Package 'iscoCrosswalks'

Title: Crosswalks Between Classifications of Occupations
Description: Allows the user to perform approximate matching between the occupational classifications using concordances provided by the Institute for Structural Research and Faculty of Economics, University of Warsaw, <doi:10.1111/ecot.12145>. The crosswalks offer a complete step-by-step mapping of Standard Occupational Classification (2010) data to the International Standard Classification of Occupations (2008). We propose a mapping method based on the aforementioned research that converts measurements to the smallest possible unit of the target taxonomy, and then performs an aggregation/estimate to the requested degree Occupational Hierarchical level.
Authors: Alexandros Kouretsis [aut, cre], Andreas Bampouris [aut]
Maintainer: Alexandros Kouretsis <[email protected]>
License: MIT + file LICENSE
Version: 1.0.0
Built: 2025-02-01 03:11:53 UTC
Source: https://github.com/eworx-org/iscocrosswalks

Help Index

Foundation Skills

Description

Example dataset for indicator given in ISCO classification.

Usage

foundation_skills

Format

A data frame with three columns, encoded in ISCO taxonomy.

preferredLabel

ISCO official label of occupation

Occupations

Display label

Skill

Foundation skills

Value

Percentage of jobs for which foundation skills are importan

Source

https://www.cedefop.europa.eu/en/tools/skills-intelligence

Get ISCO code

Description

Adds column of ISCO code for a particular job title. Job titles should be given in the preferred label of the ISCO classification.

Usage

get_isco_code(data, lvl = 3)

Arguments

data

data.table with a column named as job
lvl

numeric value indicating the ISCO taxonomy

Value

data.table of input data with one extra column named as code

Examples

library(iscoCrosswalks)
# add mandatory column
dat <- foundation_skills[, .(job = preferredLabel, Skill, Value)]
res <- get_isco_code(dat, lvl = 1)
head(res[, .(code, Skill, Value)])

Get SOC code from label

Description

Adds SOC code for a particular job title.

Usage

get_soc_code(data, lvl = "soc_3")

Arguments

data

data.frame or data.table with two columns job and value
lvl

string that can take values from soc_1 up to soc_4

Value

data.frame of input data with one extra column named as code

ISCO occupations taxonomy

Description

A dataset containing the hierarchy of ISCO, with both code and preferred label included.

Usage

isco

Format

A data frame with two columns, encoding the ISCO taxonomy.

code

Code of ISCO occupation. Number of digits indicate the level

preferredLabel

Preferred label of the ISCO occupation

Source

https://esco.ec.europa.eu

ISCO to SOC crosswalk

Description

The 2010 Standard Occupational Classification (SOC) and the International Standard Classification of Occupations (ISCO-08) are compared. To make the crosswalk more straightforward and hence more useful, the notion of parsimony was applied. This means that while a task completed in the SOC may appear in numerous ISCOs (or vice versa), the match in some of these instances is just coincidental and adds unneeded complexity. This function allows mapping of data from the top 3 ISCO levels to the 4 SOC groups.

Usage

isco_soc_crosswalk(
  data,
  isco_lvl = 3,
  soc_lvl = "soc_2",
  brkd_cols = NULL,
  indicator = FALSE
)

Arguments

data

data.table with mandatory columns job and value
isco_lvl

numeric between 1 and 3
soc_lvl

character taking values from soc_1 to soc_4
brkd_cols

character vector with col names of stratification variables
indicator

Boolean indicating if data describe an indicator. If TRUE the mean value is computed, otherwise the sum by each breakdown group.

Value

data.table with the estimated values for the requested SOC occupational group.

References

Hardy W, Keister R, Lewandowski P (2018). “Educational upgrading, structural change and the task composition of jobs in Europe.” Economics of Transition, 26(2), 201–231.

Examples

library(iscoCrosswalks)
library(data.table)

#from ISCO level 3 group to soc_1 occupations
path <- system.file("extdata", "isco_3_brkdwn_example.csv",
                    package = "iscoCrosswalks")
dat <- fread(path)
isco_soc_crosswalk(dat,
                   isco_lvl = 3,
                   soc_lvl = "soc_1",
                   brkd_cols = "gender")

ISCO_08 to SOC_10 crosswalks

Description

A table containing the "one to many" crosswalks from ISCO version 08 to SOC10 for the 3rd hierarchical level and detailed occupations respectively.

Usage

isco08_soc10

Format

A table with the following colums.

isco08

Codes of ISCO 4th level

soc10

Codes of SOC detailed occupations

isco_label

Labels of ISCO 4th level

soc_label

Labels of SOC detailed occupations

Source

https://ibs.org.pl

SOC groups

Description

A table containing the hierarchy of SOC, with both labels and keys included.

Usage

soc_groups

Format

A table with the following columns.

soc_1

Major groups. The first two digits indicate the soc group

soc_2

Minor groups. The first 4 digits indicate the soc group

soc_3

Broad occupations. The first five digits indicate the soc group

soc_4

Detailed occupations. Digits that indicate the soc group

Source

https://ec.europa.eu/esco/portal/occupation

SOC to ISCO crosswalk

Description

The 2010 Standard Occupational Classification (SOC) and the International Standard Classification of Occupations (ISCO-08) are compared. To make the crosswalk more straightforward and hence more useful, the notion of parsimony was applied. This means that while a task completed in the SOC may appear in numerous ISCOs (or vice versa), the match in some of these instances is just coincidental and adds unneeded complexity. This function allows mapping of data from the 4 SOC groups to the 4 ISCO levels.

Usage

soc_isco_crosswalk(
  data,
  soc_lvl,
  isco_lvl,
  brkd_cols = NULL,
  indicator = FALSE
)

Arguments

data

data.table with mandatory columns job and value
soc_lvl

character taking values from soc_1 to soc_4
isco_lvl

numeric between 1 and 4
brkd_cols

character vector with col names of stratification variables
indicator

Boolean indicating if data describe an indicator. If TRUE the mean value is computed, otherwise the sum by each breakdown group.

Value

data.table with the estimated values for the requested ISCO occupational level.

References

Hardy W, Keister R, Lewandowski P (2018). “Educational upgrading, structural change and the task composition of jobs in Europe.” Economics of Transition, 26(2), 201–231.

Examples

library(iscoCrosswalks)
library(data.table)
#from soc_3 group to ISCO level 1 occupations
path <- system.file("extdata", "soc_3_brkdwn_example.csv",
                    package = "iscoCrosswalks")
dat <- fread(path)
soc_isco_crosswalk(dat,
                   soc_lvl = "soc_3",
                   isco_lvl = 1,
                   brkd_cols = "gender")

SOC_10 to ISCO_08 crosswalks

Description

A table containing the "one to many" crosswalks from SOC version 10 to ISCO version 08 for Detailed occupations and 4th hierarchical level respectively.

Usage

soc10_isco08

Format

A table with the following colums.

isco08

Codes of ISCO 4th level

soc10

Codes of SOC detailed occupations

isco_label

Labels of ISCO 4th level

soc_label

Labels of SOC detailed occupations

Source

https://ibs.org.pl