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GDPuc (a.k.a. the GDP unit-converter) provides a simple function to convert GDP time-series data from one unit to another.
To note: The default conversion parameters are from the World Bank’s World Development Indicators (WDI) database (see link). The current parameters are from April 30th 2024, with the next update planned for April 2026.
# Install from CRAN
install.packages("GDPuc")
# Or the development version from GitHub
::install_github("pik-piam/GDPuc") remotes
Load the package.
library(GDPuc)
The main function of the package is convertGDP
.
convertGDP(
gdp = my_gdp,
unit_in = "constant 2005 LCU",
unit_out = "constant 2017 Int$PPP"
)
Here, the gdp
argument takes a tibble or a data-frame
that contains, at least:
The unit_in
and unit_out
arguments specify
the incoming and outgoing GDP units. All common GDP units are supported,
i.e.:
Here “YYYY” is a placeholder for a year, e.g. “2010” or “2015”, and “LCU” stands for Local Currency Unit.
For a quick conversion of a single value use
convertSingle
.
convertSingle(
x = 100,
iso3c = "FRA",
year = 2000,
unit_in = "current LCU",
unit_out = "constant 2017 Int$PPP"
)
library(GDPuc)
<- tibble::tibble(
my_gdp iso3c = "USA",
year = 2010:2014,
value = 100:104
)print(my_gdp)
#> # A tibble: 5 × 3
#> iso3c year value
#> <chr> <int> <int>
#> 1 USA 2010 100
#> 2 USA 2011 101
#> 3 USA 2012 102
#> 4 USA 2013 103
#> 5 USA 2014 104
convertGDP(
gdp = my_gdp,
unit_in = "constant 2005 LCU",
unit_out = "constant 2017 Int$PPP"
)#> # A tibble: 5 × 3
#> iso3c year value
#> <chr> <int> <dbl>
#> 1 USA 2010 123.
#> 2 USA 2011 124.
#> 3 USA 2012 126.
#> 4 USA 2013 127.
#> 5 USA 2014 128.
convertSingle(
x = 100,
iso3c = "USA",
year = 2010,
unit_in = "current LCU",
unit_out = "constant 2017 Int$PPP"
)#> [1] 112.0447
# When converting between constant currencies, the year of the GDP value is not important,
# and can be left out.
convertSingle(
x = 100,
iso3c = "USA",
unit_in = "constant 2005 LCU",
unit_out = "constant 2017 Int$PPP"
)#> [1] 123.1357
convertGDP
has other arguments that allow you to:
choose conversion factors (see “Choosing conversion factors”)
print out information on the conversion process and/or return the conversion factors used (see “Getting information on the conversion process”)
handle missing conversion factors (see “Handling missing conversion factors”)
convert regional GDP data (see “Converting regional GDP data”)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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