Using high-frequency data for real-time tracking of the economic impact of COVID-19 on the District of Columbia

The COVID-19 pandemic has wreaked havoc on US national, state, and local economies. One of the difficulties in assessing the extent of the economic impact is the lack of timely data. While measures to control the pandemic rapidly destroyed jobs in the retail and hospitality and leisure sectors, official US Bureau of Labor Statistics figures on jobs at the national level were not available until a week after the end of the month when the jobs were lost.  And at the state and local level, the jobs numbers are available two are more weeks after the end of the month.  Lag times for personal income and gross domestic product (GDP) measures are even longer. Initial estimates of national GDP are not available until a month after the end of a quarter, and it is even longer for state and local governments. For example, the US Bureau of Economic Analysis (BEA) published 1st quarter personal income figures for states and the District of Columbia on June 23, almost three months after the end of the quarter, and first quarter GDP figures for states and the District will not be available until July 30th.

To track the unfolding impact of the pandemic, we have used various high-frequency data, including daily and weekly unemployment claims, smartphone counts in the District of Columbia, and credit card data on expenditures. Below we described the trends for the smartphone counts and credit card spending before and after the start of the lockdown to control the pandemic.


Daytime District population, which includes commuters and tourists and almost doubles the resident population, drives the economic activity in the District. So, tracking the impact of the pandemic on daytime population is a key measure of the pandemic’s impact on DC’s economy. Figure 1 below shows the smartphone counts in the District from January 2017 through June 2020. With schools and businesses closed, DC saw its lowest daytime population numbers, by a wide margin, since the data was first collected in January 2017. The data, provided to the District by Thasos, shows a 69% drop in the number of people in DC compared to the same period the year prior (April 1-June 1). To put that in perspective, the drop from the historically highest average week for DC (first week in April AKA spring break), to the lowest average week (winter holidays/New Year’s Day), is 37%.

Figure 1: DC Average Daytime Population by Week

daytime pop

Tableau Link

When looking at specific days, blizzards and Christmas in DC have traditionally been the lowest days at 430k-450k daytime population, and the COVID-19 lockdowns have seen days in the 300k range.

Note: The data received by the District is one aggregate number per day and is therefore completely anonymized. The data pulls from a geofence that is aimed at capturing commuters and while it captures most of the city, it does not account for every person in DC every day.

Credit Card Data

Credit card spending data from Earnest Research, which is aggregated and stripped of any personal identification information, give a real-time view of how spending has declined during COVID-19. As Figure 2 shows, in DC total spending has fallen by about 30% since April 15, 2020 compared to the same period 1 year before.

Figure 2: DC Credit Card Spending, All Categories

DC All Spending

Tableau Link

As Figures 3-5 shows, some sectors had larger declines than others. Two of the hardest hit sectors are restaurants and hotels. Figure 3 shows that restaurant spending for the week of June 17 is 46% below the same period last year, while Figure 4 shows that hotel spending is almost 90% below the same period last year. On the other hand, Figure 5 shows that grocery spending soared at the beginning of the lockdown, rising as high as 45% in the first week of April compared to the same period previous year. Grocery spending has gradually fallen back to just above pre-pandemic lockdown levels.

Figure 3: DC Credit Card Spending, Restaurants

dc restaurant spending

Tableau Link

Figure 4: DC Credit Card Spending, Lodging

dc hotel spending

Tableau Link

Figure 5: DC Credit Card Spending, Grocery

dc grocery spending

Tableau Link

DC Spending Relative to US and other Jurisdictions

National credit card spending data has basically recovered to what it was in 2019. Cities are experiencing much larger declines due to loss of commuters and having a different mix of businesses compared to suburbs/rural areas. Figure 6 shows DC compared to a select group of cities. NYC has seen the largest total spending decline of any large city with a ~50% drop. DC has been down approximately 30% and Los Angeles down ~10% during this period.

Figure 6: DC Credit Card Spending Compared to Other Jurisdictions

dc compared

Tableau Link

DC’s $15 Minimum Wage: The Commuter Effect

Last week, we presented an overview of the effects of DC’s $15 minimum wage (full paper). Part two of our analysis focuses on “The Commuter Effect”. DC is surrounded by higher population jurisdictions that have increasingly lower minimum wages when compared to DC. This incentivizes more nearby Virginia and Maryland residents to compete for employment in DC. The result of this competition will force some DC residents who previously would have been able to find jobs in DC to have to look elsewhere.


VA: Fairfax County, Arlington County, Alexandria   |   MD: Prince George’s County, Montgomery County

As the above chart shows, DC residents make up half of those working in DC and earning $12.50/hour or less. They make up a much smaller percent of those working outside DC. As DC’s minimum wage continues to increase to $15/hour, the group working outside DC will have greater and greater incentive to find work in DC. This will change the proportion of those “Working in DC” to look more like the group that is currently “Working Outside DC,” and that means proportionally fewer DC residents.

