Package 'exvatools'

Description

Produces a block diagonal matrix version of block matrix, i.e., a matrix in which the diagonal blocks are non-zero and the off-diagonal blocks are zero

Usage

bkd(df)

Arguments

Value

Block diagonal version of the original matrix.

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
# Block diagonal version of Y (coincides with Yd)
bkd(wio$Y)

Description

Diagonalize each block of a block matrix, so sectors of origin become also sectors of destination. Blocks of dimension NxN will remain NxN, but diagonalized, and blocks of dimensions Nx1 will be expanded to NxN and then diagonalized.

Usage

bkdiag(df)

Arguments

Value

Matrix df with blocks of dimension NxN diagonalized.

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
# Normal version of matrix Y
wio$Y
# Diagonal version (show first columns only)
bkdiag(wio$Y)[, 1:6]

Description

Produces a block off-diagonal matrix version of block matrix, i.e., a matrix in which the diagonal blocks are zero and the off-diagonal blocks are non-zero.

Usage

bkoffd(df)

Arguments

Value

Block off-diagonal version of the original matrix.

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
# Block off-diagonal version of Y (coincides with Ym)
bkoffd(wio$Y)

Description

Transpose a matrix by blocks, so block(s,r) becomes block(r,s), but elements within each block are not transposed.

Usage

bkt(df)

Arguments

Details

bkt() takes a matrix of ⁠c1 x c2⁠ blocks where each block has a dimension ⁠s1 x s2⁠ and transposes its blocks. Block B21 becomes B12, B31 becomes B13, etc., but blocks are not altered internally. For instance, a matrix with rows 5 exporting countries of 4 sectors each and columns with 3 importing countries with 2 aggregated sectors, i.e., a (5 x 4) x (3 x 2), matrix will become a (3 x 4) x (5 x 2) matrix. The rows will now show the importing countries and the sectors they import from, and the columns will show the the exporting countries and the sectors they export from.

Value

Block transposed version of df.

See Also

bktt().

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
# Matrix Ym (exports of final products)
wio$Ym
# Block transposed version of Ym (imports of final products)
bkt(wio$Ym)

Description

Block transpose matrix and then transpose each block. block(s,r) is transformed into block(r,s) and then internally transposed. This is not equivalent to directly transpose the matrix.

Usage

bktt(df)

Arguments

Value

Block transposed version of df with elements transposed.

See Also

bkt().

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
# Block-transpose Z and transpose blocks (show first elements only)
bktt(wio$Z)[1:6, 1:6]
# Note that directly transposing Z produces a different result:
t(wio$Z)[1:6, 1:6]

Description

Improved version of colSums() for matrix output. The sum of columns is kept as a row vector with column names and the resulting row can be named in the same command.

Usage

csums(df, row_name = NULL)

Arguments

Value

A row matrix (with rows and column names)

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
csums(wio$Y, "TOTAL_Y")

Description

Makes a diagonal matrix with the sums of columns of a matrix.

Diagonalizes the sums of each column of a matrix.

Usage

diagcs(df)

diagcs(df)

Arguments

Value

A diagonal matrix with the sums of columns in the diagonal.

A diagonal matrix with the sums of columns in the diagonal.

Examples

wio <- make_wio("wiodtest")
diagcs(wio$W %*% wio$Bd)
wio <- make_wio("wiodtest")
diagcs(wio$W %*% wio$Bd)

Description

Diagonalizes the sums of each row of a matrix.

Usage

diagrs(df)

Arguments

Value

A diagonal matrix with the sums of rows in the diagonal.

Examples

wio <- make_wio("wiodtest")
diagrs(wio$Y)

Description

Fast multiplication of a diagonal matrix by another matrix, taking taking advantage of the properties of diagonal matrices.

Usage

dmult(matrix1, matrix2)

Arguments

Details

dmult() will turn matrix1 into a vector and multiply it horizontally by every rows in matrix2. This saves precious computing time.\ The number of rows and columns of the diagonal matrix1 must be equal to the number of rows of matrix1.

Value

Product of matrix1 and matrix2.

See Also

multd().

Examples

wio <- make_wio("wiodtest")
dmult(wio$W, wio$Bd)

Description

Extracts exporting country and sector and destination data from a specific variable in an exvatools object.

Usage

get_data(
  exvatools_object,
  var,
  exporter,
  sector = "TOTAL",
  importer = "WLD",
  imp_sector = "TOTAL",
  demand_comp = "TOTAL",
  as_num = FALSE
)

Arguments

Value

A two-dimensional matrix with sector and geographical data of a variable.

