ESSAYS ON THE WTO ACCESSION, HOUSEHOLD INCOME AND MULTIDIMENSIONAL POVERTY: EVIDENCE FROM CHINA

In the course of integrating into the global market, especially since China’s WTO accession, China has achieved remarkable GDP growth and has become the second largest economy in the world. These economic achievements have substantially increased Chinese incomes and have generated more government revenue for social progress. However, China’s economic progress, in itself, is neither sufficient for achieving desirable development outcomes nor a guarantee for expanding peoples’ capabilities. In fact, a narrow emphasis on GDP growth proves to be unsustainable, and may eventually harm the life quality of Chinese citizens. Without the right set of policies, a deepening trade-openness policy in China may enlarge social disparities and some people may further be deprived of basic public services and opportunities. To address these concerns, this dissertation, a set of three essays in Chapters 2-4, examines the impact of China's WTO accession on income distribution, compares China’s income and multidimensional poverty reduction and investigates the factors, including the WTO accession, that predict multidimensional poverty. By exploiting the exogenous variation in exposure to tariff changes across provinces and over time, Chapter 2 (Essay 1) estimates the causal effects of trade shocks and finds that China’s WTO accession has led to an increase in average household income, but its impacts are not evenly distributed. Households in urban areas have benefited more significantly than those in rural areas. Households with members working in the private sector have benefited more significantly than those in the public sector. However, the WTO accession has contributed to reducing income inequality between higher and lower income groups. Chapter 3 (Essay 2) explains and applies the Alkire and Foster Method (AF Method), examines multidimensional poverty in China and compares it with income poverty. It finds that China’s multidimensional poverty has declined dramatically during the period from 1989-2011. Reduction rates and patterns, however, vary by dimensions: multidimensional poverty reduction exhibits unbalanced regional progress as well as varies by province and between rural and urban areas. In comparison with income poverty, multidimensional poverty reduction does not always coincide with economic growth. Moreover, if one applies a single measure ─ either that of income or multidimensional poverty ─ a certain proportion of those who are poor remain unrecognized. By applying a logistic regression model, Chapter 4 (Essay 3) examines factors that predict multidimensional poverty and finds that the major factors predicting multidimensional poverty in China include household size, education level of the household head, health insurance coverage, geographic location, and the openness of the local economy. In order to alleviate multidimensional poverty, efforts should be targeted to (i) expand education opportunities for the household heads with low levels of education, (ii) develop appropriate geographic policies to narrow regional gaps and (iii) make macroeconomic policies work for the poor.

Studying the Causes and Consequences of Internal Labor Migration Using Survey and Administrative Data Sources

This dissertation comprises three chapters. The first chapter motivates the use of a novel data set combining survey and administrative sources for the study of internal labor migration. By following a sample of individuals from the American Community Survey (ACS) across their employment outcomes over time according to the Longitudinal Employer-Household Dynamics (LEHD) database, I construct a measure of geographic labor mobility that allows me to exploit information about individuals prior to their move. This enables me to explore aspects of the migration decision, such as homeownership and employment status, in ways that have not previously been possible. In the second chapter, I use this data set to test the theory that falling home prices affect a worker’s propensity to take a job in a different metropolitan area from where he is currently located. Employing a within-CBSA and time estimation that compares homeowners to renters in their propensities to relocate for jobs, I find that homeowners who have experienced declines in the nominal value of their homes are approximately 12% less likely than average to take a new job in a location outside of the metropolitan area where they currently reside. This evidence is consistent with the hypothesis that housing lock-in has contributed to the decline in labor mobility of homeowners during the recent housing bust. The third chapter focuses on a sample of unemployed workers in the same data set, in order to compare the unemployment durations of those who find subsequent employment by relocating to a new metropolitan area, versus those who find employment in their original location. Using an instrumental variables strategy to address the endogeneity of the migration decision, I find that out-migrating for a new job significantly reduces the time to re-employment. These results stand in contrast to OLS estimates, which suggest that those who move have longer unemployment durations. This implies that those who migrate for jobs in the data may be particularly disadvantaged in their ability to find employment, and thus have strong short-term incentives to relocate.