No, not the accuracy. I question their determination of worker productivity and wages by using the average and the median, not the distribution. They did not attempt to measure the productivity of particular jobs (admittedly that's difficult to do).

In particular, they did not identify any particular job or category where productivity of that job was far higher than the pay. I do not believe it is accurate to assess the productivity of a job by dividing the productivity of an entire business by the number of employees, in fact, I suspect it to be a fundamental mistake in their methodology.

>Finally, take an industry that these same BLS industry productivity data indicate has seen exceptionally fast productivity growth: textile mills (78 percent productivity growth just since 1997) or transportation equipment (84 percent productivity growth since 1997). (Page 20)

They did! Of course, this is just one example, but they did attempt to point out an industry where productivity growth has been very high but wages have not.

An industry is not a job category.

If the _average_ productivity is higher than the _average_ pay, then there must exist at least one particular job or category where productivity is higher than pay. These "underpaid" jobs may be unevenly or evenly distributed across the entire spectrum of jobs, but they must exist--unless the measurement of productivity is in question.

Sure - if all the jobs were included. You'd have to include things like the CEO, contractors, etc. The accounting for all this isn't easy. If the productivity increase comes from installing a machine, that doesn't mean the machine operator is adding more value - the machine is. The productivity increase would then accrue to whoever took the risk in buying the machine.

I would agree that it is complicated to do the accounting for this, and it's easy to get confused.