To better understand the economic impact of COVID-19, researchers across the world have been closely monitoring businesses, employees, and national economies to interpret both the magnitude and nuances of this economic crisis.
To fuel this research, SafeGraph has made available various anonymized datasets on foot traffic and social distancing. To date, the SafeGraph COVID-19 Data Consortium has over 4,000 members, including organizations like the CDC, White House Council of Economic Advisors, and Federal Reserve, as well as academic institutions like MIT, Harvard, Northwestern, and the University of Chicago.
Leveraging this consortium data, researchers have been able to understand the impacts of the pandemic on businesses, individual workers, and the employment markets as a whole. Here’s 3 interesting takeaways that academic economists at MIT, U-Chicago, and Northwestern found recently from their research.
As stay-at-home orders and social distancing measures continue to persist, brick and mortar retailers in particular face a lack of traffic at their once-populated locations. Aiming to understand at a more granular level the impact of this reduced foot traffic on varying brands and businesses, researchers from the Massachusetts Institute of Technology conducted a study examining trends in retail foot traffic across restaurants. Using SafeGraph’s restaurant foot traffic data, researchers Tucker and Yu were able to illuminate the causal effect of in-restaurant dining bans on overall restaurant traffic, in the early stages of these executive orders (March/April).
The paper’s key findings can help future businesses tailor business strategies to adapt to social distancing guidelines while maintaining business operations. Notably, the researchers found:
Any ordinary consumer can observe that restaurant visits have declined dramatically, though this research shows that these impacts would have been salient even without dining bans. Further, all restaurants - even those with strong, established brand names - were impacted similarly by the pandemic. This study shows that virtually all restaurants should be planning for contingency plans throughout the duration of the pandemic; with or without dining restrictions, the entire food industry must be prepared to bear the brunt of this economic downturn.
One of the most salient impacts of the pandemic has been the closure of non-essential businesses and the subsequently skyrocketing unemployment rates. While some companies have managed to transition to a stable work-from-home environment, others like retailers and manufacturers have been forced to furlough or lay off their employees. Researchers from the University of Chicago and the Federal Reserve Bank of New York examined the impacts of the pandemic on various types of workers, notably focusing on disparities between low-income and high-income workers.
With SafeGraph social distancing data, the research team was able to understand the impact of stay-at-home orders in certain geographies. Specifically, they were able to isolate regions with less pre-virus work-from-home employment, aiming to find the extent to which these areas were affected in comparison to other geographies.
A key finding from this study was that less-educated, lower-income workers were impacted most by social distancing policies. While higher-income workers typically work at companies with the ability to transition to a work-from-home environment or in more essential roles, lower-income workers tend to occupy less essential roles that are first to be let go. Non-college educated workers experienced a 4 larger decline in employment relative to those with a college degree.
These startling findings play an important role in shaping future economic stimuli and unemployment policies, illuminating that the pandemic’s disproportionate impacts warrant a strong, tailored response for the newly-unemployed.
With most states mandating the closure of non-essential businesses, companies have naturally been forced to resort to remote work. Besides cabin fever and “Zoom fatigue,” the transition towards remote-first work poses disparate difficulties towards different segments of the labor market. Researchers from Northwestern University and MIT aimed to uncover these impacts, using SafeGraph data to fuel their economic research on the supply-side impacts of COVID-19.
SafeGraph’s anonymized foot traffic datasets helped these researchers examine the disparate impacts of the pandemic on essential and non-essential workplaces, using metrics like dwell time to better understand the demand-side influences impacting supply-side employment market trends.
Through this analysis, the research team uncovered highly noteworthy findings surrounding the employment disruptions caused by the pandemic. First, they found that sectors that are less capable of working from home experienced significantly greater declines in employment. This resulted in lower revenue, market performance, and foot traffic (as validated by SafeGraph data). This disparate effect on the employment markets trickled down to employees as well, with the researchers witnessing a higher subsequent unemployment rate for lower-paid workers, especially those with children.
These insights, combined with those surrounding businesses and individual employees, show that the economic impacts of the pandemic are much more nuanced than previously thought. While nearly all individuals are impacted economically to some extent by COVID-19, there are certain businesses and workers whose positions put them in a greater long-term position of risk. As the pandemic continues to disrupt healthcare systems and economies alike, economic policymakers should reference these research findings to better inform funding and stimulus decisions. With accessible research and data, the US can ensure that this medical disaster does not become an economic disaster.
Academic researchers, non-profits, and government organizations: Join SafeGraph’s Data Consortium to get SafeGraph data at no-cost.
If you are with a for-profit business, please contact our team today to learn how these datasets can help your business navigate this unfolding health and economic crisis.
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