Package 'iotables'

Title: Reproducible Input-Output Economics Analysis, Economic and Environmental Impact Assessment with Empirical Data
Description: Pre-processing and basic analytical tasks related to working with Eurostat's symmetric input-output tables and provide basic input-output economics calculations. The package is part of rOpenGov <http://ropengov.github.io/> to open source open government initiatives.
Authors: Daniel Antal [aut, cre] , Kasia Kulma [ctb] , Pyry Kantanen [ctb]
Maintainer: Daniel Antal <[email protected]>
License: MIT + file LICENSE
Version: 0.9.3
Built: 2024-09-04 04:52:41 UTC
Source: https://github.com/rOpenGov/iotables

Help Index

Get air pollutant data

Description

Get air emissions accounts by NACE Rev. 2 activity for environmental impact assessments.

Usage

airpol_get(
  airpol = "GHG",
  geo = "BE",
  year = 2020,
  unit = "THS_T",
  data_directory = NULL,
  force_download = TRUE
)

Arguments

airpol

The code of the air pollutant. Defaults GHG. ACG, CH4, CH4_CO2E, CH4_NMVOCE, CO, CO2, CO2_BIO, CO_NMVOCE, GHG, HFC_CO2E, N2O, N2O_CO2E, NF3_SF6_CO2E, NH3, NH3_SO2E, NMVOC, NOX, NOX_NMVOCE, NOX_SO2E, O3PR, PFC_CO2E, PM10, PM2_5, SOX_SO2E.
geo

The country code. The special value 'germany_1995' will return the replication dataset germany_airpol.
year

The year. The average employment will be created for the given year, starting with 2008, when the NACE Rev 2 was introduced in employment statistics.
unit

Defaults to "THS_T" (thousand tons.)
data_directory

Defaults to NULL, if a valid directory, it will try to save the pre-processed data file here with labelling.
force_download

Defaults to TRUE. If FALSE it will use the existing downloaded file in the data_directory or the temporary directory, if it exists.

Details

Currently tested only with product x product tables. The dataset air emissions accounts by NACE Rev. 2 activity [env_ac_ainah_r2] has five dimensions: The Air pollutant airpol variables are collected on the emissions of the following pollutants: carbon dioxide without emissions from biomass (CO2), carbon dioxide from biomass (Biomass CO2), nitroux oxide (N2O), methane (CH4), perfluorocarbons (PFCs), Hydrofluorocarbons (HFCs), sulphur hexafluoride (SF6) including nitrogen trifluoride (NF3), nitrogen oxides (NOx), Non-methane volatile organic compounds, (NMVOC), carbon monoxide (CO), Particulate matter smaller than 10 micrometre (PM10), Particulate matter smaller than 2,5 micrometre (PM2,5), Sulphur dioxide (SO2), Ammonia (NH3).

See Reference Metadata in Single Integrated Metadata Structure (SIMS) for further details, particularly on the calculation of Global warming potential GHG, Acidifying gases ACG and Tropospheric ozone precursors O3PR.

Value

A data.frame with auxiliary metadata to conform the symmetric input-output tables.

Source

Eurostat folder Air emissions accounts by NACE Rev. 2 activity

See Also

Other import functions: employment_get(), iotables_download(), iotables_metadata_get(), iotables_read_tempdir()

Examples

airpol_get(airpol = "CO2", geo="germany_1995", year = 1995, unit = "THS_T")

Backward linkages

Description

Indicate the interconnection of a particular sector to other sectors from which it purchases inputs (demand side). When a sector increases its output, it will increase the total (intermediate) demand on all other sectors, which is measured by backward linkages.

Usage

backward_linkages(Im)

Arguments

Im

A Leontief inverse matrix created by the leontief_inverse_create function.

Details

Backward linkages are defined as the column sum of the Leontief inverse, in line with the Eurostat Manual of Supply, Use and Input-Output Tables (see p506-507.) and the Handbook on Supply and Use Tables and Input-Output Tables with Extensions and Applications of the United Nations (see p636,)

Value

The vector of industry (product) backward linkages in a wide data.frame class, following the column names of the Leontief inverse matrix.

See Also

Other linkage functions: forward_linkages()

Examples

de_coeff <- input_coefficient_matrix_create( iotable_get(), 
                                             digits = 4 )
I <- leontief_inverse_create (de_coeff)
backward_linkages (I)

Create a coefficient matrix

Description

Create a coefficient matrix from a Symmetric Input-Output Table.

Usage

coefficient_matrix_create(
  data_table,
  total = "output",
  digits = NULL,
  remove_empty = TRUE,
  households = FALSE,
  return_part = NULL
)

Arguments

data_table

A symmetric input-output table, a use table, a margins or tax table retrieved by the iotable_get function.
total

Usually an output vector with a key column, defaults to "output" which equals "P1" or "output_bp". You can use other rows for comparison, for example "TS_BP" if it exists in the matrix.
digits

An integer showing the precision of the technology matrix in digits. Default is NULL when no rounding is applied.
remove_empty

Defaults to TRUE. If you want to keep empty primary input rows, choose FALSE. Empty product/industry rows are always removed to avoid division by zero error in the analytic functions.
households

Defaults to NULL. Household column can be added with TRUE.
return_part

Defaults to NULL. You can choose "product" or "industry" to return an input coefficient matrix or "primary_inputs" to get only the total intermediate use and proportional primary inputs.

Details

The coefficient matrix is related by default to output, but you can change this to total supply or other total aggregate if it exists in your table.

Value

A data.frame that contains the matrix of data_table divided by total with a key column. Optionally the results are rounded to given digits.

References

See United Kingdom Input-Output Analytical Tables 2010 for explanation on the use of the Coefficient matrix.

See Also

Other indicator functions: direct_effects_create(), input_indicator_create()

Examples

coefficient_matrix_create(data_table = iotable_get(source = "germany_1995"), 
                          total = "output", 
                          digits = 4 )

Create an empty conforming vector

Description

This helper function creates you a named vector that conforms your analytical objects, such as the use table, the Leontief-matrix, etc. With 60x60 matrixes it is easy to make mistakes with manual definition. The empty effects vector can be used in .csv format as a sample to import scenarios from a spreadsheet application.

Usage

conforming_vector_create(data_table)

Arguments

data_table

A use table, Leontief-matrix, Leontief-inverse, a coefficient matrix or other named matrix / vector.

Value

A wide-format conforming vector of data frame class, with column names matching the metadata of the data_table.

See Also

Other iotables processing functions: household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

de_input_flow <- input_flow_get(data_table = iotable_get())

conforming_vector_create (data_table = de_input_flow)

Input-output table for Croatia, 2010.

Description

1700 - Symmetric input-output table at basic prices (product x product) In thousand kunas (T_NAC)

Usage

data(croatia_2010_1700)

Format

A data frame with 13 variables.

t_rows2

Technology codes in row names, following the Eurostat convention.

t_rows2_lab

Longer labels for t_rows2

t_cols2

Technology codes in column names, following the Eurostat convention.

t_cols2_lab

Longer labels for t_cols2

iotables_col

The standardized iotables column labelling for easier reading.

col_order

The column ordering to keep the matrix legible.

row_order

The row ordering to keep the matrix legible.

iotables_row

The standardized iotables row labelling for easier reading.

unit

Different from Eurostat tables, in thousand national currency units.

geo

ISO / Eurostat country code for Croatia

geo_lab

ISO / Eurostat country name, Croatia.

time

Date of the SIOT

values

The actual values of the table in thousand kunas

Source

Državni zavod za statistiku.

