RAPID: Income and Poverty in the COVID-19 Pandemic
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$199,723Funder
National Science Foundation (NSF)Principal Investigator
Bruce MeyerResearch Location
United States of AmericaLead Research Institution
University of ChicagoResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Economic impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
Abstract
In nine weeks at the start of the COVID-19 pandemic 39 million people filed for unemployment insurance, while GDP for the first quarter of 2020 was down 4.8%. The federal government responded with unprecedented stimulus legislation that committed more than two trillion dollars to countering the effects of the pandemic. Effectively targeting and calibrating the government's fiscal response requires tracking changes in income and poverty by demographic group and geography in a timely way, which there is extremely limited ability to do. Official estimates of income and poverty for 2020 will not be available until September of 2021. This project responds directly to this need to develop new processes to help address the economic impact of the COVID-19 pandemic by providing timely and accurate information on the impact of the current pandemic on income and poverty to inform the targeting of resources to those most affected. The project aims to construct new measures of the income distribution and poverty with a lag of only a few weeks using high frequency data for a large, representative sample of U.S. families. This project will have immediate impact in advancing basic knowledge in the fields of economics and related social sciences and providing tools for policy makers by constructing new, near real-time estimates of income and poverty.
The project will validate new, timely measure of income by comparing historical estimates that rely on these data to estimates from data on income and consumption that have been used much more broadly. Importantly, these validation exercises will utilize new data that links survey data to tax and program data at the individual level. The validation will help researchers understand the advantages and limitations of using more timely income data to study changes in economic well-being. This project will also address key questions regarding the impacts of large economic shocks and survey income measurement, both critical elements of much economic research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
In nine weeks at the start of the COVID-19 pandemic 39 million people filed for unemployment insurance, while GDP for the first quarter of 2020 was down 4.8%. The federal government responded with unprecedented stimulus legislation that committed more than two trillion dollars to countering the effects of the pandemic. Effectively targeting and calibrating the government's fiscal response requires tracking changes in income and poverty by demographic group and geography in a timely way, which there is extremely limited ability to do. Official estimates of income and poverty for 2020 will not be available until September of 2021. This project responds directly to this need to develop new processes to help address the economic impact of the COVID-19 pandemic by providing timely and accurate information on the impact of the current pandemic on income and poverty to inform the targeting of resources to those most affected. The project aims to construct new measures of the income distribution and poverty with a lag of only a few weeks using high frequency data for a large, representative sample of U.S. families. This project will have immediate impact in advancing basic knowledge in the fields of economics and related social sciences and providing tools for policy makers by constructing new, near real-time estimates of income and poverty.
The project will validate new, timely measure of income by comparing historical estimates that rely on these data to estimates from data on income and consumption that have been used much more broadly. Importantly, these validation exercises will utilize new data that links survey data to tax and program data at the individual level. The validation will help researchers understand the advantages and limitations of using more timely income data to study changes in economic well-being. This project will also address key questions regarding the impacts of large economic shocks and survey income measurement, both critical elements of much economic research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.