contentiousR standardizes country and year keys; it does
not make the underlying research designs interchangeable. Cite each
source used in an analysis and consult its codebook for definitions,
scope, and limitations.
| Argument | Bundled version and coverage | Unit returned | Source |
|---|---|---|---|
GDP: "gapminder"
|
Gapminder v32 | Country-year | Gapminder |
GDP: "fariss"
|
Fariss et al. 2022, latent estimate, 1500–2019 | Country-year | Dataverse |
Population: "wpp"
|
UN World Population Prospects 2024, 1949–2023 | Country-year | UN Population Division |
Population: "nmc"
|
National Material Capabilities v7.0, 1816–2022 | Country-year | Correlates of War |
Population: "fariss"
|
Fariss et al. 2022, latent estimate, 1500–2019 | Country-year | Dataverse |
Military expenditure: "sipri"
|
SIPRI Military Expenditure Database v1.2, 1949–2025 | Country-year | SIPRI |
Military expenditure: "nmc"
|
National Material Capabilities v7.0, 1816–2022 | Country-year | Correlates of War |
Military expenditure: "barnum"
|
Barnum et al. 2025, latent estimate, 1816–2019 | Country-year | Dataverse |
"navco1.3" |
NAVCO 1.3, 1900–20191 | Campaign onset | Dataverse |
"navco2.1" |
NAVCO 2.1, 1945–2013 | Campaign-year | Dataverse |
"beissinger" |
Revolutionary Episodes Dataset, 1900–20142 | Episode onset | Mark Beissinger |
"csra" |
CSRA Revolutionary Database v1.102, 2000–2024 | Episode onset | HSE University |
"scad" |
SCAD 3.3, 1990–20173 | Country-year | Strauss Center |
"ucdp_prio" |
UCDP/PRIO 26.1, 1946–2025 | Country-year | UCDP |
"ucdp_vpp" |
UCDP VPP 26.1, 1989–2025 | Country-year | UCDP |
"mm" |
Mass Mobilization, 1990–2020 | Country-year | Project website |
"mmad" |
MMAD v5.0, 2003–2022 | Country-year | MMAD |
"mec" |
Major Episodes of Contention, 1955–2018 | Episode (global) | Article / data |
"archigos" |
Archigos 4.1, 1875–2015 | Country-year | Archigos |
"reign" |
REIGN, 1921–2021 | Country-year | REIGN |
| V-Dem | Installed vdemdata release |
Country-year | V-Dem |
Package-related transformations and explanations
SCAD repeats events when they span multiple locations. For
country-level use, contentiousR retains one row per
positive event ID before aggregating. Its documented -99,
-88, and -77 death-count values are
represented as missing rather than as negative deaths.
UCDP/PRIO expands conflicts with multiple location codes before
aggregation. ucdp_prio_incidence marks any active conflict
in a country-year, while ucdp_prio_onset is one only when
start_date2 falls in that year. The VPP file has no
equivalent episode-start field; ucdp_vpp_onset is retained
only as a backwards-compatible alias of
ucdp_vpp_incidence.
Mass Mobilization reports participant size through a mixture of exact
numbers, ranges, inequalities, and qualitative strings.
mm_participants contains the maximum of exact numeric
reports. mm_participants_reported preserves all reported
strings so users can apply a substantively appropriate recoding.
Legacy campaign and episode sources can contain several rows for one
country-year. add_conflict(aggregate = TRUE) reports their
count and takes a missing-safe maximum of numeric fields. Use
aggregate = FALSE or call conflict_data()
directly when campaign-level observations are required.
Unmatched panel rows remain NA, because absence from a
source is not always evidence of zero events.
MEC contains 2,734 reformist and maximalist contentious episodes
worldwide. contentiousR preserves its episode-level rows
and all published variables, using the source’s byear
(beginning year) as year. Fourteen left-censored episodes
have a mec_bdate before 1955 but a source
byear of 1955. With
add_conflict(aggregate = TRUE), MEC follows the same
explicit aggregation policy as the other campaign and episode sources;
use aggregate = FALSE to retain individual episodes.
The bundled UN WPP extract has three rows for some China
country-years: a combined mainland+Hong Kong+Macao+Taiwan figure, a
mainland-only figure, and a Hong Kong-only figure, all of which matched
COW code 710 during country-name conversion upstream.
load_population_data(dataset = "wpp") resolves this by
taking the median pop value within each
cow-year group (returned as
wpp_pop), which is consistently the mainland-only figure;
every other country-year has a single row, so the median is a no-op
there.
NMC’s documented -9 missing-data sentinel is recoded to
NA in nmc_tpop and nmc_upop.
Fariss, Anders, Markowitz, and Barnum’s replication files contain one
row per country-year for each underlying source indicator (e.g. Bairoch,
Penn World Table, World Bank) plus one "latent_*" row
holding the model’s combined estimate.
load_gdp_data(dataset = "fariss") and
load_population_data(dataset = "fariss") keep only the
"latent_gdp" / "latent_gdppc" /
"latent_pop" rows. Their absolute units are not
independently verified in this package; consult Fariss et al. (2022)
before using fariss_gdp, fariss_gdppc, or
fariss_pop outside of relative/comparative analysis.
The SIPRI workbook lists a small number of rows (e.g. “Africa”, “NATO”) that are regional or organizational aggregates rather than countries; these have no matching COW/Gleditsch-Ward code and are dropped.
Barnum, Fariss, Markowitz, and Morales’s military expenditure
replication file contains one row per country-year for each of 24
underlying source indicators, each in its own original currency/unit,
with no single combined value on a real monetary scale (unlike the
Fariss GDP/population files, the paper does not publish the shared
latent trait directly because “the average by itself does not have a
real or direct monetary unit”). Instead,
load_military_expenditure_data(dataset = "barnum") reports
the model’s posterior estimate of two specific indicators:
barnum_sipri ("milex_con_2022_sipri") and
barnum_nmc ("milex_con_2017_nmc"), which
extend each one’s coverage back to 1816 using information from all 24
sources. Both are in constant (inflation-adjusted) dollars, so
barnum_nmc is not directly comparable to
nmc_milex from dataset = "nmc", which NMC
documents in current-year dollars; their ratio varies smoothly over time
(around 2.4 for the United States in 1990, falling toward 1 by the
mid-2010s) rather than reflecting disagreement between the sources.
barnum_milburden (milexgdp) is a unit-free
ratio of spending to GDP and so is published directly.
Licensing
The package’s MIT license applies to the software, not to third-party
data. Gapminder and UCDP identify their bundled data as CC BY 4.0; NAVCO
2.1 and MEC are CC0; UN WPP is CC BY 3.0 IGO. Other source files,
including NMC, SIPRI, and the Fariss et al. and Barnum et al. estimates,
retain their creators’ terms — SIPRI in particular is free to use with
attribution but requires separately negotiating a royalty for commercial
use. See inst/COPYRIGHTS and verify the applicable terms
before redistributing a package build containing those files.