Only a transient weblog submit that successfully is jotting down some ideas and sources on New Caledonian nickel exports.
This submit was motivated by my (nonetheless incomplete) studying of this 2017 guide on Massive scale mines and native stage politics—between New Caledonia and Papua New Guinea, edited by Colin Filer and Pierre-Yves Le Meur. It’s fascinating, though clearly a bit dated now.
On the time of writing of that guide, the depiction of nickel mining in New Caledonia was extra optimistic, each in pure financial phrases and as an instrument of reconciliation and Kanak independence, than could be the case at the moment in 2025. With out going into all the small print, a number of mines have been mothballed or shut down in recent times. An already shaky financial development was exacerbated by the 2024 New Caledonia civil unrest. I needed to do a fast examine “is any nickel being exported in any respect? how a lot is it price?”—and therefore had a fast have a look at the info.
Exports by worth
My primary knowledge supply for that is New Caledonia’s ISEE (Institute de la statistique et des études économiques Nouvelle-Calédonie), which maintains a web page on nickel within the financial system. This seems to be like a 2019 web page, however the knowledge downloads in Excel format on the backside are being up to date month-to-month and are present proper as much as October 2025.
New Caledonia exports each ore and processed steel—there’s fairly a narrative behind this—and the export markets differ considerably. For instance Australia used to import ore however the processing plant in Queensland that was taking it was closed down. Right here is the info on ore exports, by worth and disaggregating by vacation spot:
… and right here is the comparable knowledge on processed steel:
The subsequent chart exhibits them each, now paying no consideration to vacation spot:
None of those charts are adjusted for inflation. Placing that apart, what we see in recent times from all of those in fact is fairly apparent—an enormous improve in exports by worth in 2021 and 2022, decline in 2023 and collapse in 2024 and 2025.
Right here’s the code to obtain this knowledge from the ISEE web site and draw these charts:
library(tidyverse)
library(readxl)
library(fredr)
# Nickel sector information from ISEE accessible at
# https://www.isee.nc/economie-entreprises/entreprises-secteurs-d-activites/secteur-du-nickel
obtain.file("https://www.isee.nc/element/phocadownload/class/147-consultez-les-donnees-historiques?obtain=676:les-exportations-de-nickel",
destfile = "nc-nickel-exports.xls", mode = "wb")
#--------------------minerai---------------------
ore <- read_excel("nc-nickel-exports.xls", sheet = "Minerai mensuel", vary = "A29:HG32",
col_names = c("vacation spot",
as.character(seq.Date(from = "2008-01-15", to = "2025-10-20", by = "month")))) |>
collect(date, worth, -vacation spot) |>
mutate(worth = as.numeric(worth),
date = as.Date(date),
datem = format(date, "%b %Y"),
datem = fct_reorder(datem, date),
kind = "Ore")
labs <- ranges(ore$datem)
labs[!grepl("Oct", labs)] <- ""
ore |>
ggplot(aes(x = datem, y = worth, fill = vacation spot)) +
geom_col() +
theme(axis.textual content.x = element_text(angle = 45, hjust = 1),
panel.grid.minor.x = element_blank(),
panel.grid.main.x = element_blank()) +
scale_x_discrete(labels = labs) +
scale_y_continuous(label = comma) +
labs(x = "", y = "XPF (m)", fill = "Vacation spot:",
title = "Nickel ore exports from New Caledonia, 2008-2025")
#--------------------metallurgie------------------
steel <- read_excel("nc-nickel-exports.xls", sheet = "Métallurgie mensuel", vary = "A134:HG138",
col_names = c("vacation spot",
as.character(seq.Date(from = "2008-01-15", to = "2025-10-20", by = "month")))) |>
collect(date, worth, -vacation spot) |>
mutate(worth = as.numeric(worth),
date = as.Date(date),
datem = format(date, "%b %Y"),
datem = fct_reorder(datem, date),
kind = "Processed steel")
steel |>
ggplot(aes(x = datem, y = worth, fill = vacation spot)) +
geom_col() +
