摘要
本文基于中国健康和营养调查2006年、2011年和2015年的数据,运用DID模型和Logit模型分析城镇居民医保对商业医疗保险的挤出效应。以2006年和2011年的数据作为样本组1,2006年和2015年的数据作为样本组2,初步的描述性统计发现样本组2购买商业医疗保险的概率略高于样本组1。实证结果表明,在剔除时间趋势效应后,样本组1中的城镇居民医保对商业医疗保险表现出显著的挤出效应,样本组2中的城镇居民医保则对商业医疗保险表现出显著的促进作用。因此,城镇居民医保对商业医疗保险的作用是先挤出后促进。稳健性检验的结果也支持这一结论,同时本文预测这种促进效应会随着收入水平的提高而逐渐增强。此外,对于其他影响商业医疗保险购买需求的因素,样本组1和样本组2的实证结果呈现出相似的结论:商业医疗保险的购买需求存在明显的地区差异,居住在中部以及西部地区的居民购买商业医疗保险的概率较低。
Utilizing the 2006, 2011 and 2015 data of the China Health and Nutrition Survey(CHNS),this paper uses DID model and Logit model to explore the crowding-out effect of urban residents basic medical insurance(URBMI) on commercial medical insurance(CMI). Our study takes the data from 2006 and 2011 as sample group 1, and data from 2006 and 2015 as sample group 2. Preliminary descriptive statistics finds that the probability of purchasing commercial medical insurance for the sample group 2 is slightly higher than that of the sample group 1. The empirical result shows that, after removing out the time effect, URBMI in sample group 1 shows a significant crowding out effect on CMI, while it shows a significant promoting effect on CMI in sample group 2. Therefore, URBMI crowds out CMI first and then promotes it. The results of the robustness test also support this conclusion, and the study predicts that the promotion effect will gradually increase as the income level increases. In addition, for other factors affecting the purchase demand of CMI, the empirical results of sample groups 1 and 2 show similar conclusions: there are obvious regional differences in the purchase demand of CMI, that residents living in the central and western district are less likely to purchase CMI.
出处
《暨南学报（哲学社会科学版）》
CSSCI
北大核心
2020年第2期99-109,共11页
Jinan Journal(Philosophy and Social Sciences)
基金
国家社会科学基金项目“劳动力迁移背景下基本医疗保险中‘系统老龄化风险’测度与应对研究”(批准号:17BJY205)
广州市哲学社会科学“十三五”规划课题“健康老龄化背景下公立医院‘医养结合’养老模式与政策扶持机制研究”(批准号:2016GZYB20)
中央高校基本科研业务费专项资金项目“城乡统筹背景下我国医疗保障体系问题研究”(批准号:13JNQN010)。
关键词
社会保障
医疗保险
城镇居民基本医疗保险
挤出效应
DID模型
social security
medical insurance
urban residents basic medical insurance
crowding-out effect
DID model
