The purpose of this study is to analyze the housing situation of small and medium-sized cities located in the provinces and to provide housing policy data for low-income households by analyzing empirical data concerned low-income households in small and medium-sized cities. 2,252 data for the year 2017 and 2018 of public assistant recipient households are used, and regression analysis of the amount of income recognition was conducted through curve model estimation. Age, the number of household members, and daily workers' income. The estimation of the second and third degrees shows the largest amount of income is recognized when the number of household members reaches six to seven. Due to the low birth rate and increased number of single or two-person households. The results for the full-time and daily working householders show the relationship directly proportional to the dependent variable with statistical significance. The results indicate that it is necessary to promote different approaching policies. The basic direction of the housing welfare policy would have to be more microscopic than the ongoing one. A granular approach is worth the further research.

Deciding low-income intensifies poverty rate, on July of 2017, the government of Korea has announced to raise minimum wage in order to make change to labor market structure. Income inequality has long been a social issue, and housing income is considered to be major determinant. With sample data in a medium-sized city of Korea, this study investigates causal relationship among parametric variables utilizing path analysis. We find that the quality of job for the households leads to income of the sample data analyzed.