Drought-reliefs and Partisanship

Principal Investigator(s):  View help for Principal Investigator(s) Federico Boffa, Free University of Bozen/Bolzano & Collegio Carlo Alberto; Francisco Cavalcanti, PUC-Rio; Christian Fons-Rosen, UC-Merced; Amedeo Piolatto, Autonomous University of Barcelona & BSE & IEB

Version:  View help for Version V1

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Drought-reliefs-and-Partisanship.zip application/zip 3.8 MB 04/14/2023 12:43:PM
README.txt text/plain 1.9 KB 04/14/2023 12:50:PM

Project Citation: 

Boffa, Federico, Cavalcanti, Francisco, Fons-Rosen, Christian, and Piolatto, Amedeo. Drought-reliefs and Partisanship. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-04-14. https://doi.org/10.3886/E188961V1

Project Description

Summary:  View help for Summary Partisan bias when transferring funds across governments is an established phenomenon. 
We combine a model of symmetric information with selfish and office-motivated politicians and an RDD analysis based on close municipal elections to study partisan bias in the allocation of drought aid relief in Brazil. We identify a novel pattern of distributive politics whereby partisan bias materialises only before municipal elections, while it disappears before presidential elections. Furthermore, before mayoral elections, it fades for extreme (high or low) aridity levels while persisting for moderate levels. Our empirical results show that in this case alignment increases the probability of receiving aid relief by a factor of two (equivalent to 18.1 p.p.).
We use the Standardised Precipitation-Evapotranspiration Index (SPEI) to measure aridity.

Scope of Project

Subject Terms:  View help for Subject Terms Federalism; Distributive Politics; Partisan Alignment; Presidential Elections; Aridity; SPEI index; Brazil
Geographic Coverage:  View help for Geographic Coverage Brazil
Time Period(s):  View help for Time Period(s) 1996 – 2016
Data Type(s):  View help for Data Type(s) aggregate data; event/transaction data; geographic information system (GIS) data; other

Methodology

Data Source:  View help for Data Source Climate Research Unit at the University of East Anglia
Sistema Integrado de Informações sobre Desastres Naturais - S2ID
Tribunal Superior Eleitoral
IBGE

Unit(s) of Observation:  View help for Unit(s) of Observation Electoral outcomes at the municipality level; rain precipitation and evapotranspiration; declaration (from the federal government) of the state of emergency at the voting municipality level, motivated by aridity
Geographic Unit:  View help for Geographic Unit Brazil, municipalities

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V1 [2023-04-14]

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