How does Hodges’ unemployment rate compare to Rybak and Belton’s unemployment rates?

By Matt Johnson

On January 2, 2014, Betsy Hodges became Mayor of Minneapolis. And in January of 2014, she acquired a 4.6 percent unemployment rate. In other words, in January 2014, the average Minneapolis worker had a 4.6 percent chance of being unemployed. Almost 3 years later, the unemployment rate for Minneapolis in December of 2016 was 3.2 percent. This means that unemployment decreased by more than 30 percent during her first term as Mayor.

But if we look at and compare the Hodges, Rybak, and Belton administrations, we will see that Mayor Hodges doesn’t have the highest reduction in unemployment for a first term Minneapolis mayor. First, we will look at unemployment data for Mayor Hodges first term.

Here’s Graph/Data Table 1 for Mayor Hodges 3 years so far:

minneapolis-unemployment-rate-for-hodges-i-with-data-table-dwm
Graph/Data Table 1

Comparing Mayor Hodges to the previous 2 mayors – Sharon Sayles Belton and R.T. Rybak – with unemployment data from the Bureau of Labor Statistics, we found that Mayor Hodges so far has had the largest decrease of an unemployment rate over the course of being mayor.

However, Mayor Hodges has been in office just over 3 years while Mayor Belton served two-terms (8 years) and Mayor Rybak served three-terms (12 years). So comparing apples to apples, and oranges to oranges is important. In other words, this analysis won’t compare one-term to two-terms, one-term to three-terms, and so on and so forth.

Rather, since Mayor Hodges has only accumulated data for less than one term, we are only going to compare first terms. Thus, if we look at Mayor Sharon Sayles Belton’s first term, we will see she started her first term with an unemployment rate of 4.4 percent and ended her first term with an unemployment rate of 2.4 percent. This means unemployment decrease by more than 45 percent under Mayor Belton’s first watch.

Here’s Graph/Data Table 2 for Mayor Belton’s first term:

minneapolis-unemployment-rate-for-belton-1-with-data-table-dwm
Graph/Data Table 2

Finally, if we look at Mayor R.T. Rybak’s first term, we will see he started with a 5.1 percent unemployment rate and ended his first term with an unemployment rate of 3.6 percent, which was a 29 percent decrease in unemployment.

Here’s Graph/Data Table 3 for Mayor Rybak’s first term:

minneapolis-unemployment-rate-for-rybak-i-with-data-table-dwm
Graph/Data Table 3

Of course, this data does not show us which market inputs are correlated with unemployment behavior. However, the multivariable graphs do show us how the unemployment market behaved during each first term. For example, we can observe unemployment with respect to month and year; and we can compare unemployment with respect to month and year for each mayor, while comparing one mayor’s first term to another mayor’s first term.

Matter of fact, this is how we derive how much the unemployment rate has decrease over the length of time of the first term. Let’s use Mayor Hodges as our example, although this short method can be used to find Mayors Belton and Rybak’s unemployment rate reduction as well.

What we do is subtract the month of the first term by the last month of the first term, and divide that value by the month of the first term. Does this make sense? In other words, take 4.6 minus 3.2 and divide by 4.6. This gives us 30.4 percent.

I have provided an additional table for the reader which compares the total unemployment reduction for each first term:

minneapolis-mayor-first-term-total-unemployment-perde-dwm
Graph 4

Using this method, we could also find out how much unemployment decreased or increased every two years. There’s a lot of information hidden in the data that can be observed and utilized with a little mathematics.

Final thought, can any of these 3 mayors take credit for the behavior of unemployment during their respective times in office?

As I tell my readers in these articles and in private conversation, urban environments are probabilistic systems. They are not causal systems. So it is not the case that, for example, Mayor Hodges could apply a specific policy and expect it to cause a specific outcome with 100 percent certainty. That’s now how these urban systems work. Rather, it would more than likely be the case that Mayor Hodges would input a particular policy and maybe an expected output would produce a particular outcome.

But that’s still not quite correct, because it asserts a particular input can be traced to a particular output and that type of observational sophistication is not quite possible at this date and time (a policy acts a lot more like a roll of a dice). To pull off something like that would take a much more sophisticated form of systems analysis and mathematics beyond this article.

All we know from this short analysis of the data is that the unemployment rate decrease by more than 30 percent during Mayor Betsy Hodges time in office, so far. But in order to achieve the 45 percent reduction by Mayor Belton during her first term, the unemployment rate would need to decrease to at least 2.5 percent. That’s an entire percentage point with a little more than 10 months remaining in the 2017.

 

Matt Johnson is a writer for The Systems Scientist and the Urban Dynamics blog; and is a mathematical scientist. He has also contributed to the Iowa State Daily and Our Black News.

You can connect with him directly in the comments section, and follow him on Twitter or on Facebook

You can also follow The Systems Scientist on Twitter or Facebook.

Photo credit: Pixabay

 

 

 

 

Copyright ©2017 – The Systems Scientist

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