See Also

Other Croatia 2010 datasets: croatia_2010_1800, croatia_2010_1900, croatia_employment_2013, croatia_employment_aggregation, primary_inputs

Input-output table for Croatia, 2010.

Description

1800 - Symmetric input-output table for domestic production (product x product) In thousand kunas (T_NAC)

Usage

data(croatia_2010_1800)

Format

A data frame with 13 variables.

t_rows2

Technology codes in row names, following the Eurostat convention.

t_rows2_lab

Longer labels for t_rows2

values

The actual values of the table in thousand kunas

t_cols2

Column labels, following the Eurostat convention with differences. CPA_ suffix added to original DZS column names.

t_cols2_lab

Longer labels for t_cols2

iotables_col

The standardized iotables column labelling for easier reading.

col_order

The column ordering to keep the matrix legible.

iotables_row

The standardized iotables row labelling for easier reading.

row_order

The row ordering to keep the matrix legible.

unit

Different from Eurostat tables, in thousand national currency units.

geo

ISO / Eurostat country code for Croatia

geo_lab

ISO / Eurostat country name, Croatia.

time

Date of the SIOT

Source

Državni zavod za statistiku.

See Also

Other Croatia 2010 datasets: croatia_2010_1700, croatia_2010_1900, croatia_employment_2013, croatia_employment_aggregation, primary_inputs

Input-output table for Croatia, 2010.

Description

1900 - Symmetric input-output table for imports (product x product) In thousand kunas (T_NAC)

Usage

data(croatia_2010_1900)

Format

A data frame with 13 variables.

t_rows2

Technology codes in row names, following the Eurostat convention.

t_rows2_lab

Longer labels for t_rows2

values

The actual values of the table in thousand kunas

t_cols2

Column labels, following the Eurostat convention with differences. CPA_ suffix added to original DZS column names.

t_cols2_lab

Longer labels for t_cols2

iotables_col

The standardized iotables column labelling for easier reading.

col_order

The column ordering to keep the matrix legible.

iotables_row

The standardized iotables row labelling for easier reading.

row_order

The row ordering to keep the matrix legible.

unit

Different from Eurostat tables, in thousand national currency units.

geo

ISO / Eurostat country code for Croatia

geo_lab

ISO / Eurostat country name, Croatia.

time

Date of the SIOT

Source

Državni zavod za statistiku.

See Also

Other Croatia 2010 datasets: croatia_2010_1700, croatia_2010_1800, croatia_employment_2013, croatia_employment_aggregation, primary_inputs

Croatian employment data for the year 2013

Description

Aggregate Croatian detailed employment statistics into the Croatian (EU standard) Symmetric input-output table format.

Usage

data(croatia_employment_2013)

Format

A data frame with 107 observations in 2 variables:

code

Short labels

iotables_row

iotables style labels

employment

Employment in the sector in Croatia, not in thousands!

See Also

Other Croatia 2010 datasets: croatia_2010_1700, croatia_2010_1800, croatia_2010_1900, croatia_employment_aggregation, primary_inputs

Aggregation table for Croatian employment statistics

Description

Aggregate Croatian detailed employment statistics into the Croatian (EU standard) Symmetric input-output table format.

Usage

data(croatia_employment_aggregation)

Format

A data frame with 105 rows (including empty ones) and 2 variables.

employment_label

Labelling in DZS English language export

t_cols2

Labelling of EU/DZS SIOTs.

See Also

Other Croatia 2010 datasets: croatia_2010_1700, croatia_2010_1800, croatia_2010_1900, croatia_employment_2013, primary_inputs

Create direct effects

Description

The function creates the effects.

Usage

direct_effects_create(input_requirements, inverse, digits = NULL)

Arguments

input_requirements

A matrix or vector created by input_indicator_create
inverse

A Leontief-inverse created by leontief_inverse_create.
digits

Rounding digits, defaults to NULL, in which case no rounding takes place.

Value

A data.frame containing the direct effects and the necessary metadata to sort them or join them with other matrixes.

See Also

Other indicator functions: coefficient_matrix_create(), input_indicator_create()

Examples

nl <- netherlands_2006

input_coeff_nl <- input_coefficient_matrix_create(
 data_table  = netherlands_2006, 
 households = FALSE) 

compensation_indicator <- input_indicator_create(netherlands_2006, 'compensation_employees')

I_nl <- leontief_inverse_create( input_coeff_nl )

direct_effects_create(input_requirements = compensation_indicator, 
                      inverse = I_nl)

Get employment data

Description

Download the employment data for a country and arrange it to the 64x64 SIOTs.

Usage

employment_get(
  geo,
  year = "2010",
  sex = "Total",
  age = "Y_GE15",
  labelling = "iotables",
  data_directory = NULL,
  force_download = FALSE
)

Arguments

geo

The country code.
year

The year. The average employment will be created for the given year, starting with 2008, when the NACE Rev 2 was introduced in employment statistics.
sex

Defaults to "Total". Enter "Females" or "F" for female employment, "Males" or "M" for male employment.
age

Defaults to "Y_GE15", which is the Eurostat code for employment in all age groups starting from 15-years-old. Any Eurostat code can be used as a parameter.
labelling

Either "iotables" or the applicable short code, for product x product SIOTs "prod_na" and in the case of industry x industry SIOTs "induse".
data_directory

Defaults to NULL, if a valid directory, it will try to save the pre-processed data file here with labelling.
force_download

Defaults to FALSE. It will use the existing downloaded file in the data_directory or the temporary directory, if it exists.

Details

Currently works only with product x product tables.

Value

A data.frame with auxiliary metadata to conform the symmetric input-output tables.

Source

Eurostat statistic Employment by sex, age and detailed economic activity (from 2008 onwards, NACE Rev. 2 two digit level) - 1 000

See Also

Other import functions: airpol_get(), iotables_download(), iotables_metadata_get(), iotables_read_tempdir()

Examples

## Not run: 
 io_tables <- get_employment ( 
               geo = "CZ", 
               year = "2010",
               sex = "Total", 
               age = "Y_GE15",
               data_directory = NULL,
               force_download = TRUE
               )
 
## End(Not run)

Employment metadata

Description

An arrangement of the Eurostat national accounts vocabulary to match with employment statistics data.

Usage

data(employment_metadata)

Format

A data frame with 6 variables.

emp_code

code used in the employment statistics

code

Eurostat labels for SIOTs corresponding to emp_code

label

Eurostat label descriptions for SIOTs corresponding to emp_code

variable

Eurostat vocabulary source, i.e. t_rows, t_cols, prod_na, induse

group

Different from Eurostat tables, in thousand national currency units.

iotables_label

Custom, machine_readable snake format variable names

See Also

Other Metadata datasets: metadata_uk_2010, metadata

Symmetrically remove empty rows and columns

Description

Symmetrically remove columns with only zero values or with missing values.

