RESEARCH

work in progress

Don’t Tread On Me: Orthodox Schism and Voting in Revolutionary Russia

(with Timur Natkhov) | presentations: MPSA 2024, 2022 Workshop in Political Economy of Eurasia (Harriman Institute, Columbia University)

Post-Communist Transition as Critical Juncture: Empirical Evidence

(with Leonid Polishchuk and Kharis Sokolov)

The Anti-Authoritarian Personality: Psychology of Opposition Under Repression

presentations: PBAC (Cornell University)

The Ballot After The Bullet: Effect of Exposure to Casualties on Voting Under Autocracy

(with Nikita Savin and Konstantin Bogatyrev)

working papers

Hybrid Banditry: Theory and Empirical Evidence from Wagner Group Mercenaries

[working paper] | presentations: APSA 2024, PBAC 2024 (Cornell University)

publications

Rosenberg, Dina, and Tarasenko, Georgy (2020)

Innovation for despots? How dictators and democratic leaders differ in stifling innovation and misusing natural resources across 114 countries.

Energy Research & Social Science 68 (2020): 101543.

[paper]|[bib]

  • Conventional wisdom holds that natural resource abundance negatively affects economic development, especially in countries with weak quality of governance. In this paper we raise a related, yet separate, question that was largely overlooked in the literature - the effect of natural resource rents on technological innovations, a very specific type of economic activity. We argue that the abundance of natural resources negatively affects technological innovations, but only under authoritarian settings. Technological innovations are risky, costly, long-term and partially public goods (an idea cannot be taken back), which makes them disproportionately disadvantaged in resource-rich authoritarian countries. First, alternative economic activity is too attractive to miss out on: steady, high and short-term profits from natural resources. Second, authoritarian leaders are infamous for not encouraging or even blocking technological innovations because they redistribute political power away from the leaders (old elites) to newcomers (innovators). We corroborate our hypothesis on the extensive cross-section time-series data.