This submit is the sixth of a sequence of seven on inhabitants points within the Pacific, re-generating the charts I utilized in a keynote speech earlier than the November 2025 assembly of the Pacific Heads of Planning and Statistics in Wellington, New Zealand. The seven items of the puzzle are:
Remittances are funds from household or different contacts abroad, sometimes in a better revenue nation. The supply of remittances may be folks on comparatively brief journeys abroad—within the Pacific, examples embrace folks within the Pacific Australia Labour Mobility scheme or the New Zealand Recognised Seasonal Employer scheme—or from long run migrants who’ve made the opposite nation their indefinite residence.
The excellence between the 2 kinds of period is necessary for the place these funds seem within the Nationwide Accounts, however sadly is tough to measure statistically. Banks can hold observe of how a lot cash is being transferred and provides this data to a central financial institution or nationwide statistical workplace, however typically will be unable to categorise the sources as brief time period or long run residents.
The implications of all this, within the context of what number of Pacific islanders reside abroad and the place (the topic of earlier posts on this sequence) will all be mentioned later. However for now, right here is the chart of Pacific remittances:
That is designed largely to a) present how various Pacific international locations have very excessive ranges of remittances, relative to their nationwide economic system (greater than 40% of GDP for Tonga) in comparison with world averages and b) spotlight just a few of the Pacific island international locations particularly which might be most excessive on this respect. Generally a easy bar chart is all it’s good to make the purpose. Though this bar chart isn’t so simple as it might sound at first look; there’s fairly a little bit of thought gone into the sequencing of the nation classes on the backside to maximise the impression, and naturally colour-coding the bars to differentiate the Pacific international locations from the worldwide comparators.
Right here’s the code to provide this chart. Tremendous easy immediately, simply pulling the information from the World Financial institution’s World Improvement Indicators and turning it right into a single chart:
# This script attracts a easy bar chart of the most recent 12 months of remittances information
#
# Peter Ellis November 2025
library(WDI)
library(tidyverse)
library(glue)
picts <- c(
"Fiji", "New Caledonia", "Papua New Guinea", "Solomon Islands",
"Guam", "Kiribati", "Marshall Islands", "Micronesia, Fed. Sts.", "Nauru",
"Vanuatu", "Northern Mariana Islands","Palau", "American Samoa", "Prepare dinner Islands",
"French Polynesia", "Niue", "Samoa", "Tokelau", "Tonga", "Tuvalu", "Wallis and Futuna Islands"
)
size(picts)
type(picts) # all 22 SPC PICT members aside from Pitcairn
# Used this to see what sequence can be found:
# WDIsearch("remittance") |> View()
#
# Obtain information from World Financial institution's World Improvement Indicators.
# Apparently employee remittances is a subset of private. However
# the employee remittances are all NA anyway:
remit <- WDI(indicator = c(private = "BX.TRF.PWKR.DT.GD.ZS",
employee = "BX.TRF.PWKR.GD.ZS"), begin = 2000) |>
as_tibble()
# which international locations have we acquired?
type(distinctive(remit$nation))
# verify who lacking, simply the three NZ Realm international locations plus Wallis and futuna:
picts[!picts %in% unique(remit$country)]
# information for bar chart:
pac_data <- remit |>
group_by(nation) |>
filter(!is.na(private)) |>
prepare(desc(12 months)) |>
slice(1) |>
ungroup() |>
filter(nation %in% c(picts, "Center revenue", "Low revenue", "Small states", "World", "Australia", "New Zealand")) |>
mutate(is_pict = ifelse(nation %in% picts, "Pacific island", "Comparability")) |>
mutate(country_order = ifelse(nation %in% picts, private, 1000 - private),
nation = fct_reorder(nation, country_order))
# draw bar chart
pac_data|>
ggplot(aes(x = nation, y = private, fill = is_pict)) +
geom_col() +
scale_y_continuous(label = percent_format(scale = 1)) +
scale_fill_manual(values = c("brown", "steelblue")) +
theme(axis.textual content.x = element_text(angle = 45, hjust = 1),
legend.place = "none",
plot.caption = element_text(color = "grey50")) +
labs(x = "", fill = "",
subtitle = glue('{attr(remit$private, "label")}, {min(pac_data$12 months)} to {max(pac_data$12 months)}'),
y = "",
title = "Excessive dependency on remittances for a lot of Pacific Island international locations and territories",
caption = "Supply: World Financial institution World Improvement Indicators, sequence BX.TRF.PWKR.DT.GD.ZS")That’s all for immediately. Coming quickly (I hope), a extra narrative weblog tying all this Pacific inhabitants stuff collectively, kind of as a written model of the discuss that is all based mostly on.
