Micro data linking: Addressing new emerging topics without increasing the respondent burden

Abstract

Micro data linking (MDL) has become an important cornerstone in the production of new statistical insights. MDL is now widely acknowledged as a strategic activity to avoid increasing the respondent burden when meeting new user demands on e.g. globalisation. MDL is a strong method in combining micro data on individual entities such as enterprises, people or in a combination of both (Linked Employer-Employee Data). MDL is one of the most powerful methods to answer urgent questions on emerging policy or research topics such as the interconnectedness of the economies and its consequences for jobs, income and growth. Not only for national purposes, where economic behavior and dynamics by enterprises can be expressed in terms of job dynamics, income and welfare for its citizens, but also from an international perspective where consistent and coherent indicators play an important role. Firstly, the article addresses the central role of the Business Register for any MDL approach related to business statistics; secondly the current official statistics based on MDL such as Trade by Enterprise Characteristics (TEC) are described. Thirdly, the most common use of MDL in terms of producing experimental statistics are described, including linked employer-employee data (LEED).

Gender and food systems

“…It adds to the substantial amount of OECD analysis related to gender issues. 5 The following section discusses the roles of women in food systems as entrepreneurs, workers and consumers, and provides an assessment of evidence gaps. Section 3 explains why better evidence on the role of gender in food systems is needed for effective policy design; Section 4 describes policies addressing gender inequality in food systems and evidence gaps on assessing their effectiveness.…”

“…It does not cover evidence gaps related to the contribution and specific needs of sexual and gender minorities in food systems. Additional research is needed in this area to better inform policy makers, as highlighted recently by researchers (Hoffelmeyer, 2020[3]) (Wypler and Hoffelmeyer, 2020[4]) (Leslie, Wypler and Bell, 2019 [5]) and the OECD (2020 [6]) (2019 [7]).…”