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.
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.
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