国际研发合作对 全球价值链分工地位的影响 ——基于吸收能力的门槛效应

基于知识吸收能力的视角，从理论和实证上考察国际研发合作对全球价值链分工地位攀升的作用及其门槛变量的影响。研究结果表明：在控制其他变量的基础上，国际研发合作能够显著地促进全球价值链分工地位攀升。进一步地，国际研发合作对全球价值链分工地位的影响还要受到经济体吸收能力的影响，要素禀赋、金融发展、人力资本、研发能力及制度环境等吸收能力分项维度对国际研发合作与全球价值链分工地位之间的关系具有显著的门槛调节效应。在全球研发网络和全球产业价值链加速融合的背景下，研究结论对中国企业通过选择国际合作研发策略、嵌入全球研发创新网络、强化知识吸收能力以进一步提升企业国际竞争力具有重要的启示意义。     

How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis

In this empirical study, a five-stage methodology is used to examine the efficiency of 45 worldwide known airline companies from the financial, operation and marketing perspectives. Initially, the superefficient data envelopment model is run with inputs and outputs that are selected based on the literature review. However, because 21 out of 45 airline companies are found to be efficient based on this analysis, a stepwise regression-based mechanism is applied to four reduced models – one for each output variable – for better discrimination. The outputs are, namely, net profit margin (financial output), passengers carried, on-time departure performance (operational outputs), and customer satisfaction (marketing output). In this way, the significant input variables are found for each reduced model. In the third stage, in order to provide even more discrimination, social network-based eigenvector centrality values are used as the weights of the superefficiency scores, and the strengths and weaknesses of efficient airlines for each output are specified in terms of their related significant inputs. The results show that, when net profit margin is taken as an output, Vietnam Airlines has the top weighted superefficiency value and excels in terms of available seat kilometers and liquidity, but it should improve its debt level. Although Norwegian Airlines has the highest efficiency with respect to debt level, it is not the best role model because its eigenvector centrality value is relatively low. However, Norwegian airlines also has the highest weighted superefficiency and acts as a role model in terms of on-time departures with respect to this output. Its main strength is liquidity, and it has no significant weaknesses. On the other hand, in terms of overall satisfaction and passengers carried, Vietnam Airlines and Thai Airways are the leaders, respectively. Vietnam Airlines is the only superefficient company with respect to overall satisfaction, while the basic strengths of Thai Airways in terms of passengers carried are its employee and fleet, and it has no significant weakness. A final aggregation of the results is made by making pairwise comparisons of the relative importance of four outputs for 7 experts selected from different departments of airline companies. According to the results, Net Profit Margin has the highest priority, followed by On-time Departure and Overall Customer Satisfaction, while passengers carried has the lowest importance. Based on these relative priorities, it can be said that Vietnam Airlines can be accepted as the top performing airline company, followed by Norwegian Airlines.     

基于机器学习的斜坡堤越浪量预测方法研究

针对斜坡堤越浪量预测方法,分别建立集成神经网络(ensemble neural network,ENN)、随机森林(random for-eset,RF)和支持向量回归机(suppport vector regression,SVR)3种机器学习模型对斜坡堤越浪量进行预测,并利用决定系数R2和均方根误差RMSE来评估模型性能.最后,对3种模型的性能进行分析.结果显示,集成神经网络模型的决定系数R2和均方根误差RM S E分别约为0.96和0.0018,随机森林模型的决定系数R2和均方根误差RMSE分别约为0.97和0.0014,支持向量回归机模型的决定系数R2和均方根误差RMSE分别约为0.94和0.002.对比发现,3种模型的决定系数都达到0.9以上,都具有较高的预测精度,随机森林相比其他两个模型精度更高.     

陕北黄陵县农户生计资本评价及其生计策略研究

[目的]选取受退耕还林、封山禁牧等生态政策影响较大的陕北农户为研究对象,分析农户生计资本与生计策略之间的作用关系。[方法]基于可持续生计分析框架,采用Logistic回归模型,对17个行政村335户样本农户数据进行分析。[结果](1)研究区农户的人力资本整体得分最高,社会资本居次,物质资本中等偏下,自然资本和金融资本处于低水平;(2)农户生计分化明显,典型的纯农户很少,农户生计策略主要为兼农型和低水平非农型;(3)回归分析表明,人力资本指数高的农户倾向于外地兼农,物质资本和社会资本指数高的农户倾向于当地兼农,家庭年收入、人均教育投入和人情往来3项指标是促进农户向非农型生计策略转变的关键因子。[结论]农户生计策略的选择和转变是建立在自身资本结构上的,其往往向着发挥生计资本优势、规避生计资本短板的方向调整生计策略,进而达到提高整体生计资本水平的目的。人力资本优势主导下的黄陵县,加之沟壑区农地资源空间配置的破碎性与复杂性,外地兼农型生计策略将仍是该地区农户近期内的主要生计抉择。     

