Covid-19 And Unemployment Analysis

Yesterday we visualized Covid-19 cases, deaths and unemployment across the nation. We also learned from various news sources that on Friday, we will learn the latest unemployment numbers. Some analysts are bracing for unemployment figures to be 16% or above. If that holds true, the unemployment rate will be close to what it was during the Great Depression and significantly higher than in recent years. Also, some states have opened their economies.

Part of the national debate remains whether if it is too soon to open or not fast enough. One of the driving forces behind the demand to get businesses open again, at least for the municipalities, is the cost of unemployment benefits. The sooner workers get back to work the less stress on the unemployment costs.

In preparing the visualizations for yesterday’s post, I compiled a list of states with their corresponding pandemic reported cases and deaths. I also added the unemployment numbers to the list to try to see if a correlation existed.

Finally, I attempted to add the metric of whether the states were open for business, closed or in the process of opening again. The problem with quantifying the open for business status for each state is that there is no cohesive plan on how and what constitutes opening the economy. Each state has different standards and plans in place.

For that reason, I manually set the status for each state’s economy by taking the best guess approach as to what constitutes an open economy. Each reader may have a different understanding of whether a state is open for business or not so it will be up to them to apply their own metric to the data.

With the data set in hand, I went about identifying the best and the worst for each metric, i.e. number of cases, deaths and unemployment. But to have a better understanding of what the data represents I converted the raw numbers into rates based on a state’s population. For the unemployment numbers I looked at workers approved into the unemployment benefits programs of that state to create the rate for unemployment.

This allows us that ability to compare the results apples-to-apple without the skew effect of larger populations versus smaller ones. From there I picked the best results (in green) and the worst (red) for each metric.

The first obvious thing I noticed is that there appears to be no correlation between the mortality rate from the virus and the states that are open for business. The caveat being that some of the states marked as open may have recently opened.

But the state with the best metrics seems to be Wyoming which is open for business but also has the lowest population of the states. It is important to note that the number of reported cases is based on the number of tests conducted by the state’s officials. As such, it is impossible to draw conclusions.

However, the exercise remains important as there are no other better models to use, yet.

California has the largest population and the highest unemployment claims. But its unemployment rate, at 13.98% is well below Michigan’s at 21.77%

New York, which is closed for business, has the highest Covid-19 cases and death of all states. Its mortality rate by population is the highest as well.

At least 15 states have reported close to zero rates on mortality compared to their populations although all states have reported deaths caused by the pandemic.

Nationally, as of Sunday’s numbers, the nation has a mortality rate of 0.02% of its population due to the virus.

More data is still needed to fully understand whether closing or opening the state for business is correlated to the number of cases reported and deaths. But this quick analysis gives us a first look at what may be happening.

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