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2016/10/22. Symposium on Income Inequality and Social Policy in China: Achievement, Challenges, and Directions
The workshop will be held on 20th September 2016, and it aims to inspire discussions and knowledge sharing on minimum wage. Two famous Labor economics expert, John Addison (University of South Carolina) and David Neumark (University of California, Irvine) will be invited as keynote speakers. Many domestic economists and researchers will also be invited to promote academic communication exchange. It is with great pleasure that we write to call for your papers.
The 5 wave micro-data of Chinese Household Income Project (CHIP2013) was released
"Famous Professors Overseas" supported by Ministry of Education of the PRC
6 November, Beijing, The United Nations Development Program (UNDP) held the workshop themed “BRICS: Inequality and Sustainable Development”, co-organized by Beijing Normal University (BNU) and Actionaid China.

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Adopting a simple demand system, we aim to re-estimate China.s income inequality using the Urban Household Survey (UHS) data assuming the expenditure data is well measured. We find income inequality growth exceeds the growth rate of consumption inequality, although income inequality is still lower than consumption inequality over the period 2003-2009. We also .nd that the increase of income inequality is mainly due to the increase of inequality between the middle expenditure group and the high expenditure group, while the income inequality between the middle-expenditure group and the low-expenditure group slightly decreases. This not only confirms the presence of pervasive grey income, also implying that grey incomes mostly exist in the high-expenditure stratum. Following Aguiar and Bils (2015), we assume that the Engel coeffcient is log-linear and that the income elasticities are constant over time. In the robustness test, we relax the assumptions and find that the estimation results are still robust.
Most poverty research has explored monetary poverty. This paper presents and analyses the global Multidimensional Poverty Index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to sub-groups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.
China’s Rural Minimum Living Standard Guarantee program (Dibao) is the largest social safety-net program in the world. Given the scale and the popularity of Rural Dibao, it is necessary to rigorously evaluate it so that policymakers know the extent to which the program meets its intended objective of reducing poverty. This paper develops some new methods and uses data from the 2013 Chinese Household Income Project (CHIP2013) to examine the targeting performance of the rural Dibao program. The paper has found that the Rural Dibao program suffers from very low targeting accuracy, high exclusion error, and inclusion error, and yields a significant negative social rate of return. It discusses possible causes and argues that the fundamental mechanism has to be redesigned to increase the effectiveness of the program. The paper makes some recommendations to reform Dibao that will significantly improve targeting and reduce the cost of running the program. That will help China to achieve its goal of eradicating extreme poverty by 2020.
Numerous empirical studies have documented a strong association between social networks and individuals' migration decisions. Few papers formally analyse how social networks affect both migration decisions that affect the evolution of social networks overtime, and labor market outcomes. In order to understand these relationships, I develop and estimate a dynamic model with return and repeated migration, social network investment decisions and labor market transitions. The model distinguishes between two channels through which social networks may affect migration decisions: (1) a direct effect on migration costs and (2) an indirect effect on labor market outcomes through the job arrival rate. I use the model to study one of the largest ongoing internal migrations in human history: rural-urban migration in China. To estimate the model, I use panel data from the Chinese Household Income Project (2007-2009). The estimation results show that social networks affect both channels significantly. Individuals with networks have 40% higher job arrival rate than those without networks on average. In addition, social networks reduce average migration costs by 7%. I also show that policies that directly lower migration costs may be more cost effective at increasing rural-urban migration in China. These policy experiments also show that without considering the impact of network investment, the government has to spend more to offset the effect of no investment in social networks.
We use 1995, 2002 and 2013 CHIP data to investigate the urban household consumption expenditure inequality. The overall inequality of urban household consumption expenditure measured by Gini coefficient slightly decreases from 0.33 in 1995 to 0.32 in 2002, but increases to 0.36 in 2013. However, the percentile ratio of p90/p10 shows that consumption inequality increases all the time. Besides, the inequality of basic food consumption is much smaller than the overall consumption, its contribution to the overall consumption inequality decreases from 20% in 1995 and 2002 to 15% by 2013, and its share also decreases steadily from 34% in 1995 to 30% in 2002 and further to 24% in 2013, and finally its share steadily decreases as the overall consumption level moving up the distribution in each of the three years. The inequality of housing consumption is much larger than overall consumption but decreasing over time, its contribution to the overall consumption inequality increases 35% in earlier two years to 40% by 2013, and its share also sharply increases from 23% in 1995 to 30% in 2002 and further to 38% in 2013, besides its share shows upward sloping as overall consumption level increases in each of the three years.
Workshop on Minimum Wages and Field Experiment will be hold in Nov. 7th, 2017.