Evaluating the Dynamics Affecting Tolerance Toward Migrants in Türkiye Using Statistical Analyses

Hatice Gül Bozdeveci () and Özlem Yorulmaz ()
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Hatice Gül Bozdeveci: İstanbul Üniversitesi, Sosyal Bilimler Enstitüsü, İstanbul, Türkiye.
Özlem Yorulmaz: İstanbul Üniversitesi, İktisat Fakültesi, İstanbul, Türkiye.

EKOIST Journal of Econometrics and Statistics, 2023, vol. 0, issue 38, 199-221

Abstract: Having occurred throughout the history of humanity, migrations are a social movement closely related to societies and can cause various sociological, psychological, economic, and political problems. The most fundamental reason for migration is individuals’ desire to have a better life. The turmoil in Afghanistan, the Arab Spring, the Syrian civil war, and political instability in recent years have increased mass migration movements. Undoubtedly, Türkiye is one of the countries to have been highly affected by mass migration movements and received large numbers of migrants. The high rate of increase in the number of immigrants in Türkiye has resulted in the produced policies being insufficient, thus necessitating the production of new policies regarding immigrants. This study uses data from the last wave of the World Values Survey regarding Türkiye and involves three different statistical analyses. The first stage of the study classifies the individuals living in Türkiye using a latent class analysis in terms of tolerance toward immigrants. According to the analysis results, individuals are divided into three groups: tolerant, indecisive, and intolerant. The next stage evaluates the socioeconomic and demographic variables that distinguish these three classes from one another using a multi-category logistic regression analysis. The results show the variables of working status, income level, belief level, and political view to be determinative in identifying which of the three classes individuals will be found. The last stage visualizes the relationship between education level and tolerance toward immigrants using correspondence analysis.

Keywords: Migration; Latent Class Analysis; Correspondence Analysis; Multinomial Logistic Regression Analysis (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ist:ekoist:v:0:y:2023:i:38:p:199-221

DOI: 10.26650/ekoist.2023.38.1225344

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