《保险研究》20250704-《基于试点地区长期护理保险基金测算的保险费率厘定研究——以上海、广州、青岛、重庆为例》（毕达宁、叶豆、张建浩、张琳）

［摘   要］本文综合运用中国健康与养老追踪调查（CHARLS）数据库、多状态Markov模型、人口预测模型、利率预测模型和基金测算模型，对上海、广州、青岛和重庆四个试点城市的长期护理保险运行情况进行了深入的分析，并分别从理论和实际两个层面，对未来十年的基金结余情况进行预测。研究发现，各城市长期护理保险基金的实际结余逐年扩大，理论结余与实际结余之间存在较大差异。在此基础上，通过精算平衡测算，从保额和保障人数两个角度进一步测试了基金的承压能力，并基于动态费率调整机制测算出理论费率水平，与现行费率进行对比分析。根据费率测算结果，评估了现行费率水平下调整相关政策的可能性，测算了能够扩大的失能等级保障范围，并提出了相应的政策建议。

［关键词］试点地区长期护理保险；人口预测；基金测算模型；动态费率调整机制

［基金项目］中国保险学会2024年度课题项目“我国长期护理保险的发展困境及破局路径研究”（ISCKT2024-N-1-21）、国家自然科学基金青年项目“高维时间序列预测与推断问题研究”（72201093）。

［作者简介］毕达宁，湖南大学金融与统计学院助理教授、保险精算系副主任；叶豆，湖南大学金融与统计学院硕士研究生；张建浩，南开大学金融学院硕士研究生；张琳（通讯作者），湖南大学风险管理与保险精算研究所所长、金融与统计学院教授。

Long-Term Care Insurance Premium Setting Based on Fund Estimation in Pilot Areas：A Case Study of Shanghai，Guangzhou，Qingdao，and Chongqing

BI Da-ning，YE Dou，ZHANG Jian-hao，ZHANG Lin

Abstract：This paper comprehensively applies the CHARLS database，multi-state Markov models，demographic and interest rate forecasting models，and fund estimation models to conduct an in-depth analysis and prediction of the actual operation of long-term care insurance in four pilot cities：Shanghai，Guangzhou，Qingdao，and Chongqing.The study predicts the fund balance for the next decade on both theoretical and practical levels.The research finds that while the actual fund balance of long-term care insurance in these cities has been expanding year by year，there is a discrepancy between theoretical and actual balances.The paper further tests the pressure bearing capacity of the fund from the perspectives of benefit amounts and the number of insured individuals through actuarial balanced calculations.Based on the dynamic premium adjustment mechanism，the paper estimates the theoretical premium rates and compares them with the current premium rates.It also assesses the probability to adjust relevant policies and calculates the extent to which the disability grades can be expanded to broaden its scope of protection and offers related policy suggestions.

Key words：long-term care insurance in pilot areas;population forecasting;fund estimation models;dynamic premium rate adjustment mechanism