Conference Agenda

We study how realized climate risk affects democratic accountability by shaping electoral participation. Using municipality-level electoral returns from Italian national government and European Parliament elections between 2004 and 2023, we link detailed georeferenced records of extreme weather events to local voting outcomes. We first document, using long differences, that rising exposure to extreme precipitation is associated with declining turnout as climate shocks intensify over time. We then exploit quasi-random variation in the timing and severity of shocks relative to predetermined election dates within a staggered difference-in-differences design. Turnout falls sharply following extreme precipitation events occurring shortly before elections, with effects attenuating as temporal distance increases. Severity amplifies persistence but is not required for participation responses. Conditional on turnout, shocks temporarily shift vote shares toward green parties.

This study investigates how natural disasters and federal disaster declarations influence electoral outcomes in U.S. presidential elections from 1996 to 2020. Using county-level panel data and a two-way fixed effects framework, we analyze both incumbent vote share and voter turnout to describe the mechanisms linking disasters to political accountability. We find that severe disasters significantly reduce the incumbent party's vote share, consistent with the retrospective voting hypothesis. However, Presidential Disaster Declarations (PDDs) substantially mitigate these electoral losses, particularly in politically aligned urban areas, supporting the attentive retrospection hypothesis. Disasters tend to suppress voter turnout moderately, and PDDs only partially offset this effect, suggesting that disasters primarily harm incumbents by prompting voters to switch to the opposition rather than by discouraging their supporters from participating. Categorical analyses further reveal that partisan alignment, rather than PDD issuance alone, consistently drives electoral responses. Overall, our findings highlight how institutional coordination and federal aid shape democratic accountability in the wake of natural disasters.

Italy is highly exposed to hydrogeological risks, with floods and landslides affecting a large share of municipalities and imposing substantial fiscal costs on public authorities. This paper investigates whether political alignment between municipal governments and the central government influences the allocation of intergovernmental transfers following hydrogeological shocks. Using a panel of Italian municipalities from 2013 to 2022, we combine detailed data on weather-related disasters, emergency-related fund requests and disbursements, political affiliations of local and national officials, and socioeconomic controls. We estimate fixed-effects models to assess the relationship between political alignment, disaster occurrence, and public transfers. While political alignment alone does not appear to increase routine intergovernmental transfers, weather shocks are associated with a significant rise in transfers, averaging about 1.6 percent. Crucially, this effect is heterogeneous: municipalities politically aligned with the central government receive substantially higher transfers when hit by a hydrogeological event. Interaction estimates indicate that aligned municipalities obtain approximately 23–25 percent more transfers following a shock. Further analysis focusing on disaster-specific funding shows that politically connected municipalities receive significantly higher amounts of emergency funds and experience a markedly larger gap between funds received and funds requested—on the order of 33 percent. These findings suggest that political favoritism plays a significant role in the allocation of post-disaster public resources in Italy, amplifying fiscal disparities across municipalities in the aftermath of natural disasters.

We examine the impact of extreme hydrogeological events on local governments' fiscal responses in Italy between 2016 and 2022, with a focus on how local public finances contribute to disaster resilience. Leveraging the staggered timing of disaster declarations and employing a difference-in-differences framework, we estimate dynamic treatment effects on revenue and expenditure of municipal governments. Our findings indicate that local governments of affected municipalities significantly increase total and capital expenditures in the aftermath of disasters, particularly in functions related to emergency management, environmental protection and economic development. These spending increases are primarily financed through capital revenues and transfers from higher levels of government, with no corresponding rise in current expenditures. To explore heterogeneity in fiscal responses, we develop a fiscal resilience index combining measures of debt servicing costs and tax autonomy. We find that municipal governments with both low debt burden and high tax autonomy exhibit the strongest and most persistent post-disaster financial adjustments. In contrast, municipal governments with high debt service obligations and limited tax autonomy exhibit weaker responses, reflecting a constrained capacity to mobilize financial resources. These results underscore the critical importance of fiscal space, beyond formal fiscal autonomy, in shaping local governments’ ability to respond to climate-related shocks. From a policy perspective, our findings highlight the need to strengthen institutional and financial mechanisms that enhance fiscal resilience and ensure timely access to recovery resources for municipal governments with limited capacity.

Extreme weather events can influence climate change attitudes and behaviors. This relationship can be moderated by political ideology which dictates how individuals make inferences on the weather they observe. We investigate the effects of hurricane activity in the United States on self-reported climate change attitudes and behaviors of residents of two US cities (New York and Dallas), paying particular attention to their political preferences. We find that during periods of hurricane exposure, people worry more about climate change. The effects are more pronounced in New York than in Dallas. In addition, an ideology interaction is observed, showing a stronger effect of hurricane exposure for conservatives than for liberals. We find that the news media play a key role in how these perceptions are transmitted to the population. We then expand the geographic and time coverage of the data and develop a methodological strategy that allows to causally identify the impact of hurricane exposure in a cleaner way, making use of intrinsic hurricane characteristics.