10. High quality emigration statistics are important for policymaking. Emigration remains a fundamental component of the population equation and demographic change. Countries have an interest in the volume and attributes of their emigrants and diaspora.

11. Emigration estimates feed into population estimates, labour market statistics and characteristics. It is important for countries to understand the level and demographic of people leaving, so the policies reflect the current population, and resources can be allocated appropriately.

12. The COVID-19 pandemic highlighted the importance of understanding emigrant populations from the perspective of the source jurisdictions. As borders closed, and populations that had limited access and rights in host countries were exposed, source jurisdictions did not have good information on their citizens living outside their borders, to offer sufficient support or pathways back to the source nation.

13. In the early 2000s the Bureau of the Conference of European Statisticians recognized the need to promote and use harmonized concepts and definitions of migrants. A joint UNECE/Eurostat Task Force on Measuring Emigration Using Data Collected by the Receiving Country was set up in 2005, to develop guidelines on how to measure emigration through data on stocks and flows in host countries. The main output of the work of the task force are the Guidelines for Exchanging Data to Improve Emigration Statistics, published in 2010.

14. In addition to exchanging data, in order to produce better statistics on emigration and overcome the related problems, researchers and national statistical offices (NSOs) have developed over time various techniques, including residual methods, indirect estimation, sampling methods, and statistical modelling. In 2013, a CES working group on migration statistics¹ produced a review of those methods², discussing the relative strengths and limitations of each approach.

15. Since then, more administrative data have become available in many countries. Some countries have been able to make use of new data sources³. Administrative data or new data sources, for instance, can be used to identify emigrants who have not communicated their departure. Data integration and other methods suitable for measuring emigration data have advanced considerably. In Canada, where there is no population register, emigrants are estimated by using data from the Child Tax Benefit programme and the Canada Revenue Agency, but also from the United States Department of Homeland Security regarding emigration to the United States.

16. Considering the high policy relevance of emigration statistics, the progress made in the last few years, and the fact that there is still room for improvement in this field, it is timely to review the data sources and methods available for the production of emigration statistics, to identify good practices that could lead to improvement.

17. At its October 2022 meeting, the UNECE Group of Experts on Migration Statistics discussed topics for future work and expressed strong support for launching new methodological work on measuring emigration.

18. In February 2023, the Bureau of the Conference of European Statisticians (CES) discussed future work on migration statistics and agreed to establish a Task force on measuring emigration. In October 2023, the terms of reference of the task force were approved by the CES Bureau and the task force was established with the objectives to:

(a) Collect information and material on existing experience and plans in NSOs and other government agencies for measuring emigration, focusing on new data sources and innovative methods, on cooperation initiatives between countries, and on emigrants (not including the children of emigrant parents);

(b) Identify examples from outside official statistics to estimate migration that could be potentially relevant for NSOs for measuring emigration;

(c) Analyse and review the collected material, and provide guidance to NSOs for measuring emigration in an internationally comparable way;

(d) Compile the examples into an online reference tool and develop a mechanism for updating it with new examples.

19. The task force started its work by recognizing the activities being carried out by the United Nations Expert Group on Migration Statistics on the revision of the 1998 International Recommendations on International Migration Statistics and discussing which definition of emigration should be used by the task force. The task force agreed to use the definition of long-term emigration (12 months or more) from the 1998 recommendations. The task force recognizes that this definition is not in line with the new Recommendations on Statistics of International Migration and Temporary Mobility, which were endorsed by the United Nations Statistical Commission in March 2025 ⁴.

20. Then, the task force designed a questionnaire to collect from its members detailed information about availability and use of data sources relevant for measuring emigration, experiences using data linkage, use of mirror statistics, assumptions needed to estimate emigration in administrative data, and evaluation of emigration statistics.

21. The questionnaire (see annex) was completed by 11 countries (Albania, Australia, Canada, Hungary, Italy, Latvia, Mexico, New Zealand, Poland, the United Kingdom, and the United States). The information collected was analysed by the task force. The main results of this analysis, with some recommendations formulated by the task force based on the responses from the 11 countries, are presented in this report as described in the next section.

22. The work of the task force was presented at the meeting of the UNECE Group of Experts on Migration Statistics (Geneva, 7–8 May 2024). In the discussion, participants noted the rapid pace of change in technology, data sources and statistical methodology, and welcomed the efforts of the task force to assess the current situation across the region and develop updated guidance on these topics. It was also noted that there is a greater emphasis on timeliness than there had been in the past, as well as greater attention to quality assessment. The growing need for flexibility, such as being able to adapt a methodology rapidly to account for new phenomena or to cover events spanning very small time periods, was noted. The value of alternative methods (both sources and statistical approaches) is being more proactively explored, including not only administrative sources but also longitudinal perspectives, modelling, and the use of machine learning and artificial intelligence.

23. This chapter focuses on the data sources used by responding countries to produce their emigration statistics, the various breakdowns that are published, and the methodologies used in estimating emigration. Because the methodology considerations are driven by both the required quality and breakdown of estimates, but also by the timeliness requirements of publication, the various publication timelines of respondents are also presented.

24. It also includes information about the production timelines as well as breakdowns of the variables produced for emigration estimates, as well as information about the various data combination techniques and estimation models used by various countries.

25. The chapter presents the responses to the section of the questionnaire concerning the use of mirror statistics, including insights into how countries use them and from which countries the mirror data are collected. It then provides a detailed overview of the main barriers that have limited the use of mirror statistics for measuring emigration across countries. The chapter continues with a discussion of the key results and conclusions based on the questionnaire. Based on these findings, a set of recommendations and guidelines are provided on how mirror statistics can be used to measure emigration or to evaluate estimates of emigration.

26. The chapter concludes with three case studies — from New Zealand, Poland and Italy — that offer practical examples and insights. These case studies illustrate the diverse applications of mirror statistics: to measure emigration flows, to measure population stocks of citizens residents abroad, and to support the use of mirror statistics through international data exchanges.

27. This chapter explores the approaches used by the NSOs to evaluate and communicate the quality of their long-term emigration estimates. It provides an overview of the methods employed to assess the accuracy and reliability of emigration data, discusses the challenges NSOs face, and how they address these issues through regular evaluations or other indicators of uncertainty or confidence intervals.

28. This chapter also provides a summary of how NSOs communicate the quality of their emigration estimates. It offers practical insights into the diverse methods used to communicate migration data to help ensure that users can properly interpret and trust the data.