factors

2021-06-04 · Zhuo Wei, Hao Wang

The wide adoption of smart meters makes residential load data available and thus improves the understanding of the energy consumption behavior. Many existing studies have focused on smart-meter data analysis, but the dri…