While there is an abundant use of macro data in the social sciences, little attention is given to the sources or the construction of these data. Owing to the restricted amount of indices or items, researchers most often apply the ‘available data at hand’. Since the opportunities to analyse data are constantly increasing and the availability of macro indicators is improving as well, one may be enticed to incorporate even qualitatively inferior indicators for the sake of statistically significant results. The pitfalls of applying biased indicators or using instruments with unknown methodological characteristics are biased estimates, false statistical inferences and, as one potential consequence, the derivation of misleading policy recommendations. This Special Issue assembles contributions that attempt to stimulate the missing debate about the criteria of assessing aggregate data and their measurement properties for comparative analyses.

Scholars often study isolated media effects using one method at one time point in one country. We seek to generalise the research in this area by examining hundreds of press-worthy events across dozens of countries at various points in time with an array of techniques and outcome measures. In particular, we merge a database containing thousands of events with five waves of the European Social Survey to conduct analyses across countries and individuals as well as within countries and for specific respondents. The results suggest that there is an impressive degree of heterogeneity when it comes to how citizens react to political developments. Some events generate significant opinion changes when groups of individuals who are ‘treated’ are compared with ‘control’ cases. However, other events produce modest or even null findings with methods that employ different counterfactuals. Thus, findings of both strong and weak media effects that scholars have uncovered over the years could be a function of methodological choices as well as context-specific factors such as institutional arrangements, media systems, eras, or event characteristics. Data limitations also make some research designs possible while they preclude others. We conclude with advice for others who wish to study political events in this manner as well as discussion of media effects, broadly construed.

There is a long tradition in comparative research on industrial relations of analysis concentrating on differences and similarities between countries, that is, focusing on aggregates measured at the national level. But what happens if there are no (more) differences in industrial relations systems between countries? If there are not differences the question arises if comparative research is becoming meaningless? Concentrating predominantly on statistical and methodological aspects, it is argued in this article that over recent decades industrial relations systems have changed in such a way that the national level has become less relevant as a unit of analysis. It is explained that this development in the nature of the field affects the measurement of its indicators which form the backbone of any comparison. On the basis of an empirical comparison of key industrial relations indicators in the European Union member states, it is concluded that comparative research has not reached a dead end, but rather that the field might have to reconsider the relevant unit for analysis. It is shown that the relevant unit for analysis has shifted increasingly from the national towards the sectoral level. One consequence of this shift is that from a methodological perspective comparisons between sectors, rather than between countries, are nowadays often more informative.

Co-optation is one of the most important concepts that have been discussed in recent years to explain the persistence of autocratic regimes. Institutions like parties, legislatures, and elections have all been shown to fulfil a co-optation function. However, a broader assessment of co-optation beyond an institutional focus has yet to be undertaken. This article addresses this lacuna and presents a comprehensive concept and operationalisation of co-optation in autocratic regimes. The article argues that co-optation is constituted by the compensation of the regime’s vulnerability to threats posed by powerful societal pressure groups. The article highlights how compensation of vulnerability can be achieved through institutional inclusion or material benefits, and how this has to be tailored to the respective pressure group’s requirements. I collect twenty-six indicators of vulnerability and compensation related to six societal pressure groups and aggregate them into an index of co-optation that reflects the structure of the theoretical concept. The index is evaluated by examining distributions within and across categories of autocratic legislatures, and by testing its effect on autocratic regime breakdown in a set of Cox survival models.

What is state repression? This article explores in detail how state repression is conceptualized by the two most prevalent data sets employed by qualitative scholars: the Political Terror Scale (PTS) and the Cingranelli-Richards (CIRI) data set. The article uses disaggregated data on the characteristics of state’s repressive strategy and compare changes in these subcomponents in years when the overall measure of repression increases or decreases. Following bivariate and multivariate analyses of eighteen West African countries with a history of fluctuating human rights practices, the article finds that both the PTS and CIRI scores are primarily influenced by military involvement in human rights violations. The article highlights the need for more scholarship on the mechanisms behind the finding that democracies are less repressive than other regimes and motivates more studies on how and when repression decreases.

Empirical human rights researchers frequently rely on indexes of physical integrity rights created by the Cingranelli-Richards (CIRI) or the Political Terror Scale (PTS) data projects. Any systematic bias contained within a component used to create CIRI and PTS carries over to the final index. We investigate potential bias in these indexes by comparing differences between PTS scores constructed from different sources, the United States State Department (SD) and Amnesty International (AI). In order to establish best practices, we offer two solutions for addressing bias. First, we recommend excluding data before 1980. The data prior to 1980 are truncated because the SD only created reports for current and potential foreign aid recipients. Including these data with the more systematically included post-1980 data is a key source of bias. Our second solution employs a two-stage instrumented variable technique to estimate and then correct for SD bias. We demonstrate how following these best practices can affect results and inferences drawn from quantitative work by replicating a study of interstate conflict and repression.

Over recent decades, comparative political scientists have developed new measures at a rate of knots that evaluate the quality of democratic regimes. These indices have been broadly applied to assess the quality of democracy cross-nationally and to test the generalisability of theories regarding its causes and effects. However, the validity of these inferences is jeopardised by the fact that the quality of democracy is an abstract and contested concept. In order to address this eventuality, researchers constructing indices measuring the quality of democracy as well as researchers applying these indices should critically examine the quality of the indices. Owing to the absence of a standardised framework that is both suitable for the evaluation of contested concepts and that includes explicit coding rules so as to be directly applicable, this article seeks to fill this gap. The application of our framework is demonstrated by an evaluation of the Sustainable Governance Indicators, the Global Democracy Ranking and the Democracy Barometer. As indicated by our evaluation, the framework is a practical tool that helps to assess the conceptual foundation, validity, reliability and replicability of indices. In addition, it can be used to study the quality of indices in a comparable manner.

Political scientists often need to evaluate whether samples are comparable, for example, when analysing different countries or time points or when comparing data collected using different methods. A necessary condition for conducting such meaningful cross-group comparisons is the establishment of measurement invariance. One of the most frequently used procedures for establishing measurement invariance is the multigroup confirmatory factor analysis. This method was criticised in the literature because it may suggest that a model fits the data although it may contain serious misspecifications. We present an alternative method to test for measurement invariance using detection of local misspecifications and illustrate its use on two data sets assessing value priorities that are often analysed in political science and collected using paper-and-pencil and web modes of data collection.