Quantitative methods to measure attitudes toward immigrants and national identity

Abstract

Immigration has always been a very important dynamic phenomenon. In the 19th century, the United States experienced massive immigration from the United Kingdom, Germany and Scandinavian countries. Between the first and the second post-World War, emigration has become a very widespread phenomenon among all European countries, especially among countries that were neutral in warfare or towards American countries, such as the case of Italian emigration to Argentina (Keeling, 1999). The political and social climate of recent years has caused a hot debate on the issue of immigration. The advance of the extremist political parties that defend the national identity has triggered a social conflict between the supporters of welcoming refugees and those who, on the other hand, support a defense of the country from the economic and cultural threat of newcomers. (Alonso and Fonseca, 2012) . The nationalist escalation in the political scene in recent years has reshaped citizens’ attitudes towards immigrants. Many researchers have studied this phenomenon and how it changes according to political orientation and other socio-economic characteristics (Mart ́ın and Indelicato, 2021). In this context, the literature on studies of attitudes towards immigrants and national identity has ainly used two approaches: the Structural Equation Model (SEM) and the Confirmatory Analysis of Factors (CFA). Both approaches are based on measurement models in which latent variables are obtained using econometric models adapted to the observed elements (Meuleman, 2021; Thomsen, 2018). The aim of this study is to bring a new methodological point of view to the study of social sciences, in particular on the study of attitudes towards immigrants and nationalist sentiment. This work introduces multivariate analysis approaches, such as Data Envelopment Analysis (DEA) and Fuzzy Set Theory (FST). First, the DEA provides a synthetic indicator of openness to immigrants and refugees. FST is used to transform vague information provided by questionnaires into crisp information. Thus, synthetic indicators are obtained that measure the anti-immigrant sentiment and the national identity value of citizens, through the Technique for Order Preference by Similarity Ideal Solution (TOPSIS). The data used in this doctoral thesis project were extracted from two databases used frequently in research studies, the European Social Survey (ESS) and the International of Social Survey Program (ISSP). Round 8 and round 9 of the ESS mmigration modules and ISSP national identity modules 2003 and 2013 were used. The results show that both attitudes towards immigrants and national identity are shaped by the individual social and economic characteristics of citizens. The northern European regions and the Iberian Peninsula show greater openness towards immigrants. Furthermore, through the Apostle Method, national identity has been divided into four sub-categories according to two criteria, ethnic and civic.