Correlates of War Analysis
Also known as: COW Analysis, Correlates of War Project Data, National Material Capabilities Analysis, Composite Index of National Capability Analysis
Correlates of War (COW) analysis is the systematic, data-driven study of interstate and intrastate war pioneered by J. David Singer and Melvin Small. The COW project assembled standardized, transparently coded datasets on the membership of the state system, the wars it has fought, and the material capabilities, alliances, and disputes of its members since 1816. Singer, Bremer, and Stuckey's (1972) study of capability distribution and major-power war exemplifies the approach: combine these building blocks into state-year and dyad-year datasets and analyze, statistically, what conditions correlate with the onset of war.
Key highlights
- Provides the field's standard, transparently documented measures of states, wars, capabilities, and alliances since 1816.
- Enables cumulative, replicable research and direct comparison across decades of studies.
- The CINC index offers a single comparable summary of national power across two centuries.
- Integrates cleanly into state-year and dyad-year designs that align conflict with its hypothesized correlates.
Intuition
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How it works
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When to use it
Use COW analysis when you need standardized, long-run, transparently coded data on states, wars, capabilities, and alliances to test theories about the causes of conflict across the modern international system. It is the foundational data infrastructure of quantitative IR. It is less suited to real-time monitoring (the data are periodically updated and lag events), to fine-grained subnational or event-level questions (where ACLED/UCDP-GED are better), or to questions the coding scheme deliberately abstracts away. It underpins, rather than competes with, MID and dyadic analyses.
Strengths & limitations
- Provides the field's standard, transparently documented measures of states, wars, capabilities, and alliances since 1816.
- Enables cumulative, replicable research and direct comparison across decades of studies.
- The CINC index offers a single comparable summary of national power across two centuries.
- Integrates cleanly into state-year and dyad-year designs that align conflict with its hypothesized correlates.
- Capabilities measured by the six CINC components emphasize industrial-era mass and may misrepresent power in a technology- and information-intensive era.
- Hand coding is updated periodically, so the data lag current events and cannot support real-time analysis.
- Definitional thresholds (what counts as a state or a war) embed judgments that affect counts and have evolved across releases.
- The all-dyad-years design generates rare-events and temporal-dependence problems requiring statistical correction.
Common pitfalls
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Applications
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Frequently asked
What is the Composite Index of National Capability (CINC)?
CINC is the COW project's summary measure of a state's material power. It averages the state's share of the international system's total across six indicators — military expenditure, military personnel, energy consumption, iron and steel production, total population, and urban population — producing a single score between 0 and 1 for each state-year. It is the most widely used quantitative proxy for national power in IR.
How does COW analysis relate to MID and dyadic conflict analysis?
COW is the umbrella data project; the Militarized Interstate Disputes (MID) dataset and dyadic conflict analysis are built on its foundations. COW supplies the state system, capabilities, and alliances; MID supplies the coded confrontations; dyadic analysis combines them into pair-year models. They are layers of the same research infrastructure rather than rival methods.
What software is used for COW analysis?
EUGene historically automated the construction of dyad-year datasets from COW sources. Today the R package peacesciencer is widely used to assemble state-year and dyad-year data with CINC, alliances, distance, and MID variables, after which models are fitted in R or Stata. The raw datasets are distributed from the Correlates of War project website.
Sources
- 1.Singer, J. D., Bremer, S., & Stuckey, J. (1972). Capability distribution, uncertainty, and major power war, 1820–1965. In B. Russett (Ed.), Peace, War, and Numbers (pp. 19–48). Beverly Hills: Sage.
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Cite this page
ScholarGate. (2026, June 22). Correlates of War Analysis. ScholarGate. https://scholargate.app/international-relations/correlates-of-war-analysis