wbids
is an R package to access and analyze the World
Bank’s International
Debt Statistics (IDS). IDS provides creditor-debtor relationships
between countries, regions, and institutions. ‘wbids’ enables users to
download, process and work with IDS series across multiple entities,
counterparts, and time periods.
The wbids
package relies on a redefinition of the
original World Bank data: ‘entities’ contain both countries and regions,
while ‘counterparts’ include both counterpart areas and institutions.
wbids
provides a consistent mapping of identifiers and
names across these different types. The corresponding package
vignette provides more details on the data model.
The package is part of the EconDataverse family of packages aimed at helping economists and financial professionals work with sovereign-level economic data.
This package is a product of Teal Insights and not sponsored by or affiliated with the World Bank in any way, except for the use of the World Bank IDS API.
You can install wbids
from CRAN via:
install.packages("wbids")
You can also install the development version of wbids
like this:
# install.packages("pak")
::pak("teal-insights/r-wbids") pak
On Linux, you may need to install libcurl4-openssl-dev
as a prerequisite to build the package.
The main function ids_get()
provides an interface to
download multiple IDS series for multiple entities and counterparts and
specific date ranges.
library(wbids)
ids_get(
geographies = c("ZMB", "ZAF"),
series = c("DT.DOD.DPPG.CD", "BM.GSR.TOTL.CD"),
counterparts = c("216", "231"),
start_year = 2015,
end_year = 2020
)
The package comes with prepared metadata about available series, entities, counterparts, and topics. Please consult the package vignette for details.
ids_list_series()
ids_list_entities()
ids_list_counterparts()
ids_list_series_topics()
This data can be used to enrich the IDS series or facilitate data discovery. For further applications, please consult Teal Insights’ Guide to Working with the World Bank International Debt Statistics.
The interface and column names are fully consistent with World
Development Indicators (WDI) data provided through the
wbwdi
package. You can find details on github.com/tidy-intelligence/r-wbwdi.
Contributions to wbids
are welcome! If you’d like to
contribute, please follow these steps:
For more detailed information on the package structure and development process, please visit the project Wiki.
The package is organized around three main functional groups:
graph TB
A[wbids] --> B[ids_list_*]
A --> C[ids_get]
A --> D[ids_bulk*]
B --> B1[ids_list_counterparts]
B --> B2[ids_list_entities]
B --> B3[ids_list_series]
B --> B4[ids_list_series_topics]
D --> D1[ids_bulk]
D --> D2[ids_bulk_files]
D --> D3[ids_bulk_series]
classDef default fill:#fff,stroke:#333,color:#333
classDef main fill:#f9f,stroke:#333,color:#000,font-weight:bold
classDef group fill:#bbf,stroke:#333,color:#000
class A main
class B,C,D group
class B1,B2,B3,B4,D1,D2,D3 default