This week the US got a glimpse of how severely the coronavirus pandemic has hurt its economy, with the latest gross domestic product numbers showing a 9.5% drop in the second quarter from the first.
To understand the effects of Covid-19 going forward, however, economists within and outside the US government are parsing very different sets of data.
In addition to the traditional indicators the US Federal Reserve uses to track the economy, it has been looking more closely at real-time data, from credit and debit card transactions to foot traffic at different retailers. These weekly and daily data sets—known as high-frequency data—show that after recovering somewhat from the big slump earlier this year, economic activity has been flagging since the number of Covid-19 cases spiked in June.
“We monitor quite a lot of what we think of as sort of non-standard, high-frequency data,” Fed chair Jerome Powell said at a press conference this week. “That’s become a very important thing, even more important than usual in the work that we do, and what that data shows on balance is that the pace of the recovery looks like it has slowed.”
Take real-time small-business data from sources like Homebase, a free employee scheduling tool. The Fed has been using them to track the impact of the coronavirus pandemic on the labor market and economic activity at a more granular level. They show that after recovering somewhat from the big drop March, business and employment started worsening again in July.
Some of the other new data points show similar changes. “They all pretty consistently tell us the same story, which is that things were improving for two months from mid April to mid June, and then started to move sideways,” said Aneta Markowska, Jefferies chief financial economist. GPS data from Google Global Mobility and restaurant data from the reservation company Open Table are considered the two other main sources of alternative high-frequency data next to Homebase, she said.
Other real-time indicators the Fed is using include job postings from Indeed, local and national transportation data, as well as mobility and foot traffic from the geospatial data company Safegraph.
The use of high-frequency data has also allowed economists to measure how the pandemic is affecting different sectors of the population. An analysis of Safegraph data by the University of Chicago and the Federal Reserve Bank of New York showed workers with less education and in lower-income positions were more affected by social distancing policies and were much more likely to lose their employment compared to high-income and college-educated workers.
Economists are still figuring out how the high-frequency data sets fit in with more traditional economic indicators. “All of it is so new that we really don’t have enough history to determine the relationship between alternative data and government data,” Markowska said.
In the meantime, the frequency and variety of the new data sources are allowing economists to gauge in real time how the economy is reacting to changes, such as economic stimulus funds or the spike in coronavirus cases.