Currently Available Tools for Seasonal Adjustment of High Frequency Data

Music City Center 

High frequency data have been widely used in official statistics for several years, especially after the Covid-19 pandemic, which increased the demand for infra-monthly indicators. Since then, they have moved from an experimental status to standard production. Many infra-monthly indicators show (multiple) seasonal patterns and need to be seasonally adjusted. Therefore, well-established seasonal adjustment methods for monthly and quarterly data have been extended to meet the methodological requirements of high frequency data and additional ad hoc methods have been developed. With a wide range of algorithms and tools available today, the user is faced with a selection problem.
We provide an empirical review of the available tools and underlying algorithms for seasonal adjustment of high-frequency data, comparing them from different perspectives: quality of the seasonal adjustment process (residual seasonality, revisions, forecasting), possibility to implement methodological refinements: automatic outlier detection and parameter selection, time-varying calendar correction. We also examine the accessibility, usability and performance of the tools in a mass production approach.