基于产业关联视角的湖南省水环境污染经济分析

利用湖南省2007年、2012年和2015年的水污染排放数据与2007-2012-2015年投入产出接续表,通过区域经济环境投入产出模型分析了2007-2015年湖南省经济发展与水污染排放的成因及其变化。结果表明,湖南省水污染排放总体虽有一定改善,但各行业排放仍处于不稳定状况。随着经济发展一些支柱产业作为隐形排放源值得重视。因此,湖南省要实现经济发展与环境保护双赢的关键是加快产业结构转型升级,加强污染物治理技术运用,加大水污染物排放制度约束力度。     

基于专利的区域科技研发人才分析

通过分析授权发明专利的发明人相关数据来发现研发人才分布特征是一种新探索,解决了战略性新兴产业分类、专利IPC分类和研发人才领域分类对应关系复杂的问题,完成了对15个副省级城市专利发明人分领域相关数据的提取建库和一个样本城市细分领域研发人才的数据建库,进而比较分析研发人才分布特征,并耦合分析相关新兴产业发展态势。     

All Myth and Ceremony? Examining the Causes and Logic of the Mission Shift in Microfinance from Microenterprise Credit to Financial Inclusion

This contribution assesses the shift in the mission of microfinance from providing small loans for entrepreneurship to the broader agenda of financial inclusion. Three leading organisations' publications inform a discourse analysis, which allows the strategic shift to be analysed using two theoretical frames from organisational sociology: instrumental rationalism and sociological institutionalism. The proclaimed shift in strategy is found to consist less of rational innovation towards the aim of poverty alleviation than of “myth and ceremony” for the sake of organisational self-preservation.     

基于综合因子分析法的广佛肇经济圈投资环境动态评价

通过构建评价指标体系、方差极大正交旋转和综合因子分析,对广佛肇经济圈投资环境进行动态评价。研究发现:①2008—2016年,广佛肇经济圈的投资环境综合得分呈上升趋势,其中社会性经济实力、经济性基础设施得分增长较快,但是环境质量得分有所下降。②广佛肇经济圈投资环境内部差异较为明显,排名从高到低依次为广州、佛山、肇庆。其中广州的社会性经济实力得分最高,佛山的经济性基础设施得分最高,肇庆的投资环境处于相对劣势的地位。     

乡村旅游主题下休闲农业发展研究——以山西省100个3A级乡村旅游示范村为例

以山西省首批100个3A级乡村旅游示范村为研究对象,运用最近邻指数、地理集中指数、核密度分析等空间分析方法及建立乡村旅游资源分类体系,对其空间结构和分类特征进行测度。结果表明:样本点空间分布为集聚型,分布高密度区域主要在山西省中东部、东南部和南部,北部和西部分布密度较低。山西省休闲旅游资源丰富,为乡村旅游提供了大量资源,五种乡村发展类型中,特色文化型村庄占比最大,休闲农庄和城郊发展型村庄相对较少。最后根据研究结果提出相关建议。     

重大事项社会稳定风险评估运行框架研究——以城市新区开发建设为例

针对现行的重大事项社会稳定风险评估中存在的问题,提出建立切实可行的评估运行框架。首次以城市新区为评估对象,以发现问题、分析问题、解决问题为主线,采用定性、定量、定位、定策相结合的分析方法,对城市新区开发建设可能存在的社会稳定风险进行评估,以期实现单纯型评估、粗放型评估向精细化评估的转变。从实践层面来说,对其他新区规划的社会稳定风险评估具有借鉴意义。     

基于LDA主题模型的专利文本分析应用研究

为了解决运用传统的专利文本分析方法中出现的分类粗糙、科学性不强等问题,提出使用基于Latent Dirichlet Allocation(LDA)主题模型的专利文本分析方法。以我国转基因玉米育种领域专利文本为研究对象,对专利文本主题进行划分。通过实验表明LDA主题模型对专利文本的划分和热门领域的分类准确、有效。并得出结论:对专利文本使用LDA主题模型建模可以实现对专利文本的分类,可以实现对热门领域主题分类、子领域细分,并对未来发展态势给出意见。     

Oil price and automobile stock return co-movement: A wavelet coherence analysis

This paper explores possible co-movement between oil price and automobile stock return in a joint time-frequency domain. Daily price series from August 01, 1996 to June 20, 2017 is used in this analysis. The results indicate that the co-movement between oil price and automobile stock return is strong during November, 2000–December, 2002 and March, 2006–December, 2009. The co-movement is found to be more pronounced in the long-term and stock return is sensitive to the higher oil price emanating from the demand shock. This contravenes the conventional wisdom that crude oil is always counter-cyclical to the automobile stocks. For investor, this weakens the probable gain from including oil asset in a portfolio of automobile stocks as crude oil does not offer cushion against bearish automobile stock markets during the crisis period.     

UK's stock market reaction to Brexit process: A tale of two halves

We examine the UK's stock market reaction to 27 events associated with the likelihood of Brexit. Though the overall market reactions to these events is negative, a dissection of these events into the pre and post Brexit referendum events unearth interesting facts. In particular, we find that the market reaction is negative and significant to the events leading up to and including the announcement of Brexit results. This negative reaction is not confined to the day of announcement of the outcome of Brexit referendum only rather it spans over the events that enhanced the likelihood of the Brexit in the pre-Brexit referendum period. However, our results show a positive market reaction to events that occurred after the Brexit referendum. These findings suggest that initially market reacted negatively to the Brexit; however, as the UK's future economic relations with EU started to take a shape, the market started to see the positive side of Brexit. Consistent with this notion, our cross-sectional analysis shows a positive market reaction for the firms that are engaged in foreign sales and that much of the negative market's reaction relates to the firms that openly stated the negative effect of Brexit on their operations. Finally, we do not find evidence of market reaction to UK firms depending on European labor force; however, we do find significantly positive stock market reaction to the firms involved more in international trade. An important caveat of our study is that our reported results are sensitive to the choice of market index.     

On the power of indicators: how the choice of fuel poverty indicator affects the identification of the target population

In light of the creation of the EU Energy Poverty Observatory (EPOV) in January 2018 and the increase in debates on how fuel poverty is measured, we propose a critical analysis of fuel poverty indicators and demonstrate that choosing a given indicator is central to the identification of the fuel-poorpopulation.

First, we conducted an inter-indicator analysis to show how profiles of fuel-poor households vary depending on the indicator selected. We designed a multidimensional approach based on a multiple correspondence analysis and a hierarchical and partitioning clustering analysis to study characteristics of fuel-poor households. We highlight the difficulty of identifying a fuel-poor ‘typical profile’ and show that the composition of the population depends on the choice of the indicator.

Second, we applied an intra-indicator analysis using two objective expenditure-based indicators with thresholds. In particular, we conducted a sensitivity analysis based on a logit model including variables describing household and dwelling characteristics. We show that the profiles of fuel-poor households as well as the drivers of fuel poverty vary considerably with the chosen threshold level.Given these findings, we stress the need to review how we currently rely on conventional fuel poverty indicators to identify target groups and give some recommendations.