Regional Factors Influencing Non-Take-Up for Social Support in Korea Using a Spatial Regression Model

Abstract

The purpose of this study is to analyze the influential factors of non-take-up citizens, who do not receive social benefits, to increase their discovery rate. A spatial regression model was used to analyze the variables affecting the discovery rates. As a result of the study, there was a difference in the percentage of welfare blind spots by region. In addition, when the proportion of the elderly population, the number of unemployment benefit recipients, etc. increased, that of welfare blind spots also increased; the lower the population density was, the higher the rate of increase in welfare blind spots became. Accordingly, in order to resolve the welfare blind spots at the local level, it is necessary to reinforce policy support for the elderly population and reduce the unemployment rate. Particularly, the policy will have to be prepared to resolve the welfare blind spots in rural areas with low population density.