Creating Opportunities for Women in the Renewable Energy Sector: Findings from India

This paper identifies opportunities and constraints that low-income women face in accessing livelihoods in the renewable-energy sector in India through qualitative and quantitative research conducted in collaboration with The Energy Resources Institute (TERI) and the Self Employed Women's Association (SEWA) in 2012–13. Whereas previous research has focused on women mostly as end users of solar and biomass technologies, this research attempts also to understand women's potential as entrepreneurs, facilitators, designers, and innovators. Findings reveal that although access to technology and employment in the energy sector is limited by inadequate purchasing power and low social status, there is tremendous potential to create livelihoods for women at all levels of the energy supply chain. Broader findings indicate that women can gain optimal traction from employment in the energy sector only if there are wider socially progressive policies in place, including state intervention to create a robust social welfare infrastructure and accessible, high-quality, public services.     

La gestión mecanicista de las Instituciones de Educación Superior: un estudio desde la modelación sistémica

The bureaucratic tendencies to organize work in Higher Education Institutions (HEIs) of which facilitates personnel control and the mechanical ways to measure educational content are the ones that shatter education in pieces, under the hierarchy criterion, also shattering the professor's labor. This organizational method results in an incompetent education, leaving very negative consequences for teaching development. We address this problem by using systemic modeling and Structural Equations Systems (SEM) to confirm hypotheses from scientific observation. It was proven that there was a negative impact of mechanistic management which affected teacher's development. This was proven in context in two HEIs located in Villahermosa (Tabasco, Mexico).     

金庸小说的主题学研究与定位——刘卫英、王立《金庸小说母题及中外比较研究》读后

《金庸小说母题及中外比较研究》一书,从多种母题、主题、意象来探讨金庸小说的民族文学特征、民族文化内蕴生成以及外来佛经故事影响。注意在一个武侠文学传统的传承性链条上,发掘金庸小说的多重文化价值。在具体母题、意象的实证探究中,非常重视主题学理论方法的运用,拓展了主题学研究的视阈与空间,进一步验证和提升了主题学研究方法的学术意义与价值。     

教育本该不一样

教育本该不一样，因材施教、有教无类，说的就是不同。教育不从根本上由“批发”改为“零售”，我们就培养不出创新人才、杰出人才，甚至于培养不出我们常说的有用人才。为了培养创新人才，教育内容要力求全面，教育目标要力求明确，教育的方法要务求得当。     

Does obligational contracting lead to better performance? A comparison of global carmakers’ supply chain management approaches in Australia

Supply chain management (SCM) has been recognised as key to automobile manufacturers’ (‘buyers’) competitive advantage. However, the performance implication of two different approaches towards SCM, obligational contracting (OCR) vs. arm’s length contracting (ACR), remains inconclusive in the current literature. By focusing on examining how multiple global automobile manufacturers’ SCM practices result in different performance outcomes in the one-country setting of Australia, we are able to ascertain the direct impact of SCM approaches on buyers’ performance. We also provide detailed analysis on the specific influence of each distinguishing feature of the OCR/ACR approaches on different aspects of performance. Through a more nuanced investigation of the links between SCM approaches and automobile manufacturers’ performance at the firm level, this research contributes to a better understanding of the topic with managerially applicable insights.     

Preference aggregation and atoms in measures

This paper examines the aggregation of preferences with a finitely additive measure space of agents. We consider three types of non-dictatorship axioms: non-dictatorship, coalitional non-dictatorship, and atomic non-dictatorship. First, we show that the existence of an atom is a necessary and sufficient condition for the existence of a social welfare function that satisfies weak Pareto, independence of irrelevant alternatives, and coalitional non-dictatorship. Second, we simultaneously impose non-dictatorship and coalitional non-dictatorship, and specify a necessary and sufficient condition for the finitely additive measure that guarantees the compatibility among the axioms. Third, we impose all non-dictatorship axioms and show that the corresponding measure is extremely restricted.     

我国银行理财业务发展趋势研究

对国内商业银行理财业务的发展状况进行了简要概述， 进而对理财业务开展过程中的一些问题进行了分析， 强调指出市场化应该成为银行理财业务转型升级和创新发展的方向， 并提出了实现市场化发展方向的若干具体措施。     

Brexit: Tracking and disentangling the sentiment towards leaving the EU

On 23 June, 2016, the UK held a referendum to decide whether to stay in the European Union or leave. The uncertainty surrounding the outcome of this referendum had major consequences for public policy, investment decisions, and currency markets. We discuss some of the subtleties involved in smoothing and disentangling poll data in light of the problem of tracking the dynamics of the intention to Brexit, and propose a multivariate singular spectrum analysis method that produces trendlines on the unit simplex. The trendline yield via multivariate singular spectrum analysis is shown to resemble that of local polynomial smoothing, and singular spectrum analysis presents the nice feature of disentangling the dynamics directly into components that can be interpreted as changes in public opinion or sampling error. The merits and disadvantages of some different approaches for obtaining smooth trendlines on the unit simplex are contrasted, in terms of both local polynomial smoothing and multivariate singular spectrum analysis.     

Crime prediction by data-driven Green’s function method

We develop an algorithm that forecasts cascading events, by employing a Green’s function scheme on the basis of the self-exciting point process model. This method is applied to open data of 10 types of crimes happened in Chicago. It shows a good prediction accuracy superior to or comparable to the standard methods which are the expectation–maximization method and prospective hotspot maps method. We find a cascade influence of the crimes that has a long-time, logarithmic tail; this result is consistent with an earlier study on burglaries. This long-tail feature cannot be reproduced by the other standard methods. In addition, a merit of the Green’s function method is the low computational cost in the case of high density of events and/or large amount of the training data.     

Predicting bank insolvencies using machine learning techniques

Proactively monitoring and assessing the economic health of financial institutions has always been the cornerstone of supervisory authorities. In this work, we employ a series of modeling techniques to predict bank insolvencies on a sample of US-based financial institutions. Our empirical results indicate that the method of Random Forests (RF) has a superior out-of-sample and out-of-time predictive performance, with Neural Networks also performing almost equally well as RF in out-of-time samples. These conclusions are drawn not only by comparison with broadly used bank failure models, such as Logistic, but also by comparison with other advanced machine learning techniques. Furthermore, our results illustrate that in the CAMELS evaluation framework, metrics related to earnings and capital constitute the factors with higher marginal contribution to the prediction of bank failures. Finally, we assess the generalization of our model by providing a case study to a sample of major European banks.