Shenggen Fan

Xiaobo Zhang

Ravi Kanbur

China’s spectacular growth and poverty reduction has been accompanied by growing inequality which threatens the social compact and thus the political basis for economic growth. Chinese policy makers have realized the importance of the problem and have launched a series of investigations and policy initiatives to address the issues. The regional dimension of inequality—rural/urban and inland/coastal—dominates in a country as large as China, and especially with its particular history. Not surprisingly, regional inequality has come to loom large in the policy debate in China. The policy debate has been informed by, and to some extent instigated by, a parallel analytical literature which has quantified the magnitude of the problem and identified recent trends, offered explanations based on rigorous analysis, and proposed policy interventions in light of the facts and understanding. Through a series of articles which have been published in leading journals, the editors have been involved in a systematic investigation into the nature and evolution of regional inequality in China for over a decade.

Trends, Explanations and Policy Responses

Regional Inequality in China

Xiang Zhou

Yu Xie

Qi Xu

Chunni Zhang

Knowledge of actual poverty prevalence is important for any society concerned with improving public welfare and reducing poverty. In this paper, we calculate and compare the poverty incidence rate in China using four nationally representative surveys: the China Family Panel Studies (CFPS) of 2010, the Chinese General Social Survey (CGSS) of 2010, the Chinese Household Finance Survey (CHFS) of 2011, and the Chinese Household Income Project (CHIP) of 2007. Using both international and official domestic poverty standards, we show that poverty prevalence at the national, rural, and urban levels based on the CFPS, CGSS, and the CHFS are much higher than the official estimation and those based on the CHIP. The study highlights the importance of using independent datasets to validate official statistics of public and policy concern in contemporary China.

New Evidence from Four Recent Surveys

An Evaluation of Poverty Prevalence in China

This book reviews the latest research on the molecules and mechanisms of marine host stress responses to viral infections and tumorigenesis. It offers an overview of the state of the art in the field as well as future directions. Metabolism disorder is a characteristic of tumorigenesis. Since viruses complete their life cycle in host cells, such infections cause metabolic disorders in the host. As such, the mechanisms of virus pathogenesis and tumor progression are similar or even identical. In essence, the role of antiviral molecules is to maintain the metabolic homeostasis of infected host cells, and the antiviral molecules induced by virus infection may play an important role in antitumor pathways, resulting in cancer cell death or restoring the disordered metabolism of cancer cells. The molecules generated during host stress responses to viruses can also contribute to the antitumor mechanisms in humans. However, the relationship between host stress responses to virus infection and tumorigenesis has not been extensively explored. In recent years, studies have shown that marine host stress responses to viral invasion can be good models for exploring human antitumor mechanisms. Stimulating further research in the field, this book offers graduate students and researchers with comprehensive insights into host stress responses to viral invasion and tumor progression. It is also a valuable resource for those working in the pharmaceutical industry interested in drug discovery based on molecules derived from host stress responses to viral infection.

Hints from Marine Hosts’ Stress Responses

Virus Infection and Tumorigenesis

Linxiu Zhang

Growth, inequality, and poverty; Public capital e investment; Concptual framework and model; Data, estimation, and results.

The Role of Public Investments

Growth, Inequality, and Poverty in Rural China

Sachi Nandan Mohanty

Tanupriya Choudhury

Rabinarayan Satpathy

Suneeta Satpathy

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

A Machine Learning Perspective

Data Analytics in Bioinformatics

Haipeng Xing

Inspired by the wide adoption of rigorous randomized controlled trials (RCTs) in medical research, economists and other social scientists have increasingly used RCTs in their research. As researchers pick up projects amenable to the RCT methodology, they likely leave out important questions to which RCTs cannot be directly applied. As a result, RCTs have been criticized for the proclivity of addressing trivial questions. As a matter of fact, in medical research RCTs are an integral part of adaptive sequential experiment designa few steps must be taken to screen out drugs that have toxins and strong side effects before running any RCTs on humans. In this paper, we argue that economists can learn a great deal from the design principles implemented in medical research. We develop a theoretical model to show the logic of adaptive sequential experiment design in the presence of uncertainty over negative effects and discuss how to choose samples in a population to minimize the experiment cost. We also point out the applications of our proposed framework in the economic domain, such as economic reforms and new product design.

The Logic of Adaptive Sequential Experimentation in Policy Design

Shang-Jin Wei

S. M. Ravi Kanbur

This Oxford Companion to the Economics of China presents a new collection of perspectives on the Chinese economy's past, present and future. The contributors of these entries include: the best of young Chinese researchers based in China and outside; renowned academics from the top universities in China, Europe and North America; present and past senior officials of international agencies like the World Bank and the International Monetary Fund; seniorChinese government officials from the Centre and the Provinces; and four recipients of the Nobel Prize in Economics. The Editors are four global leaders in Chinese economic analysis and policy who between them have held or hold the following positions: Director General, International Food Policy ResearchInstitute; Co-Editor, China Economic Review; President Chinese Economists Society; Assistant Director of Research at the IMF; Principal Adviser to the Chief Economist of the World Bank; and Professors of Economics at Ivy League Universities.

Xiaobo Zhang

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