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Beyond BLS

Beyond BLS briefly summarizes articles, reports, working papers, and other works published outside BLS on broad topics of interest to MLR readers.

December 2024

What is the best metric to gauge wage growth?

Summary written by: Richard Hernandez

The Phillips curve model (originally used to gauge wage inflation) has often been used to quantify the relationship between the unemployment rate and inflation. The Phillips curve model posits that low unemployment leads to higher inflation because there are fewer workers available per job position. Conversely, when unemployment is high, the model predicts a lower rate of inflation because there are more workers available than job positions. However, is there a better predictor for wage growth? In a recent working paper, “Wage growth and labor market tightness” (Federal Reserve Bank of the New York, Staff Reports no. 1128, October 2024), authors Sebastian Heise, Jeremy Pearce, and Jacob P. Weber investigate a different method for analyzing wage growth in the United States.

Heise, Pearce, and Weber construct a variable to aid in their analysis. They divide the number of vacancies by the number of effective job searchers, where “effective job searchers” is the number of people seeking a job (be they employed, unemployed, or out of the labor force) weighted by an estimate of job-search intensity. In their model, Heise, Pearce, and Weber use the quits rate as well as vacancies divided by effective job searchers. The authors find that those two variables explained about two-thirds of the variation in wage growth since 1990. Over the same period, the authors find that the unemployment rate only explained 34 percent of the variation in wage growth. By themselves, the vacancy-to-effective-job-searcher ratio explained 52 percent of the variation in wage growth and the quits rate explained 55 percent, making them much better predictors of wage growth. The authors also find that the same two variables explained 78 percent of the variation in wage growth from the second quarter of 2020 to the second quarter of 2024.

The model the authors use also better measures labor market slack. By accounting for the quits rate and the vacancies-to-effective-job-searchers variable, the model more accurately captures the metric that the traditional Phillips curve model tries to measure. In regard to market labor tightness, the authors found that the unemployment rate is negatively correlated, while the vacancy-to-effective-job-searcher ratio and the quits rate are positively correlated. The authors also test how well productivity predicted wage growth. They find that it is a weak indicator in predicting future wage growth.

Finally, the authors construct the Heise-Pearce-Weber Tightness Index, an index that can be used for more accurately forecasting wage growth. For policymakers to have accurate models for setting monetary policy, the authors believe that those models must include variables like the quits rate and the vacancy-to-effective-job-searcher ratio.