Using Conjoint Experiments to Analyze Elections: The Essential 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 begin with a general framework for analyzing voter preferences in multi-attribute elections using conjoints. With this framework, we demonstrate that the Average Marginal Component Effect (AMCE) is well-defined in terms of individual preferences and represents a central quantity of interest to empirical scholars of elections: 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 essential role of AMCEs for understanding elections, a conclusion buttressed by a corresponding literature review. We also provide practical advice on interpreting AMCEs and discuss how conjoint data can be used to estimate other quantities of interest to electoral studies.