İşsizliğin Sosyo-Ekonomik Belirleyicileri: Karma Yöntemli Nedensel Analiz ve Politika Sonuçları

Abstract

Araştırmanın amacı, işsizlik oranına etki eden sosyo-ekonomik değişkenlerin hem tekil hem de bütünsel anlamda nedensel ilişkilerini ortaya koymaktır. Ayrıca ülkelere özgü sonuçlar ile geleceğe dönük politik öneriler ortaya çıkarmayı hedeflemektedir. Bu amaçlara yönelik olarak işsizlik oranına etki eden faktörleri hem simetrik (korelasyon analizi, yapısal eşitlik modellemesi) hem de asimetrik (fsQCA) yöntemlerle analiz etmektedir. OECD ve ILO gibi uluslararası kuruluşlardan 2023 yılı verileri kullanılarak yapılan analizde, çalışılan saat sayısı (HW), serbest meslek oranı (SER), genç kadın işsizlik oranı (UYF), insan hakları endeksi (HRI), eğitim seviyesine göre istihdam (EEL) ve işgücü gelir payı (LIS) değişkenleri incelenmiştir. Korelasyon analizleri sonucunda, UYF ile UER, HRI ile LIS ve SER ile HW arasında güçlü ve pozitif ilişkiler belirlenmiştir. Ayrıca, HW ile EEL, SER ile EEL ve HRI ile SER arasındaki ilişkilerin negatif yönlü olduğu görülmüştür. Yapısal model sonuçlarına göre modelin p=0.030 ve R2 değerinin 0.761 olduğu tespit edilmiş, bu sonuç modelin anlamlı olduğu ve yüksek açıklayabilirleğe sahip olduğunu göstermiştir. FsQCA analizine göre, tüm değişkenler işsizlik oranı açısından tekil olarak yeterli bulunmuş, UYF'nin yokluğu ise gerekli değişken olarak belirlenmiştir. Konfigürasyon analizleri, işsizlik dinamiklerinin ülkeler bazında farklılaştığını ortaya koymuş, bu farklılıklar politika yapıcılar için sürdürülebilir gelişim adına yönerge önerisini ortaya çıkarmıştır

Keywords

• İşsizlik
• İşgücü piyasası
• Sosyal Politika
• Yapısal Eşitlik Modeli
• fsQCA

Socio-Economic Determinants of Unemployment: A Mixed-Method Causal Analysis and Policy Implications

Abstract

The aim of the research is to reveal the causal relationships of socio-economic variables affecting the unemployment rate both individually and holistically. It also aims to reveal country-specific results and future policy recommendations. For these purposes, it analyzes the factors affecting the unemployment rate with both symmetric (correlation analysis, structural equation modeling) and asymmetric (fsQCA) methods. In the analysis using data from international organizations such as OECD and ILO for 2023, the number of hours worked (HW), self-employment rate (SER), young female unemployment rate (UYF), human rights index (HRI), employment by education level (EEL) and labor income share (LIS) variables are examined. As a result of correlation analyses, strong and positive correlations were found between the IIP and UER, HRI and LIS, and SER and HW. Moreover, the relationships between HW and EEL, SER and EEL, and HRI and SER are found to be negative. According to the results of the structural model, p=0.030 and R2 value of the model is 0.761, which shows that the model is significant and has a high explanatory power. According to the FsQCA analysis, all variables were found to be individually sufficient for the unemployment rate, while the absence of the NIF was determined as a necessary variable. Configuration analysis reveals that unemployment dynamics differ across countries, and these differences suggest guidelines for policymakers for sustainable development.

Keywords

• Unemployment
• Labor Market
• Social Policy
• Structural Equation Modeling
• fsQCA

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