Technical Information about Standard Errors for Employment Cost Index Estimates
To assist users in ascertaining the reliability of Employment Cost Index (ECI) series, standard errors of all current quarter estimates except seasonally adjusted series are made available shortly after publication of the news release. Standard errors provide users a tool to judge the quality of an estimate to ensure that it is within an acceptable range for their intended purpose. These standard errors are available in TXT and PDF format.
The ECI is derived from a sample survey and thus, it is subject to sampling errors. Sampling errors are differences that occur between the results computed from a sample of observations and those computed from all observations in a population. Estimates derived from different samples selected using the same sample design may differ from each other. (In the case of the ECI, the population of an estimate is an industry or occupation in a civilian, private, or state and local government economic sector.)
The standard error is a measure of the variation among these differing estimates. It can be used to measure the precision with which an estimate from a particular sample approximates the expected result of all possible samples. The standard errors can be used to define a range or level of confidence (confidence interval) around an estimate. For instance, the 90 percent confidence level means that if all possible samples were selected and an estimate of a value and its sampling error were computed for each, then for approximately 90 percent of the samples, the intervals from 1.6 standard errors below the estimate to 1.6 standard errors above the estimate would include the "true" average value. For example, the 90 percent confidence interval for an index percent change estimate of 5.0 percent with a standard error of 1.1 percentage points would be 5.0 percent plus or minus 1.8 percentage points (1.6 standard errors times 1.1 percentage points) or 3.2 to 6.8 percent.
The chances are about 68 out of 100 percent that an estimate from the survey differs from the true population figure within one standard error. The chances are about 90 out of 100 percent that this difference would be within 1.6 standard errors. This means that in the example above, the chances are 90 out of 100 percent that the estimated index percent change is between 3.2 and 6.8 percent.
Comparative statements appearing in ECI publications are statistically significant at the 90 percent level of confidence, unless otherwise indicated. This means that for differences cited, the estimated difference is greater than 1.6 times the standard error of the difference.
Last Modified Date: July 26, 2021