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In addition, the pandemic might accelerate the growth in card transactions as people avoid the risks associated with exchanging physical cash and because of the growth in online spend. We may be particularly concerned about this type of substitution at a time of acute economic disruption when households might turn to credit cards to smooth their consumption. Our estimates could be biased to the extent that there is substitution between these alternative channels and Chase credit cards coincident with our analysis period. We do not observe spending using debit cards, cash, electronic payments, and non-Chase credit cards. Finally, we stratify the sample by individuals’ industry of employment to test whether those employed in sectors with higher expected rates of job loss cut spending by a larger amount.ĭespite these strengths, our findings come with several important caveats that stem from the fact that, at the time of writing, we only observe the subset of spending that occurs on a household’s Chase credit cards through April 11. We also look at changes in spending across the pre-COVID income distribution. We decompose the spending drop into non-essential and essential spending, speaking to the pandemic-induced closure of many non-essential businesses. We are thus able to provide detailed estimates of the spending drop and to analyze heterogeneity in this drop across household characteristics and across categories of spending. The key strengths of these data are a large sample size and the ability to track the spending patterns of specific households across time.
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For a subset of our analyses we pair these credit card data with checking account data through February 2020, which allow us to segment our population by income levels and industry of employment before the COVID shock 3. We focus on a sample of 8 million families across all fifty states who have been active users of their credit cards since January 2018 2. To answer these questions, we use a dataset based on the universe of transactions made on Chase credit cards through April 11, 2020. This will be increasingly important as the pandemic and policy impacts interact with increasing job loss and additional policies to ameliorate the job loss, such as stimulus payments and UI. First, how much has individual spending fallen, and how does this drop vary across households 1? Second, can heterogeneity across households provide suggestive evidence about the spending decline caused by the nearly ubiquitous pandemic and policies intended to contain it versus the initial round of income losses during that period? With consumer spending accounting for roughly 70 percent of GDP, understanding the magnitude and causes of changes in consumption is critical to identifying policy interventions that could aid in accelerating an economic recovery. In this report, we provide preliminary high-frequency evidence of the reaction of consumer spending to these events. The government has responded with a massive recovery act to bolster income by funding stimulus checks, Unemployment Insurance (UI) supplements, and the Payroll Protection Program. Social distancing restrictions have all but prohibited the consumption of certain goods and services. The pandemic has shut down large sectors of the economy deemed “non-essential,” leaving millions of workers jobless. These almost universal disruptions to normal activity have already had unprecedented consequences for the economy. Within a matter of weeks, vacations and special events were cancelled, and routine trips to the store, workplace, and restaurants became hindered by both the virus and the policies designed to prevent its spread.
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population was subject to “stay-at-home” orders. caseload exceeded 100,000 on March 29, and by April 6, 90 percent of the U.S.
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Following the declaration of a national emergency on March 13, 2020, the U.S. COVID-19 has rapidly transformed our nation.