Weekly Hours, Overtime, and Employment of Manufacturing Production Workers: Fluctuations over the Business Cycle Accessible Data

Figure 1: Response of Employment, Weekly Hours, and Overtime of Manufacturing Production Workers around Recessions

Figure 1 looks at the average response of weekly hours, overtime, and employment over a 24-month window around business cycle turning points. For ease of comparison, all series are scaled by their average level during peaks; in addition, we normalize their values at National Bureau of Economic Research (NBER) peaks (figure 1a) and troughs (figure 1b) to identify percentage changes relative to the turning point. Overtime hours appear most responsive to business cycle fluctuations: Six months before the business cycle peak, overtime hours are 7 percent above their value at the peak and start to decline significantly (figure 1a); similarly, six months after the trough, overtime hours recover swiftly with a 10 percent increase (figure 1b). Both weekly hours and employment, instead, tend to move more modestly around turning points, wavering around a few percentage points, but each follows different timing: Fluctuations in weekly hours closely mirror the timing of changes in overtime, while the response of employment appears somewhat delayed, especially during a recovery.

Note: Percentage change in average weekly hours, average overtime hours, and employment of production workers relative to average peak 1956 to 2018. NBER business cycle troughs are normalized to zero.

Source: Bureau of Labor Statistics (BLS).

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Figure 2: Cyclical Variation of Employment, Weekly Hours, and Overtime of Manufacturing Production Workers

Figure 2 isolate the cyclical components of weekly hours, overtime, and employment using a Baxter-King filter. Overtime hours display the largest swings around recessions; additional fluctuations, however, are present during expansions, likely unrelated to aggregate business cycle movements.

Note: Cyclical components from Baxter-King filter; each series is normalized by its average peak. Gray-shaded areas indicate NBER recessions.

Source: BLS.

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Figure 3: Correlation Function

Figure 3 shows the correlation function for weekly hours, overtime, and changes in employment at different business cycle leads. We calculate the correlation at a quarterly frequency to smooth through the monthly volatility. All series display the highest correlation at zero leads—i.e., with the contemporaneous change in our business cycle indicator—suggesting a high sensitivity to coincident business cycle movements. In particular, the correlation between our business cycle indicator and overtime hours is around 0.76 at zero leads. An even slightly higher correlation applies to changes in employment. The correlation coefficients decline at higher leads, following a similar trend across all three labor market series, and are not significantly different from zero for the six-quarter-ahead variables (at six leads).

Note: Correlation between an index of the business cycle and leads of employment, weekly hours, and overtime hours.

Source: BLS, Census, FRB, MacroAdvisors, and Stock & Watson.

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Figure 4: Evaluating the Performance of the Cyclical Index over Past Recessions

Figure 4 compares our business cycle indicator with the prediction implied by OLS post-Lasso method around recessions not included in the sample used for estimation. While the trends of the two series are remarkably different in the 1980s, we mostly focus on the ability of our prediction to identify business cycle turning points. In particular, our prediction points to declines in economic activity that coincide with the onset of recessions in two out of the three cases shown in figure 4. While in the 1980s our estimate seems well synchronized with the fluctuations in the business cycle indicator around recessions (figure 4a), in the 1990s our indicator remains flat for a few months before declining well after the March 1991 recession begins.

Note: Comparison between a business cycle indicator and an OLS post-Lasso-based index of weekly hours, overtime, and employment in selected industries. Indicators are normalized to 100 in 1976m1/1988m1.

Source: BLS, Census, FRB, MacroAdvisors, and Stock & Watson.

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Last Update: May 24, 2019