Bai Xiao

Dr. Bai Xiao

Zhejiang University of Finance & Economics
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2019 in Technological Forecasting and Social Change
Verified
Journal Article
Closed access
SLShibao Lu
Shibao Lu
BXBai Xiao
Bai Xiao
WLWei Li
Wei Li
NWNing Wang
Ning Wang

25 July 2022 in Economic Analysis and Policy
Verified
Journal Article
Closed access
BXBai Xiao
Bai Xiao
KWKuan-Ting Wang
Kuan-Ting Wang
TTTrung Kien Tran
Trung Kien Tran
MSMuhammad Sadiq
Muhammad Sadiq
LTLam Minh Trung
Lam Minh Trung
KKKhurshid Khudoykulov
Khurshid Khudoykulov

17 March 2023 in Economic Analysis and Policy
Verified
Journal Article
Closed access
XWXin Wu
Xin Wu
BXBai Xiao
Bai Xiao
Hanying QiHanying Qi
Hanying Qi
LLLanxin Lu
Lanxin Lu
MYMingyuan Yang
Mingyuan Yang
FTFarhad Taghizadeh-Hesary
Farhad Taghizadeh-Hesary

1 September 2016 in International Journal of Hydrogen Energy
Verified
Journal Article
Open access
MXMeng Xu
Meng Xu
BXBai Xiao
Bai Xiao
Liang PeiLiang Pei
Liang Pei
HPHulin Pan
Hulin Pan

1 October 2019 in Journal of Cleaner Production
Verified
Journal Article
Closed access
SLShibao Lu
Shibao Lu
BXBai Xiao
Bai Xiao
XZXiaoling Zhang
Xiaoling Zhang
WLWei Li
Wei Li
YTYao Tang
Yao Tang

LWLianjie Wang
Lianjie Wang
YTYao Tang
Yao Tang
FRFarnaz Roshanmehr
Farnaz Roshanmehr
BXBai Xiao
Bai Xiao
FTFarzad Taghizadeh-Hesary
Farzad Taghizadeh-Hesary
Farhad Taghizadeh-HesaryFarhad Taghizadeh-Hesary
Farhad Taghizadeh-Hesary
(1) Background: Because of the rapid expansion of the aging population in China, their health status transition and future medical expenditure have received increasing attention. This paper analyzes the health transition of the elderly and how their health transition impacts medical expenditures. At the same time, feasible policy suggestions are provided to respond to the rising medical expenditure and the demand for social care. (2) Methods: The data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015 and analyzed using the Markov model and the Two-Part model (TPM) to forecast the size of the elderly population and their medical expenditures for the period 2020–2060. (3) Results: The study indicates that: (1) for the elderly with a mild disability, the probability of their health improvement is high; in contrast, for the elderly with a moderate or severe disability, their health deterioration is almost certain; (2) the frequency of the diagnosis and treatments of the elderly is closely related to their health status and medical expenditure; alternatively, as the health status deteriorates, the intensity of the elderly individuals’ acceptance of their diagnosis and treatment increases, and so does the medical expense; (3) the population of the elderly with mild and moderate disability demonstrates an inverted “U”-shape, which reaches a peak around 2048, whereas the elderly with severe disability show linear growth, being the target group for health care; (4) with the population increase of the elderly who have severe disability, the medical expenditure increases significantly and poses a huge threat to medical service supply. Conclusions: It is necessary to provide classified and targeted health care according to the health status of the elderly. In addition, improving the level of medical insurance, establishing a mechanism for sharing medical expenditure, and adjusting the basic demographic structure are all important policy choices.