Tag: Economic Data

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.

Graph 1

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.

Graph 2

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. 

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: Jason Riedy, Flickr

 

 

 

 

 

 

Copyright ©2017 – The Systems Scientist

Educational Attainment Data: Comparing Minnesota and the United States

We can use U.S. Census Bureau data to compare the educational attainment of the United States to any of the 50 states; we can use U.S Census Bureau data to compare the educational attainment of the United States to any city contained within the United States (provided data exists);  and we can use U.S. Census Bureau data to compare the educational attainment to compare states to each other, counties to each other, cities to each other, or any combination our hearts desire.

For this blog, we will compare the educational attainment of Minnesota, and the United States. In future blogs, we will compare other city, state, and country combinations. We will also compare city, state, and county; and we will even compare zip codes to one another. Which ones will explore? We will answer this question in due time.  Let’s begin.

United States

The United States is the Super-system. This means all 50 states and their respective counties, cities, town, zip codes, etc. are contained within the borders of the United States. Readers of this blog are familiar with this idea (for a more in-depth exploration of systems and sub-systems click here). This also means the United States meets 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.

We will take this axioms to be a given for this blog. Instead we will focus on the data. As we can see, the United States is second in every category except graduate and professional.

 

As the data illustrates, the United States has a lower median annual earnings (MAE) than that of Minnesota. This is good news for many residents of Minnesota who exceed the median annual earnings at each level of the ladder.

Minnesota

As readers of this blog will know, Minnesota is a sub-system of the United States. This means Minnesota meets 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.

Again, and for our purposes here, this will be given knowledge to us realize we are dealing with different systems and should treat each data set as its own entity. However, we will observe that the three data sets in this blog have similar behaviors. That is, earnings increase at each level of the educational ladder. However, we observe there are subtle differences.

According to the data, Minnesota has the highest median annual earnings (MAE) at each level of the ladder. For example, the MAE for Minnesota is $51,239 whereas the MAE is $50,595 for the United States. It should be noted that at the professional and graduate level MAE for Minnesota is the same as the United States.

One final thought, it should be noted that the U.S. Census Bureau decomposes its data into regions and divisions as well. So, for example, Minnesota educational attainment data can be compared to Iowa educational attainment data and/or Wisconsin educational attainment data. And this is really just the start of what could be an exhaustive exploration of the educational attainment data. One could even compare men and women at each level of the United States system, if the data exists.

 

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: VideoBlocks

 

 

 

 

 

 

Copyright ©2017 – The Systems Scientist

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

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

 

Photo Credit: army.mil

 

 

 

 

 

Copyright ©2017 – The Systems Scientist