@TechReport{iza:izadps:dp18674,
            	author={Albanese, Andrea and Marguerit, David},
            	title={Labor-Market Consequences of Cross-Border Employment: A Machine Learning Approach},
            	year={2026},
	month={May},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={18674},
            	url={https://www.iza.org/publications/dp18674},
	abstract={Cross-border work is expanding in the EU, yet its labor-market effects on the cross-border workers themselves remain largely undocumented. Using linked Belgian administrative registers that identify cross-border spells in Luxembourg, we estimate the effects of cross-border employment on post-return labor-market outcomes through dynamic double machine learning. Returnees face a short-run employment penalty that fades with cross-border tenure and time since return. They are also more likely to receive Belgian unemployment benefits than comparable stayers, with higher daily benefit levels among recipients.},
	keywords={cross-border commuting;return migration;unemployment insurance;EU labor mobility;administrative data},
            }