Examples

wio <- make_wio("wiodtest")
get_data(wio, "EXGR", exporter = "ESP", sector = "MANUF")
get_data(wio, "EXGR", exporter = "ESP", sector = c("TOTAL", "MANUF", "SRVWC"),
         importer = c("USA", "FRA"))

Description

Detail from an exvadec decomposition of a country by sector and by destination

Usage

get_exvadec_bkdown(
  exvadec_object,
  exporter = "WLD",
  sector = "TOTAL",
  importer = "WLD"
)

Arguments

Value

Print result to console

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
exvadec <- make_exvadec(wio, quiet = TRUE)
get_exvadec_bkdown(exvadec, "ESP", "MANUF")

Description

Gets the ISO3 codes of standard country groups available for the different input-output tables. The resulting format can be used to extract elements of a matrix using grep.

Usage

get_geo_codes(geo_id, wiotype = "icio2025", icio_extend = FALSE)

Arguments

Value

Codes of country/countries ready to grep, e.g. AUS|ARG|BEL

Examples

# Get the codes of EU27 countries
get_geo_codes("EU27", "icio2025")
# Gets the codes for NAFTA and extends MEX to MX1|MX2
get_geo_codes("NAFTA", "icio2025", icio_extend = TRUE)

Description

Gets the ISO3 codes of standard sector groups available for the different input-output tables. The resulting format can be used to extract elements of a matrix using grep.

Usage

get_sec_codes(sector_id, wiotype = "icio2025", remove_letter = FALSE)

Arguments

Value

Codes of sector ready to grep, e.g. ⁠_01|_02|_03⁠.

Examples

# Get sector codes for manufactures in the icio2025 database.
get_sec_codes("MANUF", "icio2025")
# Get sector codes for services (including construction)
get_sec_codes("SRVWC", "icio2025")
# Get sector codes for manufacturing, removing the first letter so
# the result can be used with `grep` to select specific sectors from
# a matrix
get_sec_codes("MANUF", "icio2025", remove_letter = TRUE)

Description

Origin of value added in gross exports. It combines a make_exvadir() command and a get_data() command to obtain a result equivalent to the OECD's Origin of Value added in Gross Exports EXGR_BSCI, but with much more flexible geographical and sector options.

Usage

get_va_exgr(
  wio_object,
  va_type = "FC",
  geo_orig = "WLD",
  sec_orig = "TOTAL",
  geo_export,
  sec_export = "TOTAL",
  as_numeric = TRUE
)

Arguments

Value

A matrix, vector or data frame with export value added data.

Examples

wio <- make_wio("iciotest")
# Exports of manufactures of Spain using foreign VA from France
get_va_exgr(wio, "FC", "FRA", "TOTAL", "ESP", "MANUF")

Description

Get exports in terms of final absorption by origin of value added and final destination. It combines a make_exvadir() command and a get_data() command to obtain a result equivalent to that of the OECD's Gross Exports by Origin of Value Added and Final destination (FD_EXGR_VA, FD_EXGRFNL_VA and FD_EXGRINT_VA), but with much more flexible geographical and sector options.

Usage

get_va_exgry(
  wio_object,
  va_type = "TC",
  flow_type = "EXGRY",
  geo_orig = "WLD",
  geo_export,
  sec_export = "TOTAL",
  geo_fd = "WLD",
  as_numeric = TRUE
)

Arguments

Value

A matrix, vector or data frame with data of exports

Examples

# What part of French value added exported as US final intermediate
# manufactures ends up absorbed by Spain?
wio <- make_wio("iciotest")
get_va_exgry(wio, flow_type = "EXGRY_INT", geo_orig = "FRA",
             geo_export = "USA", sec_export = "MANUF", geo_fd = "ESP")

Description

Details of both geographical and sector origin of the VA induced by final demand. Equivalent to the OECD's Origin of Value added in Final Demand (FDVA_BSCI), but with much more flexible geographical and sector options.

Usage

get_va_fd(
  wio_object,
  va_type = "TOTAL",
  geo_orig = "WLD",
  sec_orig = "TOTAL",
  geo_fd = "WLD",
  sec_fd = "TOTAL",
  intra = FALSE
)

Arguments

Value

Matrix with source and destination of value added.

