This paper evaluates the impact of regularisation programs on immigration flows using a newly collected dataset and panel-data techniques within gravity models. The study makes two key contributions. First, it introduces a comprehensive dataset detailing regularisation policies in OECD countries, covering programs implemented between 1944 and 2023. This dataset includes information on the timing, targeted nationalities, and key policy characteristics. Second, it estimates the effect of regularisation using a gravity model of bilateral migration. It applies a Pseudo Poisson Maximum Likelihood estimator to an unbalanced panel of 193 origin countries and 32 OECD destination countries over 28 years. We also employ a staggered difference-in-differences strategy, which is heterogeneity-robust in the effects across cohorts. The main results show that regularisation programs act as a pull factor for migration, driven by higher-income destinations and origins with extended pre-existing networks. The impact is sizeable following the first regularisation, leading to a 18.7 percent increase in the immigration rates. A novelty of the findings is that the requirement of month is a significant deterrent capable of fully mitigating the pull effect. Furthermore, no significant effects were found for subsequent regularisation programs targeting previously treated country pairs.
