On Wednesday, June 17, 2020 Raj Chetty joined the Princeton Bendheim Center for Finance to discuss new research with John Friedman, Nathaniel Hendren, Michael Stepner, and the Opportunity Insights Team. The new paper uses private sector data to document the real-time impacts of COVID-19 on people, businesses, and communities.
Chetty is a Professor of Public Economics at Harvard University.
Watch the full presentation below and download the slides here. You can also watch all Markus’ Academy webinars on the Princeton BCF YouTube channel.
Economists often study the effects of shocks with household survey data, but these data—while important—have limitations. First, they have time lags and low frequencies. Second, they cannot be disaggregated. Private sector data addresses many of these limitations, but researchers must be aware that a private company’s clients may not represent the general public. In their new research, the Opportunity Insights team takes a series of steps to address this—including benchmarking these data to public sources (see examples)—and protect confidentiality.
In the first few months of the pandemic, spending fell much more for the rich than the poor (top 25% vs. bottom 25%), and the bulk of the reduction resulted from a drop in spending on in-person services. This is true in both percentage terms and absolute terms. This indicates there wasn’t necessarily a reduction in purchasing power. The reduction was related to fears of the virus.
Business revenue dropped more severely in high-income areas. The authors’ interpretation is that this is a supply shock, not a lack of purchasing power. Restaurants, for example, can no longer supply a healthy meal. “A fundamental reason” people are spending less, Chetty says, isn’t because of state-controlled closures. It’s because high income folks are working remotely and being cautious. See changes in NYC small business revenue by zip code.
CARES Act stimulus increased spending, but didn’t fill the hole created by the Covid shock. Stimulus checks did increase spending among low-income Americans, but the vast majority of the increase in spending was on durable goods, not in-person services. For stimulus to have an impact on employment in the short-run, people would have to switch jobs or move.
The Paycheck Protection Program (PPP) had limited impact on employment. The authors suggest that businesses who took the loans didn’t expect to lay off workers to begin with.
Effects of this shock on employment and inequality may be long lasting and require policy interventions. 70% of low-income workers who had jobs in wealthy parts of Manhattan lost their jobs. Chetty cites evidence, from past studies of the Great Recession, that people don’t often move in search of new jobs, suggesting policy intervention may be required. Further, there are potentially big implications for inequality. One example: Low-income students are doing far fewer math exercises on commonly used app than their higher-income peers.