Purpose The purpose of this paper is to estimate the value of a statistical life (VSL) in China using the hedonic wage model, and to explore the regional difference in VSL within the country. #n#Design/methodology/approach - Using the hedonic wage regression, this paper estimates the compensating wage differential for incremental job mortality risk among Chinese workers. The implied VSL is derived for China and its different regions. The data is from the 2005 China inter-census population survey, consisting of 1.3 million urban and rural workers. The authors also made important improvement in the model specification to explicitly address the missing variable issue in the previous studies. #n#Findings - The paper results indicate that the industry mortality risk has a significant impact on the wage rate. The implied VSL is 1.81 million RMB, a value substantially higher than previous estimates. The results also suggest a sizable urban-rural difference, with the urban VSL being 4.3 times higher than the rural estimate. The strong urban-rural inequality of income could be attributed to the segregation between the urban and rural labor markets. Practical implications The paper findings indicate the importance of reforming the current workers' compensation standard and improving the institutional environment, as well as enhancing the labor protection in the rural labor market. #n#Originality/value - This paper is the first attempt to estimate the value of life in China using the census based data. The paper results contribute to the growing literature in obtaining comparable VSL estimates in the developing countries.
For video copy detection, no single audio-visual feature, or single detector based on several features, can work well for all transformations. This article proposes a novel video copy-detection and localization approach with scalable cascading of complementary detectors and multiscale sequence matching. In this cascade framework, a soft-threshold learning algorithm is utilized to estimate the optimal decision thresholds for detectors, and a multiscale sequence matching method is employed to precisely locate copies using a 2D Hough transform and multigranularities similarity evaluation. Excellent performance on the TRECVID-CBCD 2011 benchmark dataset shows the effectiveness and efficiency of the proposed approach.
We propose a well-balanced stable generalized Riemann problem (GRP) scheme for the shallow water equations with irregular bottom topography based on moving, adaptive, unstructured, triangular meshes. In order to stabilize the computations near equilibria, we use the Rankine-Hugoniot condition to remove a singularity from the GRP solver. Moreover, we develop a remapping onto the new mesh (after grid movement) based on equilibrium variables. This, together with the already established techniques, guarantees the well-balancing. Numerical tests show the accuracy, efficiency, and robustness of the GRP moving mesh method: lake at rest solutions are preserved even when the underlying mesh is moving (e.g., mesh points are moved to regions of steep gradients), and various comparisons with fixed coarse and fine meshes demonstrate high resolution at relatively low cost. Copyright (c) 2013 John Wiley & Sons, Ltd.