Temel Ekonomik Sektörler-Gelir Eşitsizliği Bağlantısının EAGLE Ülkeleri Tahmini: Görünürde İlişkisiz Regresyon Uygulaması

Year 2025, Volume: 10 Issue: 3, 1355 - 1380

Güller Şahin , Erkan Aktaş

https://doi.org/10.25229/beta.1668874

Abstract

Bu araştırmanın amacı, 1990-2022 yılları arasında Yükselen ve Büyüme-Lideri Ekonomiler (EAGLE) olarak nitelendirilen ülkelerde ekonominin temel sektörlerindeki büyüme, işgücüne katılım, nüfus artışı ve insani gelişmenin, gelir eşitsizliği üzerindeki olası etkilerinin analiz edilmesidir. Gelir eşitsizliğinin itici faktörlerini belirleyebilmek amacıyla panel zaman serisi analizine ait metodolojiden faydalanılmıştır. Bu kapsamda panel veri analizine ilişkin yapılan eğim homojenliği ve yatay-kesit bağımlılığı ön testleri sonucunda, parametre heterojenliğini ve birimler arası korelasyonu hesaba katan bir tahminci olan Görünürde İlişkisiz Regresyon (SUR) modeli kullanılmıştır. Temel ekonomik sektörlerden tarım sektörünün gelir eşitsizliği üzerindeki etkisi istatistiki olarak anlamsız; sanayi ve hizmet sektörlerinin ise anlamlıdır. Bununla birlikte işgücüne katılım oranı, nüfus artışı ve insani gelişmenin de gelir eşitsizliğinin itici güçleri olduğu görülmektedir. Literatür kanıtları, ekonomik büyümeden gelir eşitsizliğine uzanan bir bağlantının varlığını göstermekle birlikte hem sektörel büyümenin gelir eşitsizliği üzerindeki etkilerini hem de işgücüne katılımın, nüfus artışının ve insani gelişmenin gelir dağılımını etkileyip etkilemediğini değerlendiren herhangi bir ampirik araştırmaya rastlanmamış olması bu araştırmanın özgün değerine atfedilmektedir.

Keywords

Gelir Eşitsizliği , Temel Ekonomik Sektörler , Görünürde İlişkisiz Regresyon

Estimating the Main Economic Sectors-Income Inequality Connection for EAGLE Countries: Application of Seemingly Unrelated Regression

Abstract

The target of this research is to analyze the possible effects of growth in the main sectors of the economy, labor force participation, population growth and human development on income inequality in Emerging and Growth-Leading Economies (EAGLE) countries between the years 1990-2022. The methodology of panel time series analysis was utilized to determine the driving factors of income inequality. In this context, the Seemingly Unrelated Regression (SUR) model, an estimator that takes into account parameter heterogeneity and inter-unit correlation, was used with the slope homogeneity and cross-sectional dependency pre-tests conducted for panel data analysis. While the influence of the agricultural sector, one of the main economic sectors, on income inequality is statistically insignificant, the industrial and service sectors are significant. However, labor force participation rate, population growth and human development also appear to be the driving forces of income inequality. Although literature evidence shows the existence of a connection extending from economic growth to income inequality, the fact that no empirical research has been found that evaluates the impacts of sectoral growth on income inequality and whether labor force participation, population growth, and human development affect income distribution is attributed to the original value of this research.

Keywords

Income Inequality , Main Economic Sectors , Seemingly Unrelated Regression

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