Examples

wio <- make_wio("iciotest")
# Get USA's total VA in services induced by China's manufacturing
get_va_fd(wio, geo_orig = "USA", sec_orig = "SRVWC",
         geo_fd = "CHN", sec_fd = "MANUF")
# Get world VA exported (VAX), i.e., world VA induced by the rest of
# the world not domestically absorbed
get_va_fd(wio, "VAX", "WLD", "TOTAL", "WLD", "TOTAL")

Description

Creates a global extraction matrix Anots of an exporter and its inverse Bnots.

Usage

get_xmatrix(
  wio,
  exporter,
  perim = "country",
  partner = "WLD",
  sector = "TOTAL",
  inverse = TRUE
)

Arguments

Value

The global (inverse) extraction matrix of the specified exporter.

Description

Hadamard product, i.e., element by element product of matrix df1 and matrix df2 (by blocks). Both matrices must be block matrices, and the number and dimension of blocks in matrix df1 and df2 must be compatible.

Usage

hmult(df1, df2)

Arguments

Details

In a Hadamard product, matrices are multiplied block by block, i.e., block (s,r) %*% block(s,r).

Value

Hadamard product of the two matrices.

Description

An example of an ICIO-type input-output table, with rows for MEX and CHN disaggregated into MX1 and MX2 and CN1 and CN2, respectively.

Usage

iciotest_data

Format

A matrix of 30 by 42, composed of two sub-matrices:

• Sub-matrix Z, intermediate inputs: 30 by 30 (10 countries with 3 sectors each). 4 of those 10 are the extensions of CHN and MEX).

• Sub-matrix Yfd, final demand: 30 by 12 (10 countries with 3 sectors each in rows, 6 countries by 2 demand components each in columns).

Source

Data were randomly generated with an uniform distribution.

Description

Show available countries and country groups in a specific Input-Output table

Usage

info_geo(wiotype = "icio2025", lang = "en")

Arguments

Value

Prints country codes and descriptive text in the console.

Examples

info_geo("icio2025")

Description

Show available sectors and sector groups included in a specific Input-Output table

Usage

info_sec(wiotype = "icio2025", lang = "en")

Arguments

Value

Prints ids, sector codes and descriptive text

Examples

info_sec("icio2025")

Description

Creates a list object of class wio containing the typical international input-output matrices in a standardized format, as well as a list of code names (countries, sectors and demand components) and a list of dimensions (number of countries, sectors and demand components), using custom data.

Usage

make_custom_wio(
  df,
  g_names,
  n_names = NULL,
  fd_names = NULL,
  year = NULL,
  quiet = FALSE
)

Arguments

Details

make_custom_wio() creates a wio from custom input-output data provided as a single matrix of dimension ⁠GxN x GxFD⁠, i.e., the matrix Z of intermediate inputs (dimension ⁠GxN x GxN⁠) bound with the matrix Yfd of final demand (dimension ⁠GxN x GxFD⁠). The matrices of total output X and value added VA will be automatically generated, so should not be included. Data must be exclusively numeric.

A string vector with the names of countries is required. Number of countries will be calculated from this vector. Names for sectors and final demand components can be provided or will otherwise be automatically generated. All names must be composed of alphabetic characters (no special characters are allowed).

Value

A wioobject of wiotype = "custom".

Examples

df <- as.data.frame(matrix(c(19:36), nrow = 3))
wio <- make_custom_wio(df, g_names = c("C01", "C02", "C03"))

Description

Calculates the decomposition of value added in exports of a country or a group of countries according to different methodologies.

Usage

make_exvadec(
  wio_object,
  exporter = "all",
  method = "bm_src",
  output = "standard",
  quiet = FALSE,
  ...
)

Arguments

Value

A list object of class exvadec with several matrices plus metadata.

References

• Borin, A., & Mancini, M. (2023). Measuring What Matters in Value-Added Trade. Economic Systems Research, 1-25.

• Koopman, R., Wang, Z., & Wei, S.-J. (2014). Tracing Value-Added and Double Counting in Gross Exports. American Economic Review, 104(2), 459–494.

• Miroudot, S., & Ye, M. (2021). Decomposing Value Added in Gross Exports. Economic Systems Research, 33(1), 67–87.

• Wang, Z., Wei, S.-J., & Zhu, K. (2013). Quantifying International Production Sharing at the Bilateral and Sector Levels (NBER Working Paper No. 19677). National Bureau of Economic Research, Inc.

