# Minneapolis: Labor Market Update, July 2017, Part 1

In today’s blog, we will be exploring the labor market in Minneapolis from the perspective of the labor force and the number of employed. It will be important for us to remember that these two economic systems’ variables measure the growth of a labor market.

### Labor Force

There are two things to consider when viewing labor force data. First, what is a labor force? A labor force are those workers within a labor market who are willing to work: those who have jobs and those who don’t have jobs but are looking for employment. Second, how is a labor force computed? The number is computed by adding the number of employed and the number of unemployed (those actively looking for jobs) in the labor market. Note, the number of unemployed will be addressed in Part 2.

Mathematically, this is illustrated by the following equation:

Labor Force = Number of Employed + Number of Unemployed

Looking at the Minneapolis labor force – the number of employed plus the number of unemployed – it is clear that the labor force has been increasing since at least January of 2006.

Moreove, this increasing behavior is not only observed via the flunctuating nature of this probabilistic system, but via the linearization of the data in the form of the y = mx + b equation embedded in Graph 1. Recalling basic algebra, m is the slope of the equation (the change of the labor force over the change in time) and b is the intercept, i.e., the starting point. Of course, this is an extremely simplified and rudimentary way of viewing this labor market system; but it illustrates the point nonetheless. That is, the Minneapolis labor market has been increasing for quite some time despite internal and external systems’ forces.

There are other dynamics playing out in this labor force system, but those dynamics will be set aside for the time being.

### Number of Employed

The number of employed is another part of the labor force. In this case, the data provides insights into moments in time when the number of employed decreased and moments in time when the number of employed increased. For example, from the late summer of 2008 through the early summer of 2009, the number of employed decreased in Minneapolis. But since then, the number of employed has been steadily, although stochastically, increasing.

Again, the overall behavior can be observed via the linearization of the data in the form of the y = mx + b equation embedded in Graph 2. That is, m is the slope of the equation (the change of the labor force over the change in time) and b is the intercept. And one final observation should be noted, clearly the system’s behavior of the number of employed in Minneapolis has been more variable and pronounced than that of the system’s behavior of the labor force in Minneapolis.

So what do we know about the labor market in Minneapolis from these two systems’ variables? First, the labor force has increased overall by 31,326 since January of 2006.  Second, the number of employed in Minneapolis has increased overall by 31,152 since January of 2006. In other words, these two variables indicate a growing labor market.

In the next labor market blog, the unemployment rate and the number of unemployed over the same time period in Minneapolis will be explored. Together, all four of these systems’ variables – labor force, number of employed, number of unemployed, and unemployment rate – will illustrate the strength and growth of the Minneapolis labor market.

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.

Photo Credit: Jason Riedy, Flickr

# 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.

Photo Credit: Wikimedia Commons

By Matt Johnson

Well, it took me a little bit of time, but I mined the crime statistics from the City of Minneapolis website. I organized the data into neat and accessible tables and data sets for current and later use.  I did this for a couple of reasons. First, crime is an important indicator of the attractiveness of the city.

As an adverse effect on the city, crime decreases safety, increases police presence, which takes money and resources from other applications and policies that could be utilized to increase the utility for those residents who reside in those crime infested neighborhoods.

Think of crime as a negative investment. Crime also has a bad reputation for those who would otherwise be interested in purchasing property as a potential or current resident, or for those who would otherwise be interested in opening a business and providing a product and service to the local neighborhood residents. Furthermore, crime has security costs for those already established business owners. This is money that could be better utilized in other facets of business and community.

Second, the crime tables will provide us with illustrations of behavioral patterns between the various subsystems and the general system of Minneapolis. As we’ve seen from previous articles, these systems’ behaviors can sometimes be similar in nature and sometimes they can be different in nature.

As Table 1 shows, crime increases throughout the summer months. Would these behavioral patterns of the general system exist in the subsystems of South Minneapolis? Would they be reflective of one another? Would the behavioral patterns of the wards and neighborhoods on the north side reflect the behavioral patterns of the general system of Minneapolis?

Previous articles suggest there would be similar behaviors between the north side’s subsystems and the general system of Minneapolis; whereas, these behaviors would not be similar between the General Minneapolis System and the wards and neighborhoods on the south side.