theme(axis.textual content.x = element_text(angle = 45, hjust = 1),
panel.grid.minor.x = element_blank(),
panel.grid.main.x = element_blank()) +
scale_x_discrete(labels = labs) +
scale_y_continuous(label = comma) +
labs(x = "", y = "XPF (m)", fill = "Vacation spot:",
title = "Nickel steel exports from New Caledonia, 2008-2025")
#----------------------combined------------------
each <- rbind(steel, ore) |>
group_by(datem, kind) |>
summarise(worth = sum(worth, na.rm = TRUE))
each |>
ggplot(aes(x = datem, y = worth, fill = kind)) +
geom_col() +
theme(axis.textual content.x = element_text(angle = 45, hjust = 1),
panel.grid.minor.x = element_blank(),
panel.grid.main.x = element_blank()) +
scale_x_discrete(labels = labs) +
scale_y_continuous(label = comma) +
labs(x = "", y = "XPF (m)", fill = "Sort of export:",
title = "Nickel exports from New Caledonia 2008-2025")Seasonality
I used to be fascinated about among the variability in these patterns, and turned the full worth of those exports right into a single time collection. I decomposed this into development, seasonal and random parts and was to see that there’s in actual fact a noticeable seasonal element:
The low months within the seasonal sample are usually January, February, and generally April. That is plausibly associated to the heavier rain in these months making manufacturing and transport a bit tougher. However that is simply me guessing, I’m open to info on what else could be driving this seasonality.
Right here’s the code for that point collection decomposition:
nickel_ts <- each |>
group_by(datem) |>
summarise(worth = sum(worth)) |>
pull(worth) |>
ts(frequency = 12, begin = c(2008, 10))
par(bty = "l")
plot(stl(nickel_ts, s.window = 7), col = "steelblue",
primary = "Nickel exports (ore + metals, in thousands and thousands of XPF) from New Caledonia")Causes
Why have New Caledonia nickel exports collapsed a lot? I’m not an skilled on this however suppose that it’s largely pushed by international nickel costs; with a secondary issue being difficulties particular to New Caledonia (native space politics akin to these which are the topic of the guide I began this submit with a hyperlink to; safety significantly because the 2024 civil unrest however truly courting earlier; and excessive labour prices).
I received’t go into these New Caledonia-specific causes right here. However right here’s the world costs, exhibiting an apparent rise from 2016 to a spike in 2022 and a fast collapse from 2023 to 2025:
The structural improve in value was related to the demand for nickel in batteries, together with in electrical autos. The 2022 spike took place from a real squeeze in provide when Russia invaded Ukraine, and concern about Russian nickel going off the market. Costs then fell due to Indonesian provide approaching line, and the rise of nickel-free electrical automobile batteries.
When costs go down, in fact the worth of exports goes down even when volumes keep the identical. However when the value goes down due to extra competititon, quantity goes down as nicely. And the impression could be robust sufficient to guide entire mines to shut (as has been the case in New Caledonia).
Code for the world nickel costs knowledge, which comes from the USA Federal Reserve knowledge system (FRED):
#------------------nickel prices---
fredr_set_key(Sys.getenv("FRED_API_KEY")) # assumes was beforehand set with Sys.setenv(FRED_API_KEY = "XXXXXX")
nickel_prices <- fredr(
series_id = "PNICKUSDM",
observation_start = as.Date("2008-01-01"),
observation_end = Sys.Date() # or a selected finish date
)
nickel_prices |>
ggplot(aes(x = date, y = worth)) +
geom_line(color = "brown") +
scale_y_continuous(label = greenback) +
labs(x = "", y = "US {dollars} (m)",
title = "World nickel costs",
subtitle = "(Not adjusted for inflation)")That’s all for at the moment. There’s much more to this nickel story and the way crucial it’s for New Caledonia, however I don’t have time to enter it at the moment and doubtless I’m not the fitting individual to do it anyway.
Completely satisfied new 12 months!
