[No abstract available

Abstract. Labour Market Areas (LMAs) are regions built on the basis of commuting to work data so that the majority of the labour force lives and works within their boundaries. LMAs have long being recognised as relevant for assessing the effectiveness of local policy decisions. Eurostat encourages LMA development in the European Union. The idea is to share methods and tools towards the creation of a harmonised geography. As the LMA functional approach to territorial partitioning is getting more and more used for policy purposes, the demand for indicators is increasing. The paper illustrates the shared method, the recently publicly available software package LabourMarketAreas developed at Istat for LMA design. The paper also presents examples of indicators at LMA level built from register data. Finally the small area estimation method implemented by Istat to release employment and unemployment rates at this geographical level is sketched.

This study shows that 2D-US does not provide an accurate estimation of TV and suggests that it can be improved by a mathematical model different from the ellipsoid model. If confirmed in prospective studies, this may contribute to a more appropriate management of thyroid diseases.

Most important large-scale surveys carried out by national statistical institutes are the repeated survey type, typically intended to produce estimates for several parameters of the whole population, as well as parameters related to some subpopulations. Small area estimation techniques are becoming more and more important for the production of official statistics where direct estimators are not able to produce reliable estimates. In order to exploit data from different survey cycles, unit-level linear mixed models with area and time random effects can be considered. However, the large amount of data to be processed may cause computational problems. To overcome the computational issues, a reformulation of predictors and the correspondent mean cross product estimator is given. The R code based on the new formulation enables the elaboration of about 7.2 millions of data records in a matter of minutes.

No abstract