Does the Market Pay Off? Earnings Inequality and Returns to Education in Urban China

The paper examines earnings inequality and earnings returns to education in China among four types of workers characterized by their labor market history. Compared to workers staying in the state sector, early market entrants no longer enjoyed advantages. The commonly observed higher earnings returns to education in the market sector are only limited to recent market entrants. This results from the aggregation of two very different types of workers: those who were "pushed" and those who "jumped" into the market in later stage of the reform. The findings challenge the prevailing wisdom that education is necessarily more highly rewarded by the market sector.http://deepblue.lib.umich.edu/bitstream/2027.42/39838/3/wp454.pd

Embracing the Market: Entry into Self-Employment in Transitional China, 1978-1996

This paper introduces labor market transition as an intervening process by which the macro institutional transition to a market economy alters social stratification outcome. Rather than directly addressing income distribution, it examines the pattern of workers’ entry into self-employment in reform-era China (1978-1996), focusing on rural-urban differences and the temporal trend. Analyses of data from a national representative survey in China show that education, party membership and cadre status all deter urban workers’ entry into self-employment, while education promotes rural workers’ entry into self-employment. As marketization proceeds, the rate of entry into self-employment increases in both rural and urban China, but urban workers are increasingly more likely to take advantages of the new market opportunities. In urban China, college graduates and cadres are still less likely to be involved in self-employment, but they are becoming more likely to do so in the later phase of reform. The diversity of transition scenarios is attributed to rural-urban differences in labor market structures.Market, Rural China, Self-employment, Transition, and Urban China

Study on the Wald-W Method of Uncertain Decision-making

AbstractUncertain decision-making is one of important research areas in the decision-making theory. For a long time five decision standards such as optimism decision standard, pessimism decision standard, compromised decision standard, equality decision standard and regret decision standard have been regarded as a model in all the available literatures. This article put forwards a new type of uncertainty decision-making method, and makes a more systematic study of Wald-W method through the way of solving matrix game

Predictive and Personalized Medicine with Systems Biology Solutions

poster abstractSystems biology refers to the use of systems engineering and systems science techniques to the understanding of biological systems. At Indiana Center for Systems Biology and Personalized Medicine (ICSBPM), we are particularly interested in developing systems biology techniques that can help shorten the gaps between basic biomedical research and clinical applications of genome sciences toward predictive and personalized medicine. In the past several years, ICSBPM has developed many critical informatics resources for the systems biology and personalized medicine community. The database and software tools that we developed have promoted systems biology and personalized medicine research communities at the national scale. These tools include: HPD, an integrated human pathway database and analysis tool (Chowbina et al., in BMC Bioinformatics 2009, 10(S11): S5); HAPPI, a human annotated and predicted protein interaction database (Chen et al., in BMC Genomics 2009, 10(S1):S16); HIP2, a Database of Healthy Human Individual's Integrated Plasma Proteome (Saha et al., in BMC Medical Genomics 2008, 1(1):12); PEPPI, a Peptidomic Database of Protein Isoforms (Zhou et al., in BMC bioinformatics 2010, 11(S6), S7); ProteoLens, a multi-scale network visualization and data mining tool (Huan et al., in BMC bioinformatics 2008, 9(S9):S5); GeneTerrain, a visual exploration tool for network-organized expression panel biomarker development (You et al., in Information Visualization 2010, 9(1)), and C-Maps, comprehensive molecular connectivity maps between disease-specific proteins and drugs (Li et al., in PLoS Computational Biology, 5(7), e1000450). These tools has been demonstrated to help improve tumor classifications, understand cancer biological systems at the systems scale, tackle biomarker discovery challenges, and facilitate clinical adoption of predictive models developed from computational techniques. We hope that our experience and resources can cement collaborative translational medicine research towards predictive and personalized medicine applications