Tag: North Minneapolis

The Bright Side of the Blight Side of Minneapolis

As we know, the 55411 zip code, which is in Minneapolis’ 5th Ward on the north side of the city, has the most depressed economic system in Minneapolis. It has the highest concentration of condemned and vacant buildings; it has the second highest concentration of foreclosures (the 4th Ward has the most); it has the highest unemployment rate in the city; and it has the second highest crime density in the city (the 3rd Ward has the highest).

But we also know from our previous articles that the 55411 zip code is a subsystem of the Minneapolis system. This means that the 55411 satisfies the (3) systems’ axioms:

  1. A system consists of a set of elements.
  2. Elements in a system interact.
  3. A system has a function, or purpose.

It has a system’s boundary and behavior (how a system’s performance changes over time) for which condemned and vacant buildings, foreclosures, the unemployment rate, and crime are all examples of in this economic system. But how does the systems’ behaviors of educational attainment of the 55411 zip code compare to the educational attainment of Minneapolis?

Do the residents of the 55411 experience greater earnings with greater attainment of education? Is it the case that a person from the north side zip code would earn more with a college degree than a person from the north side without a college degree? Is there a correlation between education and earnings in the 55411 zip code?

Graph 1

As Graph 1 of the Minneapolis system illustrates, there is an obvious increase in wages as a person’s education increases. That is, the odds are good that a person with a high school diploma will make more than a person with less than a high school education; a person with some college will more than likely make more than a person with a high school education; a person with a college degree will more than likely make more than a person without a college degree; and a person with a graduate level education will more than likely make more than a person with only a college degree.

And so the question is, will the 55411 zip code follow this system’s behavior? Indeed it will.

Graph 2

Considering the sensitivity of the marketplace on the north side, this is really remarkable. And despite the number of adverse economic conditions in the 55411 zip code, education is still a game changer. The question is now, would this behavior remain stable during a great recession just like a few years ago? And would Minneapolis policy makers utilize this data?

Indeed there are obvious differences in earnings from educational attainment between the 55411 and Minneapolis. But the fact remains, this is a bright side to blight side of Minneapolis.

 

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. 

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

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Photo Credit: army.mil

 

 

 

 

 

Copyright ©2017 – The Systems Scientist

Minneapolis: The tale of two cities 

By Robert J. Garrison

The council’s decision to divest from Wells Fargo because of their investments in the DAPL is just a political ploy by the council. They most likely haven’t thought through the ramifications of that action. The ramifications of a strictly political decision that just harms those living within the community. Yet they made it a political issue to draw attention away from their failures.

2016-11-18-1Aside from the points mentioned above my question to our readers is, how does this divestment vote address the poverty in Minneapolis?

Well, it doesn’t! It’s a political ploy by politicians to divert the focus away from their failures to address the real issues that are affecting minorities living in Minneapolis – poverty. Matt Johnson has pointed this out in his recent blog In Minneapolis, Black poverty is the problem not Wells Fargo.

This inaction of dealing with real issues of those living within the community is why so many voters have become disillusioned with typical politicians and are revolting. People are tired of talk and they want action and they want it now!

This revolt has opened the door for “political outsiders” to enter the local races in Minneapolis. One of those “outsiders” is  Nekima Levy-Pounds who is a Black Lives activist and former president of the Minneapolis NAACP. Whether Levy-Pounds wins or not, the voters can be assured issues that really matter will be at least brought up during the race.

However, as always the elites always find a way to silence or undermine “political outsiders.” We saw this happen to Senator Bernie Sanders when the DNC and Hillary’s campaign colluded to beat Sanders in the Democratic primaries.

Now, pertaining to Minneapolis the same can happen and has happened for decades. Sadly, Minneapolis is a tale of two cities – North Minneapolis and the rest of Minneapolis. It’s always been that way (even while I was growing up in Minneapolis).

North Minneapolis’ problems have been ignored for far too long. The newspapers and media don’t care about the plight going on in North Minneapolis because it doesn’t sell papers or ads. Part of the problem is voting demographics. North Minneapolis only makes up a small percentage of the voting base in the city. Unless Minneapolis begins to act as one community instead of two, the problems of North Minneapolis might never change.

