Record Details

Distinguishing Occasional Abstention from Routine Indifference in Models of Vote Choice

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

View Archive Info
 
 
Field Value
 
Title Distinguishing Occasional Abstention from Routine Indifference in Models of Vote Choice
 
Identifier https://doi.org/10.7910/DVN/3JR2YL
 
Creator Bagozzi, Benjamin
Marchetti, Kathleen
 
Publisher Harvard Dataverse
 
Description Researchers commonly employ multinomial logit (MNL) models to explain individual level vote choice while treating “abstention” as the baseline category. Though many view abstainers as a homogeneous group, we argue that these respondents emerge from two distinct sources. Some nonvoters are likely to be “occasional voters” who abstained from a given election due to temporary factors, such as a distaste for all candidates running in a particular election, poor weather conditions, or other temporary circumstances. On the other hand, many nonvoters are unlikely to vote regardless of the current political climate. This latter population of “routine nonvoters” is consistently disengaged from the political process in a way that is distinct from that of occasional voters. Including both sets of nonvoters within an MNL model can bias the estimated effects of variables on candidate-selection or turnout, leading to faulty inferences. As a solution, we propose a baseline-inflated MNL estimator that models heterogeneous populations of nonvoters probabilistically, thus accounting for the presence of routine nonvoters within models of vote choice. We demonstrate the utility of this model using replications of existing public opinion research.
 
Subject Social Sciences
 
Contributor Bagozzi, Benjamin