The Society for Social Work and Research

2013 Annual Conference

January 16-20, 2013 I Sheraton San Diego Hotel and Marina I San Diego, CA

Asset Poverty in Urban China: A Study Using the 2002 Chinese Household Income Project

Schedule:
Friday, January 18, 2013: 3:30 PM
Marina 2 (Sheraton San Diego Hotel & Marina)
* noted as presenting author
Minchao Jin, MSW, Student, Washington University in Saint Louis, St. Louis, MO
Jin Huang, PhD, Assistant Professor, Saint Louis University, St. Louis, MO
Suo Deng, PhD, Assistant Professor, Peking University, Beijing, China
Baorong Guo, PhD, Assistant Professor, University of Missouri-Saint Louis, St. Louis, MO
Li Zou, MSW, International Director, Washington University in Saint Louis, St Louis, MO
Michael Sherraden, PhD, Benjamin E. Youngdahl Professor of Social Development and Director of the Center for Social Development, Washington University in Saint Louis, St. Louis, MO
Background and Purpose:Since the economic reform in 1978, the remarkable economic growth of China has drawn the world’s attention.  However, it has also brought significant inequality in wealth distribution. By defining asset poverty as insufficiency of assets to satisfy household basic needs for a limited period of time, the study estimates asset-poverty rates in urban China based on different asset-poverty lines, investigates characteristics of asset-poor households, then examines interactions between asset poverty, income poverty, and public assistance, and finally, discusses policy implications of asset-poverty research in China.  

Methods:This study uses the China Household Income Project (CHIP) 2002 data, which is the most updated national representative data including asset assessment. Samples of the CHIP study uses a multistage stratified probability sampling method, including cases from eastern, central, and western regions of China. The sub-dataset for urban area has a sample size of 6,835 households and 20,632 individuals from 77 cities. Referring to Minimum Living Standard (MLS), Khan’s poverty line, and the minimum expense self-reported, different asset-poverty lines are set for calculating asset-poverty rate based using net worth, net worth minus home equity, and liquid asset. In addition to the descriptive statistics, logistic regression and multinomial logit model are conducted to test the association among asset poverty, income poverty, and household demographics.

Results:The asset poverty rate based on net worth is from 2.16% to 2.39% varied by different asset-poverty lines, while the rate based on net worth minus home equity is from 5.05% to 6.36%. The liquid asset poverty rate based on the MLS line is about 17%, five times that of the income poverty rate (3.3%) in urban China. Households headed by males, young adults (age from 20-29), non Communist Party members, non-married persons, renters, or people with low income, are more likely to be asset poor.

Conclusions and Implications: We find that asset poverty rates in urban China are lower than those of developed countries, in part due to Chinese households’ strong commitment to precautionary savings and the low poverty standards. Despite these low asset-poverty rates, asset poverty still appears to be a serious problem as indicated by the ratio of the liquid asset-poverty rate to the income poverty rate. To exacerbate this situation, social protection programs in China are poorly funded. Therefore, it is crucial to encourage poor people to accumulate assets against economic hardship, which asks for asset-building policy innovations that target vulnerable populations.