Using Conjoint Experiments to Analyze Election Outcomes : The Central Role of the Average Marginal Component Effect (AMCE)

Political scientists have increasingly deployed conjoint survey experiments to understand multi-dimensional choices in various settings. We demonstrate that the Average Marginal Component Effect (AMCE) constitutes an aggregation of individual-level preferences that translates into a primary quantity of interest to empirical election scholars: the effect of a change in an attribute on a candidate or party's expected vote share. This property holds irrespective of the heterogeneity, strength, or interactivity of voters' preferences and regardless of how votes are aggregated into seats. Overall, our results indicate the AMCE's central role in understanding elections, a conclusion buttressed by a corresponding literature review. We also provide practical advice on interpreting AMCEs. Finally, we propose, formalize, and evaluate the feasibility of using conjoint data to estimate alternative quantities of interest to electoral studies, including the effect of an attribute on the probability of winning