| Type: | Package |
| Title: | Global Value Chain Decomposition for Value-Added Trade |
| Version: | 0.1.1 |
| Description: | Provides tools for decomposing Global Value Chain (GVC) participation and value-added trade. It implements the frameworks proposed by Borin and Mancini (2023) 10.1080/09535314.2022.2153221> for source-based and sink-based decompositions, and by Borin, Mancini, and Taglioni (2025) 10.1093/wber/lhaf017> for tripartite and output-based GVC measures. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| Depends: | R (≥ 4.0.0) |
| Imports: | Matrix, methods, stats |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| VignetteBuilder: | knitr |
| RoxygenNote: | 7.3.3 |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2025-12-02 09:36:15 UTC; ballavbabu |
| Author: | Lila Ballav Bhusal
|
| Maintainer: | Lila Ballav Bhusal <krish.bhula@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-12-09 07:40:01 UTC |
BM_2023 pure bilateral decomposition of exports from s to r
Description
BM_2023 pure bilateral decomposition of exports from s to r
Usage
bm_2023_bilateral_pure(io, s, r)
Arguments
io |
A |
s |
Exporter country (name or index). |
r |
Importer country (name or index). |
Value
A data frame with the pure bilateral value-added decomposition.
BM_2023 pure bilateral (/sr) decomposition for all pairs
Description
BM_2023 pure bilateral (/sr) decomposition for all pairs
Usage
bm_2023_bilateral_pure_all(io)
Arguments
io |
A |
Value
Data frame of pure bilateral decomposition for all pairs.
BM_2023 sink-based bilateral decomposition of exports from s to r
Description
BM_2023 sink-based bilateral decomposition of exports from s to r
Usage
bm_2023_bilateral_sink(io, s, r)
Arguments
io |
A |
s |
Exporter country (name or index). |
r |
Importer country (name or index). |
Value
A data frame with the sink-based value-added decomposition.
BM_2023 sink-based bilateral decomposition for all pairs
Description
BM_2023 sink-based bilateral decomposition for all pairs
Usage
bm_2023_bilateral_sink_all(io)
Arguments
io |
A |
Value
Data frame of sink-based decomposition for all pairs.
BM_2023 source-based bilateral decomposition of exports from s to r
Description
BM_2023 source-based bilateral decomposition of exports from s to r
Usage
bm_2023_bilateral_source(io, s, r)
Arguments
io |
A |
s |
Exporter country (name or index). |
r |
Importer country (name or index). |
Value
A data frame with the source-based value-added decomposition.
BM_2023 source-based bilateral decomposition for all pairs
Description
BM_2023 source-based bilateral decomposition for all pairs
Usage
bm_2023_bilateral_source_all(io)
Arguments
io |
A |
Value
Data frame of source-based decomposition for all pairs.
BM_2023 exporter-perspective decomposition of total exports of s
Description
BM_2023 exporter-perspective decomposition of total exports of s
Usage
bm_2023_exporter_total(io, s)
Arguments
io |
A |
s |
Exporter country (name or index). |
Value
A data frame with the exporter-total decomposition.
BM_2023 exporter totals for all countries
Description
BM_2023 exporter totals for all countries
Usage
bm_2023_exporter_total_all(io)
Arguments
io |
A |
Value
Data frame of exporter totals for all countries.
BM_2025 output-based GVC components by exporter
Description
BM_2025 output-based GVC components by exporter
Usage
bm_2025_output_components(io)
Arguments
io |
A |
Value
Data frame with output-based GVC components.
BM 2025 output components by country and sector
Description
BM 2025 output components by country and sector
Usage
bm_2025_output_components_sector(io)
Arguments
io |
A |
Value
Data frame with sectoral output components.
BM_2025 output-based GVC participation indicators
Description
BM_2025 output-based GVC participation indicators
Usage
bm_2025_output_measures(io)
Arguments
io |
A |
Value
Data frame with output-based GVC participation measures.
BM 2025 output participation measures by country and sector
Description
BM 2025 output participation measures by country and sector
Usage
bm_2025_output_measures_sector(io)
Arguments
io |
A |
Value
Data frame with sectoral GVC measures.
BM_2025 exporter-level GVC trade totals
Description
BM_2025 exporter-level GVC trade totals
Usage
bm_2025_trade_exporter(io)
Arguments
io |
A |
Value
Data frame of exporter totals.
BM_2025 trade-based GVC participation indicators
Description
BM_2025 trade-based GVC participation indicators
Usage
bm_2025_trade_measures(io)
Arguments
io |
A |
Value
Data frame of trade-based indicators.
BM_2025 tripartite GVC trade decomposition for one pair (s,r)
Description
BM_2025 tripartite GVC trade decomposition for one pair (s,r)
Usage
bm_2025_tripartite_trade(io, s, r)
Arguments
io |
A |
s |
Exporter country (name or index). |
r |
Importer country (name or index). |
Value
Data frame for the pair (s,r).
BM_2025 tripartite GVC trade decomposition for all pairs
Description
BM_2025 tripartite GVC trade decomposition for all pairs
Usage
bm_2025_tripartite_trade_all(io)
Arguments
io |
A |
Value
Data frame for all pairs.
Build a bm_io object from IO table blocks
Description
Build a bm_io object from IO table blocks
Usage
bm_build_io(Z, Y, VA, X, countries, sectors)
Arguments
Z |
Intermediate demand matrix (GN x GN). |
Y |
Final demand matrix. Can be (GN x G) OR (GN x (G * FD_categories)). |
VA |
Value added. Can be a vector (length GN) or matrix (Rows x GN). |
X |
Output vector (length GN). |
countries |
Character vector of country names/codes (length G). |
sectors |
Character vector of sector names/codes (length N). |
Value
An object of class "bm_io".
Exports from s to r (sectoral)
Description
Exports from s to r (sectoral)
Usage
bm_get_e_sr(io, exporter, importer)
Arguments
io |
bm_io object. |
exporter |
Exporter country (name or index). |
importer |
Importer country (name or index). |
Value
Numeric vector of exports.
Total exports of s to all foreign destinations
Description
Total exports of s to all foreign destinations
Usage
bm_get_e_star(io, exporter)
Arguments
io |
bm_io object. |
exporter |
Exporter country (name or index). |
Value
Numeric vector of total exports.
Toy 4-country, 3-sector IO table for bmGVC
Description
A small multi-country input–output data set used in bmGVC examples and vignettes. It contains four countries (China, India, Japan, ROW) and three sectors (Primary, Manufacturing, Service).
Format
- bm_toy_Z
numeric matrix
12 x 12- bm_toy_Y
numeric matrix
12 x 4- bm_toy_VA
numeric vector of length 12
- bm_toy_X
numeric vector of length 12
- bm_toy_countries
character vector of length 4
- bm_toy_sectors
character vector of length 3
Details
The data are stored in six objects:
-
bm_toy_Z: 12 x 12 intermediate demand matrix -
bm_toy_Y: 12 x 4 final demand matrix -
bm_toy_VA: length-12 value-added vector -
bm_toy_X: length-12 gross output vector -
bm_toy_countries: character vector of length 4 -
bm_toy_sectors: character vector of length 3
The ordering of industries is (China P,M,S; India P,M,S; Japan P,M,S; ROW P,M,S).