Visiting Scholar Steven J. Davis

The Job Openings and Labor Turnover Survey (JOLTS) is an innovative data program that delivers national, regional and industry estimates for the monthly flow of hires and separations, and for the stock of unfilled job openings. Analysts have seized on JOLTS data as a valuable source of insights about U.S. labor markets and an important new research tool for evaluating theories of labor market behavior. Recent studies draw on JOLTS data to investigate the cyclical behavior of hires and separations (Hall, 2005), the Beveridge curve relation between unemployment and job vacancies (Valetta, 2005; Fujita and Ramey, 2007; Shimer, 2007b), the connection between quits and employer recruiting behavior (Faberman and Nagypál, 2007), and the relationship among vacancies, hires and employment growth at the establishment level (Davis, Faberman, and Haltiwanger, 2006, 2007). Given the key roles played by job vacancies and worker flows in prominent search-based theories of unemployment along the lines of Mortensen and Pissarides (1994), JOLTS will continue to attract keen interest from researchers.

In addition to notable virtues, the JOLTS program presents measurement issues that are imperfectly understood and not widely appreciated. Reasons for concern can be seen in three simple comparisons to other data sources. First, the aggregate employment growth implied by the flow of hires and separations in JOLTS consistently exceeds the growth observed in its national benchmark, the Current Establishment Statistics survey.[1] Cumulating the difference between hires and separations from 2001 to 2006 yields a discrepancy of 6.6 million nonfarm jobs. Second, JOLTS hires and separations are surprisingly small compared to similar measures in other data sources.[2] Third, the cross-sectional density of establishment growth rates shows much less dispersion in JOLTS than in data sources with comprehensive establishment coverage.[3] . . .

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Steven J. Davis is a visiting scholar at AEI.

Notes

1. See Wohlford et al. (2003), Nagypál (2006) and Faberman (2005a).
2. See Faberman (2005a) and Davis, Faberman and Haltiwanger (2006).
3. See Faberman (2005a).