Extended reference table covering all polities and aggregate regions, including countries, territories, and statistical composites that appear in international databases but may lack standard ISO codes.
Format
A tibble where each row corresponds to one polity or aggregate region. It
contains the following columns (same definitions as polities_cats,
minus the five trailing 0...36–0...40 artefact columns):
legacy_polity_prefix: Legacy current polity prefix, kept for compatibility with older code that expected ISO3-like values. Not a polities code: it was calledpolity_codeuntil whep#687, where the name promised an identity none of its 271 non-NAvalues holds, so a join to polities or polity_area_crosswalk on it returned nothing. Readreporting_polity_codefor the polity.polity_name: Current polity, country, territory, or aggregate name.V1: Internal row index.code: Numeric FAOSTAT country/region code.polity_area_code: Numeric WHEP reporting area code used in matrix workflows.reporting_polity_code: Current periodized WHEP polity code forcode.reporting_polity_name: Current WHEP polity name forcode.reporting_polity_has_geometry: Logical flag indicating whether the current reporting polity has a polygon.iso3c: ISO 3166-1 alpha-3 code (NAfor aggregates).FAOSTAT_name: Name used in FAOSTAT (may be"#N/A"for aggregates).EU27: Logical EU27 membership flag.name: Name used in external databases.eia: EIA country identifier.iea: IEA country identifier.water_code: Water statistics numeric code.water_area: Name used in water statistics.baci: BACI trade database country code.fish: Fisheries dataset numeric code.region_code: Numeric regional code.cbs: Logical CBS dataset membership flag;TRUEif the area has a commodity balance sheet of its own. 202 areas.fabio_code: FABIO database numeric code, and the valuepolity_area_codeis derived from, so it is the fold instruction as well as a fact about FABIO. It is the area's owncodefor acbsreporter and 999 (Rest of World) otherwise, with seven exceptions: 62 -> 238, 276 -> 206 and 277 -> 206 are successor-state folds, and 153, 154, 209 and 212 arecbsreporters folded into 999 anyway. Those four are a contradiction inside this table – FABIO's own published region list enumerates all four as regions of their own – left standing because correcting it would move published values. See folded_reporting_areas and issue 556.ADB_Region: Asian Development Bank region.region: General world region.uISO3c: UN M49 numeric code.Lassaletta: Lassaletta et al. nitrogen study grouping.region_krausmann: Krausmann regional grouping.region_HANPP: HANPP study regional grouping.region_krausmann2: Alternative Krausmann grouping.region_UN_sub: UN M49 sub-region.region_UN: UN M49 macro-region.region_ILO1: ILO primary region.region_ILO2: ILO secondary region.region_ILO3: ILO tertiary region.region_IEA: IEA region.region_IPCC: IPCC region.region_labour: Labour-focused region.region_labour_agg: Aggregated labour region, one of"SAA","LACA","Europe","AUS","SE-Asia","MENA","FSU","NAME"or"RoW". Northern Mariana Islands (code 163) instead holds"Micronesia", its ownregion_UN_subvalue.region_labour_mech: Labour mechanisation region,"mech"or"no_mech". Two cells hold a sub-region name instead – Angola (code 7)"Middle Africa"and Northern Mariana Islands (163)"Micronesia", each its ownregion_labour-family value – which looks like a column shift in the source spreadsheet. At code 163 the shift is two columns wide, sinceregion_labour_aggis damaged in the same row; Angola'sregion_labour_aggis intact. Nothing here reads either column, so nothing computes on the bad cells; which class each belongs in is not recoverable from anything shipped with the package, and no public taxonomy defines this mechanised/not-mechanised split, so they are pinned intest_region_classifications.Rrather than guessed at (whep#855). Group agreement is suggestive but not deductive: the other eightregion_labour == "Middle Africa"rows are all"no_mech"and the other eightregion_UN_sub == "Micronesia"rows are all"mech", yet the column is not a function of either grouping –"Pacific","FSU"and"South America - South Cone"each split across both classes.
Source
Compiled from FAOSTAT, UN M49, ILO, IEA, and other international statistical sources.
Which regional groupings WHEP reads
The grouping columns are not all inputs to this package. Six have a consumer
in the tree, measured over R/, data-raw/, tests/, vignettes/ and
inst/: region (carried into polity_area_crosswalk at build time),
region_krausmann (the residue recovery rate, and the IPCC excreta regions
of prepare_spatialize_all.R), region_HANPP (the modern-variety adoption
share), region_UN_sub (the residue feed-use fraction, since whep#405),
ADB_Region (build_primary_production area keys) and EU27 (the EU
aggregate of the FABIO comparison). region_code carries no information
region does not – the two are a 1:1 relabelling – so it needs no
consumer of its own.
The rest – Lassaletta, region_krausmann2, region_UN, region_ILO1,
region_ILO2, region_ILO3, region_IEA, region_IPCC, region_labour,
region_labour_agg, region_labour_mech – are published third-party
taxonomies shipped for downstream analysis and read by nothing in the
package. They are shipped as reference, and carry no promise of being
re-validated against their upstream taxonomy on release, so a consumer should
check the gap it inherits before keying anything by one (whep#386).
The gap the present-day taxonomies share is dissolved states. Over the 202
cbs reporters, region_ILO1, region_ILO2, region_ILO3, region_IEA
and region_IPCC are each NA for exactly the four federations WHEP still
books commodity balances for – Czechoslovakia (51), Serbia and Montenegro
(186), the USSR (228) and the Yugoslav SFR (248) – and complete everywhere
else; region_UN labels three of the four and leaves only Czechoslovakia
NA. ROW (999) carries an explicit "RoW" value in all of them rather
than NA. Grouping by one of these without deciding what to do with the
federations silently drops the pre-succession record. region_UN_sub, which
shares the gap and does have a consumer, is pinned against it in
test_region_classifications.R.
A region_test column with two values ("Europe", "Other") and no
consumer was dropped in whep#386.
See also
polities_cats for the subset restricted to sovereign countries.
Examples
head(regions_full)
#> # A tibble: 6 × 38
#> legacy_polity_prefix polity_name V1 code iso3c FAOSTAT_name EU27 name
#> <chr> <chr> <dbl> <int> <chr> <chr> <lgl> <chr>
#> 1 ROW Rest of World 30 30 ATA NA FALSE Antar…
#> 2 NA NA 259 351 NA China FALSE China
#> 3 ROW Rest of World 149 152 NTZ NA FALSE Neutr…
#> 4 ROW Rest of World 245 254 OXY NA FALSE Other…
#> 5 ROW Rest of World 260 999 ROW NA FALSE RoW
#> 6 ROW Rest of World 244 252 UXY NA FALSE Unspe…
#> # ℹ 30 more variables: eia <chr>, iea <chr>, water_code <dbl>,
#> # water_area <chr>, baci <dbl>, fish <dbl>, region_code <dbl>, cbs <lgl>,
#> # fabio_code <dbl>, ADB_Region <chr>, region <chr>, uISO3c <dbl>,
#> # Lassaletta <chr>, region_krausmann <chr>, region_HANPP <chr>,
#> # region_krausmann2 <chr>, region_UN_sub <chr>, region_UN <chr>,
#> # region_ILO1 <chr>, region_ILO2 <chr>, region_ILO3 <chr>, region_IEA <chr>,
#> # region_IPCC <chr>, region_labour <chr>, region_labour_agg <chr>, …