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Bu çalışmada, Türkiye’de toplumsal refah artışını engelleyen hanehalkı göreli yoksulluğunun, boyutları ve temel belirleyici faktörleri incelenmektedir. Bu amaçla analizde Türkiye İstatistik Kurumu (TÜİK) (2017) yılı Gelir ve Yaşam Koşulları Araştırması mikro veri seti kullanılmıştır. İlk olarak hanehalkı medyan fert gelirinin %60’ına göre yoksulluk sınırı hesaplanmıştır. Bağımlı değişkenin yoksulluk sınırına göre yoksul ve yoksul olmayanlar olarak ele alındığı İkili Lojistik Regresyon analizinde, hanehalkı demografik özellikleri, işgücü piyasası ve coğrafi özellikleri içeren açıklayıcı değişkenler kullanılmıştır. Elde edilen sonuçlara göre Türkiye’de eğitim düzeyi, yaş, Sosyal Güvenlik Kurumu’na kayıtlı olma ve sanayi sektöründeki istihdam yoksulluk riskini azaltırken işsizlik, yevmiyeli çalışma, evli olma ve hane büyüklüğü yoksulluk riskini artırmaktadır.
This study examines the proportional poverty, dimensions and fundamental determining factors of households that prevent the increase in social well-being in Turkey. For this purpose, the analysis was used by the Turkish Statistical Authority (TÜIK) (2017) year Income and Life Conditions Research micro data set. Firstly, the poverty limit was calculated according to 60% of the households’ median fert income. In the bilateral logistical regression analysis, where the dependent variable is treated as poor and non-poor according to the poverty limit, there have been used explanatory variables containing household population demographic characteristics, labour market and geographical characteristics. According to the results obtained in Turkey, the level of education, age, registration in the Social Security Institution and employment in the industrial sector reduce the risk of poverty while unemployment, food work, marriage and household size increases the risk of poverty.
This study investigates the factors that determine the relative household poverty which prevents the growth of social welfare in Turkey. For this purpose, Turkish Statistical Institute (Turkstat) (2017) Income and Living Conditions micro dataset were used. The poverty line is calculated by using 60% of household median income. In the binary logistic regression analysis, dependent variable was considered as poor and non-poor according to poverty line. Household demographic characteristics, labour market conditions and geographical characteristics are employed as explanatory variables. The estimation results indicate that education, age, formal employment, employment in industry sector decreases relative household poverty. On the contrary unemployment, causal employee, marriage and size of the household increase the risk of household poverty.
Field : Sosyal, Beşeri ve İdari Bilimler
Journal Type : Uluslararası
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