This dissertation is to connect empirical findings with grounded theoretical analysis on two economic
issues. One of the studies investigates industrial productivity by fitting in a theoretical model with quantitative
methods. In addition, I explore how a demographic policy in China brings forth a profound impact
in all aspects of the fast-growing economy.
The first chapter, “Casual Labor, Uncertainty, and Technology Adoption in Agriculture,” examines why
both the technology adoption rate and labor productivity in agriculture are low in the context of developing
countries. A two-stage model is built to explain how the availability of casual (non-permanent) labor ex-post,
in the presence of uncertainty may affect agents’ ex-ante technology choices. A higher degree of uncertainty
induces the agents to choose traditional production technology that relies heavily on the labor input instead
of using any modern intermediate inputs. By calibrating the model to fit the micro data in Tanzania, I
show that this proposed framework can be used to account for two targets of interest: low aggregate labor
productivity and the low technology adoption rate. Counterfactual exercises suggest that the severity of
uncertainty before the harvest stage and the abundance of casual labor are the potential drivers for the two
targets to be explained.