Investigating the social assistance policy practices and factors affecting the household benefit levels in rural areas: Case of the province of Antalya

During the last decades, the social assistance programs gained increasing importance in Turkey. The country public social assistance programs, social funding and the number of assistance programs beneficiaries increase over the years. The main objective of this research is to investigate the implementation of social assistance system, the households benefit levels and the factors affecting these benefit levels in the province of Antalya. Especially within the scope of this research, the functioning system of social assistance has been determined, the assistance and income ratio has been calculated, and the factors affecting the household benefit levels and the factors affecting this benefit levels have been determined. The survey has been conducted in the district of Konyaaltı and primary data have been collected through household survey from 100 households purposely selected from the list of the beneficiaries of Social Assistance and Solidarity Foundation who were willing to participate in survey. Primary data have been collected through household's survey from 100 households purposely selected from the list of the beneficiaries of Social Assistance and Solidarity Foundation of the district of Konyaaltı. In addition, primary data have been collected from 5 municipal and 5 districts (Konyaltı, Muratpaşa, Kepez, Aksu and Döşemealtı) responsible for social assistance and services Antalya. Descriptive statistics have been used to determine the socio-economic characteristics of the beneficiary households and social assistance programs and the main indicators of the social assistance systems. In addition, multiple regression analysis has been used to determine the factors affecting the households assistance and income ratio and multinomial logistic regression analysis has been used to determine the factors affecting the households needy levels from social assistance. According to the research findings, 50% of the households in Konyaaltı district were less needy, 15% was needy and 35% of households were very needy from public social assistance. It was observed that the number of persons, the number of employees, the monthly income of the persons living in the household, the sex of the head of household and the frequency of delivering the social assistance to the household affected negatively the assistance and income ratio. The age of the head of household, the number of people with primary and secondary school educational level living in the household and the monthly amount of the assistance received by the household affected positively the assistance and income ratio. In respect to less needy households, the age of the head of household, the group of social assistance and the monthly income of the persons living in the household were significant predictive factors of needy households. The age of the head of household, the number of people living in the household, the group of social assistance and the monthly income of the persons living in the household were significant predictive factors of very needy households. In addition, the research findings revealed a lack of an integrated social assistance system including all public institutions executing the social assistance therefore there is a need for an integrated social assistance system at the country level. In pursuance to the researches findings it is urgent to simplify the types of social assistance and to implement a country integrated "social assistance monitoring system" including all public and other relevant institutions. This could ensure the effective use of the resources devoted to fight against poverty. Besides, the fact that all the institutions and organizations executing social assistance use a common criterion in evaluating the application for social assistance will increase the trust of needy citizens towards these institutions. KEYWORDS: Assistance and income ratio, assistance benefit level, public social assistance, multiple regression analysis, multinomial logistic regression analysis, integrated social assistance system, Antalya, Turkey.