Power Politics in Authoritarian Regimes

Session Submission Type: Full Paper Panel

Session Description

Power is one of the most important determinants of politics especially in authoritarian regimes, where institutions are too weak to guarantee binding commitment. Existing literature of authoritarian regimes, however, emphasize more on the study of institutions — their functions and how they can be established in these regimes — and power is usually treated as a constant, background factor. This panel brings together scholars who study the dynamics of power politics in authoritarian regimes using a plurality of methodological approaches, including formal theory, text analysis, and machine learning. Authors explore questions including how to define and measure political power, how does power change endogenously and in what way, and the effect of power politics on policy making.

Jiang and coauthors use text data collected from Google Ngram to develop a new measure of power and apply the measure to study the inter-temporal distribution of power between authoritarian leaders and their predecessors. Luo develops a game-theoretic model to study the endogenous dynamics of power distribution and derive conditions under which power would be consolidated or shared over time. Xi and coauthors use a game-theoretic model and observational data in China’s agricultural reform to investigate both the positive and negative effect of power politics in economic reforms. Using original data of Chinese online petitions, Liu and coauthor study how informal power could help individuals to get responses from the government.

Sub Unit

• Division 6: Political Economy

Individual Presentations

• In the Shadows of Great Men - Junyan Jiang, Columbia University; Tianyang Xi, Peking University

• Self-Enforcing Power Dynamics - Zhaotian Luo, University of Chicago

• Pilot or Persuasion? The Politics of Reform Dynamics in Authoritarianism - Tianyang Xi, Peking University; Shuo Chen; Zhaotian Luo, University of Chicago

• What Makes a Government Respond? A Data-Driven Approach - Shiyao Liu, Peking University; Tianguang Meng, Tsinghua University

Chair

• Ji Yeon (Jean) Hong University of Michigan

Discussant

• Anne Meng University of Virginia