Usage

empty_remove(data_table)

Arguments

data_table

A symmetric input-output table, or a symmetric part of a use table or a supply table.

Value

A tibble/data.frame with a key row and a symmetric matrix, after removing all empty columns and rows at the same time.

Examples

test_table <- input_coefficient_matrix_create(iotable_get(source = "germany_1995"))
test_table[, 2] <- 0
empty_remove (test_table)

Solve a basic (matrix) equation

Description

The function matches to parts of the matrix equation, using the named formats with row names and solves the matrix equation.

Usage

equation_solve(LHS = NULL, Im = NULL)

Arguments

LHS

A left-hand side vector with a key column containing the industry or product names for matching, for example the employment coefficients.
Im

A Leontief-inverse with a key column containing the industry or product names for matching.

Details

This function is used in wrapper functions, such as multiplier_create. to solve particular problems, but it can be used directly, too. The function only performs the lhs pairing industries and checking for exceptions.

Value

A data.frame with auxiliary metadata to conform the symmetric input-output tables.

Examples

Im = data.frame (
a = c("row1", "row2"), 
b = c(1,1), 
c = c(2,0))
LHS = data.frame (
a = "lhs", 
b = 1, 
c = 0.5)
equation_solve (Im = Im, LHS = LHS)

Forward linkages

Description

The increased output of a sector indicates that additional amounts of products are available to be used as inputs by other sectors which can increase their production, which is captured in this indicator vector.

Usage

forward_linkages(output_coefficient_matrix, digits = NULL)

Arguments

output_coefficient_matrix

An output coefficient matrix created with the output_coefficient_matrix_create function.
digits

Number of decimals for rounding, defaults to NULL.

Details

Forward linkages as defined by the Eurostat Manual of Supply, Use and Input-Output Tables (pp. 506–507) and the United Nations Handbook on Supply and Use Tables and Input-Output Tables with Extensions and Applications p637.

Value

The vector of industry (product) forward linkages in a long-form data.frame, containing the metadata column of the the row names from the output_coefficient_matrix.

See Also

Other linkage functions: backward_linkages()

Examples

data_table = iotable_get()

de_out <- output_coefficient_matrix_create ( 
 data_table, "tfu", digits = 4
 )

forward_linkages(output_coefficient_matrix = de_out, 
                 digits = 4 )

Simple input-output table for Germany, 1995.

Description

Replication data taken from the Eurostat Manual, Table 15.4: Input-output table of domestic output at basic prices (Version A)

Usage

data(germany_1995)

Format

A data frame with 228 observations and 10 variables.

prod_na

Technology codes in row names, following the Eurostat convention.

prod_na_lab

Longer labels for t_rows2.

induse

Column labels, following the Eurostat convention with differences.

iotables_row

Row labels, i.e. to be used in key column, for iotables package abbreviations.

iotables_col

Column labels for iotables package abbreviations.

values

The actual values of the table in million euros.

unit

MIO_EUR, the same as Eurostat.

unit_lab

Million euros. Eurostat usually has euro and national currency unit values, too.

geo

ISO/Eurostat country code for Germany, i.e. DE.

geo_lab

ISO/Eurostat country name, Germany.

time

Date of the SIOT.

Details

For testing and documentation purposes a well documented example is taken the Eurostat Manual. The table in the Eurostat manual is brought to the format used by the Eurostat database. It is a small dataset for examples, but it is also instructive to understand how Eurostat stores the highly structured SIOTs in long-form tidy datasets. The labels were slightly alterred to reflect the transition from the vocabulary of ESA95 to ESA2010 since the publication of the Manual.

Source

Eurostat Manual of Supply, Use and Input-Output Tables p 482

See Also

Other Validation datasets: germany_airpol, netherlands_2006, uk_2010_data, uk_test_results

Air Pollution Table for Germany, 1995.

Description

Air pollution values for validation.

Usage

data(germany_airpol)

Format

A data frame with 72 observations and 4 variables.

airpol

The abbreviation of the air pollutant.

induse

Column labels, following the Eurostat convention with differences.

iotables_col

Column labels for iotables package abbreviations.

value

The actual values of the table in thousand tons.

Details

For testing purposes and cross-checking with the Eurostat manual. The labels were slightly alterred to reflect the transition from the vocabulary of ESA95 to ESA2010 since the publication of the Manual.

Source

Eurostat Manual of Supply, Use and Input-Output Tables p 482.

See Also

Other Validation datasets: germany_1995, netherlands_2006, uk_2010_data, uk_test_results

Create the inverse of a Ghosh-matrix

Description

Create the Ghosh-inverse from the output coefficients.

Usage

ghosh_inverse_create(output_coefficients_matrix, digits = NULL)

Arguments

output_coefficients_matrix

A technology coefficient matrix created by the output_coefficient_matrix_create.
digits

An integer showing the precision of the technology matrix in digits. Default is NULL when no rounding is applied.

Details

The Ghosh-inverse is

G=(I−B)−1G = (I-B)^-1

where B is the output coefficient matrix created by output_coefficient_matrix_create. See the United Nations Handbook on Supply and Use Tables and Input-Output Tables with Extensions and Applications pp 622–639.

For the similar inverse created from input coefficients, see the leontief_inverse_create function.

See Also

Other analytic object functions: input_flow_get(), leontief_inverse_create(), leontief_matrix_create()

Examples

om <- output_coefficient_matrix_create( 
  data_table = iotable_get()
  )
  
ghosh_inverse_create( output_coefficients_matrix = om )

Return the position of final household expenditure

Description

Return the position of final household expenditure

Usage

household_column_find(data_table)

Arguments

data_table

A symmetric input output table, a use table or a supply table.

Value

An integer value with the final household expenditure. Returns NULL if not found.

Examples

household_column_find( iotable_get ( source = 'germany_1995') )

Return Final Household Expenditure

Description

Return Final Household Expenditure

Usage

household_column_get(data_table)

Arguments

data_table

A symmetric input output table, a use table or a supply table.

Value

The column containing final household expenditure. If not found NULL is returned.

See Also

Other iotables processing functions: conforming_vector_create(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

household_column_get(iotable_get (source = 'germany_1995'))

Create indirect effects

Description

The function creates the indirect effects vector.

Usage

indirect_effects_create(input_requirements, inverse, digits = NULL)

Arguments

input_requirements

A matrix or vector created by input_indicator_create
inverse

A Leontief-inverse created by leontief_inverse_create.
digits

Rounding digits, defaults to NULL, in which case no rounding takes place.

Value

A data.frame containing the indirect effects and the necessary metadata to sort them or join them with other matrixes.

Examples

nl <- netherlands_2006

input_coeff_nl <- input_coefficient_matrix_create(
 data_table  = netherlands_2006, 
 households = FALSE) 

compensation_indicator <- input_indicator_create(netherlands_2006, 'compensation_employees')

I_nl <- leontief_inverse_create(input_coeff_nl)

indirect_effects_create(input_requirements = compensation_indicator, 
                        inverse = I_nl)

Create an input coefficient matrix

Description

Create an input coefficient matrix from the input flow matrix and the output vector. The two input vectors must have consistent labelling, i.e the same column names must be found in the use table (input flow) and the output vector.

