By Paige Benattar, Hannah Phaup and Alister Ratcliffe
Each year the Bank publishes an analysis of revisions to its monthly data on money, credit, and effective interest rates produced by the Data and Statistics Division (DSD). This year’s analysis shows that the revisions have been immaterial for most series tested. This is the same broad conclusion as the 2017 analysis of 2012-14 data and the 2016 analysis of 2011-13 data.
Revisions are a normal part of the data production process. There are several reasons why data might be revised after initial publication. Reporters of data to the Bank may submit corrections to earlier data if they discover errors or make improvements to their data systems. In addition, the Bank might change the methodology it uses to produce the data. Also, the seasonal adjustment process can lead to revisions to an entire series, as each new data point provides new information about the seasonal pattern of the data.
Revisions analysis gives users an indication of how much weight to place on data when it is first released. Data that is not usually revised much can be regarded as less noisy and more reliable.
Revisions are measured in different ways: the average size of the revisions, bias, and their variability. We consider each of these in turn below.