The effect of economic development and ıncome distribution on poverty: an econometric analysis

*Bu makale, Nurten ASANDAŞ’ın, Prof. Dr. Nihat IŞIK danışmanlığında Kırıkkale Üniversitesi Sosyal Bilimler Enstitüsü Ekonometri Anabilim Dalı’nda tamamlamış olduğu Yüksek Lisans tezinden revize edilerek üretilmiştir.Bu çalışmada, 2003-2016 yıllarını kapsayan Türkiye dâhil 16 gelişmekte olan ülke için; ekonomik kalkınma ve gelir dağılımının yoksulluk üzerindeki etkisi Dinamik Panel Veri tahmin yöntemlerinden Sistem Genelleştirilmiş Momentler Metodu (SGMM) kullanılarak tahmin edilmiştir. Bu amaçla iki farklı model kullanılmıştır. SGMM tahmincisinden elde edilen sonuçlarda, iki modelde de yoksulluk değişkeni kendi gecikmeli değeri ile %1 önem düzeyinde pozitif ve istatistiksel olarak anlamlı bulunmuştur. Elde edilen bu bulgunun yoksulluğun kısır döngüsü ile uyumlu olduğu söylenebilir.The common goal of the countries is to provide economic development together with economic growth, to reduce poverty by minimizing income injustice, and to live peacefully in a safe environment. Today, nevertheless, this environment cannot be provided in many countries, especially in African countries. One of the most important factors cited as the reason for this situation is the unequal distribution of national income. Unjust income distribution creates poverty, and poverty creates social problems along with it. In this study that covers the years 2003-2016 for 16 developing countries including Turkey; the impact of economic development and income distribution on poverty was estimated using the System Generalized Moments Method (SGMM), one of the Dynamic Panel Data estimation methods. Two different models were used for this purpose. In the first model used, the variable poverty is dependent; while human development index, income distribution and unemployment rate are included as independent variables; in the second model, the variable poverty is dependent; human development index, income distribution and inflation rate are taken part in as independent variables. In the results obtained from the SGMM estimator, the poverty variable in both models was found to be positive and statistically significant with its own lagged value. It can be asserted that this finding is compatible with the vicious circle of poverty. On the other hand, while unemployment and inflation rates and the increase of inequality in income distribution increase poverty, poverty decreases as the level of human development index