Aggregate by dated group membership

Roll countries up to a group such as the EU or the OECD using the members of each row's own year, not today's list. An "EU" series built from the current 27 members misstates every year before 2020 and every year before an accession; this builds it from whoever was a member at the time, under the same coverage rule as aggregate_regions().

Usage

aggregate_groups(
  data,
  value,
  groups,
  as_of = NULL,
  fun = "sum",
  weight = NULL,
  min_coverage = 2/3
)

Arguments

data

A country-level frame with an iso3c column, and a year column for a panel.

value

The value column to aggregate (unquoted).

groups

One or more group names (see country_groups()).

as_of

NULL (default) uses each row's year when data has one (a bare year is 1 January of that year, as in in_group()), and the current membership otherwise. A single date or year applies one membership to every row.

fun, weight

As in aggregate_regions().

min_coverage

The smallest share of the group's members that has to report before an aggregate is computed. Default 2/3, the World Bank's rule. 0 computes every group-year from whatever it has.

Value

A tibble of group (and year for a panel), the aggregated value, n_countries (members on that date), n_reporting, coverage, and for a weighted mean coverage_weighted.

Who counts as a member

Coverage is measured against the group's full membership on that date, taken from country_groups_history, not against the members that happen to be in data: a member with no row is counted as missing. That is the difference from aggregate_regions(), which can only count what it is given. For fun = "weighted_mean" the weighted share is computed over the members present, since an absent member's weight is unknown. A group with no dated history (Commonwealth, G20, OPEC) warns and uses the current membership for every year.

See also

aggregate_regions(), in_group(), country_groups_history

Examples

pan <- data.frame(iso3c = rep(c("GBR", "FRA", "DEU", "HRV"), each = 2),
                  year = rep(c(2012, 2021), 4), gdp = 1:8)
# The United Kingdom counts in 2012 and not in 2021; Croatia the reverse.
aggregate_groups(pan, gdp, "EU", min_coverage = 0)
#> # A tibble: 2 × 6
#>   group  year   gdp n_countries n_reporting coverage
#>   <chr> <dbl> <int>       <int>       <int>    <dbl>
#> 1 EU     2012     9          27           3    0.111
#> 2 EU     2021    18          27           3    0.111