A Study on Improving the Designation Indicators for Population Decline Areas Using Binary Logistic Regression Analysis

This study critically examines the limitations of the current 'Population Decline Index,' which serves as a core basis for the Korean government's designation and support policies for population decline areas.The purpose of this study is to propose an alternative analytical framework that can explain the structural causes of local extinction.For this purpose, a factor analysis and a binary logistic regression analysis were conducted on all 229 basic local governments in South Korea, using a total of 14 variables that supplement the existing index with socio-economic and settlement condition indicators.The factor analysis revealed that the phenomenon of regional decline is underlain by three latent factors: 'Population Vitality and Growth Potential,' 'Urbanization and Settlement Conditions,' and 'Regional Economic Base.'The subsequent logistic regression analysis demonstrated that these three factors could predict the designation of population-decline areas with an accuracy of approximately 97.8%.All factors acted as protective factors, lowering the probability of designation.Notably, the 'Urbanization and Settlement Conditions' factor emerged as the most powerful predictor, suggesting that the quality of life and an urban environment attractive to the youth play a decisive role in regional sustainability.This study contributes to interpreting the population decline phenomenon in a multidimensional manner and to exploring new policy directions that consider factors influencing population inflows.