创新驱动下中国区域高质量发展——基于平衡充分发展水平的门槛分析

创新驱动是破解中国区域不平衡不充分发展的突破口,是实现高质量发展的助推器。采用2003～2017年中国30个省市面板数据,运用全局参比Malmquist模型测度了中国区域高质量发展水平,并通过构建指标体系分别对中国各省市的平衡发展和充分发展水平进行了评价,然后通过门槛回归模型分析了在不同平衡和充分发展水平下创新驱动对于高质量发展的影响机制。结果发现：①区域高质量发展水平呈现出先下降后上升的变化趋势；②各省市平衡和充分发展水平均呈现上升趋势,但各省市之间的变化情况差异较大,有明显的空间集聚特征；③在不同的平衡及充分发展水平下,创新驱动对高质量发展的影响机制是不同的,当平衡充分发展水平较低时,创新驱动对高质量发展没有显著影响；当平衡充分发展达到一定水平时,创新驱动对高质量发展起到一定的促进作用；随着平衡充分发展水平的进一步提高,创新驱动对高质量发展的促进作用越来越大。     

Moral hazard and subsidized crop insurance

Along with adverse selection, moral hazard is one of the major hurdles that private and public insurance plans must contend with. Moral hazard occurs if risks are endogenous to a producer's behavior and if the insurer is unable to properly monitor the insured. We review the role of moral hazard in the US crop insurance program. We conduct an empirical analysis of one important aspect of the US crop insurance program—prevented planting. This provision provides indemnity payments if conditions are not suitable for planting. The program has been the subject of considerable controversy, especially during 2019, when the rate of claims is expected to be especially high. Because loss adjustors may encounter difficulties in assessing the weather conditions associated with prevented planting claims, the program is susceptible to moral hazard. We consider the extent to which prevented planting claims may be endogenous to prices. We find significant evidence of moral hazard. The likelihood of prevented planting claims increases as the expected market price decreases or as fertilizer costs increase for corn and soybeans in the Prairie Pothole Region and for grain sorghum and cotton in all states.     

中美玉米期货市场功能效率比较

价格发现与套期保值是期货市场的基本功能,能够反映期货市场的运行效率。通过对比中美贸易摩擦前后期货市场的价格发现和套期保值功能,分析中美玉米期货市场效率间的差距,探究我国玉米期货市场运行效率低的原因。利用格兰杰(Granger)因果分析、协整检验、分位信息份额模型、套期保值比率及绩效分析方法,定量对中美两国2013—2019年玉米期货及现货的数据进行分析,结果表明,中国玉米期货市场存在较强的价格发现功能,但套期保值绩效不佳。使用前沿分位信息份额模型和滚动格兰杰因果法分析中美两国期现货市场动态关系的区别,发现中国仅存期货市场对现货市场的单向引导,而美国在中美贸易摩擦前表现为玉米期现货市场具有相近的引导能力,套期保值效率较高,中美贸易摩擦增强了其现货市场对期货市场的引导能力,降低了期货市场运行效率。从期现货市场双向引导关系视角来看,中国玉米期货市场效率低的原因主要是现货市场的信息不完全、发展不完善,期现货市场缺少长期稳定的双向引导关系抑制了期货市场功能发挥。中国应全面加强期货市场建设,提升期货市场定价效率,推动农产品期货市场快速健康发展。     

一种利用机器学习优化MIMO窃听信道天线选择的方法

为保障多输入多输出窃听信道系统中信息传输的保密性，提出了一种基于机器学习的天线选择方案。首先利用机器学习解决分类问题准确率高、处理大数据高效这一优势，设计了基于奇异值分解的特征值提取、基于信干噪比的标签赋值方案，建立了k最近邻分类器和逻辑回归分类器选择最优天线最大化保密性能（可达保密速率和保密中断概率）。与传统天线选择方案相比，所提方案获得了几乎一致的保密性能，并且大幅降低了系统的选择复杂度和误比特率。     

Separate waste collection in mountain municipalities. A case study in Campania

This paper aims to analyse the impact of land characteristics (i.e. altimetry and housing dispersion) on separate waste collection, with a focus on mountain municipalities. The high spatial heterogeneity of the driving factors of separate waste collection allows traditional techniques, such as OLS, to offer only a partial depiction of the situation, missing important information. In this view, we perform the Geographically Weighted Regression (GWR), which allows to control for the local determinants of waste management. Our data cover 550 municipalities of Campania, in Southern Italy. We control for a set of morphological and socio-economic variables, drawn from official records for 2012. Our results show that the relationships between land characteristics and separate waste collection are not constant over space. Moreover, they suggest that in the presence of non-modifiable factors (such as land characteristics) local governments should act on citizen motivations, promoting awareness on environmental issues, and should implement time-saving collection methods.     

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.