The Current Employment Statistics (CES) survey uses a program called X-13ARIMA-SEATS to seasonally adjust its data. This program, developed by the U.S. Census Bureau and Statistics Canada, uses a procedure to automatically select from a variety of ARIMA models during the annual seasonal adjustment process. Effective with the release of January 2017 data on February 3, 2017, CES began using an alternative method of automatic model selection known as Time Series Regression with ARIMA Noise, Missing Observations, and Outliers (TRAMO), developed by Victor Gómez and Agustin Maravall of the Bank of Spain.
Research suggested that using the TRAMO procedure to seasonally adjust CES national estimates yielded improvements to forecasts and overall model fit, while showing little-to-negligible change across other statistical measures such as data revisions and model selection errors.
For more comprehensive and technical information about differences between the two methodologies, see Comparing Automatic Modeling Procedures of TRAMO and X-12-ARIMA, an Update (2007) (PDF).
Last Modified Date: February 3, 2017