We develop and implement a method to improve estimates of worker flows and job openings based on the Job Openings and Labor Turnover Survey (JOLTS). Our method involves reweighting the cross-sectional density of employment growth rates in JOLTS to match the corresponding density in the comprehensive Business Employment Dynamics (BED) data. To motivate our work, we compare JOLTS to other data sources and document large discrepancies with respect to aggregate employment growth, the magnitude of worker flows, and the cross-sectional density of establishment growth rates. We also discuss issues related to JOLTS sample design and nonresponse corrections. Our adjusted statistics for hires and separations exceed the published statistics by about one-third. The adjusted layoff rate is more than 60 percent greater than the published layoff rate. Time-series properties are also affected. For example, hires exhibit more volatility than separations in the published statistics, but the reverse holds in the adjusted statistics. The impact of our adjustment methodology on estimated job openings is more modest, raising the vacancy rate by about 8 percent.
Published as Steven J. Davis, R. Jason Faberman, John C. Haltiwanger, Ian Rucker. "Adjusted Estimates of Worker Flows and Job Openings in JOLTS," in Katharine G. Abraham, James R. Spletzer, and Michael Harper, editors, "Labor in the New Economy" University of Chicago Press (2010)