Wages

# Comparing Minneapolis wages to wages in North Minneapolis

As Aristotle explored in his Metaphysics: Book Delta, the parts of something, say the parts of a city, are divisions of the whole that can be differentiated from one another by quantification or by qualification. In the sense of quantifying, North Minneapolis can be differentiated from Minneapolis by observational data, for example, unemployment rates, education rates, and wages.

In the sense of qualifying, North Minneapolis can be differentiated by recognition of area. But it should be noted that the geography of North Minneapolis is still the geography of Minneapolis. It is just a recognition of a specified area, which is not Northeast Minneapolis, South Minneapolis, or Southwest Minneapolis.

Furthermore, North Minneapolis is broken down further by quantification and qualification into area codes: 55411 and 55412. Thus, the 55411 and 55412 zip codes are distinguishable by name and specific geography, this is obvious, and by observational data.

For example, previous articles in this blog have shown the 55411 zip code to be the zip code with the highest number of reported crimes in North Minneapolis; whereas, previous articles in this blog have shown the 55412 zip code to be the zip code with the highest number of foreclosures over the past decade.

Graph 1

Utilizing this systemic approach, the wages between Minneapolis and North Minneapolis, specifically the 55411 zip code, can be differentiated and analyzed.

Thus, are the dynamics of the wages (how wages change over time) shown to be relatively equal to one another? Are the dynamics of the wages of the 55411 zip code shown to be greater than Minneapolis? Or are the dynamics of the wages of the 55411 zip code shown to be less than Minneapolis?

As Graph 1 illustrates, we can see that the wage rate of Minneapolis is steeper than the wage rate of the 55411 zip code in Graph 2. And we’re not just eyeing this. We can see this distinctly via the linearization equations in Graph 1 and Graph 2.

The linearization equation in Graph 1 (y = 6.4152x + 1083.1) shows a rate of 6.4 and the linearization equation in Graph 2 (y = 2.2805x + 823.6) shows a rate of 2.3, if both rates of change are rounded-off. Obviously, 6.4 is greater than 2.3, and by quite a bit. Why is this important?

Graph 2

Dynamically (how wages change over time), this shows the wages of Minneapolis are growing at a greater rate than the wages of the 55411 zip code. Of course, these equations also show that the average weekly wages of Minneapolis are between \$250 and \$300 higher than the 55411 zip code.

This little bit of information ought to provide policy makers with some much-needed direction to create and apply economic policy. Of course the operative modal verb is “ought to.”

So do you think local policy makers would consider differentiating between the part and the whole when creating economic policy? Or do you think local policy makers would just create and apply the same policy for both the part and the whole?

Photo credit: Wikimedia Commons