Job Losses

The commuter effect is the main reason that DC residents will lose 82% of all jobs lost in DC due to the minimum wage increase. Our model predicts by the year 2026, 2,489 total jobs will be lost, with 2,046 of those jobs previously being held by DC residents. Without the commuter effect, our model still estimates that there would be job losses as businesses and consumers react to changes in prices due to the minimum wage increase, but the commuter effect concentrates the losses on DC residents.


What exactly is this data?

American Community Survey data was used to show where people live and work in the DC area. For a similar take on this data, see our previous post on DC workers and where they come from.

Where District workers live and the $15 minimum wage

The country is debating a $15/hour minimum wage and a ballot proposal, if approved, will place D.C. among the company of Seattle, San Francisco, and Los Angeles, which have already raised their minimum wages to $15/hour. If this happens, whose wages will be affected? We looked at D.C. workers who earn up to $15 an hour and where they live. It turns out, a majority of the workers who currently receive an hourly wage under $15 are not D.C. residents.

Using American Community Survey 2013 data, we found that almost 70 percent of D.C. workforce is comprised of out-of-state residents (roughly 550,000 out of 800,000). Furthermore, there were 50 percent more out-of-state resident workers than D.C.-resident workers who earned between $8 and $15 an hour.

• 550,000 Total out-of-state residents working in D.C.
• 250,000 Total D.C.-residents working in D.C.
• 60,000 Out-of-state residents who work in D.C. and earn between $8-15/hour.
• 40,000 D.C. residents who work in D.C. and earn between $8-15/hour.

Of the approximately sixty thousand under-$15/hour- workers who commute to the District, 63 percent come from the Maryland counties closest to D.C., especially Prince George’s county. Northern VA residents account for another 20 percent. The remainder commute from further-away places. This composition of residency is similar to the share among the higher income commuters.



What exactly is this data?
Data on where people live and work are from the 2013 American Community Survey (ACS) with a margin of error of +/-11%. This range does not overpower the effect for this research. The number of D.C. jobs, 800,000 include self-employed and military. Our monthly statistics on the jobs in the District is lower at about 750,000 because it excludes these two groups. We excluded from our analysis people making less than $8/hour—the minimum wage in D.C. is above that, which suggests that these people won’t be affected by another hike in the minimum wage.

Growth in Master’s Degree attainment in DC

We know that the DC metro area is home to a greater share of college graduates than the nation as a whole. We’ve been wondering, though, how the education levels of District residents have changed as the city has gained more residents and seen changes in its job market.

We looked at educational attainment in the District since 2008 and found that while the portion of residents with a bachelor’s degree has remained about the same, there has been a meaningful increase in the percent of residents with a Master’s degree. In 2008, 15 percent of District residents had a master’s degree. That number increased to 19.5 percent by 2013. This increase was greater than the increase nationwide.

District of Columbia 2008 2009 2010 2011 2012 2013 Margin     of Error Change
Less than high school 14.2% 12.9% 12.6% 12.8% 11.4% 9.9% +/- 2.2% -30.3%
High School Graduate 19.8% 20.0% 20.3% 17.7% 18.4% 18.6% +/- 0.8% -6.1%
Some college, no degree 14.7% 16.0% 13.8% 14.2% 14.0% 13.4% +/- 0.8% -8.8%
Associate’s degree 3.0% 2.6% 3.2% 2.8% 3.2% 3.1% +/- 0.5% 3.3%
Bachelor’s degree 21.6% 20.5% 23.2% 23.3% 23.0% 22.7% +/- 1.3% 5.1%
Master’s degree 15.0% 15.7% 15.3% 17.3% 17.6% 19.5% +/- 1.0% 30.0%
Professional school degree 7.4% 8.3% 8.1% 8.0% 8.7% 8.9% +/- 0.7% 20.3%
Doctorate degree 4.3% 4.0% 3.6% 3.9% 3.7% 4.0% +/- 0.4% -7.0%

The District now has a greater proportion of residents with a master’s degree than Montgomery County and is closer to Fairfax County than in 2008. The interactive chart below can show other local educational attainment trends too.

(view interactive here)

Dashboard 1

What exactly is this data?

  • Educational attainment was found using American Community Survey (ACS) data. ACS data is provided by the U.S. Census Bureau. Educational attainment is defined as the highest level of education attained by an individual.
  • The reason for choice of surrounding counties has to do with population size and related margins of error.
  • The reason for choice of years has to do with a survey question change that would have made comparing data prior to 2008 less reliable.