Usage

input_coefficient_matrix_create(data_table, households = FALSE, digits = NULL)

Arguments

data_table

A symmetric input-output table, a use table, a margins or tax table retrieved by the iotable_get function.
households

Defaults to NULL. Household column can be added with TRUE.
digits

An integer showing the precision of the technology matrix in digits. Default is NULL when no rounding is applied.

Details

The input coefficients of production activities may be interpreted as the corresponding cost shares for products and primary inputs in total output. Our terminology follows the Eurostat Manual of Supply, Use and Input-Output Tables. Input-Output Multipliers Specification Sheet and Supporting Material, Spicosa Project Report, which cannot be linked due to a malformatted url, but can be found with a search engine. this matrix is called 'technological coefficients'. The results of the function are tested on both sources. This is a wrapper function around coefficient_matrix_create.

Value

A data frame that contains the matrix of first quadrant of the use table as input_flow divided by output supported by a key column of product or industries, with a key column. Optionally the results are rounded to given digits.

An input coefficient matrix of data.frame class. The column names are ordered, and the row names are in the first, auxiliary metadata column.

Examples

input_coefficient_matrix_create ( 
                           iotable_get(), 
                           digits = 4 )
                           
#This is a wrapper function and equivalent to                           

coefficient_matrix_create( iotable_get(), 
                           total = "total", 
                           return = "products")

Create an inter-industry or input flow matrix

Description

Select the first quadrant of the symmetric input-output table.

Usage

input_flow_get(data_table, empty_remove = FALSE, households = TRUE)

Arguments

data_table

A symmetric input-output table or use table retrieved by the iotable_get function.
empty_remove

Defaults to TRUE. If you want to keep empty primary input rows, choose FALSE. Empty product/industry rows are always removed to avoid division by zero error in the analytic functions.
households

Defaults to FALSE. If TRUE, the final household expenditure is added to the input flow table.

Details

The first quadrant is called the input flow matrix, or the input requirements matrix, or the inter-industry matrix in different contexts.

Value

A data flow matrix (a symmetric use table) with a key column.

See Also

Other analytic object functions: ghosh_inverse_create(), leontief_inverse_create(), leontief_matrix_create()

Examples

input_flow <- input_flow_get(data_table = iotable_get(), 
                             empty_remove = FALSE,
                             households = TRUE)

Create input indicator(s)

Description

The function creates the input indicators from the inputs and the outputs.

Usage

input_indicator_create(
  data_table,
  input_row = c("gva_bp", "net_tax_production"),
  digits = NULL,
  households = FALSE,
  indicator_names = NULL
)

Arguments

data_table

A symmetric input-output table, a use table, a margins or tax table retrieved by the iotable_get function.
input_row

The name of input(s) for which you want to create the indicator(s). Must be present in the data_table.
digits

Rounding digits, if omitted, no rounding takes place.
households

If the households column should be added, defaults to FALSE.
indicator_names

The names of new indicators. Defaults to NULL when the names in the key column of input_matrix will be used to create the indicator names.

Value

A tibble (data frame) containing the input_matrix divided by the output_vector with a key column for products or industries.

See Also

Other indicator functions: coefficient_matrix_create(), direct_effects_create()

Examples

input_indicator_create( data_table = iotable_get(), 
                        input_row = c("gva", "compensation_employees"),
                        digits = 4, 
                        indicator_names = c("GVA indicator", "Income indicator"))

Create input multipliers

Description

The function creates the multipliers (direct + indirect effects).

Usage

input_multipliers_create(
  input_requirements,
  Im,
  multiplier_name = NULL,
  digits = NULL
)

Arguments

input_requirements

A matrix or vector created by input_indicator_create
Im

A Leontief-inverse created by leontief_inverse_create.
multiplier_name

An optional name to be placed in the key column of the multiplier. Defaults to NULL.
digits

Rounding digits, defaults to NULL, in which case no rounding takes place. Rounding is important if you replicate examples from the literature, rounding differences can add up to visible differences in matrix equations.

Value

A data frame with the vector of multipliers and the an auxiliary metadata column, containing an automatically given row identifier (for joining with other matrixes) which can be overruled with setting multiplier_name.

See Also

Other multiplier functions: multiplier_create()

Examples

nl <- netherlands_2006

input_coeff_nl <- input_coefficient_matrix_create(
 data_table  = netherlands_2006, 
 households = FALSE) 

compensation_indicator <- input_indicator_create(netherlands_2006, 'compensation_employees')

I_nl <- leontief_inverse_create(input_coeff_nl)

input_multipliers_create(input_requirements = compensation_indicator, 
                        Im = I_nl)

Get An Input-Output Table Fom Bulk File

Description

This function is used to filter out a single input-output table from a database, for example a raw file downloaded from the Eurostat website. It provides some functionality to avoid some pitfalls.

Usage

iotable_get(
  labelled_io_data = NULL,
  source = "germany_1995",
  geo = "DE",
  year = 1990,
  unit = "MIO_EUR",
  stk_flow = "DOM",
  labelling = "iotables",
  data_directory = NULL,
  force_download = TRUE
)

Arguments

labelled_io_data

If you have downloaded a bulk data file with iotables_download, it is faster to work with the data in the memory. Defaults to NULL when the data will be retrieved from the hard disk or from the Eurostat website invoking the same function.
source

A data source, for example naio_10_cp1700.

naio_10_cp1700

Symmetric input-output table at basic prices (product by product)

naio_10_pyp1700

Symmetric input-output table at basic prices (product by product) (previous years prices)

naio_10_cp1750

Symmetric input-output table at basic prices (industry by industry)

naio_10_pyp1750

Symmetric input-output table at basic prices (industry by industry) (previous years prices)

naio_10_cp15

Supply table at basic prices incl. transformation into purchasers' prices

naio_10_cp16

Use table at purchasers' prices

naio_10_cp1610

Use table at basic prices

naio_10_pyp1610

Use table at basic prices (previous years prices) (naio_10_pyp1610)

naio_10_cp1620

Table of trade and transport margins at basic prices

naio_10_pyp1620

Table of trade and transport margins at previous years' prices

naio_10_cp1630

Table of taxes less subsidies on products at basic prices

naio_10_pyp1630

Table of taxes less subsidies on products at previous years' prices

For further information consult the Eurostat Symmetric Input-Output Tables page.
geo

A country code or a country name. For example, SK or as Slovakia.
year

A numeric variable containing the year. Defaults to 2010, because this year has the most data.
unit

A character string containing the currency unit, defaults to MIO_NAC (million national currency unit). The alternative is MIO_EUR.
stk_flow

Defaults to DOM as domestic output, alternative IMP for imports and TOTAL for total output. For source = 'naio_10_cp1620' and trade and transport margins and source = 'naio_10_cp1630' taxes less subsidies only TOTAL is not used.
labelling

Defaults to iotables which gives standard row and column names regardless of the source of the table, or if it is a product x product, industry x industry or product x industry table. The alternative is short or eurostat which is the original short row or column code of Eurostat or OECD.
data_directory

Defaults to NULL, if a valid directory, it will try to save the pre-processed data file here with labelling.
force_download

Defaults to TRUE. If FALSE it will use the existing downloaded file in the data_directory or the temporary directory, if it exists. Will force download only in a new session.

