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Research has become the main reference point for academic life in modern universities. Research incentives have been a controversial issue, because of the difficulty of identifying who are the main beneficiaries and what are the long-term effects. Still, new policies including financial incentives have been adopted to increase the research output at all possible levels. Little literature has been devoted to the response to those incentives. To bridge this gap, we carry out our analysis with data of a six years program developed in Madrid (Spain). Instead of using a traditional econometric approach, we design a machine learning multilevel model to discover on whom, when, and for how long those policies have an effect. The empirical model consists of an automated nested longitudinal clustering (ANLC) performed in two stages. Firstly, it performs a stratification of academics, and secondly, it performs a longitudinal …