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

Gyubeom Park, Kichan Yoon and Munjae Lee

SAGE Open, 2021, vol. 11, issue 4, 21582440211061562

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.

Keywords: non-take-ups; regional variables; geographic information system; elderly proportion; spatial regression model (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/21582440211061562 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:11:y:2021:i:4:p:21582440211061562

DOI: 10.1177/21582440211061562

Access Statistics for this article

More articles in SAGE Open
Bibliographic data for series maintained by SAGE Publications ().