• The Korean Journal of Applied Statistics
• /
• v.28 no.4
• /
• pp.663-683
• /
• 2015

The change of the population pyramid due to low fertility and rapid aging threatens the financial sustainability of National Health Insurance. We construct statistical models for prevalence rates and medical expenses using National Health Insurance Service (NHIS) sample cohort data from 2002-2013. We then project yearly expenditures and income of national health insurance until 2060 that considers various assumptions in regards to future population structure and economic conditions. We adopt a VECM-LC model for prevalence rates and the double exponentially smoothing method for the per capita co-payment of healthcare expense (in which the two models are institution-disease-sex-age specific) to project of national health insurance expenditures. We accommodate various assumptions of economic situations provided by the national assembly and government to produce a financial projection for national health insurance. Two assumptions of dependents ratios are used for the projection of national health insurance income to conduct two future population structures by the two assumptions of aging progresses and various assumptions on economic circumstances as in the expenditure projection. The health care deficit is projected to be 20-30 trillion won by 2030 and 40-70 trillion won by 2060 in 2015 constant price.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.6
• /
• pp.1175-1188
• /
• 2015

The Ministry of Education of Korea announced the university structural reform plans which reduces 160,000 of the university entrance quota during 10 years from January 2014. Because the reduction plans of entrance quota influence regional economy as well as students and universities, naive evidence of the Ministry of Education of Korea is disappointed. In this research, we forecast the total number of the university entrance exam candidate by 2032 including not only third grade high school students but also repeaters according to the 16 metropolises and provinces in Korea. We also forecast the regional university recruiting rate using the forecasts of the total number of the university entrance exam candidates. However, we can not make more realistic results because we can not apply the inter-regional movement of students to the forecast. In order to handle this limitation, we first estimated the rank of the whole 7,277 departments of all universities in Korea and assigned the quotas according to the estimated rank for each departments and then we calculated the local university recruiting rate. The estimated the university recruiting rates of 16 metropolises and provinces can provide more noticeable results of characteristics and problems than that of nationwide.