Tip of the hat to Ted Fertik for bringing Servaas Storm’s unpacking of total-factor-productivity growth (TFP) to my attention. Storm shows that TFP can be regarded mechanically as a weighted sum of the growth rates of labor and capital productivity, roughly in a 3:1 ratio in that order. TFP, of course, is a measure of our ignorance. It nudges us to look inside firms, ie the supply side. This leads down the path to situated communities of skilled practice, ie Crawford’s ‘ecologies of attention.’ But perhaps it is better to work directly with labor productivity, certainly if Storm is right. Some say that high wages incentivize firms to invest in labor-saving innovations thereby increasing labor productivity. This is certainly consistent with the standard microeconomics view of firm behavior in that they are expected to do whatever it takes to get a competitive advantage in the market. A straightforward implication of this hypothesis is that real wage growth ought to predict productivity growth. We’ll see what the evidence has to say about this presently. But let us first note the policy implications of the theory.

The fundamental challenge of contemporary Western political economy is how to restore economic dynamism. The first-best solution to the rise to China is for the West to maintain its technical and economic lead. Similarly, the first-best solution to political instability and the crisis of legitimacy is a revival in the underlying pace of economic growth. So far no one has offered a credible solution; Trump’s tariffs, nationalist socialism á la Streeck, restoration of high neoliberalism á la Macron, are all small bore. But if the hypothesis that a significant causal vector points from real wage growth to productivity growth holds, then a bold new Social Democratic solution to the fundamental challenge of Western political economy immediately becomes available.

What I have in mind is a new mandate for central bankers. To wit, Congress should mandate the Federal Reserve to maximize real median wage growth subject to monetary and labor market stability. Until now central banks have targeted labor market slack as understood in terms of employment and inflation. But the real price of labor (more precisely, productivity-adjusted real median wage) is also an excellent measure of labor market slack. The hypothesis implies that targeting productivity-adjusted real median wage growth could restore productivity growth; perhaps dramatically. My suggestion is consistent with social democracy’s concern with distributional questions as well as with standard central banking practice. So if the result holds, it’s very useful indeed.

We start of by checking that real wage growth predicts productivity growth in the United States. The correlation is large and significant (r=0.531, p<0.001). This is suggestive.

In order to systematically investigate this question we interrogate the data from the International Labor Organization (ILO). The ILO provides estimates of real output per worker, unemployment rate, and the growth rate of real wages. We restrict our sample to N=30 industrial countries since wage growth has diverged so significantly between the slow-growing advanced economies and fast-growing developing countries. We estimate a number of linear models and collect our gradient estimates in Table 1.

We begin in the first column that reports estimates for the simple linear model that explains productivity growth by 1-year lagged real wage growth. In the second column, we introduce controls for a temporal trend and lagged productivity growth. This sharply reduces our estimate for the gradient suggesting that the estimate reported in column 1 was inflated due to autocorrelation. We introduce country-fixed effects (ie country dummies) in column 3, which modestly reduces our estimate of the gradient. Instead of country fixed-effects, in the fourth column, we control for the unemployment rate, which turns out to be significant and which very modestly increases our gradient estimate. In the last two columns we introduce random effects for country and year. What this means is that instead of dummies for each country and year which is equivalent to having fixed intercepts by country and year, we admit the possibility that the intercept for a given country and year is random.

Table 1. Linear mixed-effect model estimates. |
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Intercept | Yes | Yes | Yes | Yes | No | No |

Trend | No | Yes | Yes | Yes | Yes | Yes |

AR(1) | No | Yes | Yes | Yes | Yes | Yes |

Country fixed-effect | No | No | Yes | No | No | Yes |

Unemployment Rate (lagged) | No | No | No | Yes | Yes | Yes |

Real wage growth (lagged) | 0.233 |
0.136 |
0.104 |
0.140 |
0.108 |
0.100 |

standard error | 0.037 | 0.042 | 0.046 | 0.042 | 0.037 | 0.044 |

Country random effect | No | No | No | No | Yes | Yes |

Year random effect | No | No | No | No | Yes | Yes |

Source: ILO. Estimates in bold are significant at the 5 percent level. Dependent variable is real output per worker at market exchange rates. The number of observations is 480. |

We note that the gradient for lagged real wage growth remains significant across our linear models even after controlling for a temporal trend, lagged term for the dependent variable, lagged unemployment rate, country fixed-effects, and random effects for country and year. We can thus be fairly confident that real wage growth predicts productivity growth across the industrial world. The next step would be to embed this in a macro model to interrogate the viability of real median wage growth targeting by central banks.