A Measurement Error Model of Dichotomous Democracy Status

Abstract

We use a Bayesian measurement error model to derive a probabilistic measure of democracy from several existing dichotomous data sets. This approach accepts the premise that democracy may usefully be construed as a bivalent concept for certain theoretical and technical purposes, but it also makes more explicit our collective uncertainty about where some cases fall in that binary scheme. We believe the resulting data provide a firmer foundation than measures of countries' degree of democracy for studies that require a dichotomous measure of regime type.

Keywords: political science, democracy, Bayesian modeling

JEL Classification: P16, C11