Details

Unless you want to work with bulk data files, you should not invoke iotables_download directly, rather via this function, if and when it is necessary.

Value

A wide format data.frame with a well-ordered input-output table. The bulk data files on the Eurostat website are in a long form and they are not correctly ordered for further matrix equations.

Examples

germany_table <- iotable_get( source = "germany_1995", 
                 geo = 'DE', year = 1990, unit = "MIO_EUR", 
                 labelling  = "iotables" )

Get the available years from bulk downloaded input-output tables

Description

The function selects the available tables by year or time as a date for a specific country and currency unit in the Eurostat bulk file.

Usage

iotable_year_get(
  labelled_io_data = NULL,
  source = "germany_1995",
  geo = "DE",
  unit = "MIO_EUR",
  time_unit = "year",
  stk_flow = "TOTAL",
  data_directory = NULL,
  force_download = TRUE
)

Arguments

labelled_io_data

If you have downloaded a bulk data file with iotables_download, it is faster to work with the data in the memory. Defaults to NULL when the data will be retrieved from the hard disk or from the Eurostat website invoking the same function.
source

A data source, for example naio_10_cp1700. Symmetric input-output table at basic prices (product by product) (naio_10_cp1700) Symmetric input-output table at basic prices (industry by industry) (naio_10_cp1750) Symmetric input-output table at basic prices (product by product) (previous years prices) (naio_10_pyp1700) Symmetric input-output table at basic prices (industry by industry) (previous years prices) (naio_10_pyp1750) Table of trade and transport margins at basic prices (naio_10_cp1620) and at previous' years prices (naio_10_pyp1620) Table of taxes less subsidies on products at basic prices (naio_10_cp1630) and at previous' years prices (naio_10_pyp1630) For further information consult the Eurostat Symmetric Input-Output Tables page.
geo

A country code or a country name. For example, SK or as Slovakia.
unit

A character string containing the currency unit, defaults to MIO_NAC (million national currency unit). The alternative is MIO_EUR.
time_unit

Defaults to 'year' and years are returned as numbers. Alternative is to return 'time' as vector of dates.
stk_flow

Defaults to DOM as domestic output, alternative IMP for imports and TOTAL for total output. For source = 'naio_10_cp1620' and trade and transport margins and source = 'naio_10_cp1630' taxes less subsidies only TOTAL is not used.
data_directory

Defaults to NULL. Use if it you used a data_directory parameter with iotable_get or iotables_download.
force_download

Defaults to TRUE. If FALSE it will use the existing downloaded file in the data_directory or the temporary directory, if it exists. Will force download only in a new session.

Details

Unless you want to work with bulk data files, you should not invoke iotables_download directly, rather via this function, if and when it is necessary.

Value

A vector with the years that have available input-output tables.

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

germany_years <- iotable_year_get ( source = "germany_1995", geo = 'DE', 
                                    unit = "MIO_EUR" )

Download input-output tables

Description

This function downloads standard input-output table files. Currently only Eurostat files are supported. You are not likely to use this function, because iotable_get will call this function if necessary and properly filter out an input-output table.

Usage

iotables_download(
  source = "naio_10_cp1700",
  data_directory = NULL,
  force_download = FALSE
)

Arguments

source

See the available list of sources above in the Description.
data_directory

Defaults to NULL when the files will be temporarily stored in the path retrieved by tempdir. If it is a different valid directory, it will try to save the pre-processed data file here with labelling.
force_download

Defaults to FALSE which will use the existing downloaded file in the data_directory or the temporary directory, if it exists. TRUE will try to download the file from the Eurostat warehouse.

Details

The data is downloaded in the tempdir()under the name the statistical product as an rds file. (For example: naio_10_cp1750.rds) The temporary directory is emptied at every normal R session exit.

To save the file for further use (which is necessary in analytical work because download times are long) set the download_directory [see parameters]. The function will make a copy of the rds file in this directory.

naio_10_cp1700

Symmetric input-output table at basic prices (product by product)

naio_10_pyp1700

Symmetric input-output table at basic prices (product by product) (previous years prices)

naio_10_cp1750

Symmetric input-output table at basic prices (industry by industry)

naio_10_pyp1750

Symmetric input-output table at basic prices (industry by industry) (previous years prices)

naio_10_cp15

Supply table at basic prices incl. transformation into purchasers' prices

naio_10_cp16

Use table at purchasers' prices

naio_10_cp1610

Use table at basic prices

naio_10_pyp1610

Use table at basic prices (previous years prices) (naio_10_pyp1610)

naio_10_cp1620

Table of trade and transport margins at basic prices

naio_10_pyp1620

Table of trade and transport margins at previous years' prices

naio_10_cp1630

Table of taxes less subsidies on products at basic prices

naio_10_pyp1630

Table of taxes less subsidies on products at previous years' prices

uk_2010_siot

United Kingdom Input-Output Analytical Tables data

Value

A nested data frame. Each input-output table is in a separate row of the nested output, where all the metadata are in columns, and the actual, tidy, ordered input-output table is in the data data column. The data is saved into the actual tempdir(), too.

See Also

Other import functions: airpol_get(), employment_get(), iotables_metadata_get(), iotables_read_tempdir()

Examples

io_tables <- iotables_download(source = "naio_10_pyp1750")

Get Metadata from Nested iotables File

Description

Remove the data column and return only the metadata information of input-output (or related tables) from a source. If dat is not inputed as a nested data frame created by iotables_download, validate the source input parameter and try to load the table from the current sessions' temporary directory.

naio_10_cp1700

Symmetric input-output table at basic prices (product by product)

naio_10_pyp1700

Symmetric input-output table at basic prices (product by product) (previous years prices)

naio_10_cp1750

Symmetric input-output table at basic prices (industry by industry)

naio_10_pyp1750

Symmetric input-output table at basic prices (industry by industry) (previous years prices)

naio_10_cp15

Supply table at basic prices incl. transformation into purchasers' prices

naio_10_cp16

Use table at purchasers' prices

naio_10_cp1610

Use table at basic prices

naio_10_pyp1610

Use table at basic prices (previous years prices) (naio_10_pyp1610)

naio_10_cp1620

Table of trade and transport margins at basic prices

naio_10_pyp1620

Table of trade and transport margins at previous years' prices

naio_10_cp1630

Table of taxes less subsidies on products at basic prices

naio_10_pyp1630

Table of taxes less subsidies on products at previous years' prices

uk_2010_siot

United Kingdom Input-Output Analytical Tables data

Usage

iotables_metadata_get(dat = NULL, source = "naio_10_cp1700")

Arguments

dat

A nested data file created by iotables_download. Defaults to NULL in which case an attempt is made to find and read in the nested data from the current R sessions' temporary directory.
source

See the available list of sources above in the Description.

Value

A data frame, which contains the metadata of all available input-output tables from a specific source.