And finally, as I progress as a scientist and a writer, and I learn to harness my inner Neil deGrasse Tyson, I will begin to engage, push back against, and challenge those who talk or write about events, statistics, or ideas in the urban environment. As an example, John Eligon recently wrote in an article in The New York Times

…the highest crime rate of the city’s five police precincts was in the Fourth Precinct covering North Minneapolis, which reported 1,428 violent crimes last year through November, including 18 murders.

Is this true statement true? Is it true that the highest crime rates in the City of Minneapolis reside in the city’s north side? Is it true that there were 1,428 violent crimes throughout the 2014 year? Is it true that there were “18 murders” in north side in 2014? What does he mean by “North Minneapolis?” And lastly, is this biased reporting by a person who doesn’t understand the north side and its dynamics?

With the data that I’ve extracted from the City of Minneapolis, I will be able to confirm or falsify Mr. Eligon’s statement and assertions. I will be able to address the data in his statement, which by the way was not linked to a source. Apparently, he’s just saying it. And notice his article doesn’t provide any direction or solutions.

I realize that I have not yet provided any solutions, or speculative solutions, myself. I’ve done this for two reasons. First, I wanted to establish myself and some of the data. I am slowly but surely building a systems model for Minneapolis and its subsystems. It takes time and dedication. It’s not an easy process, nor should it be.

The people of North Minneapolis have seen flimsy and questionable policies from a variety of people from all walks of life. I’m not calling anybody out. What I’m saying is that the residents of the north side deserve better and if I’m gonna write or propose something, I’m gonna make damn sure that its been thoroughly thought through and that it’s supported by the data and systems analysis that I’ve been slowly building. It’s taken decades if not centuries for this bipolar existence to happen in the inner cities of the United States and I won’t add to the problem.

For further reading on similar subject matter, I invite you to read The Simple Behaviors of Cities, 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.

By Matt Johnson

I have touched on the general behaviors of the Minneapolis General System, but I have not delved into great detail on the subject matter nor have I given the general system its due attention. On the other hand, I have discussed some systems behaviors in the 2nd, 4th, 5th, 10th, and 12th Wards of Minneapolis. More specifically,  I discussed the 4th and 5th Wards in the greatest detail compared to the other wards.

In this short article, I will begin an analysis of the general, and simple, behaviors of the general system of Minneapolis starting with foreclosures. This is important and necessary because I want to show that there are differences or similarities in behaviors between various subsystems in Minneapolis and the general system of Minneapolis itself.

As we can see in Figure 1, foreclosures in Minneapolis have been decreasing since they peaked near 900 properties in early 2008. In fact, foreclosures have decreased by almost 9 times. And with the exception of the spike in 2010, foreclosures have dropped down to near 100 properties for the City of Minneapolis in the 2nd Quarter of 2015.

Clearly that’s quite a recovery and a step, if not two or three steps, in the right direction. It’s something that isn’t necessarily pointed out or focused on in the press or social media, at least from this perspective. And to be honest and forthright, the economic positives have not been discussed very much here on Urban Dynamics. But this author digresses.

Now, this graph only provides us with a single perspective of the system, but it provides us with a piece of the picture nonetheless. And from this narrow perspective, we can still speculate, infer, and make predictions that there are other positive things happening in the general system and we should expect other positive things to happen in accordance with a reduction in foreclosures.

But we should ask ourselves a question before we analyze and address other general system’s patterns, “Do the foreclosure behaviors of the different Minneapolis wards mimic or reflect the behavior of the general Minneapolis system?” In other words, will the behavior of the 5th Ward in North Minneapolis or the 2nd Ward in Southeast Minneapolis, for example, be similar to the general system’s behavior of Minneapolis? And if they aren’t the same, what does it mean? Food for thought!

For further reading on similar subject matter, I invite you to read Foreclosure Rates: Wards 2, 4, and 5 from 2006 to 2015 to view foreclosure patterns and compare. Are the foreclosure patterns different or similar? And I invite you to read Urban Decay and North Minneapolis.

