Help for package gvc (original) (raw)

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.comVictor 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 )