The estimation of the factors that determined conditional cash transfers in turkey with logistic regression analysis

Poverty is the condition in which people are unable to satisfy their fundamental needs. This condition causes major social and economic instabilities in both developed and developing countries. For this reason, finding methods of fighting poverty is of great importance among the subjects which all countries consider.In recent years, one of the most effective political methods that is used to fight poverty is Conditional Cash Transfers (CCT), used primarily in Latin America and later on in many other countries. According to this aiding policy, cash is given out to the poor, primarily to woman and children, in exchange to their realizing some specific conditions. This policy has been used in Turkey in the education and health fields since 2003. In econometric studies where the dependent variable takes two or more values, models with dummy dependent variables are used. The factors which explain the dependent variable in the logistic regression model, which is one of the models with dummy dependent variables, depends on the probabilistic nature of the decision process. In this study, the factors affecting CCT in Turkey in order to fight poverty were investigated with the help of logistic regression. The data for the model was extracted from the 2003 - 2010.The results of the studies show that in Turkey, households which have more children aged 0 - 6, women over the age of 40, people who have had low levels of education, unemployed heads of houses who are searching for employment, people who live with disabled people in their households, and people who live in provinces which are prioritized for development have higher probabilities of receiving CCT when compared with others.Key Words:1.Logistic Regression2.Binary Logistic Regression3.Poverty Reduction4.Targeting Mechanism5.Conditional Cash Transfers (CCT)