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Replication Data for: The Composition of Descriptive Representation

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication Data for: The Composition of Descriptive Representation
 
Identifier https://doi.org/10.7910/DVN/BIQZNT
 
Creator Gerring, John
Jerzak, Connor T.
Öncel, Erzen
 
Publisher Harvard Dataverse
 
Description Replication Data and Code for: The Composition of Descriptive Representation




Authors: John Gerring, Connor T. Jerzak, Erzen Öncel




Note: See http://glp.la.utexas.edu for a user-friendly interface to the core replication data.




Abstract: How well do governments represent the societies they serve? A key aspect of this question concerns the extent to which leaders reflect the demographic features of the population they represent. To address this important issue in a systematic manner, we propose a unified approach for measuring descriptive representation. We apply this approach to newly collected data describing the ethnic, linguistic, religious, and gender identities of over 50,000 leaders serving in 1,552 political bodies across 156 countries. Strikingly, no country represents social groups in rough proportion to their share of the population. To explain this shortfall, we focus on compositional factors—the size of political bodies as well as the number and relative size of social groups. We investigate these factors using a simple model based on random sampling and the original data described above. Our analyses demonstrate that roughly half of the variability in descriptive representation is attributable to compositional factors.
 
Subject Social Sciences
Descriptive representation; Leadership; Political institutions; Social groups; Elites
 
Date 2023-09-11
 
Contributor Jerzak, Connor