On Saturday, I listened to Orley Ashenfelter’s AEA presidential address about cross-country wage comparisons. For a few years, Ashenfelter has been collecting data on “McWages“, so as to “to measure wages for virtually identical jobs, producing identical products in firms with identical technology.” In making these comparisons, he deflates the McDonald’s wage by the price of a Big Mac, thereby calculating the real producer wage.

Yesterday, the Atlantic’s Richard Florida had a post titled “Which Countries Pay Blue Collar Workers the Most?” It featured this BLS table:

What does this table mean? Florida writes:

A quick look at the table above suggests that the level of compensation provided to manufacturing workers reflects a nation’s overall level of economic, social, and human development. And that is indeed the case, according to a simple statistical analysis by my colleague Charlotta Mellander.

Manufacturing compensation is closely related to productivity (measured as economic output per capita), global economic competitiveness and overall human development as well as my own Global Creativity Index. This is all in line with basic economics. And manufacturing compensation and wages are higher in nations with higher levels of education and where greater shares of the workforce are employed in knowledge, professional and creative jobs. In other words, manufacturing compensation and wages rise as nations become more post-industrial. Higher manufacturing compensation is also related to lower levels of inequality and higher levels of happiness.

Manufacturing workers are paid the best in the most advanced nations, places that boast advanced safety nets, generous benefit systems and high productivity. Post-industrial economies might not have the most manufacturing jobs, but their workers are the best paid. Instead of adopting a low-road strategy of trying to reduce manufacturing costs and wages in order to compete with China or other emerging economies, the U.S. would be better off with a high-road one, promoting policies that improve innovation, skills and productivity.

I think that we learn a lot about cross-country wage comparisons by thinking about what this table does not mean.

Does this table rank countries by the welfare of their blue-collar workers? No. Welfare depends on real consumer wages, not nominal wages, so a welfare comparison would necessitate deflating these nominal wages by local prices. For example, Switzerland is a notoriously expensive place to live; its price level is about 1.5 times that of the US. Those interpreting the table as saying that a US-to-Switzerland migration would raise their wages by 50% would be disappointed when they discovered the accompanying 50% price increase. So this table isn’t about workers’ welfare.

Does this table rank countries by their manufacturing TFP? No, for many (potential) reasons. For example, worker quality may differ considerably across countries. Suppose that all these countries are producing the same goods using the same technology, but different countries’ workers embody different numbers of efficiency units of labor. You’ll then observe substantial wage variation even if the unit cost of labor and manufacturing TFP are identical across countries.

Does this table rank countries by their labor productivity in manufacturing? It would if you believe we’re in a world of factor price equalization so that differences in wage rates must reflect differences in workers’ labor productivity. But are these workers making the same product using the same technology? Are enough factors of production sufficiently mobile to put us in the FPE set? Can large trade costs support differences in unit costs? And so forth.

[By the way, manufacturing employees aren’t all “blue-collar workers”. There is cross-country variation in the white-collar-blue-collar ratio of manufacturing, which will move the average hourly compensation measure.]

The BLS measure “hourly compensation costs in manufacturing” is a straightforward number, but cross-country wage comparisons are not a straightforward economic concept. Richard Florida suggests that we understand something about it by looking at its correlates. I would suggest that teaching students what this table does not mean may convey even more economic lessons.