The ruler’s game of musical chairs: Shuffling during the reign of Ethiopia’s last emperor

The Myth of the Benevolent Autocrat? Internal Constraints, External Constraints, and Economic Development in Autocracies

“…First, experience can signal strength, which is the view taken in this thesis. Experienced ministers may be more powerful, since they have connections and access to resources (Woldense 2018). Therefore, they may be more costly to purge.…”

“…Thus, competent ministers might be more likely to be fired and Quiroz Flores (2016), indeed, finds that competent ministers in autocracies quickly are dismissed from their cabinet positions. However, ultimately, all members of the ruling coalition may be in risk of losing their jobs -or worse -as is evident from the broad purging of subordinates that has taken place in some authoritarian regimes (Kenyon 2018;Svolik 2012;Woldense 2018).…”

“…Svolik (2012, p. 79) argues that the purging of members of the elite protects the dictator by preventing coalition partners from establishing an independent power base. Kroeger (2018) argues that in African autocracies, personal leaders more easily than party leaders can fire ministers without destabilizing the regime, and Woldense (2018) shows that Haile Selassie constantly shuffled around members of cabinet to avoid cliques. These studies are supported by a wealth of qualitative descriptions of how dictators have shuffled around or purged important ministers to consolidate their power (Arendt 1951;Kenyon 2018;Montefiore 2004).…”

“…The Selection and Deselection of Political Elites (SEDEPE) research network offers a dataset on 19 European countries from 1945 to 1984 (Dowding and Dumont 2008), while Alexiadou (2016) offers data on 18 OECD countries from 1945 to 2000, and Bértoa (2020) presents a new dataset on European democracies since 1848.The equivalent longitudinal data resources covering emerging democracies and autocracies are less developed. Many studies tend to focus on single countries(Buehler and Ayari 2018;Kung and Chen 2011;Schleiter 2013;Woldense 2018) while studies that aim at cross-country comparisons tend to focus on a small number of countries from a specific region such as Latin America(Camerlo and Martinez-Gallardom 2020;Camerlo and Pérez-Liñán 2015;Escobar Lemmon and Taylor-Robinson 2005), Central-Eastern Europe(Bego 2014;Semenova 2018) and Sub-Saharan Africa(Arriola and Johnson 2014;Francois et al 2014;Kroeger 2018). Other scholars have reduced the temporal coverage, and increased the number of countries.…”

A statistical model for the analysis of mobility tables as weighted networks with an application to faculty hiring networks

“…The number of mobile individuals between two locations determines the edge weight. Examples of empirical analyses of such mobility networks include individuals' change in occupation over the life-course (Toubøl and Larsen, 2017;Cheng and Park, 2020), inter-generational mobility between social classes (Melamed, 2015), migration patterns between countries (Windzio, 2018), residential moves between neighbourhoods (Müller et al, 2018), patients transfers between hospitals (Stadtfeld et al, 2016), hiring of graduates between universities (Clauset et al, 2015;Gondal, 2018), and mobility of government officials between branches (Woldense, 2018). 1 The varying mobility issues outlined above are treated as network questions for one of two broad reasons-first, to explore the data with descriptive networks analyses, or, second, to uncover dependence structures in these mobility networks with statistical network models.…”