Let’s have a closer look at migration, the subject under study in YOUMIG. This phenomena is so complex that we will need a set of measurement tools we call indicators to describe it. This includes looking at things like the inflows and outflows of population, the permanent stock of the foreign population, in total and by nationalities, but also age groups, as well as things like migrants’ education levels and professions, attitudes towards migration and intentions to migrate.

What is an indicator?

As Eurostat experts explain “the term `indicator’ has its roots in the Latin words indicare (to point out, to show, to indicate) and index, literally meaning `anything used for pointing’ and `the finger used for pointing’” (Eurostat, 2014). In the modern world, when multiple spheres and disciplines are interconnected, an indicator will point at one specific aspect of a complex phenomenon.

The important characteristics of an indicator is its ability to compress a range of information into one single number for a given time period. By comparing the values of indicators we can assess some trends relevant for our topic. For example, we might speak of a growing number of students studying abroad from one year to another and come up with policy-relevant conclusions about the direction these trends are taking. However, when interpreting the figures, one should not forget that the interpretation is closely related to the questions asked! Thus growing outbound student mobility fits nicely into the goal of increasing international cooperation in the education sector, but without additional measures, it might go against a country’s desire to keep brain drain at a low level. Moreover, the indicator itself does not explain why a tendency occurs. A study of which factors drive the oscillations of indicators is a separate, though highly relevant, topic for policy-making.

Aren’t there enough indicators already collected?

The answer is “yes” and “no”. Over the last decades, the world and all of its processes have been picking up speed dramatically. Interrelations between countries and spheres of life have deepened, new phenomena have appeared.

In such a complex and fast-changing world, a “diagnosis” of a phenomenon might require a better fine-tuning of data. In other words, the disaggregation of existing data into smaller units such as geographic and socio-demographic (and economic) subgroups is necessary. For example, the data on student enrolment in vocational training might only be available at the county level, while a municipality might need such information, too, in order to assess further employment gaps for some occupations. Similarly, not only the number of returnees, but also their education levels and occupations are seen as precious information in order to improve their reintegration and labour force participation chances.

The collection of information, even through so-called administrative registers or databases, and the further estimation of relevant indicators, is not always straightforward. While reporting some information is required by law, for instance the place of birth for requesting a residence permit, the enforcement of registration and de-registration might be lacking. This is where the human factor comes into play. For example, we can speak of de-registration from the municipality of origin for working migrants, which results in the “odd” statistical situation of the same person residing in both the sending and receiving country. In other cases, the definitions describing the same phenomena might differ across countries, for example how long a person must have been away from the country to be counted as a “returnee”. Such discrepancies make it difficult to accurately assess information on the volume and composition of migration flows and stocks, and make it hard for truly informed policy decisions to be developed and undertaken. International comparisons might be inaccurate, too.

In some cases, administrative information might be collected, e.g. number of immigrants in a neighbourhood, while the data is used only for registration purposes and not for the assessment of long-term tendencies such as the concentration of migrants in some quarters of a municipality. Individual information of such kind is also highly sensitive, and in some cases might not be disclosed to researchers or policymakers at all, due to privacy protection, e.g. income data collected by tax authorities. Further, some kinds of information are not collected at all at municipality level, and are only to be found in national representative datasets, which is especially true for subjective indicators such as well-being, trust, and intention to migrate. A further example is qualitative data: while the number of foreign-born entrepreneurs in a municipality only indicates the extent of the phenomena, it does not give us information on the motivations of immigrants to follow this professional path. There can be many underlying reasons for choosing one’s profession: from successful programmes stimulating entrepreneurship to an inability to integrate into the labour market due to difficulties with diploma and skills recognition, or required proficiency in the local language for available vacancies.

The development of further informational and computer techniques and a rise in international and intranational cooperation between data collecting agencies and policy-makers is likely to improve our ability to collect and process the data and use it for informed decisions at different levels. However, this process can take some time.

What do we mean by improved indicators within the YOUMIG project?

The YOUMIG project directly, and indirectly, focuses on three main aspects. These are youth (in a wide sense, to include individuals up to the age of 34), migration, and local development. Youth - its share in the population, sex and nationality composition, educational levels and professions acquired - can determine the success of local development in the immediate present and in the future, too. . The stage of local development and its success can make an area more or less attractive for local youth who decide to stay there and for foreign youth who are newcomers to the area.

In YOUMIG’s indicator lab, work started with a general assessment of existing sources of information in order to understand which indicators relevant to the three aspects mentioned above are already collected by different countries. At the second stage, all partners accessed the availability of such indicators specifically in their own country. For those indicators that were found to be unavailable, municipality representatives and experts discussed the desirability of the collection of the missing data.

At the current stage, researchers and statisticians are concentrating on the most important group of core indicators for each municipality, and especially on those that are unavailable at the current state of affairs. For each country, deep digging took place to list the possible sources of data which could serve as a basis for calculating what was missing. Such sources included administrative sources, national and international individual and household data collections. In some cases, no source was found, and here researchers are designing a small-scale survey for the municipality in order to estimate the current value of the indicator in question.

When several alternative data sources are available, we can confront the information provided by each of the sources. This means identifying any difference in definitions, the age frame, and the population covered. Then one can estimate the values of that indicator and assess the consistency of the estimates across datasets. In cases when only one source is available for an indicator estimation, a small-scale survey will include, where possible, a comparable question. This way we can see how well the existing source reflects reality.

As a result of this process, the YOUMIG data lab will not only collect the values of existing indicators, but also propose the methodology and the sources for the estimation of currently missing indicators.  Supplying missing data can enable partners to better assess the youth migration situation in their municipality in the future. By doing this the project makes sure that the collection of core indicators becomes sustainable in a longer run. In particular, experts are working on finding the sources that can be used for the estimation of indicators on a regular basis and beyond the scope of the YOUMIG project.

Sustainability and a long life of this process is also ensured by the Data Toolkit, another outcome of the project. The Data Toolkit is designed to present indicators to local decision makers in a user-friendly format. More information on the Data Toolkit is forthcoming soon…

Text by Ekaterina Skoglund, IOS, leader of YOUMIG Work Package 4