Organization profile

Profile Information

With the free movement of individuals within the EU, political instability and global inequality, more and more people have been crossing borders in recent decades, either as refugees, regular migrants or as daily transnational commuters. These cross-border movements generate important challenges for EU countries, and has particularly strong implications for its labour market, public finances, social cohesion and regional governance around border areas. In this context, it is important to have tools to monitor, analyse and improve the understanding of causes and consequences of these flows - a prerequisite for relevant advice to policy-makers. 

The cross-departmental Research Programme on ‘Crossing Borders’ seeks to coordinate, develop and contribute to the Cross-Border work carried out within and across the any of the three departments of LISER. 

The Research Program on Crossing Borders has specific objectives:

(i)      Assess the size and structure of historical and recent cross-border flows, and understand their root drivers.

(ii)     Use innovative sources of data to study the interplay between different forms of mobility.

(iii)   Analyse the economic and societal consequences of these flows for all parties concerned.

(iv)   Build projection tools to anticipate future movements.

(v)     Develop tools to help policy decision-makers to maximise the gains and/or minimise the cost of current and future movements for European countries in general, and for the Luxembourg society in particular.

(vi)   Provide stakeholders and the civil society with databases and expert analyses that help them
understanding the forces at work and the consequences of policy actions.

(vii) Contribute to the training of PhD researchers on these topics.

Network Recent external collaboration on country level. Dive into details by clicking on the dots.


Photo of Frédéric Docquier


Research Output

  • 7 Article
  • 4 Working paper
  • 1 Conference contribution
  • 1 Other contribution

An Aggregate Learning Approach for Interpretable Semi-supervised Population Prediction and Disaggregation Using Ancillary Data

Derval, G., Docquier, F. & Schaus, P., 30 Apr 2020, Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019: Würzburg, Germany, September 16–20, 2019, Proceedings, Part III. Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M. & Robardet, C. (eds.). Springer, p. 672-687 (Lecture Notes in Computer Science book series (LNCS); vol. 11908).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Birthplace diversity and economic growth: evidence from the US states in the Post-World War II period

Docquier, F., Turati, R., Valette, J. & Vasilakis, C., Mar 2020, In : Journal of Economic Geography. 20, 2, p. 321–354

Research output: Contribution to journalArticle

COVID-19 Crisis Management in Luxembourg: Insights from an Epidemionomic Approach

Burzynski, M., Machado, J., Aalto, A., Beine, M., Haas, T., Kemp, F., Magni, S., Mombaerts, L., Picard, P., Proverbio, D., Skupin, A. & Docquier, F., 25 Jun 2020, Esch-sur-Alzette: LISER, 52 p. (Working papers; no. 2020-08).

Research output: Working paper

Open Access