Keywords: Challenges of comparative research and International Survey Projects, cross-cultural concerns in data collection and measurement issues

Ex-post harmonization of cross-national public opinion surveys uses extant surveys to create new datasets with greatly expanded geographical and time coverage, creating opportunities for new methodological and substantive insights. Survey Data Recycling (SDR, dataharmonization.org), developed by Slomczynski and Tomescu-Dubrow (2015), is an analytic framework, with a foundation in Multinational, Multiregional and Multicultural (3M) survey research, providing tools for using data from ex-post harmonized surveys to improve substantive analyses. Yet, there are few empirical illustrations of how to apply this framework to the analysis of social and political phenomena. This paper provides a roadmap from harmonization to substantive analyses based on the principles of SDR via a detailed empirical illustration.
Specifically, I examine individual- and macro-level determinants of participation in demonstrations. Data come from the Survey Data Recycling dataset that provides harmonized variables on protest participation, political attitudes, and their selected correlates. I use a part of the SDR dataset: five cross-national surveys: Americas Barometer, Asia-Europe Survey, European Values Study, International Social Survey Programme, and the World Values Survey, covering 86 countries between 1990 and 2009.
In this paper I discuss how to apply the SDR framework to measure participation in demonstrations and political trust, and analyze their determinants. The core of the SDR framework is the recording of methodological information about the original (source) surveys as separate methodological variables in the harmonized dataset to be included in multi-level models designed to test hypotheses of the relationship between the measures. These methodological variables are of two types. Harmonization control variables accompany each target (harmonized) variable to capture properties of survey items that would be lost in the process of harmonization, such as question wording or length of response scales. Quality control variables address the inter-survey variation in the methodology and quality of the survey process, e.g. the type of sampling scheme or presence of fieldwork control. In SDR, these control variables can be used for the selection of surveys that meet pre-defined criteria or as control variables.
Substantive results support findings of previous research and point to new insights. I found that high political trust decreases the probability of participating in demonstrations in countries at all levels of the quality of democracy. The harmonized data also reveals systematic variation in the effects of education on participation in demonstrations; while the effect of education is positive in all countries, the effect is much stronger in democracies than in non-democracies. Generally, this paper illustrates how to use harmonized data from a diverse set of cross-national surveys and how to analyzed these data in substantive comparative research on a global scale.