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

# Patterns of the 12th Ward: “Race”

By Matt Johnson

I must be honest. I am from the 12th Ward. More specifically, I was raised in the 55406 zip code; and more specifically than that, I was raised in the Standish neighborhood. So I must check my biases as I analyze, write, and share this series with you. The 12th Ward is my island.

I remember my friends and I running around like Calvin and Hobbes in the 80’s. Indeed, we were loud, obnoxious, and mischievous little boys. Xbox and Playstation didn’t exist yet. And of course, we didn’t have handheld devices. So we had to entertain ourselves somehow. We had to rely on our creative personalities and wit. It was a marvelous time and as little boys do so often, we made our world much bigger and fantastical.

During my time in the old neighborhood, I remember my time with my friends and our interactions with the neighbors. Of our little crew, we were all “white.” In fact, I can’t remember a time when the crew wasn’t that composition. At school, it was different. It was much different. We were exposed to a variety of different skin tones and colors. It was normal and we didn’t think anything of it for the most part, but that’s a different article for another time.

In the old neighborhood, the vast majority of the neighbors were “white.” From time to time, a “black” family would move in. But there were never more than a couple of “black” families, nor were there more than a couple of Asian families. For good or bad, it was always mostly “white.” And this brings us to today.

As you can see from Figure 1, my perception of the old neighborhood and today isn’t much different. That’s if you accept the narrative of a little renegade boy from the 80’s?

As the graph illustrates, the 55417 zip code is near 80 percent “white” and my boyhood zip code, 55406, is between 70 and 75 percent “white.” As far as the 55407 is concerned, that is another matter.

There are a couple of things that need to be brought forth concerning the 55407. First, it is clearly less “white” and contains a higher number of “black” and Latino residents. Second, a very small amount of the 55407 resides in the 12th Ward. This can be seen from the zip code map of the City of Minneapolis and the precinct map of the 12th Ward. Obviously, this means that the vast majority of the 12th Ward population may be more “white” than the graph reveals. A bit more digging and precision will be necessary to bear this assumption as relatively true.

Going forward, the Patterns of the 12th Ward is a five article series and “race” is just the first. Over the course of the series, I will share with you the unemployment rates, the foreclosure rates and numbers, education levels per zip code, and in the final article, I will bring it all together to illustrate the Patterns of the 12th Ward.

What should we expect to see? Would it be unreasonable to expect low unemployment rates? Would it be unreasonable to expect low forclosure rates and numbers? Would it be unreasonable to expect higher education levels? Would it be unreasonable to expect these types of patterns in “white” dominated wards and zip codes in Minneapolis?

Let me ask you this question. Would it be unreasonable to expect a bunch of young boys from the south side to act like Calvin and Hobbes?

I invite you to read the companion series Patterns of the 5th Ward: “Race” and Comparing Zip Codes | Median Household Income for Minneapolis and Foreclosure Rates: Wards 2, 4, and 10 from 2006 to 2015. These articles will provide you with a bit of contrast between the south side and the north side’s 5th Ward.

And remember, you are always welcome, and encouraged, to post your comments, thoughts, and predictions below. Feedback is always appreciated.

# Patterns of the 5th Ward: “Race”

By Matt Johnson

Over the next five articles, I am going to share with you some interesting patterns I’ve discovered in the 5th ward. In this first article, we well look at the difference in the population percentage with respect to the top four “racial” groups in Minneapolis – Asian, Black, Latino, and White.

In the second article, we will look at the unemployment rates between the zip codes of the 5th Ward – 55401, 55405, and 55411. In the third, we will look at the contrast of foreclosures between the 55401, 55405, and 55411 zip codes, and there is quite a difference. In the fourth article, we will look at the education levels between the three zip codes. And finally in the fifth and last article, we will bring everything together to illustrate these clear and striking differences and what they may tell us about the patterns of the 5th Ward with respect to the sub-system of the 5th Ward and the general system of Minneapolis.

As Figure 1 illustrates, there is a noticeable difference between a zip code and the group with the largest population. For example, In both the 55401 and 55405, we see that the vast majority of residents are “white.” After that, the two zip codes diverge in regards to what other group is second, third, and fourth, respectively.

