Data

New! The SDR Master Box version 1.0 is available via Dataverse.

 

The Data Harmonization project created a database that combines data from various sources. The core of this database are data from international survey projects (see here for details on survey data): 3112 national samples from 156 waves and 24 projects, covering 142 countries/territories between 1966 and 2017. The harmonized variables will include variables from five main groups:

(1) socio-demographics (age, gender, household size, marital status, education, income, labor market status/occupation, urban/metropolitan place or residence),

(2) political engagement including interest in politics, voting, and protest behavior (participation in demonstrations and signing petitions),

(3) trust in political institutions (trust in the national parliament, legal system, political parties, national government),

(4) social capital (generalized social trust and membership in organizations),

(5) well-being (self-rated health, life satisfaction, happiness).

 

These survey data are complemented with macro-level variables from non-survey sources (see here) describing the social, economic and political environment (e.g. population, GDP per capita, Freedom House Index, Gini coefficient) measured at the country-year level.

 

Additionally, we provide two types of methodological control variables:

  1. Quality-control variables on how the data were gathered, described, and recorded refer to the result of evaluating original materials: general survey documentation, specific description of data, and computer data files, respectively. We also evaluate the quality of weights to ensure the representativeness of the survey samples.
  2. Harmonization controls deal with the correspondence between source and target variables. They describe the main differences among the project-specific questionnaire items (source variables) that will be combined across surveys into a common measure (target variable), and how source variables were harmonized (e.g. number of source variables within given national survey, rescaling). These control variables may be used in assessing the inter-survey validity and reliability of the target variables.
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