Examples

# Create a test wio
wio <- make_wio("iciotest")
# Make Borin and Mancini (2023) source decomposition for Spain
exvadec <- make_exvadec(wio, exporter = "ESP", method = "bm_src")
# Make Wang et al. (2013) decomposition for all countries
# expressed in the traditional 16 terms
exvadec <- make_exvadec(wio, method = "wwz", output = "terms")

Description

Direction of value added in exports, i.e., details of both geographical and sector origin of the VA incorporated in exports and of the final destination (in gross terms or in terms of final absorption).

Usage

make_exvadir(
  wio_object,
  exporter,
  va_type = "TC",
  flow_type = "EXGR",
  orig_geo = "all",
  sec_orig = "all",
  via = "any",
  perspective = "exporting",
  intra = FALSE
)

Arguments

Value

Matrix with source and destination of value added in exports

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
# Foreign services content of value added incorporated in exports of Spain,
# by country of origin and final destination, expressed in gross terms
# (equivalent to OECD TiVA’s indicator EXGR_SERV_FVA).
exvadir <- make_exvadir(wio, va = "FC", flow="EXGR", exp="ESP",
                        sec_orig="SRVWC")
summary(exvadir)

Description

Creates a list object of class wio containing the typical international input-output matrices in a standardized format, as well as a list of code names (countries, sectors and demand components) and a list of dimensions (number of countries, sectors and demand components). It can use source files from well-known databases or internal data (test data).

Usage

make_wio(wiotype = "icio2025", year = NULL, src_dir = NULL, quiet = FALSE)

Arguments

Details

make_wio() directly unzips and processes the original source files for the different international input-output tables and returns a list with the traditional matrices, including the coefficient matrix A, the Leontief global inverse matrix B, the Leontief matrix of local inverse matrices Ld and others.

Original source files can be obtained from the OECD's ICIO web page, the University of Groningen's WIOD web page, the Eurostat web page or the Asian Development Bank MRIO web page

If source files are used, they must be previously downloaded and placed in an accessible folder in disk, without renaming them. The following name pattern is expected:

• XXXX-XXXX.zip for "icio2025" and "icio2023" (.csv files)

• XXXX-XXXX_SML.zip for "icio2025s" and "icio2023s" (.csv files)

• ICIO_XXXX-XXXX.zip for "icio2021" (.csv files)

• ICIO2018_XXXX.zip for "icio2018" (.csv files)

• ICIO2016_XXXX.zip for "icio2016" (.csv files)

• WIOTS_in_R.zip for "wiod2016" (.RData files)

• WIOTS_in_EXCEL.zip for "wiod2013" (.xlsx files). Requires package openxlsx.

• lr_wiod_wiot_final_filled.csv for "lrwiod2022". Requires packages data.table and reshape2.

• matrix_eu-ic-io_ind-by-ind_2Xed_XXXX.csv for ⁠"figaro202Xi⁠ and matrix_eu-ic-io_prod-by-prod_2Xed_XXXX.csv for ⁠"figaro202Xp⁠ (.csv files).

• ADB-MRIO[XX]-XXXX_xxx202X.xlsx for the "mrio202X", "mrio202Xx" and ⁠ADB MRIO XXXX, at constant 2010 prices.xlsx⁠ for the "mrio62-202Xk" tables (with some exceptions and updates).

The input-output framework follows the traditional demand model of Leontief (1936), which makes assumptions about the stability of inputs (and therefore value-added) as a proportion of production. This allows production and value-added to be expressed as the result of variations in final demand.

Details about the content of the world input-output object (wio) produced by make_wio() can be obtained with the command summary(wio_object).

Value

A list object of class wio including input-output matrices, dimensions, and names.

See Also

make_custom_wio()

Examples

wio <- make_wio("iciotest")
summary(wio)
## Not run: 
# The following examples require the previous download of the source
# files in the working directory or in a directory specified by `src_dir`.
wio <- make_wio("icio2025", 2022)
wio <- make_wio("wiod2023", 2020)
wio <- make_wio("wiod2023", 2020, src_dir = "C:/Users/John/R/")

## End(Not run)

Description

Meld ICIO matrix with extended countries. Melds countries CHN and MEX from their extended versions e.g., CN1 and CN2 are melded into CHN.

Usage

meld(df, meld_rows = TRUE, meld_cols = TRUE)

Arguments

Value

Melded version of ICIO matrix.

Description

Fast multiplication of a matrix by a diagonal matrix, taking advantage of the properties of diagonal matrices.

