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Version: 6.4.0
Title: Global Value Chains Tools
Description: Several tools for Global Value Chain ('GVC') analysis are implemented.
Maintainer: Bastiaan Quast <bquast@gmail.com>
Depends: R (≥ 3.5.0)
License: GPL-3
URL: https://qua.st/gvc, https://github.com/bquast/gvc
BugReports: https://github.com/bquast/gvc/issues
Imports: decompr, diagonals
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.2.0
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-06-19 17:35:38 UTC; bquast
Author: Bastiaan Quast ORCID iD [aut, cre], Victor Kummritz [aut]
Repository: CRAN
Date/Publication: 2022-06-19 17:50:02 UTC

Domestic Final Demand Domestic Value Added

Description

Domestic Final Demand Domestic Value Added

Usage

dfddva(x, aggregate = FALSE)

Arguments

x

A Leontief decomposed Inter-Country Input Output table as created by decompr, which should be post multiplied with final demand (using the parameter: post="final_demand")

aggregate

should dfddva be aggregated along source industries to a national sum?

Examples

# load the decompr package
library(decompr)

# load example data
data(leather)
attach(leather)

# create a leontief decomposed data set
l <- decomp(x = inter,
            y = final,
            k = countries,
            i = industries,
            o = out,
            method = "leontief",
            post = "final_demand")
 
 # apply dfddva
 dfddva( l )

Domestic Final Demand Foreign Value Added

Description

Domestic Final Demand Foreign Value Added

Usage

dfdfva(x, aggregate = FALSE)

Arguments

x

A Leontief decomposed Inter-Country Input Output table as created by decompr, which should be post multiplied with final demand (using the parameter: post="final_demand")

aggregate

should dfddva be aggregated along source industries to a national sum?

Examples

# load the decompr package
library(decompr)

# load the example data
data(leather)
attach(leather)

# create a leontief decomposed data set
l <- decomp(x = inter,
            y = final,
            k = countries,
            i = industries,
            o = out,
            method = "leontief",
            post = "final_demand")

 # apply dfdfva
 dfdfva( l )

Downstreamness

Description

Downstreamness

Usage

downstream(x)

Arguments

x

an object of class "decompr" as created using the load_tables_vectors() function from the decompr package.

Examples

# load the decompr package
library(decompr)

# load example data
data(leather)
attach(leather)

# create a leontief decomposed data set
l <- load_tables_vectors(x = inter,
                         y = final,
                         k = countries,
                         i = industries,
                         o = out        )
 
 # apply downstream
 downstream( l )

Exporting to Re-export

Description

Exporting to Re-export

Usage

e2r(x, by = NULL, subset = NULL)

Arguments

x

A Leontief decomposed Inter-Country Input Output table as created by decompr

by

variable to subset by

subset

value(s) of the subset variable to select

Examples

# load the decompr package
library(decompr)

# load the example data set
data(leather)
attach(leather)

# create a leontief decomposed data set
l <- decomp(x = inter,
            y = final,
            k = countries,
            i = industries,
            o = out)
 
 # apply the Exporting to Re-export
 e2r( l )

Foreign Final Demand Domestic Value Added

Description

Foreign Final Demand Domestic Value Added

Usage

ffddva(x, aggregate = FALSE)

Arguments

x

A Leontief decomposed Inter-Country Input Output table as created by decompr, which should be post multiplied with final demand (using the parameter: post="final_demand")

aggregate

should dfddva be aggregated along source industries to a national sum?

Examples

# load the decompr package
library(decompr)

# load example data
data(leather)
attach(leather)

# create a leontief decomposed data set
l <- decomp(x = inter,
            y = final,
            k = countries,
            i = industries,
            o = out,
            method = "leontief",
            post = "final_demand")

 # apply ffddva
 ffddva( l )

Global Value Chain analysis

Description

Several tools for Global Value Chain ('GVC') analysis are implemented.

Author(s)

Bastiaan Quast bquast@gmail.com Victor Kummritz

References

Wang, Zhi, Shang-Jin Wei, and Kunfu Zhu. Quantifying international production sharing at the bilateral and sector levels. No. w19677. National Bureau of Economic Research, 2013.

See Also

https://qua.st/decompr


Importing to Export

Description

Importing to Export

Vertical Specialization

Vertical Specialisation

Usage

i2e(x, by = NULL, subset = NULL)

vertical_specialisation(x, by = NULL, subset = NULL)

vertical_specialization(x, by = NULL, subset = NULL)

Arguments

x

A Leontief decomposed Inter-Country Input Output table as created by decompr

by

variable to subset by

subset

value(s) of the subset variable to select

Examples

# load the decompr package
library(decompr)

# load the example data set
data(leather)
attach(leather)

# create a leontief decomposed data set
l <- decomp(x = inter,
            y = final,
            k = countries,
            i = industries,
            o = out)
 
 # apply the Import to Exports analysis
 i2e( l )

New Revealed Comparative Advantage

Description

New Revealed Comparative Advantage

Usage

nrca(x)

Arguments

x

A decomposed Inter-Country Input Output table as created by decompr

Examples

# load the decompr package
library(decompr)
           
# load the example data set
data(leather)
attach(leather)

# perform Leontief decomposition
l <- decomp(x = inter,
            y = final,
            k = countries,
            i = industries,
            o = out,
            method = "leontief",
            post = "exports"    )

# load gvc package
library(gvc)

# perform New Revealed Comparative Advantage
nrca(l)


Upstreamness

Description

Upstreamness

Usage

upstream(x)

Arguments

x

an object of class "decompr" as created using the load_tables_vectors() function from the decompr package.

Examples

# load the decompr package
library(decompr)

# load example data
data(leather)
attach(leather)

# create a leontief decomposed data set
l <- load_tables_vectors(x = inter,
                         y = final,
                         k = countries,
                         i = industries,
                         o = out        )
 
 # apply upstream
 upstream( l )

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.
Health stats visible at Monitor.