Improving JOLTS Methodology
With the release of January 2009 data on March 10, 2009, BLS has implemented improvements to the methodology used to generate estimates of hires, separations, and job openings from the Job Openings and Labor Turnover Survey (JOLTS). These changes are designed to improve the measurement of hires, separations, and openings and to more closely align the hires and separations estimates with monthly employment change as measured by the BLS establishment survey.
Research comparing the relationship between JOLTS hires and separations to the monthly employment change measured by the Bureau’s Current Employment Statistics (CES) program (the establishment survey) indicates substantial discrepancies in employment trends over time. While JOLTS does not produce estimates of month-to-month change in employment, an implied employment change can be derived from JOLTS data by subtracting the separations estimate from the hires estimate for a given month. When viewed over time, this derived JOLTS measure of employment change does not track well with the CES, the Bureau’s larger and better-known establishment survey. The CES is designed specifically to measure month-to-month employment change, collects data from a much larger sample, and benchmarks annually to universe employment counts, making CES the more reliable source of monthly employment change. Further, comparison of JOLTS hires and separations data to similar data produced in the Bureau’s Current Population Survey (CPS or household survey) also indicates that JOLTS may be understating the levels of hires and separations.
BLS engaged in a multi-year research project to better understand these two issues, to establish their probable causes, and to develop improvements. As a result of this research, BLS has implemented improvements in the following areas:
Improvements to the JOLTS Sample Design
Currently, the JOLTS sample is constructed from individual panels of sample units drawn on an annual basis. The full sample consists of one certainty panel made up of large units selected with virtual certainty based on their size, and 24 non-certainty panels. Each year a new set of panels is drawn from the Bureau’s Longitudinal Database (LDB), a product of the Quarterly Census of Employment and Wages (QCEW) program. Each month a new non-certainty panel is rolled into collection, and the oldest non-certainty panel is rolled out. The collection life of a sample panel is therefore 24 months. This means that at any given time the JOLTS sample is constructed from panels from three different sampling frames, the most current being slightly over one year old and the oldest being slightly over three years old. Thus the JOLTS sample design reflects established firms that have been in business for a minimum of one year.
To better reflect the impact of younger establishments in the JOLTS sample, BLS has modified the JOLTS sample design in the following ways. First, when a new set of panels is selected each year, the birth units in the sample (those not in existence on the previous year’s frame) will be initiated for collection first, rather than waiting until their associated panel is initiated. Second, each quarter the newly updated LDB will be reviewed to identify birth establishments and a supplemental sample of these units will be drawn and added to the survey; at the same time, out-of-business units will be dropped from the sample on a quarterly basis. Thus, the JOLTS sample will be refreshed quarterly rather than annually. Third, the entire sample of old plus new panels will be poststratified and re-weighted annually to represent the most recent sampling frame; at present, this is not done for sample drawn from earlier frames. This procedure will make the sample more efficient than at present.
JOLTS Business Birth/Death Model
As with any sample survey, the JOLTS sample can only be as current as its sampling frame. The sampling frame for JOLTS is drawn from the LDB, which is updated quarterly from files submitted to the BLS QCEW program as part of the State Unemployment Insurance system. The built-in time lag from the birth of an establishment until its appearance on the sampling frame is approximately one year. In addition, many of these new units may fail within the first year. Since these universe units cannot be reflected on the sampling frame immediately, the JOLTS sample cannot capture job openings, hires, and separations from these units during their early existence. To develop data for these units that cannot be measured through sampling, BLS has developed a model to estimate the contribution of these units to the current month estimates. The birth/death model estimates birth/death activity for the current month by examining the birth/death activity from previous years on the LDB and projecting forward to the present using an econometric technique known as X-12 ARIMA modeling. The birth/death model also uses historical JOLTS data to estimate the amount of “churn” (hires plus separations) that exists in establishments of various sizes. The model then combines the estimated churn with the projected employment change to estimate the number of hires and separations taking place in these units that cannot be measured through sampling.
The model-based estimate of total separations is distributed to the three components: quits, layoffs, and other separations, in proportion to their contribution to the sample-based estimate of total separations. Additionally, job openings for the modeled units are estimated by computing the ratio of openings to hires in the collected data and applying that ratio to the modeled hires.
The estimates of job openings, hires, and separations produced by the birth/death modeling process will then be added to the sample-based estimates produced from the survey to arrive at the final estimates for hires, separations, and openings.
Because JOLTS estimates did not previously include this step, addition of the birth/death model will raise the levels and rates of the hires, separations, and openings measured by JOLTS, and allow the series to more accurately reflect the current labor market.
Modifications to Data Collection Procedures
As stated earlier, an implied measure of employment change can be derived from the JOLTS data by subtracting separations from hires for a given month. Aggregating these monthly changes in the current series, however, generally produces employment levels that overstate employment change as measured by CES, at the total nonfarm level. Research into this problem has shown that a significant amount of the divergence between the CES employment levels and the derived JOLTS employment levels can be traced to the Employment Services industry and to the State Government Education industry. In the former industry, businesses have a difficult time reporting hires and separations of temporary help workers. In the latter industry, employers have a difficult time reporting hires and separations of student workers. BLS plans to devote additional resources to the collection, editing, and review of data for these industries. BLS analysts will more closely examine reported data that do not provide a consistent picture over time, and will re-contact the respondents as necessary. Analysts will work with the respondents to adjust their reporting practices as possible. Units that cannot be reconciled but are clearly incorrect on a consistent basis will be dropped from the estimation process and imputed for using existing techniques.
Establishment of an Alignment Procedure
Over time, employment change derived from JOLTS hires minus separations should track well with employment change measured through the CES. However, there are some definitional differences between the series that can cause legitimate differences for individual months. The major reasons for these month-to-month divergences are:
Both of these definitional differences can result in differing seasonal patterns between the two series, and therefore cause JOLTS to diverge from the CES in the short-term. Over time however, the computation of JOLTS hires minus separations should reflect employment changes that are consistent with the trends measured by the CES. The three changes to JOLTS that have been described above are expected to produce JOLTS series’ that are much more consistent with the CES. The residual divergence will be controlled through a monthly alignment procedure that allows JOLTS to vary from CES for the reasons listed above, while ensuring that the long-term trends in JOLTS hires-minus-separations match those of the CES net employment change.
The goal of this process is to use current monthly CES employment trends to align the JOLTS implied employment trend (hires minus separations) to be approximately the same, but without forcing all the seasonal patterns to be the same between the surveys. This method takes advantage of the fact that the CES employment series for the current reference month is available prior to the production of JOLTS estimates for that same reference month.
Revisions to Historical Series
NOTE: The information in this section reflects revisions made to data in March 2009. The data provided in the links to the tables are no longer current since they are revised annually. The links remain active so users can see the affect of the change in methodology. To query current JOLTS data, please click here.
The monthly JOLTS series begin with estimates for December 2000. All published estimates back to that point have been revised to reflect the addition of the birth-death model and the new alignment procedure, as well as selected adjustments to individual survey reports. On March 10, 2009, new historical series for job openings, hires, total separations, quits, layoffs and discharges, and other separations replaced the previously available series. Tables comparing the original and revised series are below (again, please note the data have been revised and are no longer current):
To query current JOLTS data, please click here.
For more information, please send e-mail or call (202) 691-5870.
Last Modified Date: March 9, 2010