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RESEARCH Local Commerce Data Series: Pandemic Spending

COVID-19 has rapidly transformed everyday life. While the scope of the pandemic is global, consumers experience the economic impacts locally.

To help decision-makers understand the impact of the COVID-19 pandemic on local economies, we created a local commerce data series which provides a place-based view of local spending. Based upon transactions made by over 70 million de-identified credit and debit card users a month on average, the series provides a view of local commerce spending growth.

The downloadable data and charts capture year-over-year growth rates and growth contributions for local commerce spending for 16 metro areas. The "national" view is constructed as the aggregate trend across these 16 metro areas. For all geographies, growth is broken out by consumer age, product type (e.g. restaurants), and channel (i.e. online/offline) to help local stakeholders better understand how consumer spending varied prior to and over the course of the pandemic.

Map of America

 With spending growth continuing to decline after October 2020, cities are seeing their lowest growth rates since before July 2020

All CBSAs still experienced sharp spending contractions in April


While online growth continues to be positive over time, overall growth has been dominated by contractions in offline spending

While online growth continues to grow over time, overall growth has been dominated by contractions in offline spending.


Despite rapid growth during the summer of 2020, spending on general goods (e.g. department stores, large online retailers) declined notably in Q4 2020


Grocery is the only product type to have consistently seen positive spending growth throughout the pandemic chart

We hope these data can provide a better understanding of current local economic conditions and inform ongoing efforts to aid the recovery of local economies.  Let us know of any feedback or questions by emailing institute@jpmchase.com.

Frequently Asked Questions


We thank Chris Wheat, Marvin Ward, Lindsay Relihan, James Duguid, Anu Raghuram, and Bryan Kim for their substantial contributions to the production and analysis of this data series. We also thank colleagues at the JPMorgan Chase Institute for their comments and suggestions.