One of the most complex policy issues that developing countries will face as a result of the employment crisis caused by the Covid crisis is the question of how they can better protect the unemployed. However, the analysis of unemployment insurance (UI) in developing economies with large informal sectors is in its infancy, with few papers providing solid empirical evidence. This paper therefore makes several contributions: first, it applies Chetty's 2008 landmark work on UI to a transition economy (Chile) and shows that the moral hazard effects expected by policy makers, who designed the system are minimal, while liquidity effects were entirely neglected. Second, it demonstrates that it is not enough merely to quantify effects such as moral hazard, but to understand their causes as unemployment generated by moral hazard or liquidity constraints has different welfare implications and should therefore result in different policies. By means of an RDD, this paper analyses the Chilean UI system using a large sample of administrative data, which allows for an extremely precise analysis of how the system works, thus providing invaluable empirical lessons for other countries.