Leave no migrant behind: Why data disaggregation by migratory status is critical to the 2030 Agenda in Asia and the Pacific and beyond

In consonance with the aim of the UN World Data Forum to build a pathway for better data in support of the implementation of the 2030 Agenda, and particularly Thematic Area 2 which calls for maximizing the use and value of data for better decision making, we argue that data disaggregation by migratory status is critical to ensuring migrants are not left behind in this global agenda.

As the origin of more than 83 million emigrants and the destination of 42 million immigrants, countries in Asia and the Pacific are characterized as the places of origin, destination, and transit for international migration. Migration to, from and within the region has been mainly motivated by economic opportunities, labour demand, emerging threats and conflicts, disasters, and the effects of unsustainable development. These drivers of migration were heavily disrupted by the COVID-19 pandemic, as border closures and movement restrictions reduced mobilities worldwide. However, the pandemic response also highlighted stories of migrant resilience and their immense contributions to societies across the region and the world, as showcased in the IOM Regional Data Hub’s Asia-Pacific Migration Data Report 2021 and 2020.

Migration is closely interlinked with numerous areas of development outlined in the Sustainable Development Goals (SDGs) and the Global Compact for Safe, Orderly and Regular Migration (GCM). Migrants can be key development actors in the fields of poverty reduction, food security, health, education, gender equality, decent work and economic growth, peace, justice and institution strengthening, amongst others. For instance, migrants are powerful drivers of poverty reduction, innovation, and economic development in both the countries of origin and destination, and they often constitute the backbone of many health systems. In other words, migrants’ contributions to sustainable development cannot be understated. However, migrants are often disproportionally at risk of vulnerability, such as heightened risks of poverty, food insecurity and malnutrition related conditions, human rights violation and discrimination compared to non-migrants.

Although several SDG indicators focus on topics directly related to migration, such as migrant deaths and disappearances, refugees, recruitment cost, remittance cost and migration governance, other SDG indicators generally provide no information on how migrants’ outcomes or progress towards achieving the SDGs differ from non-migrants. The COVID-19 pandemic has not only revealed but often exacerbated inequalities for vulnerable groups, reminding us how important it is for policy to be inclusive of all population groups, including migrants.

SDG Target 17.18 calls for increasing the availability of “high-quality, timely and reliable data disaggregated by income, gender, cage, race, ethnicity and migratory status”. Moreover, Objective 1 of the GCM calls for the “collection and utilization of accurate and disaggregated data as a basis for evidence-based policies”. To fully achieve these commitments, disaggregated data are needed to show how different segments of a country’s population are making progress or falling behind. Understanding the many positive links between migration and the SDGs is central to the effective implementation of the SDGs, and the GCM in policymaking. Additionally, disaggregated data are fundamental to the design of effective, evidence-based policies that are inclusive of migrants. Despite its complexity, leaving no one behind lies at the core of the 2030 Agenda for Sustainable Development and data disaggregation is key to achieving this.

In the Asia-Pacific region, data for monitoring the SDGs remain scarce, especially when accounting for disaggregation by migratory status. A recent IOM Regional Data Hub’s study found that, out of 24 SDG indicators recommended by the UN Expert Group on Migration Statistics for disaggregation, only six indicators related to labour and education are currently available for disaggregation by migratory status across the region, and few countries have data available for these indicators. While disaggregated data on earnings (SDG Indicator 8.5.1) are available for 18 out of 40 Asia–Pacific countries since 2010, data for the other five indicators, including unemployment (SDG Indicator 8.5.2), youth not in employment, education or training (SDG Indicator 8.6.1), learning (SDG Indicator 4.1.1), literacy (SDG Indicator 4.6.1) and occupational injuries (SDG Indicator 8.8.1), are available for fewer countries. Indeed, disaggregated data on occupational injuries are only available for Pakistan.

Given the scarcity of data disaggregated by migratory status, these findings reveal that migrants remain largely invisible in official SDG data in Asia and the Pacific. Meanwhile, data collection is not always available, complete, or disaggregated across the various migration topics nor is it comparable among countries. While existing evidence focuses on the Asia-Pacific region, such data gap and its implications might be more widespread than known. This implies that, as we approach 2030, little is known about whether migrants are left behind and to what extent, in the region and beyond.

There is therefore an urgent need for a reliable, consolidated, and up-to-date evidence base to enhance the understanding of migration pathways and drivers, to aid policymaking and to inform public discourse on migration. The IOM Regional Data Hub for Asia and the Pacific responds to this need in its aim to monitor the SDGs and GCM by centralizing information from the region, leveraging quantitative insights, harmonizing data processes, and promoting good data practices. Echoing the call of the UN World Data Forum, it is important to emphasize that regional and global efforts to leave no migrant behind will inevitably count on the collection and utilization of timely and accurate data with disaggregation by migratory status, which will help countries build a solid evidence base for the development of truly inclusive policies. In particular, Session TA1.14 on Diverse Partnerships for Inclusive Data on Migration of the Forum will provide a valuable opportunity for data producers and users to exchange good practices and unpack the challenges of collecting data disaggregated by migratory status at the global, regional and national levels.

Learn More: