Project Proposal (COVID's effect on small businesses)

Domain of Interest

Why are you interested in this field/domain?

1. Every individual is experiencing the effects of the Coronavirus pandemic in some way, shape, or form, just as we all bear responsibility for slowing its spread. Nine months of lockdown, well over a quarter of a million Americans dead, and millions more infected have lead to one of the largest mass casualty events in our history. A brutal virus that relegates individuals to their homes is the enemy of the small business, with tens of thousands closing in the wake of our economic downturn.
2. We know that the recession/depression has resulted in the permanent closure of thousands of small businesses in the wake of COVID-19. What is the scope of this devastation? Is there a business size most likely to close, or is the likelihood of closure more tied to profit/ expenditure per employee? Local businesses are integral to every community, with certain establishments gaining a special or cult status with its residents. What is Seattle without Dick's Drive-In? What about your favorite local coffee shop on the Ave? These establishments who do not have the luxury of being "too big to fail" are currently in a perilous position - what is our government doing about it?
3. The federal response to Coronavirus relief has been highly politicized, with White House aides openly sharing their discontent for “Blue” states. Just as every citizen has to deal with the Coronavirus, we all bear a burden of our federal response (or lack thereof). Does the difference in business closures also fall into these partisan lines? Or, like the virus, do populated/heavily concentrated areas see higher business closures compared to rural America?

Related Projects/Studies

1. PNAS economic impact study on over 5,800 small businesses in the United States
2. Washington Post article detailing permanent closures of small businesses due to COVID-19 (as of May 12th)
3. McKinsey & Co. consulting firm paper on which small businesses are most vulnerable to COVID-19/the subsequent recession.

Data-Driven Questions

1. How many businesses have closed across the US during the pandemic and where are they clustered/located?
2. What was the average income of businesses that closed during the pandemic? (How much profit did these businesses need to be making to stay afloat?)
3. How many people were on the payroll of businesses that closed vs. stayed open?
4. Was there a peak during a specific date for unemployment claims? Or have they remained about the same throughout the pandemic?

Identified Datasets

1. Department of Labor weekly unemployment claims.

• Collected by US DOL
• Our data has 2808 rows, one observation per week since January 7th, 1967
• 11 features broken up between Initial Claims and Continued Claims with sub-headings of Not Seasonally Adjusted (NSA), Seasonal Factors (SF), Seasonally Adjusted (SA), and 4 Week Seasonally Adjusted (SA 4-Week)
• This dataset will let us answer if there was a peak in unemployment claims during the pandemic, and when that peak occurred.

2. Layoffs.fyi provides live tracking of layoffs in tech startups across the globe during the pandemic.

• Collected from multiple sources, with each individual observation cited from a different, but reputable source.
• This dataset has 614 rows since March 11th 2020
• 13 features of Company, Location, Number of those laid off, Date, Percent of workforce laid off, Industry the company served/serves, Source for data, List of employees laid off, Stage, Money Raised, Country, Date added, and reference
• This dataset can give some global context to areas hit hard (in the tech industry) by the pandemic. We can also see if there is a tech business that is essentially "too small" to survive in this recession.

3. Census Bureau provides information about work sectors and how much they were affected by COVID.

• Collected from the United States Census Bureau.
• This dataset has 1905 rows since October 4th, 2020.
• 5 features of Work Sector, Instrument ID, Answer ID (measures the positive or negative effect COVID has had on the business), Percentage (of businesses affected in the selected sector) and Standard Error.
• This dataset can answer questions about what sectors of the American economy were hit the hardest by COVID and which sectors had the most favorable outcomes.