Tag: Economic Systems

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

Minneapolis crime pattern since 2013

With the Minneapolis mayoral and city council elections only a few weeks away, crime is still a top issue. How will the mayoral candidates fair and will crime continue to remain a top issue?

Graph 1

As Graph 1 illustrates, crime is seasonal as it goes through its peaks during the summer months and valleys during the winter months. What is also interesting about this graphical representation, besides the fact that it’s dynamical, is that it shows how crime decreased each year from 2013 through 2015.

You can check for yourself by aligning a ruler with the peak crime months of 2013, 2014, and 2015. As you’ll notice, the ruler is tipping downward, i.e., a downward (negative) slop.

But 2016 illustrates an increase when compared to the previous months and years; and it appears 2017 will maintain that trend of increasing crime.

Thus, you can perform the same exercise with the ruler with the peak months of 2015, 2016, and 2017. You’ll notice an increasing slope with this set of months, i.e., increasing crime rates.

Of course, the increasing slope of crime doesn’t appear to be as pronounced as the decreasing slop of crime, but the decrease and increase are obvious nonetheless. Something to think about with city elections on the horizon.

 

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: Wikimedia Commons

 

 

 

 

 

 

Copyright ©2017 – The Systems Scientist

 

Minneapolis: July’s Top 7 Neighborhoods for Crime in 2017

There are few things to consider when sifting through this data set. First, the highest number of reported crimes in Minneapolis are not in the Jordan neighborhood in North Minneapolis, or any  other neighborhood in North Minneapolis for that matter. To the contrary, Downtown West has the highest number of reported crimes. In fact, it has had the highest number of reported crimes in each month this year, and it generally does year after year.

Second, 6 of the 7 neighborhoods in the top 7 are not in North Minneapolis. Of course, this doesn’t mean there aren’t other North Minneapolis neighborhoods that don’t experience a relatively high number of crimes. As a group of neighborhoods, the north side definitely illustrates a concentration of reported crimes. This will be illustrated in a future blog.

Crime: 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
(Neighborhood/Total) x 100% 0.14 1.74 9.42 7.68 8.84 66.7 5.36 0.14 100

(Source: City of Minneapolis)

And lastly, 66.7 percent of the of the reported crimes of the top 7 neighborhoods are Larceny. Matter of fact, Larceny is between 65 and 75 percent of the reported crime each month in Minneapolis. Of course this statistic varies from neighborhood to neighborhood, but it’s a fairly consistent statistic for 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. 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: Tony Webster, 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

Minneapolis: Education pays, according to the data

Odds are if you lived in Minneapolis in 2015 and didn’t have a high school diploma, then you probably made less than $19,200.00 in that year. If you’re keeping track, that’s $10.00 per hour. Matter of fact, if you were the average person with no high school diploma, then the odds were good you made $18,165.00. In contrast, if you were the average person with a graduate or professional degree, then the odds were good you made $62,757.00 in 2015.

It is clear from the data, at least this data, that education pays for those who work and reside in Minneapolis. That is, earnings increase at each level of the educational ladder. Those residents with a high school diploma earn more than those residents with less than a high school education on average; those residents with some college or an associate degree earn more than those residents with a high school diploma on average; those residents with a bachelor’s degree earn more than those residents with some college or an associate degree on average; and those residents with a graduate or professional degree earn more than those residents with a bachelor’s degree on average.

In fact, it is striking how each level earns significantly more than the next educational level down. For example, there is a $7,092.00 difference annually between a high school diploma and no high school diploma; and there is a $21,812.00 difference annually between a college degree and a high school diploma. Of course, is this the case no matter what city data is observed? Does this educational advantage remain if one were to compare the north side of Minneapolis to the south side of Minneapolis? Does this educational advantage remain if one were to compare different parts of North Minneapolis itself?

But what if it were the case that education remained financially advantageous no matter the geographical local, i.e., any part of the United States (take your pick)?

