Early Life Adversities and Well-being Later in Life: Evidence from China
As living conditions and healthcare technologies improve, individual life expectancy increases. The pattern is not only evident in developed countries but also in developing countries such as China. According to the World Population Prospect 2017 report by the United Nations, average life expectancy at birth in China has risen from 69.7 between 1990 and 1995 to 76.5 between 2015 and 2020, and it is projected to rise to 81.1 in the period 2045-2050. Yet, the goals of public health are not only about quantity but also about quality of life. Even though people now live longer, they wish to live in good health and financial well-being.
An expanding body of literature has documented that conditions early in life are important determinants of well-being at older ages. Therefore, if we want to understand how to improve financial, physical and mental health of older individuals, it is crucial to take a life-cycle perspective. In this thesis, I study the early life determinants of well-being at older ages in China.
I mainly focus on two factors that might affect old-age well-being: children’s support and early life adversities. Covered by less generous social insurance plans, poor households in China have to seek alternative support to finance their oldage consumption. One natural solution for parents is to find supports from their children. Children’s economic support for their parents might be further determined by parental human capital investment in children when they were at schooling ages. The second factor is the role of early life adversities. In China, the current cohort of older people might have experienced the Chinese Great Famine and/or the Cultural Revolution, potentially resulting in income losses during life and long-term negative health effects.
The main data is drawn from the China Health and Retirement Longitudinal Study (CHARLS). CHARLS is a nationally representative survey focusing on individuals aged above 45 years old, including data on intergenerational transfers, individual lifetime work histories, and blood-based biomarker information.