  Active labor market programs are important instruments used by European
employment agencies to help the unemployed find work. Investigating large
administrative data on German long-term unemployed persons, we analyze the
effectiveness of three job search assistance and training programs using Causal
Machine Learning. Participants benefit from quickly realizing and long-lasting
positive effects across all programs, with placement services being the most
effective. For women, we find differential effects in various characteristics.
Especially, women benefit from better local labor market conditions. We propose
more effective data-driven rules for allocating the unemployed to the
respective labor market programs that could be employed by decision-makers.
