![]() In reality, the CES sample estimates include sampling and nonsampling errors, and the QCEW census data include nonsampling errors. It assumes that the census value used in the alignment is essentially without error. This generalized statement is, however, overly simplified in some cases. To ensure that the accumulated error does not get too large in any direction, the CES program benchmarks the survey estimate level by using a lagged population value.īenchmarking is used to align a survey estimate with a census value. The hope, of course, is that the errors are random and offsetting-that is, some errors on the positive side are balanced by some errors on the negative side. The primary estimator for state and metropolitan area employment estimates, a derivative of the weighted link-relative estimator, includes a robust procedure for identifying and reducing the influence of unusual reports (or outliers).Īlthough the link-relative estimator is an efficient estimator for employment change, errors may accumulate over time because each estimate is linked to the one before it. Is the net birth/death factor for month c. Is the change ratio for current month c (equation 1), and Is the employment estimate for prior month p, Is the employment estimate for current month c, The weighted link-relative estimator, shown below, is composed of Is the employment for prior month p for establishment i. Is the employment for current month c for establishment i, and Is the sampling weight associated with establishment i, ![]() Is an establishment that reported both this month and last month, The primary employment estimator, 1 shown just below, provides an efficient estimate of over-the-month (OTM) change and is also referred to as the "change ratio" for month c: An estimated adjustment value is then added to account for the net employment change in businesses not captured by the survey this estimated adjustment value is called the net birth/death factor. It takes the ratio of current-month weighted employment to prior-month weighted employment (based on a matched sample of collected data) and multiplies that quotient by the prior-month employment level. The primary estimator for national employment data is referred to as a weighted link-relative estimator. BLS produces about 50,000 data series each month, using the business reports collected for the CES program. The national data are revised two times on the basis of additional data collected for the reference period, and the subnational data are revised once. About 2 weeks later, data are produced for states and metropolitan statistical areas. The survey produces employment, hours, and earnings data by detailed industry levels. The reference period is the payroll period that includes the 12th of the month. BLS produces and publishes the initial estimates from the survey about 3 weeks after the reference period. The CES survey is a quick-response business survey that provides some of the earliest information about the state of the U.S. The QCEW covers about 97 percent of the employment that is in scope for CES estimates. Bureau of Labor Statistics (BLS) Quarterly Census of Employment and Wages (QCEW) serves as both the population list and the primary source of benchmark employment. In the Current Employment Statistics (CES) survey, the U.S. Many surveys may select a sample from a population list (at time t), take the requisite time to collect the survey data, and then align the survey estimates with population values from an updated population list (at time t + 1) to make the estimates as current, relevant, and accurate as possible when published. For example, a high-quality sampling frame-a list of all those within a population who can be sampled-usually includes a population measure or census count correlated to a major statistic to be collected. In a statistical sense, a benchmark is a high-quality population value against which a survey estimate may be judged in order to assess the quality of the estimate.įor surveys, a benchmark is something obtained outside the survey. A benchmark is generally described as a standard of excellence against which other things are judged.
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