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Are workers’ wages keeping up with productivity gains?

by xyonent
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Readers might be surprised to learn that the question of whether workers’ wages are keeping up with productivity growth depends on 1) how you measure workers’ wages and 2) how you measure productivity growth. Scott Winship considers the alternatives and problems in “Understanding Worker Wage Trends Over the Last 50 Years.” (American Enterprise Institute, May 2024).

To understand what’s at stake in this dispute, let’s first look at the numbers from the annual report. Economic Report of the President The White House Council of Economic Advisers’ annual report for 2022:

As Winship points out, this statistic — showing that workers’ compensation is not keeping up with their productivity — is often used in reports trying to show inequality in the US economy.

But if you look at the way the numbers are written, you’ll notice that “productivity” is “net total economic productivity,” which refers to the economy as a whole, and “net” means that capital depreciation is subtracted. “Non-managerial compensation” raises the question of what workers are included here.

When Winship runs his favorite calculations, one of the graphs looks like this:

Notice how Productivity and Wages match up nicely. Also notice that the variables are defined slightly differently. Now “Productivity” is in the “Non-Farm Sector,” so government, non-profits, and agriculture are excluded. All “paid employees” in this part of the economy are counted, but the self-employed are excluded, which may not be the same as “Non-managerial workers” in the previous chart. Or there is another way to measure Winship.

Again, wages and productivity are equal, where “productivity” is measured in the “non-financial corporate sector,” which is a subset of the “non-farm business sector” that excludes finance.

I want to emphasize that all of the underlying data here comes from official U.S. government sources, such as the Bureau of Economic Analysis and the Bureau of Labor Statistics. So the underlying lesson here is that what seem like small differences in the labels of numbers actually represent quite different concepts. Here are some of the issues Winship points out:

The category of “non-managerial” workers in the first figure excludes about 20 percent of private sector employees, as well as government employees and, increasingly, the self-employed, so comparing this group to “total economic productivity” can be misleading.

The part of gross domestic product that measures the economy as a whole is called “total housing value added.” For renters, this is measured as rent. For homeowners, government statisticians calculate “imputed” rent – the rent that homeowners pay to live in their own homes. Winship writes:

One reason that economy-wide productivity has risen faster than compensation is because the total value added of housing has risen faster than the part of GDP that is associated with the goods and services that workers primarily produce.19 But this divergence does not actually indicate that workers are not being compensated commensurate with their value to their employers. The housing sector should be excluded from analyses that compare productivity and compensation, which is one reason why many researchers focus on the nonfarm sector.

Winship argues that in apples-to-apples comparisons, “over 75 or 100 years, workers’ aggregate wages have moved closely together with productivity gains. Wage differences across industries, across firms within an industry, and within firms all seem to correspond to productivity differences.”

But he also argues that productivity differences are occurring unequally across the U.S. economy. Productivity and wages are becoming more unequally distributed across industries, between firms within a given industry, and even within individual firms, even as average wages track average productivity. He writes (footnotes omitted):

While we don’t have an individual-level measure of productivity, much of the evidence we have indicates that productivity inequality is growing among individual workers. First, productivity inequality is growing across industries. For example, industries with more educated workers are more productive. Industries with more educated workers in 1989 saw stronger productivity growth through 2017.

Productivity inequality has also grown between companies. Moreover, wage inequality and productivity inequality have grown primarily between companies in the same industry, rather than within companies or across industries. Research has shown that companies with more productive workers pay their workers higher wages, benefiting everyone from the lowest-paid to the highest-paid employees. Moreover, increased productivity for companies translates into higher wages for employees.

The widening productivity gap between firms is similar to the widening wage gap. A study analyzing U.S. firms from 1977 to 2007 found that both productivity and wage gaps between firms widened, with the productivity gap widening being larger. These widenings occurred in each of eight industries. … Productivity gaps are not only widening between industries and firms, but are also likely to be widening within firms. A recent paper shows that in highly productive firms, the wage gap between the highest and lowest paid workers is larger. More surprisingly, a firm’s productivity increase raises the wages of all employees in that firm, but not equally. In a firm that has become more productive, the highest paid worker receives a larger increase in income than the lowest paid worker. These findings suggest that highly productive firms are disproportionately productive because of their highest paid workers, that is, the highest paid workers are more productive than the lowest paid workers.

I have written many times about the widening productivity gap between industries and companies, and even between companies within the same industry (see, for example, here, here and here). This appears to be an international phenomenon. Over time, productivity laggards will adapt or shrink, but the process can be slow.

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