Usage

multd(matrix1, matrix2)

Arguments

Details

multd() will turn matrix2 into a vector and multiply it horizontally by every row in matrix1. This saves precious computing time.\ The number of columns of matrix1 must be equal to the rows and columns of diagonal matrix2.

Value

The product of matrix1 and matrix2.

See Also

dmult().

Examples

wio <- make_wio("wiodtest")
multd(wio$B, wio$E)

Description

Print method for exvadec class

Usage

## S3 method for class 'exvadec'
print(x, ...)

Arguments

Value

Printout to console

Description

Print method for exvadir class

Usage

## S3 method for class 'exvadir'
print(x, ...)

Arguments

Value

Printout to console

Description

Print method for wio class

Usage

## S3 method for class 'wio'
print(x, ...)

Arguments

Value

Printout to console

Description

Improved version of rowSums() for matrix output. The sum of rows is kept as a column vector with rows names and the resulting column can be named in the same command.

Usage

rsums(df, col_name = NULL)

Arguments

Value

A column matrix (with rows and column names)

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
rsums(wio$Y, "Y")

Description

Sets to zero specific rows and columns of a matrix, to include and exclude specific geographical and sector effects.

Usage

set_zero(df, orig = NULL, dest = NULL, wiotype = NULL, invert = FALSE)

Arguments

Value

The same matrix with specific rows and columns set to zero.

Examples

wio <- make_wio("wiodtest")
# Set to zero Spanish exports of intermediates of manufacturing to
# non EU27 countries (for any sector of destination) in the coefficient
# matrix A
set_zero(wio$A, list("ESP", "MANUF"), list("NONEU27", "TOTAL"), "wiodtest")
# Set to zero Spanish exports of intermediates (extraction matrix of Spain)
set_zero(wio$A, list("ESP", "TOTAL"), list("WLDxESP", "TOTAL"), "wiodtest")

Description

Groups a matrix by columns, by summing blocks of columns of size n each. Matrix columns should be multiple of n.

Usage

sumgcols(df, n, col_names = NULL)

Arguments

Value

A matrix where each column is the sum of groups of n columns of the original matrix.

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
sumgcols(wio$Yfd, wio$dims$FD, wio$names$g_names)

Description

Groups a matrix by rows, summing blocks of rows of size n each. Matrix rows should be multiple of n.

Usage

sumgrows(df, n, row_names = NULL)

Arguments

Value

A matrix where each row is the sum of groups of n rows of the original matrix.

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
sumgrows(wio$Y, wio$dims$N, wio$names$g_names)

Description

Summary method for exvadec class

Usage

## S3 method for class 'exvadec'
summary(object, ...)

Arguments

Value

Printout to console

Description

Summary method for exvadir class

Usage

## S3 method for class 'exvadir'
summary(object, ...)

Arguments

Value

Printout to console

Description

Summary method for wio class

Usage

## S3 method for class 'wio'
summary(object, ...)

Arguments

Value

Printout to console

Description

Groups a matrix by columns, summing every Nth column. Matrix should be multiple of N.

Usage

sumncol(df, N, col_names = NULL)

Arguments

Value

A matrix with N columns, where each columns is the sum of every Nth column of the original matrix.

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
sumncol(wio$Yfd, wio$dims$FD, paste0("WLD", "_", wio$names$fd_names))

Description

Groups a matrix by rows, summing every Nth row. Matrix should be multiple of N.

Usage

sumnrow(df, N, row_names = NULL)

Arguments

Value

A matrix with N rows, where each row is the sum of every Nth row of the original matrix.

Examples

wio <- make_wio("wiodtest", quiet = TRUE)
sumnrow(wio$Y, wio$dims$N, paste0("WLD", "_",
        gsub("^D", "", wio$names$n_names)))

Description

Gives a descriptive text of id codes from a vector of id codes, like those in rows or columns of exvatools objects.

Usage

txt_from_ids(
  id_list,
  type = "sec",
  lang = "en",
  ver = "short",
  wiotype = "icio2023"
)

Arguments

Value

A string vector with text

Examples

txt_from_ids("MANUF")
txt_from_ids("MANUF", lang = "es")

Description

An example of a WIOD-type input-output table.

Usage

wiodtest_data

Format

A matrix of 18 by 30, composed of two sub-matrices:

• Sub-matrix Z, intermediate inputs: 18 by 18 (10 countries with 3 sectors each).

• Sub-matrix Yfd, final demand: 18 by 12 (6 countries with 3 sectors each in rows, 6 countries by 2 demand components each in columns).

Source

Data were randomly generated with an uniform distribution.