Introduction to gerda

Overview

The gerda package provides functions to access and work with GERDA datasets. The German Election Database (GERDA) provides a comprehensive dataset of local, state, and federal election results in Germany. The data is intended to facilitate research on electoral behavior, representation, and political responsiveness at multiple levels of government. All datasets include turnout and vote shares for all major parties. Moreover, GERDA contains geographically harmonized datasets that account for changes in municipal boundaries and mail-in voting districts.

GERDA was compiled by Vincent Heddesheimer, Florian Sichart, Andreas Wiedemann and Hanno Hilbig.

This vignette will introduce you to the main functions of the package and demonstrate how to use them.

Available Datasets

To see a list of all available GERDA datasets, you can use the gerda_data_list() function:

gerda_data_list()
#> |data_name            |description                                                                          |
#> |:--------------------|:------------------------------------------------------------------------------------|
#> |municipal_unharm     |Local elections at the municipal level (1990-2020, unharmonized).                    |
#> |municipal_harm       |Local elections at the municipal level (1990-2020, harmonized).                      |
#> |state_unharm         |State elections at the municipal level (2006-2019, unharmonized).                    |
#> |state_harm           |State elections at the municipal level (2006-2019, harmonized).                      |
#> |federal_muni_raw     |Federal elections at the municipal level (1980-2025, raw data).                      |
#> |federal_muni_unharm  |Federal elections at the municipal level (1980-2025, unharmonized).                  |
#> |federal_muni_harm_21 |Federal elections at the municipal level (1990-2025, harmonized to 2021 boundaries). |
#> |federal_muni_harm_25 |Federal elections at the municipal level (1990-2025, harmonized to 2025 boundaries). |
#> |federal_cty_unharm   |Federal elections at the county level (1953-2021, unharmonized).                     |
#> |federal_cty_harm     |Federal elections at the county level (1990-2021, harmonized).                       |
#> |ags_crosswalks       |Crosswalks for municipalities (1990-2025).                                           |
#> |cty_crosswalks       |Crosswalks for counties (1990-2025).                                                 |
#> |ags_area_pop_emp     |Crosswalk covariates (area, population, employment) for municipalities (1990-2025).  |
#> |cty_area_pop_emp     |Crosswalk covariates (area, population, employment) for counties (1990-2025).        |

This function displays a formatted table with the names and descriptions of all available datasets.

Loading Data

The main function for loading GERDA data is load_gerda_web(). This function allows you to load a specific dataset from a web source. Here’s an example of how to use it:

# Load the municipal harmonized dataset
municipal_harm_data <- load_gerda_web("municipal_harm", verbose = TRUE, file_format = "rds")

The load_gerda_web() function takes the following parameters:

file_name: The name of the dataset to load (as shown in the gerda_data_list() output)
verbose: If set to TRUE, it prints messages about the loading process (default is FALSE)
file_format: Specifies the format of the file to load, either “rds” or “csv” (default is “rds”)

Example Workflow

Here’s an example of a typical workflow using the gerda package:

List available datasets:

gerda_data_list()
#> |data_name            |description                                                                          |
#> |:--------------------|:------------------------------------------------------------------------------------|
#> |municipal_unharm     |Local elections at the municipal level (1990-2020, unharmonized).                    |
#> |municipal_harm       |Local elections at the municipal level (1990-2020, harmonized).                      |
#> |state_unharm         |State elections at the municipal level (2006-2019, unharmonized).                    |
#> |state_harm           |State elections at the municipal level (2006-2019, harmonized).                      |
#> |federal_muni_raw     |Federal elections at the municipal level (1980-2025, raw data).                      |
#> |federal_muni_unharm  |Federal elections at the municipal level (1980-2025, unharmonized).                  |
#> |federal_muni_harm_21 |Federal elections at the municipal level (1990-2025, harmonized to 2021 boundaries). |
#> |federal_muni_harm_25 |Federal elections at the municipal level (1990-2025, harmonized to 2025 boundaries). |
#> |federal_cty_unharm   |Federal elections at the county level (1953-2021, unharmonized).                     |
#> |federal_cty_harm     |Federal elections at the county level (1990-2021, harmonized).                       |
#> |ags_crosswalks       |Crosswalks for municipalities (1990-2025).                                           |
#> |cty_crosswalks       |Crosswalks for counties (1990-2025).                                                 |
#> |ags_area_pop_emp     |Crosswalk covariates (area, population, employment) for municipalities (1990-2025).  |
#> |cty_area_pop_emp     |Crosswalk covariates (area, population, employment) for counties (1990-2025).        |

Load a dataset (in this case, the federal elections at the county level, harmonized):

federal_cty_harm <- load_gerda_web("federal_cty_harm", verbose = TRUE)

Party Crosswalk Function

The party_crosswalk() function provides a mapping between GERDA party names and standardized party information from the ParlGov database. This is particularly useful for linking GERDA data with other political science datasets or for obtaining standardized party characteristics.

Usage

The function takes two main parameters:

party_gerda: A character vector of GERDA party names
destination: The name of the column from the ParlGov view_party table to map to

Available Mapping Options

You can map GERDA party names to various standardized party characteristics, including:

left_right: Left-right position scores
party_name_english: English party names
party_name_short: Short party names
country_name: Country names
And many other ParlGov variables

Example

# Map GERDA party names to left-right positions
parties <- c("cdu", "spd", "linke_pds", "fdp")
left_right_scores <- party_crosswalk(parties, "left_right")
print(left_right_scores)

# Map to English party names
english_names <- party_crosswalk(parties, "party_name_english")
print(english_names)

This function is especially useful when you want to:

Analyze parties along ideological dimensions
Merge GERDA data with other comparative datasets
Standardize party names across different data sources
Access additional party metadata from ParlGov

Conclusion

The gerda package provides easy access to a wide range of German election and related data. By using the gerda_data_list() function to explore available datasets and load_gerda_web() to load them, you can quickly incorporate this data into your research or analysis projects.

For more information or to provide feedback, please contact hhilbig@ucdavis.edu or visit the GitHub repository at https://github.com/hhilbig/gerda.