COVID-19: The Fall And Rise Of Jobs

COVID-19 has put a lot of people out of work.  In many cases states and jurisdictions have forbidden certain businesses from operating, which obviously makes it hard to stay employed if you work at that business.

In other cases businesses have laid off workers or closed simply because people have been obeying stay at home orders and stopped frequenting them.  I posted about unemployment from COVID-19 back in May, and boy have things changed. 

The official July unemployment numbers show the unemployment rate fell to 10.2%, from 11.1% in June.  Things seem to be getting better, for now.

I found a cool new mapping site that shows this rise and subsequent fall of the unemployment rate in bi-weekly intervals at a county level for the entire United States.

The Map

The map is hosted by Sites U.S.A. and uses data from Applied Geographic Solutions.  Of note, the AGS data is not the official unemployment data as recognized by the U.S. government.  That data comes from the Bureau of Labor Statistics, whom I’ve posted about before.  But in general the AGS data tracks very closely and their methods have shown results on par with BLS data. 

Enough already, here’s the map.

Notice the chart on the left that shows the unemployment rate in 2 week intervals as well as the total number of unemployed. 

Please stop believing the media when they say “40 million Americans are unemployed because of COVID-19”.  Many big media outlets are still saying this and it’s a lie!  They’re practicing shoddy journalism. 

Yes, over 40 million American have applied for unemployment benefits since COVID-19 started, but way more than half of them are back at work.  As you can see the current number of unemployed Americans is around 16.3 million, according to the official BLS numbers.  That link shows the official data, so don’t let the media continue to try to deceive you.

Sixteen million people out of work is still not good, but a far cry from 40 million, which if true would be an unemployment rate of about 25%! 

Get Clicky With It

Back to the map.  You can click on any county and the chart on the left will adjust to show that counties respective unemployment rate throughout the time frame.  It will also compare it to the general rate for the state it resides in as well as the U.S. rate as a whole.

The key to this map is the blue “play” button in the lower left.  Click that button and watch the unemployment rate change in 2 week intervals from early March till present for every U.S. County.  As lockdowns started easing in June and July, unemployment really started to drop across the country. 

I find it especially interesting to see state borders show up so clearly.  This is likely due to different state policies about which business are allowed to be open.  Or it could be due to the amount of unemployment benefits provided by each state.  We’ve all heard the cases of those who were collecting more from unemployment than they made at the job they lost.

Sentiment Mapping

In the upper left of the chart box on the map, if you click “unemployment data” you’ll notice that you have another option – “social sentiment”. 

Here’s what the social sentiment map looks like:

They use a simple 5 level rating system with “positive” as the highest rating and “negative” as the lowest.  It’s based on data from a company called Spatial.ai who gather information from social media using artificial intelligence. 

As the map says it uses the “VADER (Valence Aware Dictionary and Sentiment Reasoner) sentiment model”, which is a “sort of” standard for gauging sentiment.  You can read dorky papers about it if you’d like.  Again, click the blue play button in the bottom left and you can watch an animation of sentiment anywhere in the country play out. 

I have some problems with this analysis because it only uses social media as the input data.  Let’s face it, millions and millions of people are not on social media, and the ones who are… well, don’t get me started. 

Yes I’m on it, but mostly to promote my blog and graphic arts businesses.  Not to bully and berate people. 

Bottom line, I take this analysis with a grain of salt because it does not pull from a cohesive and inclusive sample of people across the country.  But it’s still neat to look at because it’s on a map, and I love maps 🙂 

I hope you find this post interesting and as always I’ll be on the lookout for cool mapping sites that show data related to money and all things financial.

* I’ll be doing some very analog outdoor adventuring this week and will get to comments as soon as I can.