This article shows that highly correlated measures can produce different results. We identify a democratization model from the literature and test it in over 120 countries from 1951-1992. Then, we check whether the results are robust regarding measures of democracy, time periods, and levels of development. The findings show that measures do matter: while some of the findings are robust, most of them are not. This explains, in part, why the debates on democracy have continued rather than been resolved. More importantly, it underscores the need for more careful use of measures and further testing to increase confidence in the findings. Scholars in comparative politics increasingly are drawn to large-N statistical analyses, often using datasets collected by others. As in any field, we show how they must be careful in choosing the most appropriate measures for their study, without assuming that any correlated measure will do.

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This paper considers the case of the international migrants’ confidence in political institutions, from a social embeddedness perspective on political trust. We use country-level aggregates of confidence in institutions as indicators of specific cultures of trust, and by employing data from the European Values Study, we test two competing hypotheses. First, as confidence in institutions depends on the values formed during early childhood, the international migrant’s confidence in political institutions in the current country of residency will be influenced by the confidence context from the country of origin. Second, the host country may have different norms of trust in political institutions, and a process of re-socialization may occur. Therefore, the immigrants’ confidence in institutions is influenced by two confidence contexts: one from the origin country and one from the host country. The time spent in the two cultures, along with other characteristics from these contexts, shape the interaction effects we tested in multilevel cross-classified models.

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The Global State of Democracy Indices: Technical Procedures Guide, Version 2 is the second in a series of documents prepared by International IDEA to present the Global State of Democracy (GSoD) Indices. It outlines the technical aspects of constructing the Indices, and complements The Global State of Democracy Indices Methodology: Conceptualization and Measurement Framework, Version 2 (Skaaning 2018), which presents the theoretical framework that guided the construction of the Indices, and The Global State of Democracy Indices Codebook, Version 2 (Tufis 2018), which presents information about the data set, including variables, attributes of democracy, subattributes, subcomponents and indicators. The GSoD Indices depict democratic trends at the country, regional and global levels across a broad range of different attributes of democracy in the period 1975-2017 but do not provide a single index of democracy. The Indices produce data for 158 countries. The data underlying the Indices is based on 97 indicators developed by various scholars and organizations using different types of sources, including expert surveys, standards-based coding by research groups and analysts, observational data and composite measures. The Global State of Democracy is a biennial report that aims to provide policymakers with an evidence-based analysis of the state of global democracy, supported by the GSoD Indices, in order to inform policy interventions and identify problem-solving approaches to trends affecting the quality of democracy around the world. The first edition of the report (International IDEA 2017), explored the conditions under which democracy can be resilient and how to strengthen its capacity as a system to overcome challenges and threats. The full publication, as well as the GSoD Indices Database, can be accessed online: . 4. Assessing the unidimensionality of the Indices (see Chapter 4); 5. Aggregating the indicators into Indices (see Chapter 5); 6. Scaling the Indices (see Chapter 6); 7. Computing the confidence intervals (see Chapter 7); and 8. Conducting validity checks (see Chapter 8). After a brief description of the theoretical structure that guided this project, the Guide presents the data sources, the coverage of the data set, the indicators used to construct the main attributes of democracy, the procedures used to compute these attributes and the structure of the complete data set.

Version 3 of the GSoD Indices depicts democratic trends at the country, regional and global levels across a broad range of different attributes of democracy in the period 1975-2018 but does not provide a single index of democracy. The Indices produce data for 158 countries. The data underlying the Indices is based on a total of 97 indicators developed by various scholars and organizations using different types of source, including expert surveys, standards-based coding by research groups and analysts, observational data and composite measures.The Global State of Democracy is a biennial report that aims to provide policymakers with an evidence-based analysis of the state of global democracy, supported by the GSoD Indices, in order to inform policy interventions and identify problem-solving approaches to trends affecting the quality of democracy around the world. The first edition of the report (International IDEA 2017), explored the conditions under which democracy can be resilient and how to strengthen its capacity as a system to overcome challenges and threats. Original variable Constructed variable GSoD name ID_country_yearDefinition This is an identification variable, which uniquely identifies each combination of country and year (the country-year) in the data set. It has been constructed by concatenating the Correlates of War country code (COWcode) and the year, so that the last four digits of the variable always indicate the year, while the remaining one to three digits preceding the year represent the COWcode. ID Country Name (ID_country_name) Original variable Constructed variable GSoD name ID_country_nameDefinition This is an identification variable, which uniquely identifies each of the 158 countries in the data set. The values this variable takes are the names of the countries included in the data set. Countries

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