SAS Learning Post

Risks to US employment – automation and offshoring

Employment – that’s been a hot topic here in the US lately. Many of the manufacturing jobs we had in past decades are gone now, and it would be great if there was a crystal ball to predict which jobs might be at risk of disappearing in the future. The researchers at Ball State University (BSU) have been working on just that – in the form of a map! And being a graph guy, I couldn’t help but try to make a few little changes and improvements…

BSU set up a web page where they published the results of their study. They provide a paper, an executive summary, an appendix with the maps, and a spreadsheet of their data. Here’s a snapshot of one of their maps:

analytics, employment, map

It was an OK map, but I noticed several things I would like to change about it. Here is a list of my changes, followed by my new SAS version of their map:

  • The legend would be easier to read if only 1 decimal place is shown.
  • The legend would be more intuitive with the larger values at the top, rather than at the bottom.
  • I prefer the ‘footnote’ at the bottom of the map.
  • I only shade the land areas – not the water in the Great Lakes.
  • I label the legend using the more descriptive text that was in the spreadsheet.
  • I use a % sign in the legend label, so people can quickly tell the values show percent.

analytics, employment, map

I thought my version was an improvement, but it still just didn’t quite feel right. With the 10 gradient shades of color, it was just too difficult to look at a county’s shade and know where it fit into the legend scale. So I decided to go through one more round of changes. Rather than dividing the data into 10 bins and gradient shading, I used 5 bins (quintiles) and a diverging color scale. Now you could quickly tell which quintile (riskiest 20%, safest 20%, etc) each of the counties is in. You can also click the images below to see the interactive versions, with html mouse-over text for each county!

analytics, employment, map

And similarly, here’s my SAS version of their map showing counties at risk of losing jobs to offshoring.

analytics, employment, map


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