I study the problem of monitoring in a dynamic setting, where the monitor's detection ability is endogenous. An agent chooses how much to offend and privately develops evasion technologies to make future offenses undetectable, while the monitor can invest to restore her detection ability. I analyze the dual effect of enforcement policies on offending and investment dynamics, revealing a trade-off: deterring detectable offenses increases the agent's investment incentives, leading to a more intense arms race with higher R&D spending and more evasion by the agent. Applications include digital security, drug trafficking, environmental monitoring of toxic emissions, doping, and tax evasion.

I study the optimal procurement mechanisms in environments where the relevant production technology is unknown at the time of designing contracts. A principal's mechanism choices influence how agents endogenously sort across available technologies, resulting in an endogenous ex-post participation and distribution of types and information for each state of the world. The paper's main result shows that for any targeted vector of ex-ante probabilities of technology adoption, the optimal mechanism has the following properties: the set of types adopting each technology is continuous, efficient types adopt the technology which is most likely to be relevant, less efficient types mix between the two technologies, whereas intermediary types mix with a strictly interior probability. Compared to mechanisms that induce pure technology adoption, mixing reduces rents across all types and strictly increases efficiency. The paper has applications to technological procurement in contexts such as the development of renewable energy technologies, quantum computing, vaccine production, and defense contracts.

This paper studies the problem of resource allocation in the presence of moral hazard. An agent exerts effort and privately chooses resource allocation between two types of capital: one that increases the productivity of exerting effort and one that reduces its cost. Our analysis provides conditions such that the agent’s problem exhibits complementarity between effort and productivity. In this case, we show that the agent under-allocates resources to increase productivity. The paper’s main result provides sufficient conditions on the production problem such that the agent strictly benefits from the allocation being private information. The model can be applied to several economic environments, such as technology procurement, product development, and time allocation in labor settings.

This paper develops a comprehensive framework to analyse the role of surplus sharing and violence in shaping criminal relationships. Combining evidence from the literature with game-theoretical models, we analyze the determinants and impact of violence and surplus sharing on cooperation in extra-legal environments. Firstly, we show that peaceful cooperation is only possible in high-value activities and requires "fair surplus" distribution. This result explains why some criminal markets such as international cocaine trafficking are functional even under low levels of violence. Secondly, we show that a credible threat of violence is essential for low-value generating activities such as extractive protection. Additionally, we show that a higher ability to exert violence induces more surplus appropriation. We use these results to reassess the mechanisms used in extra-legal settings by focusing on their impact on value creation, benefit distribution, and the credibility of threats of violence.