Yuri M. Zhukov

Yuri M. Zhukov

Political scientist studying armed conflict, repression, and geospatial data science.

Ongoing Research

Banner

Categories

Funded

↑ back to top

SUNGEO: Sub-National Geospatial Data Archive

Kollman, Kenneth (PI) and Yuri M. Zhukov (co-PI). “SUNGEO: Sub-National Geospatial Data Archive.” Data infrastructure, 2022.
National Science Foundation RIDIR Grant (SES-1925693).
Website (sungeo.org) | R package (CRAN) | R package (GitHub)

Abstract Research on political, social, and economic behavior and phenomena increasingly depends on combining multiple distinct sources of sub-national data, which are often collected at disparate spatial scales and units of analysis. Using different methods of linking data, not to mention different data sources, can affect inferences. Yet analysts' critical decisions on both dimensions are often ad hoc and driven mainly by the idiosyncratic needs and constraints of a particular project. These practices reduce the reliability, transparency, and replicability of empirical research. The Sub-National Geospatial Data Archive (SUNGEO) will relieve bottlenecks in research by integrating multiple sources of sub-national data in a common data repository at multiple, customizable spatio-temporal scales, and developing a suite of methods for data processing and analysis. This infrastructure includes three main components. First is a user-friendly web interface, where researchers can select among many pre-loaded variables [e.g. elections, violent events, weather, land use, public health outcomes], choose levels and methods of spatio-temporal (dis)aggregation, interpolation and integration, and easily construct their own sub-national datasets. Second is an open-source software package, in the R statistical programming language, that processes user-supplied data, merges them with pre-loaded geo-referenced data, and produces a more customizable output based on user needs and specifications. Third is an archiving tool, which allows users to contribute original data to the repository.

Working Papers

↑ back to top

Fratricidal Coercion in Modern War

Lyall, Jason, and Yuri M. Zhukov. “Fratricidal Coercion in Modern War.” Working paper, 2023.
Download PDF

Abstract Armies sometimes use fratricidal coercion --- violence and intimidation against their own soldiers --- to force reluctant soldiers to fight. Though quite common historically, we know little about how it affects battlefield performance. We study fratricidal coercion using a mixed-method strategy, drawing on (1) monthly panel data on Soviet Rifle Divisions in World War II, built from millions of declassified personnel files; (2) paired comparisons of Rifle Divisions at the Battle of Leningrad; and (3) cross-national data on 526 land battles and war outcomes from 75 conflicts (1939--2011) to assess generalizability. We offer three sets of empirical findings. First, coercion keeps some soldiers from fleeing the battlefield, but at the cost of higher casualties and reduced battlefield initiative. Second, wartime and prewar coercion (e.g. mass repression, officer purges) affect soldiers' behavior in similar, mutually reinforcing ways. Third, the resolve-boosting, initiative-dampening effects of fratricidal coercion generalize across belligerents and wars. Fratricidal coercion generates compliance through fear, compelling soldiers with variable levels of resolve to conform to a uniform standard of battlefield behavior. But the net utility of this approach is dubious. On balance, countries employing fratricidal coercion are less likely to win their wars.

Are Competitive Elections Good for Your Health? Evidence from the 1918 Flu and Covid-19

Walden, Jacob, and Yuri M. Zhukov. “Are Competitive Elections Good for Your Health? Evidence from the 1918 Flu and Covid-19.” Working paper, 2021.
Download PDF

Abstract Do more electorally vulnerable government officials respond to public health emergencies more aggressively than officials in less competitive seats? Using novel data on local government responses to the 1918 influenza A (H1N1) "Spanish Flu" and 2020 Covid-19 pandemics in the United States, we study how the competitiveness of federal, state and local elections shapes the policy choices of incumbents. We find that, in 1918, vulnerable incumbents enacted more and longer nonpharmaceutical interventions (e.g. quarantines, closures), enforcing them more aggressively than in less-competitive jurisdictions. Their constituents subsequently experienced fewer influenza-related deaths and lower overall excess mortality. In 2020, more competitive constituencies similarly experienced lower rates of Covid-19 infection and death, but they implemented fewer nonpharmaceutical interventions and relied more on pharmaceutical measures. This policy substitution was feasible in part due to political geography: more competitive localities became more suburban, and more conducive to social distancing in the absence of government mandates.

Political Regime Type and Warfare: Evidence from 600 Years of European History

Blank, Meredith, Mark Dincecco and Yuri M. Zhukov. “Political Regime Type and Warfare: Evidence from 600 Years of European History.” Working paper, 2017.
Download PDF

Abstract This paper presents new evidence that, historically, the relationship between political regime type and warfare was different than it is today. Using a novel database of interstate conflict in Europe between 1200 and 1800, we perform the first quantitative analysis of domestic political institutions and warfare across the pre-modern era. We find that early parliamentary regimes -- the institutional predecessors of modern democracies -- were disproportionately more likely to experience armed conflict than their absolutist counterparts. Our empirical strategy makes use of two complementary approaches: a standard dyadic analysis of conflict initiation, and a dynamic network analysis that accounts for interdependence between dyads. These analyses show that early parliamentary regimes fought in significantly more wars than absolutist monarchies, both against one another and overall. Such regimes, we argue, had a relatively large capacity to make war, but, unlike modern democracies, not enough institutional constraints to prevent it.

How Selective Reporting Shapes Inferences about Conflict

Zhukov, Yuri M. and Matthew A. Baum. “How Selective Reporting Shapes Inferences about Conflict.” Working paper, 2017.
Download PDF

Abstract By systematically under- or over-reporting violence by different actors, media organizations convey potentially contradictory information about how a conflict is likely to unfold, and whether outside intervention is necessary to stop it. These reporting biases affect not only statistical inference, but also public knowledge and policy preferences. Using new event data on the ongoing armed conflict in Eastern Ukraine, we perform parallel analyses of data from Ukrainian, rebel, Russian and third party sources. We show that actor-specific reporting bias can yield estimates with vastly different implications for conflict resolution: Ukrainian sources predict frequent unilateral escalation by rebels, pro-Russian rebel sources predict unilateral escalation by government troops, while outside sources predict that transgressions by either side should be quite rare. Experimental evidence suggests that news consumers tend to support intervention against whichever side is shown to be committing the violence. We argue that these kinds of reporting biases can potentially make conflicts more difficult to resolve -- hardening attitudes against negotiated settlement, and in favor of military action.