Household behavior and socio-economic effects of using personal loan

The personal loan utilization which became widespread in recent twenty years period of time in Turkey brought with the increase in the debt of the household to the financial section. Increasing household indebtedness contains various risks both socially and economically. Household indebtedness which could not be managed properly not only influence the economy through the balance sheet of the demand and balance sheet of the financial institutions but also causes the loss of confidence and consideration in the social environment of the individuals. In this respect, the determination of the factors affecting the personal loan demand is important for the estimation and management of the potential risks.In this study which is prepared for the purpose of determining the factors affecting the personal loan utilization in Turkey; first of all the consumption theories and the household social and economical characteristics are examined in Turkey. In the application section of the study, according to the BRSA data, the survey study is applied in Istanbul, Ankara and İzmir which are there provinces with the most intensive personal loan utilization in Turkey. The logistics regression model is used through E-views program for the analysis of the survey data. According to the analysis results; while the factors such as age, gender, marital status, number of children, asset accumulation, settlement place do not affect the personal loan utilization, it is seen that getting indebted by the individuals from another source, high interest rates, not preferring to the credit usage due to the religious concerns, request of benefiting from the commodity and service purchase in advance by means of utilizing credits, educational status of the individuals who are effective in the decision making process and the future income expectation of the household affect the personal loan utilization behavior.Keywords: Personal Loan, Consumer Credit, Credit Card, Household Indebtedness, Logistics Regression