badata is a data package that provides data from the German Federal Employment Agency (Bundesagentur für Arbeit – BA) about unemployed persons, employees, and jobs in Germany from 2012 to 2021 by district (Kreis) and occupational group.
Installation
You can install the development version of badata from GitHub with:
# install.packages("devtools")
devtools::install_github("RegioHub/badata")Usage
badata provides the following datasets as tibbles/data.frames:
library(badata)
employees_by_workplace
#> # A tibble: 2,131,200 × 6
#> region occupational_group year type group n
#> <chr> <chr> <int> <chr> <chr> <dbl>
#> 1 01001 111 2016 social insurance total 185
#> 2 01001 111 2016 social insurance foreigners NA
#> 3 01001 111 2016 social insurance women 62
#> 4 01001 111 2016 marginal part-time total 8
#> 5 01001 111 2016 marginal part-time foreigners NA
#> 6 01001 111 2016 marginal part-time women NA
#> 7 01001 111 2017 social insurance total 62
#> 8 01001 111 2017 social insurance foreigners 0
#> 9 01001 111 2017 social insurance women 12
#> 10 01001 111 2017 marginal part-time total 13
#> # … with 2,131,190 more rows
employees_by_residence
#> # A tibble: 2,131,200 × 6
#> region occupational_group year type group n
#> <chr> <chr> <int> <chr> <chr> <dbl>
#> 1 01001 111 2016 social insurance total 134
#> 2 01001 111 2016 social insurance foreigners 6
#> 3 01001 111 2016 social insurance women 48
#> 4 01001 111 2016 marginal part-time total 19
#> 5 01001 111 2016 marginal part-time foreigners NA
#> 6 01001 111 2016 marginal part-time women 5
#> 7 01001 111 2017 social insurance total 55
#> 8 01001 111 2017 social insurance foreigners 4
#> 9 01001 111 2017 social insurance women 12
#> 10 01001 111 2017 marginal part-time total 24
#> # … with 2,131,190 more rows
unemployed_total
#> # A tibble: 580,000 × 5
#> region occupational_group year total women
#> <chr> <chr> <int> <dbl> <dbl>
#> 1 01001 111 2012 15.2 1.08
#> 2 01001 111 2013 14.7 2
#> 3 01001 111 2014 12.5 1.58
#> 4 01001 111 2015 10.8 1.5
#> 5 01001 111 2016 12.9 1.33
#> 6 01001 111 2017 20.6 1
#> 7 01001 111 2018 19.7 2.5
#> 8 01001 111 2019 15.8 2.75
#> 9 01001 111 2020 19.7 2.17
#> 10 01001 111 2021 15.5 1.92
#> # … with 579,990 more rows
unemployed_foreigners
#> # A tibble: 580,000 × 5
#> region occupational_group year total women
#> <chr> <chr> <int> <dbl> <dbl>
#> 1 01001 111 2012 1.92 0.917
#> 2 01001 111 2013 2.58 1.17
#> 3 01001 111 2014 1.33 0
#> 4 01001 111 2015 1.92 0
#> 5 01001 111 2016 4.17 0
#> 6 01001 111 2017 10.8 0
#> 7 01001 111 2018 8.67 0
#> 8 01001 111 2019 7.5 1.08
#> 9 01001 111 2020 9.42 0.75
#> 10 01001 111 2021 6 0.667
#> # … with 579,990 more rows
jobs
#> # A tibble: 581,450 × 5
#> region occupational_group year total social_insurance
#> <chr> <chr> <int> <dbl> <dbl>
#> 1 01001 111 2012 0.0833 0.0833
#> 2 01001 111 2013 0.0833 0.0833
#> 3 01001 111 2014 0.417 0.333
#> 4 01001 111 2015 0.333 0.333
#> 5 01001 111 2016 0 0
#> 6 01001 111 2017 0.25 0.25
#> 7 01001 111 2018 0 0
#> 8 01001 111 2019 0.0833 0.0833
#> 9 01001 111 2020 0.0833 0.0833
#> 10 01001 111 2021 0.25 0.25
#> # … with 581,440 more rowsCodes and full names of regions and occupational groups can be looked up in the respective tables:
region_codes
#> # A tibble: 401 × 2
#> code name
#> <chr> <chr>
#> 1 01001 Flensburg, Stadt
#> 2 01002 Kiel, Landeshauptstadt
#> 3 01003 Lübeck, Hansestadt
#> 4 01004 Neumünster, Stadt
#> 5 01051 Dithmarschen
#> 6 01053 Herzogtum Lauenburg
#> 7 01054 Nordfriesland
#> 8 01055 Ostholstein
#> 9 01056 Pinneberg
#> 10 01057 Plön
#> # … with 391 more rows
occupational_group_codes
#> # A tibble: 145 × 2
#> code name
#> <chr> <chr>
#> 1 111 Landwirtschaft
#> 2 112 Tierwirtschaft
#> 3 113 Pferdewirtschaft
#> 4 114 Fischwirtschaft
#> 5 115 Tierpflege
#> 6 116 Weinbau
#> 7 117 Forst-,Jagdwirtschaft, Landschaftspflege
#> 8 121 Gartenbau
#> 9 122 Floristik
#> 10 211 Berg-, Tagebau und Sprengtechnik
#> # … with 135 more rowsCitation
To cite package ‘badata’ in publications use:
Nguyen HL, Tsolak D (2023). {badata}: Regional Job Market Data from the German Federal Employment Agency (Bundesagentur für Arbeit – BA). https://doi.org/10.5281/zenodo.7636114, https://github.com/RegioHub/badata
A BibTeX entry for LaTeX users is
Disclaimer
The variable names were translated from German into English, the data itself remains unchanged and is subject to the copyright of the German Federal Employment Agency (BA). © Statistik der Bundesagentur für Arbeit
This package is in no way officially related to or endorsed by BA.