Manifesto Project Main Dataset (Party Preferences)

For further information regarding the dataset history please check our Release Notes (PDF) or our Release Notes (PDF) for South America.
You can download most of our old dataset versions on our list of former dataset versions.
The data set is updated biannually, in summer and winter.
By using our data you also agree to our terms of use.

Manifesto Project Dataset (version 2022a) E: 779 P: 1216 M: 4778

Lehmann, Pola / Burst, Tobias / Matthieß, Theres / Regel, Sven / Volkens, Andrea / Weßels, Bernhard / Zehnter, Lisa (2022): The Manifesto Data Collection. Manifesto Project (MRG/CMP/MARPOR). Version 2022a. Berlin: Wissenschaftszentrum Berlin für Sozialforschung (WZB). https://doi.org/10.25522/manifesto.mpds.2022a

Dataset stata14 stata12 spss csv xlsx

Documentation Codebook Coding Instructions List of Coded Documents (incl. Titles) (CSV) List of Political Parties (PDF) List of Political Parties (CSV)

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Manifesto Project Dataset: South America (version 2022a) E: 28 P: 64 M: 104

Lehmann, Pola / Burst, Tobias / Matthieß, Theres / Regel, Sven / Weßels, Bernhard / Zehnter, Lisa (2022): The Manifesto Data Collection: South America. Version 2022a. Berlin: Wissenschaftszentrum Berlin für Sozialforschung (WZB). https://doi.org/10.25522/manifesto.mpdssa.2022a

Mapping Policy Preferences II E: 180 P: 623 M: 1261

Klingemann, H.-D., Volkens, A., Bara, J., Budge, I., and McDonald, M. (2006). Mapping Policy Preferences II: Estimates for Parties, Electors, and Governments in Eastern Europe, European Union and OECD 1990-2003. Oxford: Oxford University Press.

Dataset stata12 spss csv xlsx

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Mapping Policy Preferences I E: 364 P: 288 M: 1991

Budge, I., Klingemann, H.-D., Volkens, A., Bara, J., and Tanenbaum, E. (2001). Mapping Policy Preferences. Estimates for Parties, Electors, and Governments 1945-1998. Ox- ford: Oxford University Press.

Dataset stata12 spss csv xlsx

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Hint: If you are searching for dataset files that cover only the most recent update or all updates since MPPII you can simply download the most recent full dataset and use the variable dataset_origin to filter the observations in that sense.