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2023 Eight-yearly Module Implementation and Development and Improvement of the Finnish LFS: 2022-FI-LFS-LMB
Details
Locations:Finland
Start Date:Aug 1, 2022
End Date:Dec 31, 2024
Sectors: Labour Market & Employment, Statistics
Categories:Grants
Funding Agencies:
Date posted:Dec 21, 2022
Description
Programme(s): Single Market Programme (SMP)-undefined
Topic(s): SMP-ESS-2022-LFS-LMB-H3-S-6005-6247-IBA
Type of action: SMP European Statistics
Project ID: 101101065
Objective:
The overall objective is to support NSIs to improve labour market statistics. The specific objective is to support the NSIs to implement the legal provisions governing the EU-LFS from 2021, as set out in Regulation (EU) 2019/1700 of the European Parliament and of the Council, and in particular Commission Delegated Regulations (EU) 2020/256, 2020/257 and 2020/1640 as well as, Commission Implementing Regulations (EU) 2019/2180, 2019/2181, 2019/2240 and 2020/1642. Firstly, the background of project lies in the implementation of the data collection on the eight-yearly variables on ‘pension and labour market participation’, related the explanatory notes made available by Eurostat. These eight-yearly variables will be collected as a sub-sample of the Finnish LFS. Secondly, the objectives consist of testing the new variables related to a future implementation of the ICSE-18 in the LFS (as it will be agreed by the LAMAS working group in 2022); and the development of dependent interviewing as well as the instructions and household formation at the web questionnaire; and the use of administrative registers to fulfill the precision requirements in Regulation (EU) 2019/1700, as well as testing the information content of the registers in relation to LFS content. Furthermore, we intend to implement a responsive data collection strategy by assigning differing contact mode priorities based on evidence from contact attempts of past data collection. As a secondary approach, we also intend to consider and possibly experiment a substitute respondent approach for a limited sub-group of hard-to-reach sample units and consider its implications to both data quality and bias to our estimates. As this will be an experiment, the data provided by the substitute respondents will not be included in the LFS data sets but used only to analyze the effectiveness and possible problems of this new approach.