5th-ward-and-13th-ward-crime-pattern-dwmThe only way that Minneapolis can be united as one is if we begin to heal and address the issues that affect us all and come together. Out of sight does not mean out of mind. We must be conscious of the hurting going on around our city. We are our brothers/sisters keeper whether they live next door to us or on the other side of town.

It is only through this united sense of community that we can elect leaders who do not live inside a political bubble that just pay lip service to the voters every election cycle. It’s time to stop playing politics with people’s lives and start serving the community, all of the community. The time is ripe for change, are you ready? are you in?

Matt Johnson also contributed to this article.

Robert J. Garrison is a political and religious writer for The Systems Scientist. You can connect with him directly in the comments section, follow him on Twitter or on Facebook, or catch up on his articles in the Archives.

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

Photo credit: Wikimedia

Graphics Credit: Urban Dynamics

Copyright ©2016 – The Systems Scientist

The Simple Behaviors of Cities

By Matt Johnson

Cities are complex systems with complex and chaotic behaviors, but yet those same systems as philosopher of science Michael Streven’s explains in his book Bigger than Chaos: Understanding Complexity through Probability can contain simple behaviors as well. As Strevens elucidates, “Simplicity in complex systems’ behavior is everywhere.”

Figure 1
Figure 1

As examples, he uses ecosystems, economic systems, the weather, chemical reactions, and societies to explain such simplicity. In his example of societies, he states

…the familiar positive correlation between a person’s family’s social status or wealth and that person’s success in such areas as educational achievement [is a simple behavior].

We have seen simple systems’ behaviors with the graphical information presented time and time again with respect to the systems research of the City of Minneapolis by Urban Dynamics. For example, in a previous post about the foreclosures in the general system of Minneapolis, we saw that although the total foreclosures in the city peaked out around 900 properties in 2008, there has been a fairly consistent decrease over the past 7 to 8 years. Explicitly this is an example of a simple behavior in the system and Figure 1 illustrates this simple behavior.

We have also been exposed to the simple behaviors of some of the subsystems of Minneapolis. For example, we learned that the foreclosure rates of the 2nd Ward in Southeast Minneapolis, and the 4th and 5th Wards in North Minneapolis exhibited different behaviors in their respective locations as illustrated in Figure 2. But adding a bit more systems language, philosophy, and science to our analysis, we now know that the respective behaviors in these subsystems are also simple in nature.

And finally, if we compare the simple behaviors between the general system of Minneapolis and the respective subsystems of Minneapolis, we can see that there are some differences and some similarities. The contrast of the systems’ rates and behavior can provide us with some worthwhile information.

Figure 1
Figure 2

For example, we see a decreasing foreclosure rate in Figure 1. The General Minneapolis System (let’s call it the GMS) is tending downwards towards the horizontal (the x-axis) of the graph. In addition, both the 4th and 5th Wards are exhibiting similar general systems behaviors in their respective subsystems. It appears as though the foreclosures of the GMS and the 4th and 5th Wards are converging if we compare Figure 1 and Figure 2.

As a consequence of this information, are we to assume that as the city goes, the 4th and 5th Wards go? In other words, does the behavior of the 4th and 5th Wards depend on the behavior of the GMS? Do the simple systems’ behaviors of the 4th and 5th Wards reflect the simple system’s behavior of the GMS? Why would we think this?

As we can also see from Figure 2, the 2nd Ward’s behavior is rather flat over the course of the ten years or so. The simple behavior of the 2nd Ward doesn’t seem to be influenced or dependent on the behavior of the GMS. As the GMS is doing its thing, the 2nd Ward is exhibiting completely different behavior. Why might this be?

We must caution ourselves first before we try to answer this question, or any other questions for that matter. We must caution ourselves before assuming too much from the data. If we try to extract more information from the data than we actually can, we risk drawing conclusions that make little sense. Moreover, our overreaching conclusions could have disastrous effects if applied to policy. This data has limits.

