Is the U.S. Labor Market for Truck Drivers Broken? An Empirical Analysis Using Nationally Representative Data

The US trucking industry trade press often portrays the US labor market for truck drivers as not working, citing persistent driver shortages and high levels of firm‐level turnover, and predicting significant resulting constraints on the supply of motor freight services. We investigate the truck driver labor market using three techniques. First, using data from the Occupational Employment Statistics of the Bureau of Labor Statistics, we delineate the structure of the driver workforce. Second, from the same source we find that the trucking labor market has displayed some characteristics of a "tight" labor market since 2003: rising nominal wages, stable/growing employment, and lower rates of unemployment than other blue-collar jobs. Third, using data from the Current Population Survey we describe the occupations and industries from which drivers come and to which drivers go, when they change occupations, and statistically analyze these entries and exits. We find relatively high rates of occupational attachment among drivers, and importantly, we also find that truck drivers respond in the expected manner to differences in earnings across occupations. Finally, we point out that the issues discussed by the industry are concentrated in one segment of the overall market, that for drivers in long distance truckload (TL) motor freight, which contains between one sixth and one fourth of all heavy and tractor‐trailer truck drivers. These findings suggest a more nuanced view of this labor market. The market as a whole appears to work as well as any other blue‐collar labor market, and while the truck driver market tends to be "tight," there do not appear to be any special constraints preventing entry into (or exit from) the occupation. There is thus no reason to think that driver supply should fail to respond to price signals in the standard way, given sufficient time. The persistent issues localized in the TL segment are not visible in the aggregate data, and require a distinct analysis.