Road development, economic growth, and poverty reduction in China

"Since 1978, China has adopted a series of economic reforms leading to rapid economic growth and poverty reduction. National Gross Domestic Product (GDP) grew at about 9 percent per annum from 1978 to 2002, while per capita income increased by 8 percent per annum. The post-reform period was also characterized by an unprecedented decline in poverty. However, income inequality has worsened between coastal and interior provinces as well as between rural and urban areas. A number of factors contributed to this widening disparity in regional development in China, including differences in natural resources endowments, and infrastructure and human capital development... The objective of this study is to assess the impact of public infrastructure on growth and poverty reduction in China, paying a particular attention to the contribution of roads. ...The most significant finding of this study is that low quality (mostly rural) roads have benefit/cost ratios for national GDP that are about four times larger than the benefit/cost ratios for high quality roads. Even in terms of urban GDP, the benefit/cost ratios for low quality roads are much greater than those for high quality roads." from Authors' AbstractHuman capital ,

Road development, economic growth, and poverty reduction in China:

"Since 1985, the Chinese government has given high priority to building roads, particularly high-quality roads that connect industrial centers. This report evaluates the contribution roads have made to poverty reduction and economic growth in China over the last two decades. It disaggregates road infrastructure into different classes to account for differences in their quality, and then estimates the impact of road investments on overall economic growth, agricultural growth, urban growth, urban poverty reduction, and rural poverty reduction. The report makes the case for a greater focus on low-quality and rural roads in future infrastructure investment strategies in China. It does so by showing how investing in low-quality and rural roads will generate larger marginal returns, raise more people out of poverty per yuan invested, and reduce regional development disparity more sharply than investing in high-quality roads. The study's findings will have considerable implications for China's infrastructure policy." Authors' AbstractHuman capital,

Combining Local Appearance and Holistic View: Dual-Source Deep Neural Networks for Human Pose Estimation

We propose a new learning-based method for estimating 2D human pose from a single image, using Dual-Source Deep Convolutional Neural Networks (DS-CNN). Recently, many methods have been developed to estimate human pose by using pose priors that are estimated from physiologically inspired graphical models or learned from a holistic perspective. In this paper, we propose to integrate both the local (body) part appearance and the holistic view of each local part for more accurate human pose estimation. Specifically, the proposed DS-CNN takes a set of image patches (category-independent object proposals for training and multi-scale sliding windows for testing) as the input and then learns the appearance of each local part by considering their holistic views in the full body. Using DS-CNN, we achieve both joint detection, which determines whether an image patch contains a body joint, and joint localization, which finds the exact location of the joint in the image patch. Finally, we develop an algorithm to combine these joint detection/localization results from all the image patches for estimating the human pose. The experimental results show the effectiveness of the proposed method by comparing to the state-of-the-art human-pose estimation methods based on pose priors that are estimated from physiologically inspired graphical models or learned from a holistic perspective.Comment: CVPR 201

Rural and urban dynamics and poverty: Evidence from China and India

"Like many developing countries, China and India followed development strategies biased in favor of the urban sector over the last several decades. These development schemes have led to overall efficiency losses due to misallocation of resources among rural and urban sectors. It also led to large income gaps between rural and urban areas. The urban bias was greater in China than in India. Indeed, official data show that both the income gap and the difference in poverty rates between rural and urban areas are much larger in China than in India. Both countries have corrected the rural-urban divide to some extent as part of reform processes. But the bias still exists. Other studies also support the idea presented here that correcting this imbalance will not only contribute to higher rural growth, but also secure future urban growth (Fan and Chan-Kang 2005). More important, correcting the urban bias will lead to larger reductions in poverty as well as more balanced growth across sectors and regions. Correcting a government's bias towards investment in urban areas is one of the most important policies to pursue." from Authors' AbstractRural-urban linkages ,Poverty ,