Патрональная политика и ротация губернаторского корпуса в России: Опыт сетевого анализа

Полития: Анализ. Хроника. Прогноз. 2023. № 3(110). С. 67–90.

Balandin Y., Gaivoronsky Y.

The article is devoted to testing different approaches to explaining the turnover of the heads of the Russian regions after the return of direct gubernatorial elections. Until recently, two basic explanatory models of gubernatorial turnovers — electoral and socio-economic — were the most popular among the Russian political scientists. The influence on such turnovers of informal institutions and practices, which play a significant role in Russian politics, largely remained outside of view of researchers, and even today it is rather understudied. Therefore, the authors focus on identifying the possible role of this factor, employing network and regression analysis for this purpose. Based on the Henry Hale’s concept of patronal politics, the authors operationalize informal practices as patron-client relations, which implies unification of federal political and economic actors (patrons) and heads of regions (clients) into a patronal network, the position in which is potentially capable of influencing political stability. To measure a key indicator that reflects the weight of the head of the region in the patronal network, the authors make use of the centrality index that they calculated on the basis of their unique database, which covers all individuals who held the post of a governor from 2012 to 2021, as well as federal actors associated with them. The authors’ regression analysis of the factors that influence governors’ turnover testifies to the high explanatory power of the network model: the governor’s presence within the patronal network and his proximity to the key (central) actors of this network reduce the likelihood of resignation. At the same time, alternative explanatory models (electoral and socio-economic), as well as personal characteristics of governors (age, length of tenure, end of term at the office) retain their significance.

Keywords: сетевой анализ, governors, губернаторы, social network analysis, patronal networks, federal center, федеральный центр, Патрональная политика, Патрональная сеть, patronal politics