Cities can seem a bit overwhelming sometimes. At the ground level, they seem chaotic, and indeed they are. There are a plethora of interactions and activities taking place every second of the day. But the good news is that systems contain simple behaviors in all of the chaos. And the better news is that this simple behavior can be extracted from the chaos and analyzed to provide citizens and policy makers with some much-needed and worthwhile information.

For further reading on similar subject matter, I invite you to read The General System of Minneapolis: ForeclosuresForeclosure Rates: Wards 2, 4, and 5 from 2006 to 2015 and Patterns of the 5th Ward: “Race”.

Remember, you are always welcome to post your comments, thoughts, and questions below. Feedback is always appreciated.

Some Thoughts on Systems

By Matt Johnson

We’ve spent some time talking about elements of systems, but what do we mean by the elements of system? And what are they?

Well, we’ve discussed the foreclosure rates, condemned and vacant buildings (CVBs), the median household incomes, and unemployment rates in North and South Minneapolis, and Minneapolis in general. These are elements of the system of Minneapolis. But more importantly, these are, as this systems scientist believes, the most important elements in the system that have been identified thus far and as of this writing. This is because they play a significant role in the lives of residents (please note that I am a scientist, so I open to changing my mind as the data is presented to me).

And what have we learned from these elements? Well in the case of the 4th Ward, specifically 55412, we’ve learned that the foreclosures rates are higher relative to the rest of the city except when compared to the 55411. 55412 also has a higher than average population of “black” residents, it has a lower than average level of median household income, the education level is lower than average when compared to the rest of the city, and the unemployment rate is higher than average. According to City Data, the unemployment rate was 16 percent in 2013, only second to the 55411’s 21.9 percent.

In contrast, these elements look very different in other parts of the city. As we have learned from the data, the 2nd Ward in Southeast Minneapolis and the 10th Ward in Southwest Minneapolis have much lower foreclosure numbers and percentages than Wards 4 and 5 in North Minneapolis. These areas are also mostly populated by “white” residents and have higher levels of education. In the case of the 2nd Ward, there is an anomaly. The zip code 55455 is in the 2nd Ward and it has an unemployment level of more than 33 percent. But it also has a poverty level of less than 1 percent. What the…???

This is because this is one of the zip codes for the University of Minnesota. They are students my dear Watson. And yes, we should expect that type of rate with a large population of students, which is why we throw it out as an anomaly.

The element of the median household income also looks different in the 55406 and 55419 in South Minneapolis. In 2013, almost 40 percent of households in the 55406 had a median household income greater than $75 thousand and just under 60 percent of the households in the 55419 had a median household income greater than $75 thousand.

In that same year, less than 25 percent of households in the 55412 had a median household income greater than $75 thousand and a bit more than 16 percent of the households in the 55411 had a median household income greater than $75 thousand. Obviously the median household income element shows different faces in different wards and zip codes.

We’ve taken our first step in understanding systems. To recap, we know what the primary elements of the system are for this particular system and we know that they show different faces in different parts of the system. We must also understand that they perpetuate different interactions with other elements of the system, which gives rise to the purpose of this particular system. but that is another discussion for another day.

We are indeed moving towards a greater understanding of systems and Urban Dynamics my dear readers.

Which zip code has the lowest median household income in Minneapolis?

We have established some differences between different parts of the City of Minneapolis. For example, we know that the foreclosure numbers and rates are the highest in Wards 4 and 5 in North Minneapolis as Figure 2 demonstrates. We know that both of those wards also have the highest concentration of condemned and vacant buildings. But we now have some additional information to add to this difference – Median Household Income.

Figure 1 provides us an opportunity to compare and contrast two zip codes in North Minneapolis and two zip codes in South Minneapolis. As we can see, the percentage of median household incomes in the two zip codes in South Minneapolis – 55406 and 55419 – are higher than the two zip codes on the north side.

2013 Median Household Income for Minneapolis Zip Codes greater than $75 K
Data Provided by http://www.city-data.com – Data Organized and Presented by Urban Dynamics –  Figure 1

 

Whereas the median household income greater than $75 thousand is above 35 percent in the 55406 and almost 60 percent in the 55419, we see that the median household income greater than $75 thousand is only about 15 percent for the 55411 and about 25 percent for the 55412. Clearly, there is a difference ranging from 10 percent to 45 percent depending on what zip codes we compare.