In contrast, we see that “black” residents are the largest population in the 55411. And drawing on our knowledge from previous articles, we know that the percent of median household incomes greater than \$75 thousand is much much lower for “black” residents than it is for “white” residents overall in the City of Minneapolis.

We also know that the 55411 has the lowest percentage of median household income earners greater than \$75 thousand in the City of Minneapolis. We also know from American history that “black” Americans were partitioned into undesired neighborhoods in the northern industrial cities during the Great Migration from about 1920 to 1940.

And we also know that for the vast majority of American history, “black” Americans have been partitioned from economic and political opportunities by bondage, redlining policies including parks, schools, and other city services, and so on and so forth. So given this information, what should we expect to find when we look at a depressed part of an American city?

Should we find a difference between the number of “black” and “white” residents? Should a depressed part of town have a higher percentage of American citizens who are “black?” Should this same part of town have higher foreclosure rates when compared to other more affluent parts of town? It wouldn’t be unreasonable for these more affluent parts of town to be mostly “white,” would it?

Should we expect to find a difference in unemployment rates? Should we find that “black” unemployment is higher than “white” unemployment? Should we see a correlation between the unemployment rates, foreclosure rates, and what group has the highest percentage of residents? In other words, should a higher percentage of “black” residents correlate with higher unemployment rates, and higher foreclosure rates?

Furthermore, should we expect to see a difference in education levels? Based off this one graph, which zip code would you expect to have the highest percentage of bachelor degrees or higher? Would it be the 55401, the 55405, or the 55411?

And finally, should we expect to see a correlation between a higher percentage of “black” citizens, higher unemployment rates, higher foreclosure rates, and lower education levels? Post your comments, thoughts, and predictions below.

And remember, you can refresh your memory on some of these topics with the following articles: Comparing Zip Codes | Median Household Income for Minneapolis and Foreclosure Rates: Wards 2, 4, and 5 from 2006 to 2015.

By Matt Johnson

As Figure 1 illustrates, the 4th Ward has had the highest percentage of foreclosures in the City of Minneapolis since at least the fourth quarter of 2006 with the exception of the second quarter of 2007 when the 5th Ward held the highest frequency.

But is every zip code and neighborhood created equal when it comes to the numbers and percentages within the 4th Ward?

As we can see from Figure 2, there are distinct differences between the zip codes of the 4th Ward in North Minneapolis – 55411, 55412, and 55430. It is clear that 55412 contains the highest numbers of foreclosures from quarter to quarter throughout 2014.

And the distinction is fantastically highlighted when we look at the differences in relative frequency. As Figure 3 indicates, between 70 to 80 percent of the foreclosures in the 4th Ward were concentrated in the 55412 zip code throughout the respective quarters of 2014.

But there are a couple of differences to keep in mind while we continue to analyze these three zip codes over the course of Urban Dynamic’s analysis of the north side.

55412 is the largest zip code by area in the 4th Ward at 3.6 square miles and it comprises most of the 4th Ward’s land area.  55430 comprises the next most land area for the 4th Ward at 1.23 square miles. This is because only 22.07 percent of 55430 resides in Minneapolis. But there are some other differences between 55430 and 55412. According to City Data, 55430 has a higher proportion of “white” to “black” residents, a lower unemployment rate, and a higher level of education from high school through graduate school than 55411, 55412. How much of this difference between “white” and “black” residents in the 55430 zip code exists? That’s an additional question that will require a bit more digging.

Continuing our decomposition of the 4th Ward, 55411 is the smallest zip code in area in the 4th Ward. This is because most of 55411 resides in the 5th Ward, so in this analysis, 55411 and 55412 won’t be compared.

55411 will be considered in future articles when we analyze the 5th Ward and when we directly compare the 4th Ward to the 5th Ward. However, it should be noted that 55411 and 55412 contribute most of the foreclosures in the 4th and 5th Wards.

Moreover, future articles will explain how the number and percent of foreclosures in North Minneapolis increase as one moves from north to south (or from south to north depending on your reference point); that is, from 55430 to 55412 to 55411 and to 55405 and 55401. Future articles will also attempt to illustrate this same thinking and pattern for unemployment, median household income, education level, and “race.” Remember, as each article is published, another part of the painting is created.