See Also

Other import functions: airpol_get(), employment_get(), iotables_download(), iotables_read_tempdir()

Examples

# The table must be present in the sessions' temporary directory:
iotables_download(source = "naio_10_pyp1750")

# Now you can get the metadata:
iotables_metadata_get(source = "naio_10_pyp1750")

Read input-output tables from temporary directory

Description

Validate the source input parameter and try to load the table from the current sessions' temporary directory.

Usage

iotables_read_tempdir(source = "naio_10_cp1700")

Arguments

source

See the available list of sources above in the Description. Defaults to source = "naio_10_cp1700".

Details

Possible source parameters:

naio_10_cp1700

Symmetric input-output table at basic prices (product by product)

naio_10_pyp1700

Symmetric input-output table at basic prices (product by product) (previous years prices)

naio_10_cp1750

Symmetric input-output table at basic prices (industry by industry)

naio_10_pyp1750

Symmetric input-output table at basic prices (industry by industry) (previous years prices)

naio_10_cp15

Supply table at basic prices incl. transformation into purchasers' prices

naio_10_cp16

Use table at purchasers' prices

naio_10_cp1610

Use table at basic prices

naio_10_pyp1610

Use table at basic prices (previous years prices) (naio_10_pyp1610)

naio_10_cp1620

Table of trade and transport margins at basic prices

naio_10_pyp1620

Table of trade and transport margins at previous years' prices

naio_10_cp1630

Table of taxes less subsidies on products at basic prices

naio_10_pyp1630

Table of taxes less subsidies on products at previous years' prices

uk_2010_siot

United Kingdom Input-Output Analytical Tables data

Value

A nested data frame. Each input-output table is in a separate row of the nested output, where all the metadata are in columns, and the actual, tidy, ordered input-output table is in the data data column.

See Also

Other import functions: airpol_get(), employment_get(), iotables_download(), iotables_metadata_get()

Examples

# The table must be present in the sessions' temporary directory:
iotables_download(source = "naio_10_pyp1750")

iotables_read_tempdir (source = "naio_10_pyp1750")

Check if HTML output is required

Description

Check if HTML output is required

Check if Latex output is required

Description

Check if Latex output is required

Create a key columnn

Description

Create a key column for matching the dimensions of matrixes.

Usage

key_column_create(key_column_name, key_column_values = NULL)

Arguments

key_column_name

The name of the key column.
key_column_values

The value(s) of the key column

Details

This function will likely be used with the creation of coefficients that need to be matched with a matrix that has a key column.

Value

A tibble with one column, named key_column_name and with values key_column_values.

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), matrix_round(), output_get(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

key_column_create ("iotables_row", c("CO2_multiplier", "CH4_multiplier"))

Create the inverse of a Leontief-matrix

Description

Create the Leontief inverse from the technology coefficient matrix.

Usage

leontief_inverse_create(technology_coefficients_matrix, digits = NULL)

leontieff_inverse_create(technology_coefficients_matrix, digits = NULL)

Arguments

technology_coefficients_matrix

A technology coefficient matrix created by the input_coefficient_matrix_create.
digits

An integer showing the precision of the technology matrix in digits. Default is NULL when no rounding is applied.

Details

The Leontief-inverse is

L=(I−A)−1L = (I-A)^-1

where B is the input coefficient matrix created by input_coefficient_matrix_create. For the similar inverse created from output coefficients, see the ghosh_inverse_create function.

See Also

Other analytic object functions: ghosh_inverse_create(), input_flow_get(), leontief_matrix_create()

Examples

tm <- input_flow_get ( 
  data_table = iotable_get(), 
  households = FALSE)
I <- leontief_inverse_create( technology_coefficients_matrix = tm )

Create a Leontief matrix

Description

Create a Leontief matrix from technology matrix after some basic error handling. Most likely you will need this function as a step to invoke the function to create its inverse: leontief_inverse_create.

Usage

leontief_matrix_create(technology_coefficients_matrix)

leontieff_matrix_create(technology_coefficients_matrix)

Arguments

technology_coefficients_matrix

A technology coefficient matrix created by the input_coefficient_matrix_create or output_coefficient_matrix_create.

Value

A Leontief matrix of data.frame class. The column names are ordered, and the row names are in the first, auxiliary metadata column.

See Also

Other analytic object functions: ghosh_inverse_create(), input_flow_get(), leontief_inverse_create()

Examples

tm <- input_flow_get ( 
  data_table = iotable_get(), 
  households = FALSE)
L <- leontief_matrix_create( technology_coefficients_matrix = tm )

Round all matrix values to required number of digits.

Description

For comparison with results created with other software or published with rounding, systematically round the values of an input-output table, a use, supply, tax or margins table.

Usage

matrix_round(data_table, digits = 0)

Arguments

data_table

A symmetric input output table, a use, supply, tax or margins table.
digits

An integer number, defaults to 0.

Value

The matrix, with the intact key column and the numeric columns rounded.

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), output_get(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Metadata

Description

An arrangement of the Eurostat national accounts vocabulary, used to correctly order wide format rows and columns from bulk long-form tables.

Usage

data(metadata)

Format

A data frame with 8 variables.

variable

Eurostat vocabulary source, i.e. t_rows, t_cols, prod_na, induse

group

Informal labelling for macroeconomic groups

code

Eurostat labels

label

Eurostat label descriptions

quadrant

Where to place the data from a long-form raw data file

account_group

Different from Eurostat tables, in thousand national currency units.

numeric_label

ordering from quadrant, account_group, digit_1, digit_2

iotables_label

Custom, machine_readable snake format variable names

See Also

Other Metadata datasets: employment_metadata, metadata_uk_2010

Multipliers and effects (product) for testing from the United Kingdom Input-Output Analytical Tables, 2010

Description

The Excel-imported UK data.

Usage

data(uk_2010_data)

Format

A data frame with 10 variables.

variable

Constant for the iotable_get function.

uk_row

The UK row identifier. Dots and '&' converted to '-'.

uk_col

The UK row identifier. Dots and '&' converted to '-'.

uk_row_label

The original UK row labels.

uk_col_label

The original UK column labels.

eu_prod_na

The Eurostat vocabulary equivalent of uk_row

row_order

Ordering variable for rows.

col_order

Ordering variable for columns.

prod_na

The Eurostat-like key values for rows.

induse

The Eurostat-like column names

See Also

Other Metadata datasets: employment_metadata, metadata

Create multipliers

Description

This function is in fact a wrapper around the equation_solve function, adding a key column with the name to the multiplier the maintain structural consistency.

Usage

multiplier_create(
  input_vector,
  Im,
  multiplier_name = "multiplier",
  digits = NULL
)

Arguments

input_vector

An input matrix or vector created by the input_indicator_create function.
Im

The Leontief inverse as a named object created by the leontief_inverse_create function.
multiplier_name

A variable name to be given to the returned multipliers. Defaults to multiplier.
digits

Rounding digits, if omitted, no rounding takes place.

Details

As opposed to direct effects, multipliers are expressed per input of product/industry.

Value

A data frame with the vector of multipliers and the an auxiliary metadata column (for joining with other matrixes.)