Percent of Foreclosures for Wards 4 5 and 10 2006 to 2015
Data Provided by http://www.city-data.com – Data Organized and Presented by Urban Dynamics –  Figure 1

Moving forward, this data will add to our already accumulated knowledge of North Minneapolis and Minneapolis in general. But what are some questions we may want to ask from this new information? Since we have some knowledge about foreclosure rates and condemned and vacant buildings, perhaps we will want to see if there is a correlation between median household incomes and foreclosures and condemned and vacant buildings.

Or what about knowing the levels and rates of home ownership in the respective zip codes? How does the north side compare to the south side in home ownership? These questions are important because we agree that home ownership is a part of the American dream, right? And finally, these questions are important because eventually they will lend to future policies.

Author’s Notes:

  1. Data from Figure 1 is drawn from http://www.city-data.com and represents the year 2013.
  2. Data from Figure 2 is drawn from the City of Minneapolis’ Minneapolis Trends Report.

Foreclosure Rates: Wards 2, 4, and 5 from 2006 to 2015

Figure 1
Figure 1

Continuing the analysis of foreclosure rates in Minneapolis from the previous article Foreclosure Rates: Wards 4, 5, and 10 from 2006 to 2015, it is important to compare and contrast the wards with the highest foreclosure numbers and the wards with the lowest foreclosure numbers in the City of Minneapolis.

As Figure 1 illustrates, the 2nd Ward’s foreclosure numbers have been relatively linear since the fourth quarter of 2006. Furthermore, it can been seen that the 2nd Ward peaked at 14 foreclosures during the third quarter of 2010. In contrast, Wards 4 and 5 in North Minneapolis accounted for 172 and 86 foreclosures, respectively in that same quarter and year. That is of course a striking difference.

Indeed, Southeast Minneapolis is a smaller part of Minneapolis in area compared to North Minneapolis. But contrasting the two parts of town directly, North Minneapolis, which accounted for 258 foreclosures while Southeast Minneapolis accounted for just 14 foreclosures in the third quarter of 2010, is paramount. Thus, North Minneapolis accounted for about 18 times the number of foreclosures than Southeast Minneapolis during that time period.

Figure 2
Figure 2

We can see this difference in Figure 2 in another way. The Figure 2 graph also shows the pattern of Minneapolis foreclosures from the fourth quarter of 2006 to the second quarter of 2015. From the graph, it is clear that Ward 2’s foreclosure participation is flat and does not play much of a part in the totality of the foreclosure market in Minneapolis. However, North Minneapolis tells a different story.

It is clear from the data that Minneapolis’ foreclosure numbers have been steadily decreasing since 2008 with one sharp market peak in 2010. But during that time of recovery and increased market competitiveness and productivity, Wards 4 and 5 in North Minneapolis accounted for a large chunk Minneapolis’ total number of foreclosures. In other words, Wards 4 and 5 have accounted for a larger proportion of the foreclosure market in Minneapolis in general since at least the fourth quarter of 2006.

Figure 3
Figure 3

To really see and understand this idea of proportionality, we must view Figure 3. What Figure 3 illustrates is what is called relative frequency in mathematics and statistics. Simply put, relative frequency expresses proportionality.

Figure 2 tells a story that the total number of foreclosures in Minneapolis have been steadily decreasing, and this is certainly a positive economic component of recovery, but Figure 3 expresses North Minneapolis’ foreclosure rates have remained fairly constant compared to the rest of the city and appear to have increased in greater proportion in the past few quarters. Sending this point home, North Minneapolis has the greatest proportion of foreclosures in the City of Minneapolis.

Although it is clear from the data that the total number of foreclosures in the 4th and 5th Wards have been decreasing over the past few years, their recovery has been relative. In other words, there is still a greater proportion and total number of foreclosures in North Minneapolis than any other part of the city; that is, Northeast Minneapolis, Southeast Minneapolis, Southwest Minneapolis, and South Minneapolis.

