The FRED graph above shows a disturbing pattern: Since the early 1970s, there’s been an apparent disconnect between labor productivity and real wages. (The accumulated difference was 70% at the end of 2022.)
Our goal here is to better understand these statistics, so let’s first define what we’re talking about.
- Labor productivity is computed by taking the ratio of total production in the economy (i.e., real GDP) to total number of hours worked in the economy.
- Real wages is computed by taking total compensation paid to non-farm employees and dividing it first by an estimate of total number of hours worked and then by the consumer price index, thus providing an idea of the purchasing power of an hour of work.
This graph is disturbing because it seems to show that US workers only partially benefitted from the increases in their productivity since the 1970s. This decoupling isn’t unique to the United States, however, so let’s look more closely at what’s behind the data.
First, these averages may hide much of what’s going on across the distribution of wages—in particular, the sectoral composition of the economy. For example, there was high productivity growth over the past decades in some sectors, such as finance and information, that wasn’t matched by labor compensation, despite substantial increases. And there was no decoupling at all in other industries.
Second, the price index we use matters. So we replicated the graph above with two more series: Labor compensation is now deflated by the GDP deflator and by the producer price index (PPI).
The results are quite different, and the decoupling isn’t as stark. The original real labor compensation line describes what purchasing power workers have, as it is deflated by a price index that tracks a typical basket of goods a household would buy. The two new lines look at this from the employer side: How much are workers paid compared with (i) the value of all things produced (GDP deflator) and (ii) the prices that producers are getting for their wares (PPI)? These two lines are much closer to the productivity line, indicating that the choice of prices matters.
Why would you take one price series over another? It depends on what question you’re asking of the data. If you want to understand how businesses decide to allocate resources to factors of production (labor, capital, intermediates), then the second graph is relevant. If the topic is about worker purchasing power, then the first graph is relevant. But more fundamentally, why would these price indexes differ so much? That’s the topic of our next blog post…
How these graphs were created: For the first graph, search FRED for “hourly compensation” and select the non-farm series. Click on “Edit Graph,” add a series by searching for the CPI, apply formula a/b, and change the units to a custom index with 100 as of 1970-01-01. Now open the “Add Line” tab and look for labor productivity. Apply the same custom index. For the second graph, take the first and add two more lines, using the same steps to add the GDP implicit price deflator and the PPI (instead of the CPI).
Suggested by Christian Zimmermann.