Jiajing Sun

Jiajing Sun

PhD, CFA charterholder, FIMA, Member of the London Mathematical Society. Associate Professor and the Deputy Director of the Department of Statistics and Data Science, School of Economics and Management, University of the Chinese Academy of Sciences.

Political Turnover and Innovation-System Resilience: Patent and R&D Evidence from 45 Economies

Published:

This working paper studies whether political turnover disrupts national innovation systems. It treats turnover as a potential stress test for innovation-system resilience rather than as a uniform measure of political instability, and asks whether research and patent indicators are detectably disturbed after changes in political leadership or governing party.

Authors:

Weimin Jiang, Jin Dong, Jiajing Sun, and Michael Cole.

Summary and Contribution:

The paper assembles a country-year panel of 45 economies from 1980 to 2020, combining R&D indicators and patent measures with political-turnover data and institutional measures. It distinguishes leader-only turnover from leader-and-party turnover, and estimates dynamic switcher-based difference-in-differences models for recurring political-turnover events.

The paper contributes to the literature by separating political turnover as an observable event from broader concepts such as political instability and policy uncertainty. This distinction allows the analysis to ask a more precise question: under what conditions, if any, are national innovation inputs and outputs disrupted after a recorded change of political leadership or governing party?

Evidence:

The central finding is deliberately cautious. Using calendar-valid event starts, the paper finds no robust average short-run decline in R&D intensity, researcher stocks, a PATSTAT-derived patent indicator, highly cited patent shares, or utility-model applications after either leader-only or leader-and-party turnover.

Exploratory evidence suggests possible areas for future work, including leader-driven policy change and weaker institutional buffers. However, the relevant cells are small and classification-sensitive, so these patterns are treated as exploratory rather than confirmatory.

Keywords:

National innovation systems; innovation policy; political turnover; institutional capacity; patent indicators.

Recommended citation: Jiang, W., Dong, J., Sun, J., & Cole, M. (2026). Political Turnover and Innovation-System Resilience: Patent and R&D Evidence from 45 Economies. Working paper.