See Also

Other multiplier functions: input_multipliers_create()

Examples

data_table <- iotable_get()

coeff_de <- input_coefficient_matrix_create( data_table )

de_gva_indicator <- input_indicator_create (
  data_table = data_table, 
  input = 'gva')  #this is a correct input

I_de <- leontief_inverse_create( coeff_de )

de_gva_multipliers <- multiplier_create ( 
  input_vector    = de_gva_indicator,
  Im              = I_de,
  multiplier_name = "employment_multiplier", 
  digits = 4 )

Simple input-output table for the Netherlands, 2006.

Description

This simplified SIOT is taken from the Science Policy Integration for Coastal Systems Assessment project's input-output multiplier specification sheet. It is used as a simple example SIOT for controlled analytical results. The column names were slightly altered to resemble more the current Eurostat conventions and the main example dataset germany_1995.

Usage

data(netherlands_2006)

Format

A data frame with 14 observations and 13 variables.

A data frame of 13 observations in 14 variables.

prod_na

Product name, simplified, following the Eurostat conventions

agriculture_group

Simple aggregated agricultural products

mining_group

Simple aggregated mining products

manufacturing_group

Simple aggregated manufacturing products

construction_group

Construction

utilities_group

Simple aggregated utilities products/services

services_group

Simple aggregated services products

TOTAL

Column / row sums, simple summary, not included in the original source

final_consumption_private

Simple aggregated final private use

final_consumption_households

Simple aggregated final household consumption

final_consumption_government

Simple aggregated final government consumption

gross_fixed_capital_formation

Gross fixed capital formation 'GFCF'

exports

Simple aggregated exports

total_use

Simple aggregated total use

Source

Source: Input-Output Multipliers Specification Sheet and Supporting Material in the Spicosa Project Report

See Also

Other Validation datasets: germany_1995, germany_airpol, uk_2010_data, uk_test_results

Create an output coefficient matrix

Description

Create an output coefficient matrix from the input flow matrix or a symmetric input-output table.

Usage

output_coefficient_matrix_create(data_table, total = "tfu", digits = NULL)

Arguments

data_table

A symmetric input-output table, a use table, a margins or tax table retrieved by the iotable_get. In case you use type="tfu" you need to input a full iotable, create by the iotable_get, because the final demand column is in the second quadrant of the IOT.
total

The output='total' (or CPA_TOTAL, depending on the names in your table, default) returns the output coefficients for products (intermediates) while the final_demand returns output coefficients for final demand. See Eurostat Manual of Supply, Use and Input-Output Tables p495 and p507.
digits

An integer showing the precision of the technology matrix in digits. Default is NULL when no rounding is applied.

Details

The output coefficients may be interpreted as the market shares of products in total output. If there are zero values in present, they will be changed to 0.000001 and you will get a warning. Some analytical equations cannot be solved with zero elements. You either have faulty input data, or you have to use some sort of data modification to carry on your analysis.

Value

An output coefficient matrix of data.frame class. The column names are ordered, and the row names are in the first, auxiliary metadata column.

Examples

data_table <- iotable_get() 

output_coefficient_matrix_create (data_table = data_table, 
                                  total = 'tfu',
                                  digits = 4)

Get an output vector

Description

This is a wrapper function around the primary_input_get function.

Usage

output_get(data_table)

Arguments

data_table

A symmetric input-output table or use table retrieved by the iotable_get function.

Value

A data frame with the vector of multipliers and the an auxiliary metadata column (for joining with other matrixes.)

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

output_get ( data_table = iotable_get () )

Create output multipliers

Description

Create a data frame of output multipliers.

Usage

output_multiplier_create(input_coefficient_matrix)

Arguments

input_coefficient_matrix

A Leontief inverse matrix created by the input_coefficient_matrix_create function.

Details

Output multipliers as defined by the Eurostat Manual of Supply, Use and Input-Output Tables on p500.

Value

A data frame with a key column and the output multipliers of the industries.

Examples

de_input_coeff <- input_coefficient_matrix_create( 
                          iotable_get(), 
                          digits = 4)
                           
output_multiplier_create (de_input_coeff)

Get primary inputs

Description

This function will retrieve any primary input from the input-output table.

Usage

primary_input_get(data_table, primary_input = "compensation_employees")

Arguments

data_table

A symmetric input-output table, a use table, or a supply table retrieved by the iotable_get function.
primary_input

The primary input to be returned from the table.

Value

A data frame with the vector of multipliers and the an auxiliary metadata column (for joining with other matrixes.)

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

comp_employees_de <- primary_input_get(
  data_table = iotable_get(), 
  primary_input = "compensation_employees")

Primary input abbreviations

Description

Only currently used primary inputs. Abbreviations for filtering.

Usage

data("croatia_employment_aggregation")

Format

A data frame with 105 rows (including empty ones) and 2 variables.

t_rows2

Eurostat code of the input.

t_rows2_lab

Labelling of the input by Eurostat.

source

Eurostat / DZS

indicator

Human readable abbreviation

See Also

Other Croatia 2010 datasets: croatia_2010_1700, croatia_2010_1800, croatia_2010_1900, croatia_employment_2013, croatia_employment_aggregation

Add conforming row(s)

Description

Add a conforming row, or elements of a conforming row to a names matrix.

Usage

rows_add(data_table, rows_to_add, row_names = NULL, empty_fill = 0)

Arguments

data_table

A symmetric input-output table, a use table, a margins or tax table retrieved by the iotable_get function.
rows_to_add

A data frame or a named numeric vector.
row_names

An optional name or vector of names for the key column. Defaults to NULL.
empty_fill

What should happen with missing column values? Defaults to 0. If you want to avoid division by zero, you may consider a very small value such as 0.000001.

Details

If you want to add a single row manually, you can input a named numeric vector or a data frame with a single row. For multiple rows, input them as wide form data frame (see examples.)

Value

An extended data_table with the new row(s) binded.

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), supplementary_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

rows_to_add <- data.frame(iotables_row      = "CO2_emission", 
                          agriculture_group =  10448, 
                          industry_group    =  558327, # -> construction is omitted
                          trade_group       =  11194)

rows_add (iotable_get(), rows_to_add = rows_to_add)

rows_add (iotable_get(), 
          rows_to_add = c(industry_group    =  1534, 
                          trade_group       =  4),
          row_names    = "CH4_emission" )

Add supplementary data

Description

Add supplementary data to a SIOT, a use, supply or margins table.

Usage

supplementary_add(data_table, supplementary_data, supplementary_names = NULL)

Arguments

data_table

A SIOT, a use table, a supply table, or a margins table.
supplementary_data

Supplementary data to be added. It must be a data.frame or tibble with a key column containing the indicator's name, and the column names must match with the data_table. Can be a vector or a data frame of several rows.
supplementary_names

Optional names for the new supplementary rows. Defaults to NULL.

Details

This function is a wrapper around the more general rows_add function.

Value

An extended data_table with the new row(s) binded.

A symmetric input-output table with supplementary data, of data.frame class. The column names are ordered, and the row names are in the first, auxiliary metadata column.

