The Linked Employment Cost Index: a first look and estimation methodology [Monthly Labor Review]
This article provides a first look at the Linked Employment Cost Index (Linked ECI), an index the U.S. Bureau of Labor Statistics is evaluating for potential publication. The article describes the linking Laspeyres methodology used to calculate the index, presents preliminary Linked ECI estimates, and compares these estimates with currently published estimates based on a modified Laspeyres methodology. The analysis suggests that the index estimates obtained from the two methodologies are numerically equivalent.
The U.S. Bureau of Labor Statistics (BLS) is exploring the potential publication of a new index of employment cost change. This index, called the Linked Employment Cost Index (Linked ECI), is calculated with the use of a linking Laspeyres approach and is designed to replace the modified Laspeyres ECI already produced by BLS. By evaluating the Linked ECI, BLS aims to (1) enable a more direct method for calculating the index and implementing potential sample-design improvements, (2) allow for experimentation with index derivations, such as those associated with changing compensation definitions, without the need to wait for a reweight period, and (3) achieve greater flexibility in updating the index with new information from collected data.
Currently, BLS calculates ECI estimates by using a modified Laspeyres methodology, which is a cell-link update procedure. In this article, we compare current modified Laspeyres (cell-link) estimates with Linked ECI estimates (based on an index-linking approach), showcasing that these estimates are numerically equivalent. We begin by describing the ECI conceptual framework and the methodologies used for calculating the modified Laspeyres ECI and the Linked ECI. Then, we present our analysis and results for the comparison of index estimates. Finally, because indexes that are well suited for one purpose may be ill suited for another, we identify limitations of the Linked ECI, allowing data users to assess whether the new index suits their needs. . . .
The analysis results presented in this article suggest that the preliminary estimates for the Linked ECI track closely with the currently published estimates for the modified Laspeyres ECI. In most cases, the absolute percent differences between these estimates are less than 0.1 percent. At the 95-percent confidence level, no 3- or 12-month percent-change estimates differ significantly from each other. This is because, in most cases, the differences between the percent-change estimates are less than 0.1 percentage point, while the differences between the standard errors of those estimates are often slightly greater than 0.1 percentage point. Hence, the Linked ECI and the modified Laspeyres ECI are numerically equivalent.
Producing Linked ECI estimates as a replacement for currently published ECI estimates provides several benefits. First, the Linked ECI offers a straightforward method for index computation. Moreover, because this computation is based on an index-linking approach, it enables a more direct method for implementing potential sample-design changes and offers greater flexibility in calculating standard errors. It also simplifies the process of index reweighting, allowing a change in the compensation definition without the need to wait for a reweight period.
Moving forward, BLS is interested in receiving feedback from data users about the value of calculating Linked ECI estimates and using them as a replacement for the currently published modified Laspeyres ECI estimates. One consideration in assessing this value may involve the frequency of reweighting. Currently, employment weights are updated every 10 years. A possible adoption of the Linked ECI will simplify the reweight process, but reweighting also has the potential to disrupt historical continuity. Given these considerations, BLS will consider any additional feedback from stakeholders to ensure that the frequency of reweighting accurately reflects the slow-moving shifts in the employment mix.