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Working paper

Within and Between-Country Value Diversity in Europe: Latent Class Analysis

Magun V., Rudnev M., Schmidt P.
Country averages are the most popular instrument for studying cross-national variability of values, and within-country value diversity is rarely taken into consideration in such studies. Furthermore, traditional value indices only measure distinct value priorities, but do not allow researchers to grasp a system of value preferences. In order to find an alternative way to study within-country value diversity and cross-country differences, we employed latent class analysis (LCA). Respondents from the 33 European countries were classified on the basis of their responses to 21 items on the Schwartz Portrait Value Questionnaire. LCA resulted in six value classes. Five of these classes differ by their patterns of value preferences, and the particular feature of the largest class (38%) is the lack of any pronounced value preferences at all. The results showed that each of the 33 countries is internally diverse in its value class composition, and that most countries have representatives of all six value classes. At the same time, Nordic and Western European countries are substantively different from post-Communist and Mediterranean countries by their shares of various value classes. As a formal measure of within-country diversity we have used the value fractionalization index, which measures the evenness of membership distributions between classes. Nordic and Western European countries have higher fractionalization scores than post-Communist and Mediterranean countries. This means that value class distributions are more even in the Nordic and Western countries, which highlights the fact that higher fractionalization scores happen to coincide with country advancement. In Mediterranean and post-Communist countries, low value fractionalization means that the people are divided into unequal value majorities and value minorities, with a risk that the voices of minorities are not heard in the public space.