China and the Multilateral Investment Guarantee Agency

The Multilateral Investment Guarantee Agency (MIGA), established in 1988, is part of the World Bank Group. Its mandate is to promote foreign investment in its member countries by providing political risk insurance and technical assistance to promote investment. In developing this case study of China's evolving relationship with MIGA, the author asked: Why did China decide to seek membership in MIGA? What was the outcome of the relationship between China and MIGA? How has that relationship affected economic and legal reform in China and the country's integration with the multilateral investment insurance system? How can MIGA strengthen its role? And how can MIGA prevent potential claims to its portfolio in China? MIGA's comparative advantages are its international experience in underwriting and operating its portfolio, its neutral position and approach, its mediation and legal advice, and the fact that its guarantee portfolio is unaffected by bilateral relations. The author suggested that in China, MIGA should screen foreign direct investment (FDI), not just encourage it, because some FDI in China has been of poor quality, with little transfer of skills and technology. Some local partners have conceded too many discounts to foreign investors, without considering the cost of key assets such as land and machinery. Some foreign investors have taken advantage of local officials'eagerness for foreign capital, pressuring them to grant guarantees they should not grant and to allow unacceptable levels of environmental pollution in industry. China receives one-third of all FDI in developing countries. To continue attracting such investment, it must design a rule-based legal system governing FDI, making its rules and regulations more transparent, uniform, and consistent with international practice. As a neutral third party, MIGA could make policy recommendations that authorities might consider and accept -- such as policies designed to encourage less investment in labor-intensive firms and more in high-tech industries.International Terrorism&Counterterrorism,Legal Products,Fiscal&Monetary Policy,Payment Systems&Infrastructure,Environmental Economics&Policies,Environmental Economics&Policies,Legal Products,National Governance,Foreign Direct Investment,International Terrorism&Counterterrorism

A Noise-Robust Fast Sparse Bayesian Learning Model

This paper utilizes the hierarchical model structure from the Bayesian Lasso in the Sparse Bayesian Learning process to develop a new type of probabilistic supervised learning approach. The hierarchical model structure in this Bayesian framework is designed such that the priors do not only penalize the unnecessary complexity of the model but will also be conditioned on the variance of the random noise in the data. The hyperparameters in the model are estimated by the Fast Marginal Likelihood Maximization algorithm which can achieve sparsity, low computational cost and faster learning process. We compare our methodology with two other popular learning models; the Relevance Vector Machine and the Bayesian Lasso. We test our model on examples involving both simulated and empirical data, and the results show that this approach has several performance advantages, such as being fast, sparse and also robust to the variance in random noise. In addition, our method can give out a more stable estimation of variance of random error, compared with the other methods in the study.Comment: 15 page

Bifurcation and dynamic response analysis of rotating blade excited by upstream vortices

Acknowledgements The authors acknowledge the projects supported by the National Basic Research Program of China (973 Project)(No. 2015CB057405) and the National Natural Science Foundation of China (No. 11372082) and the State Scholarship Fund of CSC. DW thanks for the hospitality of the University of Aberdeen.Peer reviewedPostprin

Eine neue Solidargemeinschaft? Die soziale Bedeutung der Flucht-und Migrationsliteratur

This thesis explores the capacity of literature about flight and migration to contribute to shaping a community of solidarity in contemporary German society. It analyses three novels published after the 2015 refugee “crisis” – Ohrfeige by Abbas Khider, Gott ist nicht schüchtern by Olga Grjasnowa and Gehen, ging, gegangen by Jenny Erpenbeck. To examine the impact of such literature on readers, I apply Rita Felski’s theory about the uses of literature, and in particular in relation to the first two novels, its capacity to create shock and deliver social knowledge. In Ohrfeige, I argue that ‘shock’ is used as a strategy to arouse uneasiness, in order to encourage thoughtful listening and understanding about the frustration experienced by asylum seekers. In Gott ist nicht schüchtern, readers are encouraged to expand their empathy while negotiating traumatic stories of war, torture and despair. In the interpretation of Gehen, ging, gegangen, I apply the theories of memory studies scholars such as Aleida Assmann and Michael Rothberg to highlight the parallels between refugees’ memories of fleeing and Germans’ memories of the Nazi and East German communist past. These parallel memory spheres resonate with each other and can lead to critical self-reflection among the German and European communities. Across these three chapters, this thesis argues that literature about flight and migration has the power to evoke empathy towards refugees and strengthen solidarity across differences in society