The Initial Household Spending Response to COVID-19

COVID-19 has rapidly transformed our nation. Following the declaration of a national emergency on March 13, 2020, the U.S. caseload exceeded 100,000 on March 29, and by April 6, 90 percent of the U.S. population was subject to “stay-at-home” orders. 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. 

These almost universal disruptions to normal activity have already had unprecedented consequences for the economy. The pandemic has shut down large sectors of the economy deemed “non-essential,” leaving millions of workers jobless. Social distancing restrictions have all but prohibited the consumption of certain goods and services. 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. 

In this report, we provide preliminary high-frequency evidence of the reaction of consumer spending to these events. We ask two main questions. First, how much has individual spending fallen, and how does this drop vary across households¹? 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.  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.

To answer these questions, we use a dataset based on the universe of transactions made on Chase credit cards through April 11, 2020. We focus on a sample of 8 million families across all fifty states who have been active users of their credit cards since January 2018². 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 shock³.

The key strengths of these data are a large sample size and the ability to track the spending patterns of specific households across time. 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. We decompose the spending drop into non-essential and essential spending, speaking to the pandemic-induced closure of many non-essential businesses. We also look at changes in spending across the pre-COVID income distribution. 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. 

Despite 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 do not observe spending using debit cards, cash, electronic payments, and non-Chase credit cards. 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 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. 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. This might cause us to understate the drop in spending.

Second, while our data include households across a wide cross-section of income levels and geographies, Chase credit card holders tend to be more affluent than the average U.S. household. As we show below, if higher-income families cut their spending to a greater extent, the sample frame could cause us to overstate the drop in spending. Thus, the net effect of these biases on our spend estimates is ambiguous.

Third, at the time of this release our preliminary data only cover the initial phase of the pandemic. Spending changes, and how these vary with household characteristics, may evolve over time particularly as income disruptions become more widespread.

In the future, we will be able to partially address these three limitations by looking at a longer time-period of data and examining checking account transactions to provide an integrated view of income and spending.

We have four main findings. First, we find that average weekly household credit card spending fell by 40 percent year-over-year by the end of March 2020, coinciding with a dramatic increase in COVID-19 cases, social distancing policies, and job losses. The magnitude of the spending drop is enormous; it is eight times larger than the spending drop typically observed among UI recipients in the first month after job loss. Second, spending cuts on non-essential goods and services account for nearly all of the total spending decline. Spending on essentials initially spiked 20 percent before falling back, while spending on non-essentials declined by 50 percent. Third, spending dropped substantially for households across the entire income distribution, with slightly larger drops for higher-income households driven by cuts in non-essential goods and services. Fourth, spending dropped dramatically for workers in all industries of employment. Similar drops occurred in industries with high and low rates of job loss as of April 2020.

In summary, we provide evidence suggesting that, as of the second week of April, the 40 percent drop in consumer spending appears to be driven to a greater extent by the pandemic and social distancing policies implemented across the country to prevent its spread and to a lesser extent by the initial round of income losses. However, as the pandemic unfolds, the balance of factors contributing to spending behavior could change dramatically. We will continue to track and disentangle these dynamics over time using administrative banking data.

Figure 1 plots the year-over-year percentage change in weekly credit card spending in 2020 and in 2019, and Figure 2 shows levels of average weekly credit card spending in 2020 and in 2019. 

Changes in spending follow a distinctive pattern — spend is stable through the beginning of March, then declines precipitously by 40 percent relative to 2019 from the second through fourth week of March. It then appears to stabilize at this lower level in the first two weeks of April.  The size of the spending drop is largely consistent with other estimates from similar administrative data sourcesduring the same time frame.