Moral hazard and adverse selection in India's and China's health insurance markets

• Main Authors: Tan, Reena Hui Ying, Seah, Charlotte Ning, Goh, Yuki (Wu Weiqi)
• Other Authors: Akshar Saxena
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Social sciences::Economic theory::Microeconomics
• Online Access: https://hdl.handle.net/10356/166300
• Institution: Nanyang Technological University

The phenomenon of adverse selection (AS) and moral hazard (MH) are significant impediments to an efficient insurance market. The Indian and Chinese health insurance markets both suffer the varying effects of AS and MH, hindering the provision of inclusive and efficient insurance coverage to their respective citizens. In this paper, we aim to analyse how adverse selection occurs in different forms of health insurance schemes (public and private) and how types of insurance enrolment affect healthcare usage (measured using hospitalisation) across various prevalent diseases, with India and China as case studies. This paper uses copula regressions due to the strengths in accounting for endogenity, potential nonlinear relationships between variables, and goes beyond the usual assumption of bivariate normality in selection models. The results for India show significant probability of AS and MH across chronic and acute diseases analysed in the public health insurance (PHI) system but relative absence in the private insurance market. In China, it has been observed that AS is not present for chronic diseases across all insurance types, while MH is observed to be significant across all diseases for PHIs but absent for private health insurance. With these findings, we discuss possible reasons for the presence or absence of AS and MH, and recommend solutions. Particularly, nationwide campaigns may empower the community and generate positive attitudes towards managing chronic diseases, and preventive healthcare coverage is effective in reducing MH. There is potential for these recommendations to be replicated in India.