This paper develops an overlapping generations (OLG) model with discrete choice agents to analyze how land asset constraints affect intergenerational welfare in China. Although urban migration provides higher wages and enhanced pension benefits, rural households incur significant costs: high housing expenditures and the loss of land value, which deter relocation. The results underscore the role of institutional barriers in perpetuating rural-urban disparities, and suggest that reforming land and pension policies is critical to mitigating long-term welfare imbalances. 

Why migrants from different regions experience unequal levels of acceptance in their destinations? I develop a Bayesian framework in which locals update beliefs about migrant quality using two types of information: personal achievements and the collective reputation of the migrant’s hometown. The model predicts that migrants from economically stronger hometowns are judged more favorably, while those from weaker origins face greater rejection, and that dialect distance magnifies both effects. The results demonstrate how language and regional identity interact with economic background to shape migrants’ experiences of acceptance and exclusion.

I develop a heterogeneous-agents overlapping-generations model with urban–rural segmentation, endogenous fertility and migration, and explicit monetary and time costs of child-rearing. Using data from the China Household Panel Survey, I assess three recent education reforms: the "double reduction" policy (cutting homework and after-school tutoring), free kindergarten, and childbirth subsidies. Lower child-rearing costs raise fertility and increase parents’ leisure in the short run, reducing aggregate output by about 0.5 percent. Fertility in urban areas is more responsive. In the longer run, larger cohorts expand labor supply and boost output when the children reach working age.