关键词: 历史政治学, 时间边界条件, 过程性因果, 动态模型

Abstract: Historical Politics (HP) has been proposed and promoted as a promising avenue for the development of Chinas autonomous body of knowledge and system of disciplines in political science. In addition to adopting the historical perspective for enriching related theoretical discussions in political science, HP has also raised new requirements and challenges for the existing mainstream empirical research methods in a methodological aspect. This paper systematically reviews key assumptions of the existing mainstream frameworks for causal inference and quantitative modeling, as well as their respective strategies of dealing with temporal dynamics. It further highlights their major deficiencies in effectively incorporating temporal dynamics. Given HPs equal emphasis on both temporal and spatial dynamics, this paper argues that the latest methodological discussions on eventful causality, dynamic modeling technique, as well as dynamic Bayesian modeling, have all contributed to improving empirical research in HP and provided more appropriate methodological tools. In order to effectively promote HP, researchers should move beyond the existing mainstream empirical research methods, take the issue of temporality more seriously, and systematically and dynamically incorporate the analysis of conditions and causality in the temporal dimension in modeling and data analysis. By improving the matching of empirical research methods to theoretical frameworks, we can truly expand political science research and refine political science theories from a historical perspective.

Key words: Historical Politics, temporal scope condition, eventful causality, dynamic modeling