Despite widespread agreement on the importance of data to effectively manage migration, the availability of reliable and comparable migration data is still limited. The reality is that we know much less about how much and what kind of migration is happening today, than we do about international trade or investment flows (CGD, 2009). Only 45 of the 193 UN Member States report statistics on migration flows and even in censuses only 50 per cent of countries ask for the year of arrival in country, making it impossible to differentiate between international migrants and temporary migrant, or ‘movers’ (IOM and McKinsey, 2018).
Despite efforts to incorporate migration-related questions into national censuses, the regular collection of disaggregated migration data continues to be a challenge for most countries. According to MGI data, 61 per cent of the participating countries included more than one migration-related question, e.g., place of residence one or five years prior, period of arrival in country, reasons for migration, or mobility patterns of household members living abroad, in their most recent national census. Unfortunately, a significant number of countries still use census forms that are limited to more generic population and demographic questions, e.g., country of birth or country of nationality (IOM, 2024b).
Part of the reason for this is that policymakers are not always convinced of the returns of investing in such data or, if the topic of migration is highly politicized, they may fear sharing or publishing the data (IOM, 2018). However, political sensitivity is not only a cause but also a consequence of data limitations, as unreliable data may lead to misperceptions about migration, potentially fuelling anti-immigrant attitudes (CGD, 2009). Political dynamics may lead stakeholders to exaggerate figures on forcibly displaced persons to increase funding allocation or to under-report figures on the same population to fit with the government's narrative of peace and security (Krynsky Baal, 2021).
Even when data are collected, they tend to be scattered across various locations and sources. Within countries there may be a lack of consolidation across different ministries or between government agencies, civil society organisations, private sector businesses and universities. Furthermore, issues related to reliability, timeliness, completeness and the level of disaggregation compromise the robustness of insights that can be drawn from available data. Poor data quality limits the extent to which conclusions for the design or the evaluation of migration policies can be reached. When decision-makers are not convinced by the evidence they are presented, for example, because the evidence differs according to which data are quoted, they are less likely to take action. Outdated data make it difficult to react to sudden developments such as natural disasters or global epidemics. Incomplete or unspecific data can lead to misrepresentation of the facts, thereby prompting unsuitable interventions. Data that are not sufficiently disaggregated prevent practitioners from delivering support and assistance in an efficient and effective way (IOM and McKinsey, 2018). Other challenges include, among others, insufficient resources and technical capacities, not only in the production but also in the analysis of data; failure to disaggregate by migratory status in data collection for other sectors such as education, health and employment; and changes in data ownership and authority due to government restructuring and reshuffling.
One of the key challenges, however, is the harmonization and standardization of concepts and definitions, which continue to differ across countries and organizations. Ensuring that data are comparable matters for several reasons. It is important for quantifying a country’s emigrant population living abroad based on the destination country’s data. Having access to similar data from another country also encourages an assessment of the quality and reliability of data produced in one’s own country (UN Expert Group on Migration Statistics, 2022). As we live in an increasingly integrated world where the responsibilities of manging migration are being shared by a greater number of countries, comparable data on the effects of migration are key to assigning those responsibilities and providing support to countries with fewer capacities for responding to migration. Finally, a lot of what we know about the individual- and contextual-level causes and effects of migration are based on cross-country comparisons, for example, comparing the numbers of IDPs across countries would enable us to identify the factors associated with those numbers. However, lack of comparability in the methods for counting IDPs across countries prevents us from observing consistent patterns or trends (Bell and Charles-Edwards, 2014).