نبذة مختصرة : Thesis (Ph.D.)--University of Washington, 2022 ; In this dissertation, I explore three seemingly disparate but inter-connected questions related to China’s strategies for human capital maintenance and accumulation. Hereinafter, a brief outline of each of the three chapters is given. In the first chapter, I investigate how efficiently the Chinese government designs a public health insurance program, namely the New Rural Cooperative Medical Scheme (NRCMS), in a hierarchical medical system. To study the welfare effects of adjusting the plan’s policies, I construct and structurally estimate a two-stage choice model based on a set of medical claims data of all inpatients enrolled in the NRCMS between 2012 and 2014 from a representative county of China. In the first stage, a patient chooses one of the hospitals available to treat his or her disease with imperfect information of health status; in the second stage, the patient decides a spending level according to his or her realized health risk, moral hazard type, and the cost-sharing structure in the chosen hospital. According to my model, patients can exhibit diverse risk attitudes that affect their hospital choices, and a higher- deductible plan can improve social welfare if generosity increases mistrust among patients with minor diseases. Indeed, empirical results confirm these concerns, and eventually lead me to suggest the Chinese government to increase both the deductible and reimbursement maximum for social welfare gains as well as public acceptance. In this first chapter, I focus on the demand side of China’s healthcare system to understand how China maintains the health capital of its rural residents. In the meanwhile, I identify efficiency issues caused by how consumers respond to the way in which China manages health capital, and propose policy recommendations to improve economic efficiency. I realize that the efficiency issues in China’s healthcare system come from not only the demand side but also the supply side. Thus, I present my second chapter, which ...
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