The Myth of the Pay-Productivity Gap

Economists and politicians alike have alleged, particularly in more recent years, that since 1973 there has been an effective separation between pay and productivity.

This talking point has been embraced by crony policymakers, anti-banking hard money advocates and socialists. However, no matter how much universal endorsement a talking point gets, it will never serve to justify it.

The supposed pay and productivity gap is, in reality, a prime example of faulty statistics and sets a bad precedent for acceptable methodology. Quite contrary to the claim that from 1979-2020 while productivity has grown by over 60%, hourly pay has only increased by 17.5%, the reality is that total compensation has grown on track with productivity.

Senator Elizabeth Warren has also previously stated that if the minimum wage had kept up with productivity, it would be at $22.00 an hour. This conclusion is drawn from improper data, shown below:

These data suffer from a vital defect in that they only examine hourly wages, and use the CPI to index for inflation. First, by only examining hourly wages this data examines only a part of total income, which includes non-cash benefits such as healthcare insurance, pensions, etc. By 2012 this accounted for over 20% of employee income. Secondly, the measures used to track inflation and productivity are incompatible. The Bureau of Labor Statistics uses the the Implicit Price Deflator (IPD) to adjust productivity for inflation, which uses different measures and goods and services than does the Consumer Price Index (CPI).

A more complete vision is given by the Economic Policy Institute but remains insufficient. They account for total compensation by including wages and benefits, they come up with a closer estimate:

As economist Veronique de Rugy has pointed out, there are still numerous defects in this model. While the study includes total compensation, it only includes those employed in production and nonsupervisory positions. The apples to oranges comparison of some employee pay with all employee productivity accounts for about 45% of the gap.

This further discludes ‘irregular’ payment methods such as performance-based pay. Workers, for example, who are self-employed have their rising productivity included in the data, but their rising pay is disregarded. This accounts for nearly 12% of the gap. However, the main flaw is again adjusting for inflation through the CPI, which accounts for about 39% of the gap. The CPI not only is incompatible with the IPD measurements, but also tends to overestimate inflation by failing to account for consumer responses to changing prices, or a “substitution effect.” The CPI also severely overestimates how much of consumers’ income is spent on utilities. This is because it relies on the Consumer Expenditure Survey, which contains recall bias.

Once these faulty comparisons and biases are fixed, the gap is significantly smaller, and hardly noticeable at all. This is shown below;

While there seems to still be a large gap, this is due to overestimated productivity growth from depreciation. With an increasing rate of capital depreciation, this means that more and more will be spent on replacing old equipment, but this does not increase income. Looking at

the graph below, we can see that capital consumption allowances have greatly increased since 1988:

James Shrek also shows the increasing depreciation on capital since 1973:

Price inflation in various types of goods, such as investment goods will also conceal depreciation and make it appear as a smaller share of the economy. Using the IDP to adjust for real NDP and GDP, another chunk of the difference is made up.

Thus, after accounting for as many relevant factors as possible, there exists little to no gap between total compensation and productivity as shown below:

The myth of the pay-productivity gap has been exposed. It is not as crony policymakers suggest an excuse to intervene in the free market in order to engineer a preferred wealth distribution. Rather, it is a faulty interpretation of data and a myth that must be busted.