Since I am sure store closures is a story that will continue I took a look at some recent data regarding retail. It is also the case that my friend Richard Carpenter (whose blog I linked to in the past and you can find in the blogroll list) asked me about some of the numbers in this situation.
Clearing out more of the questions asked on the radio lately. The announcement of the closure of the Macy’s in the local mall set some callers into fits. Their issues and questions ranged from: Is this a harbinger of future closures in Grand Forks and/or Fargo; to: this mall has inadequate numbers of stores and the wrong kind. There were lots of other issues raised too, so let’s clear a few of these things up right now.
The legislature is in session and there is a natural concern about policy in the state, and hopefully even greater concerns about the data employed to make the policy decisions. With the first round boom in the state’s oil industry over there are now significant discussions about the path forward. Obvious questions include: what is the likelihood of eventual recovery in the industry? How will an oil recovery impact the larger economy? These are great questions to ask (and there are many more), though they are actually quite complex to answer. Let’s consider some recent population data released by the U.S. Census Bureau.
By now it is well documented, here and perhaps everywhere, that North Dakota experienced a significant economic transition over the last ten years. How permanent and sustainable a change is the current question. At the risk of editorializing too much I will just point out, that is almost always the question, and we seldom have an answer until well after the fact. This issue aside, I looked at the median income data by county in North Dakota. The data are the 5-year estimates from the Census Bureau. If you want all counties in the state that is the data series you need to employ, and since I want to look at counties across the state that is what I chose. I took each county median income measure and divided it by the median income for the state as a whole to see how the individual counties changed over time. The first year was 2009.