In a continuous-time setting, we study the taxation of a state-sponsored monopolist, granted with the right to use a government-owned facility, when there is asymmetric information of demand parameters hit by imperfectly correlated shocks. We show that optimal taxation requires an appropriate combination of fixed and time-adjusted payments from actual sales. We then analyse how the optimal combination of fixed and variable transfers is impacted by the private revenue potential, by the expected variability of demand and by the importance assigned to tax receipts relative to other welfare concerns.

Do elections constrain incumbent politicians’ policy choices? To answer this longstanding question, this paper proposes a novel identification strategy to separate electoral incentives from selection effects. Taking advantage of the unique setup of lame-duck sessions in the U.S. Congress, where lame-duck incumbents who lost re-election vote on the same issues as their re-elected colleagues, I use a close election regression discontinuity design to exploit quasi-random assignment of re-election seeking representatives to lame-duck status. Comparing within-incumbent changes in roll call voting of barely unseated lame ducks to narrowly re-elected co-partisans serving the same congressional term, I find that lame ducks revert to more extreme positions with lame-duck Democrats (Republicans) voting more liberally (conservatively). Consistent with lame ducks’ loss of re-election incentives driving the result, the effect of lame-duck status on roll call extremism is more pronounced among ex-ante more vulnerable legislators.

We examine the influence of lobbying through meetings, a novel measure of such activity, between members of the European Parliament (MEPs) and interest groups during legislative procedures in Europe. Using the Transparency Register, we use data reported by MEPs on meetings and amendments written during the legislative procedure for a set of regulations to investigate whether a meeting at t-1 influences the writing of the law by the legislator. Using a pre-trained Large Language Model (LLM) as a novel method to quantify change in amendments, preliminary results suggest the writing of a share of amendments in the Digital Services Act (DSA) tends to benefit gatekeepers - defined as a firm with monopolistic behavior - and undermines consumers and other online platforms when written by rapporteurs, although it is not clear if this legal preference is caused by meetings with representatives of gatekeepers.

By employing a unique prison-specific administrative dataset encompassing the universe of 187 Italian public prisons, we analyze the determinants of the prison riot wave of March 2020 at the start of the COVID-19 pandemic. Probit estimates reveal that prison size and the extent of overcrowding positively correlate with the likelihood of riots. In contrast, a criminality index shows a negative impact on riots. Proxies for the effectiveness of prison management, composition of prison population, and level of internal violence exhibit no significant association with riots. Data support emulation effects: the likelihood of riots occurring in a given prison positively correlates with riots in nearby geographical areas. This study highlights the role of prison conditions, notably overcrowding, in the 2020 prison riot surge. We find no evidence supporting the Italian parliamentary Anti-Mafia Commission of Inquiry’s hypothesis that COVID-19-related prison riots were the result of a conspiracy orchestrated by Italian organized crime.