Gelir dağılımı çalışmaları için bir alternatif: Texas üniversitesi eşitsizlik projesi veri setleri

Gelir eşitsizliği iktisat yazınında ele alınan en önemli konulardan biridir. Neoliberal modelle birlikte 1980’li yıllardan itibaren hem ülkeler arasında hem de ülke içinde gelir eşitsizliği artmaktadır. Ancak, özellikle ge- lişmekte olan ülkelerde geniş bir dönemi kapsayan sağ- lıklı veriye ulaşmak çok güçtür. Bu çalışma, gelir da- ğılımı yazınında sıklıkla kullanılan ancak bazı önemli sorunlar içeren Deininger ve Squire (DS) veri setine alternatif olan, fakat özellikle Türkçe yazında yaygın olarak kullanılmayan Texas Üniversitesi Eşitsizlik Pro- jesi - Birleşmiş Milletler Endüstriyel Kalkınma Organi- zasyonu/University of Texas Inequality Project United Nations Indusrial Development Organization (UTIP- UNIDO) ve Tahmin Edilmiş Hanehalkı Gelir Eşitsizli- ği/Estimated Household Income Inequality (EHII) veri setlerini tanıtmayı amaçlamaktadır. Bu setler imalat sanayindeki ücret eşitsizliğinin Theil indeksinin grup- lararası bileşeni ile hesaplanması ve Gini katsayısı for- matına dönüştürülmesi ile oluşturulmuştur. Dolayısıy- la, bu çalışma genel bir gelir eşitsizliği yazın incelemesi olmayıp, spesifik olarak sadece bu veri setlerini kulla- nan bazı UTIP çalışmalarına değinmektedir.

An alternative to studies of income distribution: University of Texas inequality project data sets

Income inequality is one of the most important issues in the economic literature. Since the 1980s, in line with neoliberal model, income inequality has increased both between and within countries. However, it is not easy to have high quality data for long period of time particulary for the developing countries. This study aims to introduce the University of Texas Inequality Project - United Nations Indusrial Development Organization (UTIP-UNIDO) and Estimated Household Income Inequality (EHII) data sets, which are not commonly utilized in the Turkish literature, as alternative to Deininger ve Squire (DS) data set that has some serious problems. These data sets have been constructed by calculating pay inequality in the manufacturing sector by utilizing between-group components of Theil Index and by transforming it into Gini coefficient form. Therefore, this work is not a generel literature survey on income inequality but rather it deals with some particular works by UTIP that uses these data sets.

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