Numerous callers over the past few weeks mentioned that age increases are not really keeping pace with inflation. This is something mentioned significantly at the national level too. As a result I used the CPI to adjust the wage data from the post last (found here) week about wage comparisons to get a sense of the curve shapes after the adjustment. I put them all in terms of 200Q4 level. The adjustment is the same for the different regions so there is not added value in the comparison of the different regions really, it is more the comparison of the nominal and real values.
The radio audience really responded to the topics of income and wages the last few weeks. Along with the population posts (which I confess I find more interesting) I include another look at wages. I grabbed the data for goods producing and service providing jobs in three North Dakota counties: Cass, Grand Forks, and Williams. Nothing necessarily scientific about the county selection, just three that I know and that will likely give us something to ponder.
Replacement was another idea we talked about in the population analysis class this week. Essentially it is an estimate of the deaths and migratory outflows from the area over a specified period of time and is called replacement because it is what you would need to replace in order for population to remain the same. Not really terribly complicated, but it is a nice complement to the idea of turnover and I generated both the level and the rate for counties in North Dakota.
Keeping with the topics from recent weeks on the radio I thought I would write some more about annual pay. This time I took a look beyond the city of Grand Forks or the county to look at the state as a whole. We can delve back in to the county level again as needed but I was curious about how certain sectors would compare across states.
The topic of annual pay clearly was important to many callers last week and so I thought I would follow up with a bit of a different look at the issue. I wanted to take a look state wide at the hot spots for compensation. This is BLS QCEW data for all industries for all firm sizes. I ran it for the last ten years but we are going to look at three years, 2007, 2012, 2017.