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), rows_add(), total_tax_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

de_io <- iotable_get()
CO2_coefficients <- data.frame(agriculture_group = 0.2379,
                               industry_group    = 0.5172, 
                               construction = 0.0456,
                               trade_group = 0.1320, 
                               business_services_group = 0.0127,
                               other_services_group = 0.0530)
CH4_coefficients <- data.frame(agriculture_group = 0.0349,
                               industry_group    = 0.0011, 
                               construction = 0,
                               trade_group = 0, 
                               business_services_group = 0,
                               other_services_group = 0.0021)
CO2 <- cbind (data.frame(iotables_row = "CO2"), 
              CO2_coefficients)
CH4 <- cbind(data.frame (iotables_row = "CH4_coefficients"),
             CH4_coefficients)
de_coeff <- input_coefficient_matrix_create ( iotable_get() )
emissions <- rbind (CO2, CH4)

# Check with the Eurostat Manual page 494:
supplementary_add(de_io, emissions)

Summarize and add tax data

Description

Create and add a total tax row, if there are multiple tax rows present in the data_table.

Usage

total_tax_add(
  data_table,
  tax_names = c("d21x31", "d29x39"),
  total_tax_name = "TOTAL_TAX"
)

Arguments

data_table

A SIOT, a use table, a supply table, or a margins table that has product and production tax rows in among the primary inputs.
tax_names

Defaults to ("d21x31", "d29x39"), which are the Eurostat names for taxes. The parameter is not case sensitive.
total_tax_name

Defaults to 'TOTAL_TAX'. The name of the summarized row. It is case sensitive.

Value

A data frame with the vector of multipliers and the an auxiliary metadata column (for joining with other matrixes.)

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), rows_add(), supplementary_add(), vector_transpose_longer(), vector_transpose_wider()

Examples

de_io <- iotable_get()

total_tax_add (de_io, 
               tax_names = c("net_tax_products",  "net_tax_production"),
               total_tax_name = "total_tax")

United Kingdom Input-Output Analytical Tables, 2010

Description

Replication data exported from the Office of National Statistics.

Usage

data(uk_2010_data)

Format

A data frame with 10 variables.

uk_row

The UK row identifier. Dots and '&' converted to '-'.

uk_row_lab

The original UK row labels.

uk_col

The UK row identifier. Dots and '&' converted to '-'.

uk_col_lab

The original UK column labels.

geo

Eurostat-style geocode, i.e. UK

geo_lab

United Kingdom

indicator

The name of the indicator, i.e. Excel sheet.

unit

Eurostat label equivalents units, i.e. MIO_NAC.

unit_lab

Eurostat label equivalents, i.e. millions of national currency unit.

values

The numeric values of the variable

year

Constant = 2010.

Details

You can retrieve the data with iotable_get, setting the source parameter as follows:

uk_2010_siot

Input-Output table (domestic use, basic prices, product by product)

uk_2010_use

Domestic use table at basic prices (product by industry)

uk_2010_imports

Imports use table at basic prices (product by product)

uk_2010_coeff

Matrix of coefficients (product by product)

uk_2010_inverse

Leontief Inverse (product by product)

Source

United Kingdom Input-Output Analytical Tables 2010

See Also

Other Validation datasets: germany_1995, germany_airpol, netherlands_2006, uk_test_results

Get United Kingdom Multipliers and Effects, 2010

Description

This function will retrieve the published effects and multipliers from the United Kingdom Input-Output Analytical Tables, 2010 (consistent with UK National Accounts Blue Book 2013 & UK Balance of Payments Pink Book 2013) by Richard Wild.

Usage

uk_2010_results_get(path = NULL)

Arguments

path

A path to the downloaded file, if already exists, given with file.path() function.

Source

ukioanalyticaltablesio1062010detailedpubversion.xls

Examples

## Not run: 
uk_results <- iotables:::uk_2010_results_get ()

## End(Not run)

Multipliers and effects (product) for testing from the United Kingdom Input-Output Analytical Tables, 2010

Description

The Excel-imported UK data.

Usage

data(uk_test_results)

Format

A data frame with 12 variables.

uk_row_label

The UK row label

Output multiplier

The imported Output multipliers

output_multiplier_rank

The imported ranking of output multipliers

Employment cost multiplier

The imported Employment cost multipliers.

employment_cost_multiplier

The imported ranking of Employment cost multipliers.

Employment cost effects

The imported Employment cost multipliers.

employment_cost_effects_rank

The imported ranking of employment cost multipliers.

GVA effects

The imported GVA effects.

gva_effects_rank

The imported ranking GVA effects.

gva_multiplier_rank

The imported ranking GVA multipliers.

GVA multiplier

The imported GVA multipliers.

indicator

Indicator names.

See Also

Other Validation datasets: germany_1995, germany_airpol, netherlands_2006, uk_2010_data

Transpose a vector to a long form

Description

Many vectors (indicators, multipliers) are create in the wide form to conform matrixes in analytical functions. For printing it is more useful to have them in long form.

Usage

vector_transpose_longer(
  data_table,
  names_to = "nace_r2",
  values_to = "value",
  key_column_name = NULL,
  .keep = FALSE
)

vector_transpose(
  data_table,
  names_to = "nace_r2",
  values_to = "value",
  key_column_name = NULL,
  .keep = FALSE
)

Arguments

data_table

A matrix or vector that normally has a key column.
names_to

Defaults to 'nace_r2'.
values_to

Defaults to 'value'.
key_column_name

The name of the first column. Defaults to NULL when it is not changed. It should usually match the key column of the matrix or vector you would like to join the new vector created with vector_transpose_longer.
.keep

Keep the indicator identifier column? Defaults to FALSE.

Details

This is a wrapper around pivot_longer so you do not necessarily need to import or load the entire tidyr package.

Value

A long form vector with a key column, and optionally the identifier of the indicator in the first column.

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_wider()

Examples

vector_transpose_longer(
  data.frame(indicator = "my_inidcator", 
             agriculture = 0.0123,
             manufacturing = 0.1436,
             trade = 0.0921)
)

Transpose a vector to wider format

Description

Many vectors (indicators, multipliers) are create in the wide form to conform matrixes in analytical functions. For binding it is more useful to have them in wide format.

Usage

vector_transpose_wider(
  data_table,
  names_from,
  values_from,
  key_column_name = NULL,
  key_column_values = NULL
)

Arguments

data_table

A matrix or vector that normally has a key column. If the key column must be created or replaced, used key_column_name and key_column_values.
names_from, values_from

A pair of arguments describing which column (or columns) to get the name of the output column ('names_from'), and which column (or columns) to get the cell values from ('values_from').
key_column_name

The name of the key column.
key_column_values

You can explicitly supply key column values. Defaults to NULL when the key column values will be created from the long data.

Details

This is a wrapper around pivot_wider so you do not necessarily need to import or load the entire tidyr package.

See Also

Other iotables processing functions: conforming_vector_create(), household_column_get(), iotable_year_get(), key_column_create(), matrix_round(), output_get(), primary_input_get(), rows_add(), supplementary_add(), total_tax_add(), vector_transpose_longer()

Examples

vector_transpose_wider (data_table =  germany_airpol[, -2],
                        names_from = 'induse',
                        values_from = 'value')
                        
vector_transpose_wider (data_table =  germany_airpol[1:8, 3:4],
                        names_from = 'induse',
                        values_from = 'value', 
                        key_column_values = "CO2_emission" )