We exploit a natural experiment involving the random placement of refugee hosting facilities in an urban setting. Using survey data on voting, we estimate the causal effect of proximity to immigrants on political behaviour. By examining both refugees and long-term immigrant presence, we reconcile conflicting findings in the literature and offer a unifying framework highlighting the key role of past experiences in determining polarised responses to refugee shocks. We show that polarisation is driven by voters with limited prior contact and is amplified near migrant services or family-hosting facilities. By contrast, those with high baseline exposure remain unaffected.
Organized crime groups are known to provide electoral support to politicians, but the rewards they obtain in return remain poorly understood. We develop a theoretical framework suggesting that modern mafia support hinges on parties’ willingness to weaken anti-mafia policies, specifically by neglecting the reallocation of confiscated mafia assets. Judicial records indicate that when these assets remain unassigned, crime families can quietly repossess them, turning policy inertia into a hidden payoff. Using data from Sicilian municipalities between 1992 and 2022, we first detect vote manipulation in tightly contested majoritarian races—particularly in smaller towns—indicating strategic vote buying by the mafia. A regression discontinuity design, restricted to comparable municipalities quasi-randomly sorted around the threshold, reveals that narrowly won Forza Italia victories trigger a sharp fall in asset reallocations only within mafia-controlled areas. To measure variation in vote‑buying capacity, we exploit the mafia’s abrupt 1987 withdrawal of support from the Christian Democrats. Municipalities suffering larger DC vote losses—our proxy for historical mafia influence—experience steeper post‑election cuts in asset reallocations, but only during Berlusconi’s governments. Instrumenting modern Forza Italia support with these historical shifts further supports a causal relation between mafia vote buying and national‑level policy concessions.
We examine the impact of a nationwide data disclosure programme for Italian municipalities launched in 2014. When only expenditure indicators were public, mayors cut spending, but service provision declined by more, lowering efficiency; once output indicators were added two years later, service provision improved. Our identification strategies exploit daily variation in newspaper coverage to instrument mayors' platform access, and comparison of municipalities along treated-untreated regional borders. The findings show that governments respond to the metrics that are visible while neglecting those that are not. Designing disclosure regimes that cover both inputs and outcomes is therefore crucial to ensure efficiency gains.
Does providing politicians with low-cost access to information about their peers change their fiscal behavior? This paper investigates this question by exploiting a data disclosure program introduced by the Italian government that allowed mayors to access detailed expenditure data of other municipalities through a restricted website. By tracking digital activity on the platform, we construct a directed network of peer monitoring and analyze the strategic behavior of participating mayors. We find that mayors in the digital network differ systematically from the others: they are younger, more educated, govern larger municipalities, and exhibit strong homophily based on structural rather than political characteristics. Using an identification strategy that exploits the network's intransitivity to solve the reflection problem, we show that digital transparency alters the nature of fiscal competition. Within the network, strategic interaction in property tax setting is conditional on electoral incentives: it is strongly driven by mayors who are eligible for re-election, while term-limited mayors do not respond to their digital peers. In contrast, for municipalities outside the network, tax setting remains correlated with geographical neighbors but is unresponsive to term limits. These findings suggest that digital platforms facilitate a sophisticated, reputation-based form of yardstick competition, and that transparency tools affect politician behavior even before voters gain access to the same information.
We develop a probabilistic-voting model to study how lobbying shapes both policy outcomes and democratic participation. In our model, a lobby provides blocs of votes in exchange for weaker policy commitments, but departing from existing frameworks we allow partially ideological voters to abstain when policies tilt too strongly toward lobby interests, thereby linking lobbying not only to policy concessions but also to voter turnout. The model yields a paradoxical prediction: stronger electoral competition can worsen policy quality and depress participation, as parties increasingly depend on lobby support to secure victory. We examine these predictions in the context of Mafia lobbying in Sicily between 1994 and 2018, exploiting variation from close national contests between Forza Italia and the Democratic Party of the Left. Consistent with the theory, tighter competition in Mafia-influenced municipalities led to fewer reallocations of confiscated Mafia assets—one of Italy’s central anti-mafia policies—and to lower electoral participation. Our findings highlight a perverse consequence of democratic competition: when votes can be mobilised by powerful lobbies, more competition may erode rather than enhance accountability and participation.