Alex Domash, Lawrence H. Summers March 17, 2022
Since the start of the pandemic, labor market indicators have been sending different signals about the degree of slowdown in the US labor market. This column uses time series and cross-sectional data to show that firm-side unemployment—a measure that relates the unemployment rate to the job vacancy and quit rate—predicts wage inflation better than either the unemployment rate or the jobless rate. employment, and that the business-unemployment that the United States is currently experiencing corresponds to a degree of stress previously associated with unemployment below 2%. The results suggest that labor markets in the United States are extremely tight and will likely contribute to inflationary pressures for some time to come.
Since the start of the Covid-19 pandemic, labor market indicators that traditionally move together have sent very different signals about the level of slowdown in the US labor market. Supply-side indicators, such as the employment-to-population ratio in the oldest age group, are still below pre-pandemic levels (79.5% in February 2022 compared to 80.5% in February 2020), suggesting a slight slowdown in the labor market. On the other hand, demand-side indicators like quits and vacancy rates have reached record highs in recent months, indicating a very tight labor market.
The discrepancy between supply and demand indicators has sparked debate over which measure to use to gauge labor market tightness. Some, like Federal Reserve Chairman Jerome Powell (2021), have suggested looking at employment indicators such as the employment rate in the prime working age bracket to gauge the labor market slowdown. work. Others have found that demand-side indicators like the vacancy-to-unemployment ratio (Barnichon and Shapiro 2022) or the quit rate (Furman and Powell 2021) are the most predictive of wage inflation.
In our recent paper (Domash and Summers 2022), we use time series and cross-sectional data to compare other labor market indicators as predictors of wage inflation. We compare four different slowdown indicators – the overall unemployment rate, prime-age employment rate, vacancy rate, and quit rate – and find that unemployment is a better predictor of inflation wages than the employment rate, and the vacancy and quit rates are roughly equivalent to the unemployment rate in terms of explanatory power. We then construct a new indicator – firm-side unemployment – that relates the unemployment rate to vacancy and quit rates, and find that firm-side unemployment significantly outperforms the unemployment rate in predicting wage inflation. .
Labor market indicators have diverged sharply
Figure 1 presents Beveridge-type curves showing the relationship between supply-side and firm-side labor market indicators since 2001.
Figure 1 Relationship between measures of underemployment on the business side and those on the household side, January 2001 – December 2021
Historically, supply-side measures of underutilization, such as the unemployment rate and the prime-age (25-54) non-employment rate (one minus the employment-to-population ratio in prime age), have evolved in parallel with measures of underutilization of supply. on the demand side, such as vacancy rates and attrition rates, meaning that different indicators gave broadly corroborating signals of labor market tightness. Figure 1, however, shows that since the start of the Covid-19 pandemic, supply-side indicators and demand-side indicators have diverged considerably (shown in orange).
These shifts in the Beveridge curves imply a higher level of vacancies and quits for a given level of unemployment or non-employment. This begs the question: are supply-side or demand-side slack indicators more meaningful in predicting wage inflation?
Unemployment on the firm side has a dominant explanatory power for wage inflation
We use quarterly time series and cross-sectional data between 1990 and 2019 to compare the explanatory power of different measures of wage inflation expansion. Since data on vacancies and departures from the Job Openings and Labor Turnover Survey (JOLTS) are only available up to 2001, we use two sets of alternative data to extend these series to 1990:
- For vacancies, we use data constructed by Barnichon (2010), who uses the Help-Wanted Index published by the Conference Board to create a historical series of vacancy rates from 1960 to 2001.
- For quit rates, we use quarterly job quit estimates from Davis et al. (2012), who constructed a quarterly dataset of worker departures (DFH-JOLTS) by combining cross-sectional worker flow relationships with data on the cross-sectional distribution of establishment growth rates.
We first show that the U-3 unemployment rate is better than the prime-age employment rate in predicting wage inflation at the aggregate and state level, and that the rate vacancy rate and quit rate are comparable to the U-3 unemployment rate in their explanatory power. These results are valid for different wage series and periods. We then estimate an equivalent firm-side unemployment rate by examining which unemployment rate corresponds to the current measures of the job vacancy rate and the quit rate. We regress the unemployment rate on the logarithm of the vacancy rate and the logarithm of the quit rate, using monthly JOLTS data from January 2001 to December 2019. We run several different model specifications, including different lag lengths, a time trend and a structural break in July 2009. In general, all models fit data from 2001 to 2019 very well, but show a sharp break in the relationship after February 2020.
Figure 2 shows the relationship between the actual unemployment rate and the expected firm-side unemployment rate, using a model with 12-month lags, a time trend, and a structural break. The expected unemployment rate on the company side in January 2022 was between 1.3% and 1.7%.
Figure 2 Actual unemployment rate compared to the expected unemployment rate on the company side
Using a wage Phillips curve model that includes the actual unemployment rate and our predicted unemployment rate as regressors, we find that the firm-side predicted unemployment rate has essentially all the explanatory power to predict wage inflation on the period 2001 to 2019. These results are robust across 12 different model specifications that vary the wage series used to calculate nominal wage growth and the lag length of our explanatory variables. Moreover, the results also hold in cross-sectional data: at the state level, decreases in firm-side unemployment are more predictive of state-level wage growth than decreases in actual unemployment.
Given the extremely low unemployment rate expected by businesses today, these results provide strong evidence that the current labor market is very tight. Projected company-side unemployment rose from an average of 3.6% in Q4 2019 to an average of 1.5% in Q4 2021, corresponding to an increase in wage inflation of 4.0% to 4.9% (according to the CPS-ORG average salary). Figure 3 shows estimates of nominal wage growth from a wage Phillips curve model using expected firm-side unemployment as a drag variable and controlling for lagged inflation. The results indicate that estimated wage inflation in the fourth quarter of 2021 is the highest in 20 years for all of our four wage measures.
picture 3 Predicted year-over-year nominal wage growth using firm-side unemployment as the predictor variable
Future prospects regarding labor market tensions
Some economists believe labor market tightness will be eased in the coming year by increases in labor supply. We do a quick analysis of the current labor shortage and estimate that labor market participation is likely to remain significantly depressed at least until the end of 2022, with excessive retirements, health problems linked to Covid-19, restrictions on immigration, changes in the tastes of workers. approximated by reservation wages and changes in demographic structure explaining most of the labor shortage.
Moreover, if employment were to increase due to an increase in labor market participation, this would be accompanied by an increase in income, and therefore an increase in demand. We therefore believe that any supply-side benefits over the next year should not materially alleviate inflationary pressures in the labor market. Overall, our research concludes that labor markets are likely to continue to be very tight unless there is a significant slowdown in labor demand. These results suggest to us the need for great caution regarding the possibility of inflationary pressures in the labor market in the future.
Barnichon, R (2010), “Building a composite index of help sought”, Economics Letters 109(3): 175-178.
Barnichon, R and AH Shapiro (2022), “What is the best measure of economic slowdown? », FRBSF economic letters 2022(4): 1-05.
Davis, SJ, RJ Faberman and J Haltiwanger (2012), “Labour Market Flows Across Cross-Section and Over Time”, Monetary Economics Journal 59(1): 1-18.
Domash, A and L Summers (2022), “How Tight are US Labor Markets?”, NBER Working Paper 29739.
Furman, J and W Powell III (2021), “What is the Best Measure of Labor Market Tightness? Peterson Institute for International Economics blog post, November 22.
Powell, JH (2021), “Getting Back to a Strong Labor Market”, speech at the Economic Club of New York (via webcast), 10 February.