Prediction of Long-term Care Insurance Enrollment Trends Based on the GM (1,1) Model in the Context of Population Aging: A Case Study of Kunming
Year: 2024
Type: article
Abstract: This study aims to forecast the trend of long-term care insurance enrollment in Kunming from 2024 to 2027, with the goal of supporting strategic planning and providing a scientific basis for decision-making to address the challenges of population aging. Using the GM (1, 1) grey model, predictions were made based on enrollment data from 2021 to 2023 for long-term care insurance and basic medical insurance for urban employees. The forecast results show a steady increase in long-term care insurance enrollees, expected to reach 2.21 million by 2027, while urban employee basic medical insurance enrollment is projected to rise to 2.73346 million. The GM (1, 1) grey model effectively predicts future trends in long-term care insurance enrollment, highlighting the system's role in mitigating the impact of an aging population. It is recommended that relevant departments emphasize the development of long-term care insurance in policy planning and enhance the related policies to ensure both effectiveness and sustainability.
Authors: Xiaoyu Qi, Ye Lu, Qunjun Yu
Institution: Kunming Medical University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4409890264