Türkiye’de Bölgesel İşsizliğin Belirleyicilerinin Mekânsal Panel Veri Modelleriyle Analizi

Abstract

İşsizlik, ekonomik kalkınmanın önünde büyük bir engel olup, bireylerin yaşam kalitesini doğrudan etkileyen önemli bir sorundur. İşgücü piyasasındaki dengesizlikler, yetersiz istihdam olanakları ve bölgesel farklılıklar, işsizlik oranının dalgalanmasına yol açmaktadır. Bu nedenle, bölgesel düzeyde işsizliği etkileyen sosyo-ekonomik faktörlerin belirlenmesi, işgücü piyasasında etkili politikalar geliştirmek için önemlidir. Bu çalışmada, Türkiye’nin İBBS Düzey 2’deki 26 bölgesi için 2014-2022 yıllarına ait verilerle işsizlik oranında mekânsal etkilerin olup olmadığı ve işsizlik oranını açıklayan faktörler mekânsal panel veri modelleri yardımıyla incelenmiştir. Test sonuçlarına göre, mekânsal hata modeli (SEM) uygun model olarak belirlenmiş ve bu modelin tahmin sonuçlarına göre bölgesel büyüme oranı, girişim sayısı ve genç nüfustaki artışın bölgesel işsizliği azalttığı; diğer yandan üniversite mezun sayısı ve yoksulluk oranındaki artışın işsizlik oranını arttırdığı tespit edilmiştir. Bu sonuçların, bölgesel işsizliği azaltmaya yönelik politikaların belirlenmesinde katkı sunacağı düşünülmektedir.

Keywords

• Mekânsal Panel Veri Analizi
• Mekânsal Hata Modeli
• Türkiye Düzey2
• İşsizlik

Spatial Panel Data Analysis of Determinants of Regional Unemployment in Turkey

Abstract

Unemployment is a significant barrier to economic progress and is an important issue that directly affects individuals' quality of life. Imbalances in the labor market, insufficient employment opportunities, and regional disparities lead to fluctuations in the unemployment rate. Therefore, identifying the socio-economic factors affecting unemployment at the regional level is important for developing effective policies in the labor market. This study used spatial panel data models to examine the spatial effects of the unemployment rate and the factors explaining it in Turkey's 26 regions at the NUTS-2 level for the years 2014–2022. The test results identified the spatial error model (SEM) as the appropriate one. Based on its estimation results, we found that the regional growth rate, the number of enterprises, and the increase in the young population reduce regional unemployment, while the increase in university graduates and the poverty rate increase it. It is believed that these results will contribute to the formulation of policies aimed at reducing regional unemployment.

Keywords

• Spatial Panel Data Analysis
• Spatial Error Model
• Unemployment
• Turkiye NUTS2

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