Tag: Betsy Hodges

Wednesday Data Dump: The Most crime ridden neighborhood in Minneapolis in 2017

There are a couple of things to consider while sifting through today’s data. First, crime increases as the year progresses. This is a pretty common pattern in cities in the midwest, where temperatures change as the seasons change and there can be a 120 degree temperature difference between the middle of summer and the middle of winter. Second, larceny is the most abundant crime in the Downtown West neighborhood at 73 percent. Robbery is second at 11.2 percent.

Table 1: Crime in the Downtown West Neighborhood

Month Homicide Rape Robbery Aggravated Assault Burglary Larceny Auto Theft Arson Total
Jan 1 5 19 9 8 139 6 0 187
Feb 0 2 19 13 8 137 9 0 188
Mar 0 6 14 7 6 158 6 0 197
Apr 0 0 13 20 12 145 10 0 200
May 0 4 35 17 4 133 3 0 196
June 0 7 33 9 13 155 7 0 224
July 1 4 30 18 8 195 6 0 262
Total 2 28 163 93 59 1062 47 0 1454
(Crime/Total) x 100% 0.14 1.93 11.2 6.40 4.06 73.0 3.23 0 100

(Source: City of Minneapolis)

And finally, there have been 1,454 reported crimes in the Downtown West neighborhood through July 31st according to the data in Table 1. Minneapolis as a whole has experienced 13,511 reported crimes through July 31st. With a simple computation, Downtown West has experienced approximately 11 percent of the reported crimes in the City of Lakes.

Comparing Downtown west to the other 6 neighborhoods in Table 2, a simple computation will show that Downtown West contained about 38 percent of the reported crimes in the Top 7 neighborhoods. So two questions reveal themselves immediately. First, is it normal for Downtown West to contain 11 percent of the crimes in Minneapolis? What would the historical data say? And second, is it normal for Downtown West to contain 38 percent of the reported crimes in the Top 7 neighborhoods? Again, what would the historical data say?

Table 2: Crime in the Top 7 Neighborhoods 

Neighborhood Homicide Rape Robbery Aggravated Assault Burglary Larceny Auto Theft Arson Total
Downtown West 1 4 30 18 8 195 6 0 262
Whittier 0 1 6 5 12 59 5 0 88
Loring Park 0 2 7 3 2 55 3 0 72
Longfellow 0 1 6 2 12 46 3 0 70
Lowry Hills East 0 3 3 6 11 43 3 0 69
Marcy Holmes 0 1 5 2 6 40 12 0 66
Jordan 0 0 8 17 10 22 5 1 63
Total 1 12 65 53 61 460 37 1 690
(Crime/Total) x 100% 0.14 1.74 9.42 7.68 8.84 66.7 5.36 0.14 100

(Source: City of Minneapolis)

Downtown West was the most crime ridden neighborhood in Minneapolis. And it has been this way for sometime. This is nothing new. Although Graph 1 doesn’t provide contrasting, dynamical data with any of the other neighborhoods in Minneapolis, it does provide a few details concerning this system behavior nonetheless. For example, it appears as though there have been more reported crimes between 2014 and today than there were between 2010 and 2013.

This is indeed the case. Between 2010 and 2013, there were a total of  9,293 reported crimes in the Downtown West neighborhood; and between 2014 and today, there have been a total of 9,598 in the Downtown neighborhood (a 3.3 percent increase for those keeping track), and there are still 5 months of crime data left to report. This fact illustrates that crime has not only increased from last year, but it has been increasing for a longer period time. And so what will this mean for the Minneapolis mayoral race and city council races?

A couple of tidbits to ponder until the next data dump. Downtown West resides in Ward 3 and Ward 7. Ward 3 is represented by Jacob Frey. Council Member Frey is currently running for Mayor of Minneapolis. Second, Ward 7 is represented by Lisa Goodman, who is also up for re-election. Apparently, Lisa Goodman likes to put her already chewed gum in another person’s hand, i.e., Teqen Zéa-Aida, who is also running for the Ward 7 city council seat. Weird. Perhaps focusing on crime would be better time spent?

 

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

Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University. He is also a professional member of the Society of Industrial and Applied Mathematics and the International Society for the Systems Sciences and a scholarly member of Omicron Delta Epsilon, which is an International Honors Society for Economics. 

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

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Copyright ©2017 – The Systems Scientist

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