What would this mean for economic policy? Do examples exist of local policy makers constructing such economic policy based off of educational data? Indeed, one data set is not enough. Are there counter examples? In order to satisfy the rigors of science, data sets showing such an advantage need to be illustrated to exhaustion or boredom, whichever comes first.

 

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: U.S. Department of Education

 

 

 

 

 

Copyright ©2017 – The Systems Scientist

Chicagoland: Homicide rate increases as 2017 progresses

Unfortunately, the homicide rate is increasing in Chicago. That is, the number of homicides per month are increasing as 2017 progresses.

The year started off with 145 homicides in the 1st quarter – January, February, and March –  compared to the 151 homicides through the 1st quarter in 2016. However, things started to pick up at the beginning of the 2nd quarter. April saw seven more homicides than April of 2016. There were 41 homicides in April of 2016 compared to 48 homicides this year.

May saw a slight decrease. That was certainly good news. But then June happened.

Data Source: Chicago Tribune

June saw more homicides this year than last year – 84 to 73 – about a 15 percent increase. And now July is following suit. July of 2017 has seen more homicides than July of 2016.

For those keeping count, 409 families have lost a loved one this year compared to the 403 families at this time last year. 400 families?

August starts tomorrow. And that’s terrible news for those who live in the economically depressed parts of the city (my readers recognize these parts of Chicago as subsystems).

Last year, there were 96 homicides in August of 2016. If this homicide rate remains constant, the windy city will see 500 plus homicides by the end of the 8th month of 2017.

It is certainly possible this thing could slow down (I’m rolling my eyes). Cities are stochastic systems; that is, they are probabilistic. But it’s probably not likely that the homicide rate will slow down enough to see fewer people die this year. If the last two months are any indication of what might be possible, then it’s very likely local policy makers could be faced with answering the obvious question from journalists and others in the press, “Why were there more than 800 homicides this year?” The response will be a clutter of words and sentences in ambiguous language – doublespeak.

To be frank, Chicago hasn’t experienced such a ridiculous and appalling statistic since the mid 1990’s. Chicago saw 828 homicides in 1995; and Chicago hasn’t seen fewer than 400 homicides in decades. Wait. What?

Data Source: Chicago Tribune

Anyway, will 2017 break the 95′ threshold of 828 homicides? One would certainly hope not. It would be great if the number went down to zero starting tomorrow. But that isn’t realistic for a plethora of reasons. The challenges of the depressed economic systems, where most of these homicides happen, are not being met with judicious economic solutions.

The necessary economic tools do exist. But it might be the case that local policy makers in Chicago don’t have accessibility to the necessary economic tools: labor economics, game theory, behavioral economics, systems economics, etc… Or perhaps it’s something else entirely (I doubt it – my money is on the economic tool-kit).

Until then, enjoy the featured image for this article. It is a beautiful picture of a Chicago train surrounded by the city’s stunning architecture. Good stuff.

 

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: Pixabay

 

 

 

 

Copyright ©2017 – The Systems Scientist

Distinguishing between sets and systems through mathematics, economics, and chemistry

A set with objects

So far, we’ve presented the (3) systems’ axioms and the notions of system’s behavior and system’s boundary. We have also explored these ideas via different examples. And we’ve touched on the idea of a set. However, we now want to differentiate between what a set is and what a system is. Once we show the difference between the two, then we will be able to demonstrate the difference between a subset and a subsystem. And most importantly, we will be able to better observe, analyze, and make sense of different kinds of systems, albeit economic systems, political systems, or political systems.

So how can we differentiate between a set and a system? First, we can address this question by referencing back to 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.
Set A is a subset of set B

The difference between a set and a system is that a set satisfies the first axiom; whereas, a system satisfies all three axioms. More specifically, a set B is a collection of well-defined objects (we will use Naive Set Theory for now), for instance B = {2,4,6,8,10}. Further more, the elements in this set interact with each other. For example, the element ‘2’ interacts with element ‘8,’ or element ‘4’ interacts with element ’10,’ or some combination of possible interaction. And finally, there is a function that is produced, or purpose, via the interactions.

