A Study of Redistributive Effects of Medical In-Kind Benefits in South Korea, Using Linked Survey and Administrative Data - You, Jong Sung; Lee, Subin (International Journal of Population Data Science, 2026)
Medical in-kind benefits significantly influence households' real disposable income and medical consumption capacity. However, traditional household survey data typically lack information on in-kind benefits. To directly measure the distribution of medical in-kind benefits and to accurately estimate their effects on the inequality of income and medical consumption, this study linked income distribution data from Statistics Korea’s Survey of Household Finances and Living Conditions (SHFLC) with medical in-kind benefits administrative data sourced from the National Health Insurance Service (NHIS). While an 80 percent match rate was achieved at the individual level, only 53 percent of the SHFLC samples were perfectly matched at the household level, with imperfect matches more prevalent in larger households. Our preliminary analysis, based on reweighted perfectly matched samples, yielded several key findings: The medical in-kind benefits—including health insurance, long-term care, and social assistance—were highly progressively distributed by income, with average benefits being higher for low-income households and the elderly. Aggregately, benefits provided to the bottom income quintile were more than three times those provided to the top. The inclusion of these benefits reduced poverty rates based on adjusted disposable income by approximately 2 percentage points for the entire population and by about 10 percentage points for the elderly. These initial findings robustly demonstrate the significant redistributive power of medical in-kind benefits in mitigating poverty among vulnerable populations. To address potential selection bias from imperfect matching, we will conduct robustness checks using multiple imputation techniques for the missing data.