The BIS package package provides an R interface to data hosted by the Bank for International Settlements.
The package can be installed from either CRAN or Github.
library(devtools)
install_github("expersso/BIS") # Github
install.packages("BIS") # CRANThe get_datasets downloads a list of available datasets.
library(BIS)
datasets <- get_datasets()
head(datasets, 20)
## # A tibble: 18 x 2
## name url
## <chr> <chr>
## 1 Locational banking statistics https://www.b~
## 2 Consolidated banking statistics https://www.b~
## 3 Debt securities statistics https://www.b~
## 4 Credit to the non-financial sector https://www.b~
## 5 Credit-to-GDP gaps https://www.b~
## 6 Debt service ratios for the private non-financial sector https://www.b~
## 7 Global liquidity indicators https://www.b~
## 8 OTC derivatives outstanding https://www.b~
## 9 US dollar exchange rates (monthly, quarterly and annual) https://www.b~
## 10 US dollar exchange rates (daily) https://www.b~
## 11 Effective exchange rate indices (monthly) https://www.b~
## 12 Effective exchange rate indices (daily) https://www.b~
## 13 Triennial Survey statistics on turnover https://www.b~
## 14 Property prices: selected series https://www.b~
## 15 Property prices: long series https://www.b~
## 16 Consumer prices https://www.b~
## 17 Policy rates (monthly) https://www.b~
## 18 Policy rates (daily) https://www.b~The function get_bis takes a url as input and downloads and parses the corresponding CSV file from the BIS website. This automatic parsing of the data is the major contribution of this package, since the different CSVs follow different formats.
The following code loads monthly data on central banks' policy rates:
rates <- get_bis(datasets$url[datasets$name == "Policy rates (monthly)"], quiet = TRUE)
head(rates)
## # A tibble: 6 x 6
## freq frequency ref_area reference_area date obs_value
## <chr> <chr> <chr> <chr> <chr> <dbl>
## 1 M Monthly CH Switzerland 1946-01 1.50
## 2 M Monthly DK Denmark 1946-01 3.50
## 3 M Monthly GB United Kingdom 1946-01 2.00
## 4 M Monthly IN India 1946-01 3.00
## 5 M Monthly JP Japan 1946-01 3.29
## 6 M Monthly SE Sweden 1946-01 2.50We plot these data for a subset of countries.
library(dplyr)
library(ggplot2)
library(zoo)
rates_plot <- rates %>%
mutate(date = as.Date(as.yearmon(date))) %>%
filter(grepl("^(XM|US|CH|JP|GB|CA)", ref_area))
ggplot(rates_plot, aes(date, obs_value, color = reference_area)) +
geom_hline(yintercept = 0, linetype = "dashed",
color = "grey70", size = 0.02) +
geom_line(show.legend = FALSE) +
facet_wrap(~reference_area) +
theme_light() +
theme(panel.grid = element_blank()) +
labs(x = NULL, y = NULL,
title = "Central bank policy rates",
subtitle = "% per annum")
Note that the BIS data sets come with a number of different time formats, so it's up to the user to parse these for himself/herself. The zoo package (especially as.yearqtr and as.yearmon) should take care of most cases.
Please also note that some datasets are fairly large (especially the first three returned by get_datasets), so you may need to run 64-bit R in order to load all the data into memory.
Finally, please don't abuse BIS's servers with unnecessary calls.
This package is in no way officially related to, or endorsed by, the BIS.
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