As we can see, a set satisfies the first axiom; whereas, a system satisfies all three axioms. Now we have the tools to delve into the subsets and subsystems. We will see that subsets satisfy the first axiom while subsystems satisfy all three axioms.

As stated before, a set B is a collection of well-defined objects, for instance B = {2,4,6,8,10}. However, a subset of B can be partitioned and observed. For instance, a subset A is a subset of set B if all of the elements in the set A are contained in the set B. That is, A = {2,4,6} so since all of the elements in the set A are contained in  the set B, the set A = {2,4,6} is a subset of set B = {2,4,6,8,10}.

Thus, this subset or any combination of subsets with any of the five elements – 2,4,6,8,10 – satisfies the first system’s axiom.

To illustrate the second axiom with respect to a subsystem, we want to show that if elements interact in a subsystem, then they interact in a parent system. There are a few ways we can do this. For this article, we can do this by observing the interactions in set A = {2,4,6}. Thus if ‘2’ interacts with ‘4’ and ‘6,’ and ‘4’ interacts with ‘6’ in set A, then these elements also interact in set B because set A = {2, 4, 6} is a subset of set B = {2, 4, 6, 8, 10} because set A is contained in set B.

The final step is to show that a subsystem has a function, or purpose. It could be the case that a subsystem has the same function as its parent system, or it could be the case that it has a function different from its parent system. But either way, it ought to have a function no matter if it is the same or different from its parent system. So how can this be illustrated?

Example 1

As Donella Meadows conveyed in her book Thinking in Systems: A Primer identifying the function of a system can sometimes be difficult. Indeed, there are instances where the function or a system is fairly obvious.

One way this can be done is by mapping the elements in set B to the elements in set A. In other words, the elements in set B will go to the elements in set A.

The sketch in Example 1 illustrates this point. For instance, 1 goes to 3, and 2 also goes to 3; 4 goes to 7; and 5 goes to 8.

And so something is imputed through 1, 2, 4, and 5, and something is outputted through 3, 7, and 8. This means the elements in set B = {1, 2, 4, 5} would be the inputs of the system and the elements in set A = {3, 7, 8} would be the outputs.

To illustrate this point further, one could view a system that includes labor and wages as the elements. That is, a person exchanges their labor, hours worked, for a wage. If, for example, the wage was set at $30 per hour, then a person would obviously make more for every hour worked as Graph 1 shows.

That is, if 5 hours are imputed into the system, then $150 will be outputted from the system; if 6 hours are imputed into the system, then $180 will be outputted from the system; and if 7 hours are imputed into the system, then $210 will be outputted from the system. And of course this game could be played over and over again. Thus, as the number of hours imputed into the system increases, the number of dollars outputted from the system increases.

Example 1

Another demonstration of a function can be illustrated through an interaction between an oxygen molecule, O2, and two hydrogen molecules, 2H2. If a gaseous oxygen molecule interacts with two gaseous hydrogen molecules at a high temperature, these molecules are known as the reactants in chemistry, then two gaseous H2O molecules, known as the products in chemistry, will be produced. In other words, if one gaseous oxygen molecule and a two gaseous hydrogen molecules are imputed into a system, then the system will output two gaseous H2O molecules as Example 2 demonstrates.

Example 2

These systems’ functions and purposes are obviously not what we often think of as a function or purpose of a system. They are in one instance somewhat familiar and in another instance esoteric.

In this article, we have used mathematics along with a couple of examples from economics and chemistry to distinguish the difference between a set and a system. Moving forward, we will be able to continue building off of these axioms, notions, and examples as we begin to apply these ideas to more familiar systems such as economic systems, political systems, and social systems.

Let us now, as we have done before, attempt to disprove our notions and work in the tradition of natural philosophy until the next blog.

 

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: Pixabay

 

 

 

 

 

Copyright ©2017 – The Systems Scientist