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"This paper describes some of the methodological problems encountered with the change-over from the NACE Rev. 1.1 to the NACE Rev. 2 in business statistics. Different sampling and estimation strategies are proposed to produce reliable figures for the domains under both classifications simultaneously. Furthermore several methods are described that can be used to reconstruct time series for the domains under the NACE Rev. 2." (author's abstract)

"To maintain uninterrupted time series, surveys conducted by national statistical institutes are often kept unchanged as long as possible. When a change is proposed to improve the methods, it may affect the continuity of these series. It is important to minimise the impact so as to minimise the inconvenience for users. In this paper the authors set out the steps in an orderly transition, provide practical guidance on how to minimise discontinuities, and review methods for dealing with discontinuities if they arise so as to maintain a consistently-estimated series." (author's abstract)

Policy measures to combat low literacy are often targeted at municipalities or regions with low levels of literacy. However, current surveys on literacy do not contain enough observations at this level to allow for reliable estimates when using only direct estimation techniques. To provide more reliable results at a detailed regional level, alternative methods must be used. The aim of this article is to obtain literacy estimates at the municipality level using model-based small area estimation techniques in a hierarchical Bayesian framework. To do so, we link Dutch Labour Force Survey data to the most recent literacy survey available, that of the Programme for the International Assessment of Adult Competencies (PIAAC). We estimate the average literacy score, as well as the percentage of people with a low literacy level. Variance estimators for our small area predictions explicitly account for the imputation uncertainty in the PIAAC estimates. The proposed estimation method improves the precision of the area estimates, making it possible to break down the national figures by municipality.