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Consumer Response to Economic Impact Payments during the COVID-19 Pandemic and the Role of Subjective Assessments of Well-Being: A View from the U.S. Using a Rapid Response Survey

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  • Thesia Garner
  • Jake Schild

Abstract

COVID-19 has become a crisis that is impacting lives, economies, and ways of life around the world. Governments have responded with policies to support and protect their populations, businesses have closed or restricted access, and consumers have adapted as best as they could. Determining in the short-run how well these policies might be working and the socio-economic impact of the pandemic on individuals and households resulted in new data collection efforts worldwide and the greater use of rapid response surveys. This research reports one such effort in the United States (U.S.) to collect data using the Household Pulse Survey (HPS), with a focus on the use of government provided economic impact or stimulus payments by households. These payments were expected to have maximum and immediate impacts. Results reveal that household were most likely to use their economic impact payments to pay off debt as opposed to meeting their spending needs. Respondents who report lower levels of subjective well-being are more likely to use the stimulus payment to "mostly pay off debt" The probability of using the stimulus payment to "mostly pay off debt" increases as subjective assessments of well-being worsen. This research is one of the earliest to examine the role subjective assessments of well-being play in determining consumer response to receipt of economic impact payments during the COVID-19 pandemic.

Suggested Citation

  • Thesia Garner & Jake Schild, 2021. "Consumer Response to Economic Impact Payments during the COVID-19 Pandemic and the Role of Subjective Assessments of Well-Being: A View from the U.S. Using a Rapid Response Survey," Economic Working Papers 540, Bureau of Labor Statistics.
  • Handle: RePEc:bls:wpaper:540
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    File URL: https://www.bls.gov/osmr/research-papers/2021/pdf/ec210060.pdf
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