DOI: 10.57760/sciencedb.35801
title: Charls Database Long Term Care Insurance Dataset
title: Charls Database Long Term Care Insurance Dataset

description: This article uses data from four rounds of follow-up surveys conducted by CHARLS (China Health and Retirement Longitudinal Study) in 2013, 2015, 2018, and 2020. The survey was conducted in 28 provincial-level units across the country, with the aim of building a micro database of individuals and families that is both nationally representative and regionally heterogeneous, targeting the middle-aged and elderly population aged 45 and above. In the data processing stage, the first step is to vertically merge the data from four periods. The sample scope is limited to children whose parents have at least one parent who is covered by urban employee medical insurance and have difficulty in at least one of the 14 evaluation criteria. In all pilot cities, the insured objects of long-term care insurance include individuals who participate in urban and rural employee medical insurance, and some pilot cities also cover individuals who participate in basic medical insurance for urban and rural residents. In order to avoid the influence of differences in personal characteristics between urban employee medical insurance insured persons and urban and rural resident medical insurance insured persons on the estimation results, this study only takes urban employee medical insurance insured persons as the analysis objects. To further ensure data quality and model applicability, this article excluded samples with missing core variables such as ADL, labor participation, and employment quality, and finally retained individuals with data records before and after 2016, forming a non-equilibrium with 9154 observation values and a total of 4460 individuals. Panel dataset.
description: This article uses data from four rounds of follow-up surveys conducted by CHARLS (China Health and Retirement Longitudinal Study) in 2013, 2015, 2018, and 2020. The survey was conducted in 28 provincial-level units across the country, with the aim of building a micro database of individuals and families that is both nationally representative and regionally heterogeneous, targeting the middle-aged and elderly population aged 45 and above. In the data processing stage, the first step is to vertically merge the data from four periods. The sample scope is limited to children whose parents have at least one parent who is covered by urban employee medical insurance and have difficulty in at least one of the 14 evaluation criteria. In all pilot cities, the insured objects of long-term care insurance include individuals who participate in urban and rural employee medical insurance, and some pilot cities also cover individuals who participate in basic medical insurance for urban and rural residents. In order to avoid the influence of differences in personal characteristics between urban employee medical insurance insured persons and urban and rural resident medical insurance insured persons on the estimation results, this study only takes urban employee medical insurance insured persons as the analysis objects. To further ensure data quality and model applicability, this article excluded samples with missing core variables such as ADL, labor participation, and employment quality, and finally retained individuals with data records before and after 2016, forming a non-equilibrium with 9154 observation values and a total of 4460 individuals. Panel dataset.