To delve a bit deeper into these wards and subject matter, I suggest Patterns of the 5th Ward: “Race” and Comparing Zip Codes | Median Household Income for Minneapolis. For something a bit more general and that involves cities and astronomy, see A City on Mars: A Response to Elon Musk.

As always, I invite you to post your thoughts, comments, and questions below.

 

 

Foreclosure Rates: Wards 4, 5, and 10 from 2006 to 2015

In the previous article A Comparison of Minneapolis’ Foreclosure Rates by Ward, I compared and contrasted the difference in foreclosure rates between Wards 4 and 5 in North Minneapolis, and Ward 2 in Northeast Minneapolis and Ward 10 in Southwest Minneapolis.

Data Courtesy of the City of Minneapolis - Graph Constructed by Urban Dynamics
(Figure 1) Data Courtesy of the City of Minneapolis – Graph Constructed by Urban Dynamics

However, I only compared the wards and their respective foreclosure rates from the first quarter in 2014 to the second quarter in 2015. But even with that short of a time scale, I illustrated a clear distinction between the high rates in North Minneapolis and the low rates in Northeast and Southwest Minneapolis.

But that analysis and data facilitated new questions. For example, what would the trends of the foreclosure rates between the wards in Minneapolis look like over multiple years? What type of trends would the data set illustrate? How would the Great Recession affect the data and consequently the different wards; that is, would there be a peak in foreclosures around or during the peak of the Great Recession? Would there be a noticeable peak for any of the Wards?

In Figure 1, we see a sharp contrast between Ward 10 in Southwest Minneapolis and Wards 4 and 5 in North Minneapolis. The table provides a lot of useful information for us to digest and consider. However, for this article we will consider only three facts. First, Ward 4 from the 4th quarter of 2006 to the 2nd quarter of 2015 experienced the highest number of foreclosures in the city with the exception of two quarters.

In the second quarter of 2007 and the 4th quarter of 2008, Ward 5 had a higher number of foreclosures than Ward 4. Other than that, Ward 4 has been the central location of foreclosures along with the highest foreclosure rates in the city since the fourth quarter of 2006.

Second, the foreclosure numbers in Ward 4 had been trending downward throughout 2008. However, in early 2009, around the same time of the pinnacle of the Great Recession, the number of foreclosures in the 4th Ward began trending upward. And in the third quarter of 2010, the number of foreclosures in North Minneapolis reached pre-Great Recession numbers. In other words, as soon as North Minneapolis began to recover from 911, the Great Recession happened, which may help explain the sharp peak in late 2010.

(Figure 2) Data Courtesy of the City of Minneapolis - Graph Constructed by Urban Dynamics
(Figure 2) Data Courtesy of the City of Minneapolis – Graph Constructed by Urban Dynamics

Of course at first glance, the consequence of 911 is only speculation and probably not very good speculation. This is because it doesn’t explain the low number of foreclosures in Ward 10. And it doesn’t explain the amazingly low foreclosure numbers in Ward 2, which will be illustrated in the next article. Additional data of foreclosures from 2002 to 2006 is needed along with economic data like unemployment and education.

Finally, the number of foreclosures in Southwest Minneapolis has been fairly low and fairly consistent. Only once did the number of foreclosures rise above 30 and that was before the peak of the Great Recession. Since then, it has been on a steady downward trend into the single digits of foreclosures. In other words, the 10th Ward weathered the Great Recession quite well.

There is one bright spot in this data set that is clear. Although the 4th and 5th Wards continue to post the highest number of foreclosures month after month, there is an obvious downward trend and the data seems to suggest that Wards 4 and 5 foreclosure numbers will converge with Ward 10. That is the one positive that can be taken from this data set immediately. A caveat, Figure 2 seems to be suggesting a different story.

What’s next? First, find out if there is a correlation between the number of foreclosures and the number of condemned and vacant buildings. In a previous article, it was illustrated that Wards 4 and 5 had the highest concentrations of condemned and vacant buildings in Minneapolis. so this would be a good place to start. Second, compare the unemployment rates and this data set. Is there overlap? In other words, as the unemployment rates go, so do the foreclosure rates follow? There are other comparisons that will be researched and posted in Urban Dynamics as well.