Replication Data for: Democracy Manifest or Democracy Latent? A Unified Framework for Identifying Regime Types and Transitions

Regime types and transitions are central to a wide range of political phenomena. Reflecting this importance, prior research has produced a variety of regime measures. This diversity, however, comes with important challenges for applied research: selecting a measure among many options, having to define regime categories based on cut-offs, identifying regime transitions by specific magnitudes of change over a specific time window, and dealing with measurement uncertainty and missing data. In this paper, we introduce UNITAS (Unified Transition And Stability), a new framework that offers a solution to these challenges. Combining information from commonly used regime indicators, this approach identifies regime types and transitions probabilistically, locates the most likely periods of regime transitions, and incorporates measurement uncertainty. Through Monte Carlo simulations, we demonstrate the desirable properties and robustness of UNITAS under various scenarios. In an illustrative application, we show that stable semi-democracies are not inherently conflict-prone and that autocratization is consistently associated with higher civil war risk while democratization is not. This package contains code and data to reproduce all empirical tables and figures in the paper. The replication package includes the UNITAS dataset with regime classifications for 23,787 country-years (1800–2017), R scripts for estimation and analysis, and pre-computed results for computationally intensive steps.