TÜRKİYE’DE 2012-1/2016-3 ARASI DÖNEMDE 15-64 YAŞ GRUBU İÇİN İSTİHDAM DIŞI ORANIN BULANIK DOĞRUSAL REGRESYON ANALİZİ İLE TAHMİNİ

Abstract

The growing unemployment rates continue to be a global problem. While some countries, e.g., Germany, Holland, and Denmark are successful in both economic growth and development, others only show economic growth but not development. The reasons are different in each country. Turkey's unemployment problem is usually associated with economic growth, which is regarded as not high enough, but economic development is still expected to increase. However, when we look at the big picture, not increasing economic development can cause unemployment rates to rise. Increased prosperity expected from growth does not reach the public, and the gap between rich and poor increases with a higher Gini coefficient. In this study, unemployment rates in Turkey are based on fuzzy linear regression. Sometimes researchers encounter fuzzy relationships between variables, fuzzy variables, small sample problems, or nonlinear functional relationships. In such cases, fuzzy regression analysis can help researchers make estimations without having to transform the data set. Assumptions in classical regression need not be proved for fuzzy regression and it does not require normally distributed data, stability tests, infinite trials (large samples), or any other transformation for linearization. It handles data literally and makes truthful estimations.