Tag: #Datadump

Thursday Data Dump: Foreclosures in Minneapolis in 2016

As today’s data will illustrate, foreclosures are not distributed throughout the city equally. So here are a couple of things to keep in mind while sifting through this data table.

First, 37 percent of the foreclosures in Minneapolis resided on the north side of the city in 2016 – 22.4 percent of the foreclosures were in the 4th Ward and 14.6 percent of the foreclosures were in the 5th Ward.

Second, these were the only two wards with a foreclosure percentage greater than 10 percent. Of course, these two wards have been like this for sometime.

I wrote about this very subject a few times back in 2015. As I explained back then in A Comparison of Minneapolis’ Foreclosure Rates by Ward and Foreclosure Rates: Wards 4, 5, and 10 from 2006 to 2015, the 4th and 5th Wards accounted for about 40 percent of the foreclosures in the city. And as this current data illustrates, these two wards still account for about the same percentage.

Minneapolis: 2016 Foreclosure Data

Ward 1st Quarter 2nd Quarter 3rd Quarter 4th Quarter Total Percent
1 3 7 8 5 23 6.71
2 6 3 4 1 14 4.08
3 2 4 4 8 18 5.25
4 26 16 19 16 77 22.4
5 19 17 7 7 50 14.6
6 3 5 1 1 10 2.92
7 2 4 4 3 13 3.79
8 9 7 8 5 29 8.45
9 13 5 7 3 28 8.16
10 3 1 4 2 10 2.92
11 6 8 4 3 21 6.12
12 5 7 9 12 33 9.62
13 4 6 4 3 17 4.96
Total 101 90 83 69 343 100.0

(Source: City of Minneapolis)

So as far as proportionality is concerned, not much has changed.

The bright side is that foreclosures have definitely decreased in both wards. However, the question is what will happen to these wards when the market decides to take another nose dive?

The 4th and 5th Wards are not as economically stable as other parts of the city. But the point here is that education, as we’ve seen, provides greater earnings power, and thus greater economic stability and security. Of course as the readers of this blog know very well, earnings increases with education according to the data that has been observed so far.

So it should follow that more education will facilitate greater earnings which will in turn facilitate greater economic stability and security which in turn will decrease foreclosures.

Going forward, what does the foreclosure data look like for 2017 and how does it compare to 2016? And what does the system’s behavior of this foreclosure data look like over the period of a few years? Are foreclosures decreasing throughout Minneapolis and are there any wards  that are bucking this trend? And the big question, will this even have an impact on the mayoral and city council races?

 

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

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

 

Photo Credit: Wikimedia Commons

 

 

 

 

 

 

Copyright ©2017 – The Systems Scientist

Data Dump Saturday: United States Earnings by Education and Sex, 2015

In today’s data dump, there are three observations to keep in mind while sifting through the data. First, Graph 1 through Graph 4 illustrate that as education increases, earnings increase. This is the case for both men and women. Mathematically these observations are confirmed by a positive slope.

Graph 1

Second, there is an obvious earnings discrepancy between men and women at each level of the education ladder. As an example, the earnings of “Some College or associate’s degree” for men, $41,407, is slightly lower than the earnings of a “Bachelor’s degree” for women, $41,763. This is a fascinating statistic.

It should be noted that the purpose of this data dump is to provide information; the purpose of this data dump is not to take a side on earnings differences between men and women, nor is it to examine why it is so.

With that said, it should be noted that these discrepancies will change, increase or decrease, at different levels of the Super-system, which is the United States. For example, earnings differences between men and women will vary at the regional, the state level, the county, level, the city level, the zip code level, and so and so forth. And these earnings differences will change depending on geography, education (obviously), and industry and type of job, just to name a few parameters.

Lastly, Graph 2, Graph 3, and Graph 4 are simply partitions of Graph 1. That is, the three following graphs have been created to help the reader parse out the data a bit more clearly, i.e., make the data less busy. And it provides the reader with the opportunity to see the earnings behavior of the United States from different perspectives, while also providing the capability of comparing data in Graph 1.

Here’s Saturday’s data dump on 2015 earnings by education and sex in the United States.

Total Earnings by Education and Sex

 

Graph 2

Male Earnings by Education and Sex

 

Graph 3

Female Earnings by Education and Sex

 

Graph 4

 

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

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

 

Photo Credit: Flickr

 

 

 

 

 

 

Copyright ©2017 – The Systems Scientist