Nils-Christian Bormann’s research while affiliated with Witten/Herdecke University and other places

We describe the Archive of Interwar Europe Election Data and Assemblies (AIEEDA), a new multi-level dataset of parliamentary elections in interwar Europe (1919-1939). The data contains electoral results for all parties that ran in 137 national parliamentary elections in 25 interwar European democracies. It further offers detailed time-invariant ideological and organizational variables for 401 parliamentary parties and 35 party alliances, along with time-variant data on their participation in 412 cabinets. Next to national-level election results, we provide disaggregated constituency/municipality-level results for Estonia, Ireland, Italy, Latvia, the Netherlands, and Yugoslavia. Having collected national and disaggregated data independently, we validated each through the other. We also provide linking tables to parliamentary election results at the constituency/municipality-level for France, Germany, and the United Kingdom. The archive will be useful to social scientists interested in testing theories on voting and party politics out of sample in a historical setting, or to use historical cases to understand contemporary phenomena such as the rise of radical right-wing parties.

This data note introduces an update to the widely-used Democratic Electoral Systems (DES) data that encompasses the period from 1919 to 1945. The data include 243 legislative lower house and presidential elections in 34 interwar democracies. Information on these elections falls into four categories: first and foremost, DES contains variables that capture the institutional rules that define how elections are organized. Second, the data captures the consequences of electoral rules in the form of summary statistics of electoral outcomes. Third, we include democracy classifications for four major democracy datasets so that users can choose their preferred democracy definition when working with the data. Finally, the DES dataset contains multiple identification variables that allow linking the DES data to a wide variety of other datasets. This update to the DES data is fully compatible with prior releases for the post-war period 1–3 .

This data note introduces an update to the widely-used Democratic Electoral Systems (DES) data that encompasses the period from 1919 to 1945. The data include 243 legislative lower house and presidential elections in 34 interwar democracies. Information on these elections falls into four categories: first and foremost, DES contains variables that capture the institutional rules that define how elections are organized. Second, the data captures the consequences of electoral rules in the form of summary statistics of electoral outcomes. Third, we include democracy classifications for four major democracy datasets so that users can choose their preferred democracy definition when working with the data. Finally, the DES dataset contains multiple identification variables that allow linking the DES data to a wide variety of other datasets. This update to the DES data is fully compatible with prior releases for the post-war period (Golder2005, Bormann2013a, Bormann2022).

This data note introduces an update to the widely-used Democratic Electoral Systems (DES) data that encompasses the period from 1919 to 1945. The data include 243 legislative lower house and presidential elections in 34 interwar democracies. Information on these elections falls into four categories: first and foremost, DES contains variables that capture the institutional rules that define how elections are organized. Second, the data captures the consequences of electoral rules in the form of summary statistics of electoral outcomes. Third, we include democracy classifications for four major democracy datasets so that users can choose their preferred democracy definition when working with the data. Finally, the DES dataset contains multiple identification variables that allow linking the DES data to a wide variety of other datasets. This update to the DES data is fully compatible with prior releases for the post-war period 1–3 .

This research note describes an update to Bormann and Golder's 2013 Democratic Electoral Systems (DES) dataset. We extend the temporal scope of the previous dataset by adding information for all legislative and presidential elections that took place in democratic states from 2011 through 2020. More significantly, the DES dataset now includes information on all elections that are considered democratic by at least one of five different measures of regime type: Democracy and Dictatorship (DD), Freedom House (FH), Polity5, Boix-Miller-Rosato (BMR), and Varieties of Democracy (V-Dem). The result is that the new DES dataset has greater utility and is over 30% larger than the previous one. A brief overview of the data is presented.

Social scientists in general and conflict researchers in particular increasingly combine multiple datasets to study ethnic politics and conflict in Africa. We facilitate these efforts by systematically linking over 8,100 ethnic categories from 11 databases, including surveys, geographic data, and expert-coded lists. Exploiting the linguistic tree from the Ethnologue database, we propose a systematic solution to the grouping problem of ethnicity. An analysis of political exclusion, mistrust of state leaders, and ethnic grievances highlights different ways of linking ethnic categories from multiple datasets. The LEDA open-source software package allows researchers to link ethnic groups from any database with explicit rules and to add their own data on ethnic groups.

Recent research has shown that inequality between ethnic groups is strongly driven by politics, where powerful groups and elites channel the state's resources toward their constituencies. Most of the existing literature assumes that these politically induced inequalities are static and rarely change over time. We challenge this claim and argue that economic globalization and domestic institutions interact in shaping inequality between groups. In weakly institutionalized states, gains from trade primarily accrue to political insiders and their co-ethnics. By contrast, politically excluded groups gain ground where a capable and meritocratic state apparatus governs trade liberalization. Using nighttime luminosity data from 1992 to 2012 and a global sample of ethnic groups, we show that the gap between politically marginalized groups and their included counterparts has narrowed over time while economic globalization progressed at a steady pace. Our quantitative analysis and four qualitative case narratives show, however, that increasing trade openness is associated with economic gains accruing to excluded groups in only institutionally strong states, as predicted by our theoretical argument. In contrast, the economic gap between ethnopolitical insiders and outsiders remains constant or even widens in weakly institutionalized countries.

Binary outcome models are frequently used in the social sciences and economics. However, such models are difficult to estimate with interdependent data structures, including spatial, temporal, and spatio-temporal autocorrelation because jointly determined error terms in the reduced-form specification are generally analytically intractable. To deal with this problem, simulation-based approaches have been proposed. However, these approaches (i) are computationally intensive and impractical for sizable datasets commonly used in contemporary research, and (ii) rarely address temporal interdependence. As a way forward, we demonstrate how to reduce the computational burden significantly by (i) introducing analytically-tractable pseudo maximum likelihood estimators for latent binary choice models that exhibit interdependence across space and time and by (ii) proposing an implementation strategy that increases computational efficiency considerably. Monte Carlo experiments show that our estimators recover the parameter values as good as commonly used estimation alternatives and require only a fraction of the computational cost.

How do ethnic power-sharing coalitions affect the risk of violent conflict? We argue that government leaders anticipate costly conflict and form larger ruling coalitions as uncertainty over threats increases. We develop a formal model of ethnic coalition formation that balances rational group leaders’ desire to maximize their own power and the anticipation of future costly conflict. The model locates the key source of violent conflict in uncertainty over the size of radical sub-groups that prefer conflict over cooperation. Where ruling elites manage to satisfy radical sub-group leaders by sharing power, the risk of rebellion decreases. Using the Ethnic Power Relations dataset, we find that multiethnic ruling coalitions with internally fragmented groups decrease the risk of armed conflict while having a negligible effect on coups. A novel selection estimator reveals that the conflict-reducing effect of power sharing increases once we consider the endogeneity of coalition formation and conflict.