Beyond Continuous versus Categorical Dichotomy: Uncovering Latent Structure of Non-electoral Political Participation Using Zero-Inflated Models

While modeling political participation as a latent variable, researchers usually choose whether to conceptualize and model participation as a latent continuous or latent categorical variable. When participation is modeled as a continuous variable, factor analytic and item-response theory models are used. When modeled as a categorical variable, latent class analysis is employed. However, both conceptualizations and modeling approaches rest upon very strong assumptions. In the continuous case, all subjects are assumed to come from the same homogenous population; in the categorical case, we assume that no quantitative heterogeneity exists within the latent classes. In this work, I argue that these assumptions are implausible and propose to model participation using zero-inflated measurement and regression models that assume the existence of two latent classes-politically disengaged and politically active-with the latter class being quantitatively heterogenous (people in that class are thought to participate to a varying degree). The results show that the models accounting for the latent class of politically disengaged have much better out-of-sample predictive accuracy. Moreover, modeling the zero-inflation changes estimates of measurement and regression models, and offers new research opportunities because with zero-inflated models we can explicitly tackle the question of what impacts the probability of ending up in the latent class of politically disengaged.