29.15. Reasons for revisions to seasonally adjusted data. Revisions of seasonally adjusted data occur for two main reasons. Seasonally adjusted data may be revised as the consequence of a revision of the unadjusted data, which may be the result of an improvement in the information set. Revisions of seasonally adjusted data can also occur because of a better estimate of the seasonal pattern due to new information provided by new unadjusted data and to the characteristics of the filters and procedures for removing seasonal and calendar components. The challenge is to strike a balance between the precision of seasonally adjusted data and their stability over time. Revisions of seasonally adjusted data should be carried out in accordance with a coherent, transparent and officially announced revision policy, and should not be more frequent than the revisions to the raw data. In this regard, it is good practice to keep the model specification for seasonal adjustment as stable as possible over time, and to coordinate the timing of revisions to the model specification with the timing of major revisions of the raw data.
29.16. Trade-off between frequency and accuracy. How seasonal adjustment is carried out has implications for the revision policies. At one extreme, there is so-called current adjustment, which minimizes the frequency of revisions and concentrates the revisions mainly within a predefined review period. At the other extreme, there is so-called concurrent adjustment, which maximizes the accuracy of the adjusted data at any given point, but leads to more revisions, often from the beginning of a series, with many of them small and moving in opposite directions. In practice, other procedures are utilized, based on a combination of these two extreme approaches.
29.17. The decision regarding whether a changed time series should be published in its entirety is influenced by several factors. On the one hand, there is an incentive from a methodological perspective to treat all values identically, so as to ensure that calculations are easy to understand and to replicate. However, it is nevertheless questionable whether a newly added figure actually contains information relevant for significant revisions to the estimation of the usual seasonal fluctuations in previous decades. As a means of balancing the information gain and the revision horizon, the revision period for the seasonally adjusted data is often limited to being between three and four years longer than the revision period for the unadjusted data (see also para. 26.15).