要素匹配与中国投资效率空间差异性——基于双层嵌套型函数的分解研究

本文基于四要素双层嵌套的生产函数，利用1990-2016年全国层面及省际层面数据测算投资效率，并分析其空间结构特征及演变轨迹，检验投资效率匹配效应影响因素。研究发现：①1990-2016年我国整体投资效率呈下降趋势，资本-技能劳动匹配效应与整体投资效率走势趋同，快速累积的资本存量和不断升级的资本质量与短缺的技能劳动之间矛盾突出。②东中西部地区投资效率增长非一致性明显。东部地区资本相对投资效率明显高于中西部，但下降幅度大于中西部，中西部与东部地区之间差距缩小，其中匹配效应是区域间投资效率非平衡的主要成因。③若产业结构升级的技能劳动需求不能满足，将引发要素错配，不利于有效投资。房价与工资提升分别通过影响技能劳动供给和需求抑制要素匹配效率；教育和公路设施会对地区要素匹配产生积极影响，改善地区间投资效率非均衡性；地区投资效率存在显著正向空间相关性，毗邻地区的要素流动和经济发展相近地区的技术溢出均对投资效率产生积极的影响。     

中日城市供水系统静态效率的对比研究

文章运用DEA方法，评价了北京、东京、上海以及横滨等城市2003年-2005年间供水系统的静态效率，发现日本三个城市供水系统的效率要高于中国三个城市的效率，造成这种状况的原因主要在于中国的水价体系还不够完善，供水企业收益不能完全回收其成本。     

推进公平是市场经济体制下政府的重要职能

推进公平是政府在市场经济体制下必须履行的重要职能 ,政府推进公平是协调经济利益关系、维持社会稳定的需要 ,是提高效率的保证 ,是对“市场缺陷”的弥补。公平是发展社会主义市场经济的最终目标之一。政府干预市场是为了实现效率与公平的兼顾与协调。为防止两极分化 ,我国政府须在推进起点公平、结果公平、环境公平上应采取切实可行的措施。     

我国农村金融市场效率研究——从金融促进农村经济发展的角度

本文认为判别与评价我国农村金融市场效率应该从下面两个方面进行研究：一是我国农村金融对农村经济的促进作用；二是我国农村金融市场的金融资源的均衡。从金融促进农村经济发展的角度。实证发现我国农村金融市场的效率低于全国金融市场的效率水平，主要由于农村正规金融机构的发展水平低下、农村金融市场的需求低下和农村金融市场的“高风险低效益”等因素所导致。因此，建议：发展中小金融机构，弥补正规金融的不足：创新金融工具，聚集农村金融需求；建立农村金融风险补偿制度，降低金融风险；改革金融定价和补贴政策，提高农村金融收益水平。     

铁电体热机的等温等电压循环效率

本文用电介质热力学理论导出了等压等容过程中，处在居里点附近的单电畴铁电体的热力学量．应用这些热力学量计算了由两个等温和两个等电压过程组成的铁电体循环的效率．结果表明，该循环的效率就是卡诺效率．     

管理人员工作压力与工作效率的影响研究——以国有企业与民营企业为例

本文对我国国有与民营企业管理人员工作压力对工作效率的影响进行了研究。结果显示,民营企业管理人员工作压力对工作效率的影响值明显高于国有企业管理人员。通过对两类企业管理人员工作压力对工作效率影响比较发现,国有企业管理人员由于工作压力较低,从而导致工作效率也较低;民营企业管理人员工作压力较高,而且带来的工作效率也较高。进一步研究发现,民营企业管理人员的工作压力相对于国有企业管理人员来说比较高,但是也没有达到“临界值”,从而使管理人员工作效率没有得到最大程度的发挥。因此,在目前的状况下,为了提高管理人员的工作效率,两类企业完全有增加其工作压力的必要。     

基于时间学的思想政治教育时间规律新探

随着即时网络时代的到来，思想政治教育学要实现现代转型，探究者必须紧跟时代行进的步履，发扬探赜索隐、钩深致远的精神，深入揭示和科学应用思想政治教育新规律尤其是时间规律。基于时间学，从社会背景条件、教育对象、教育者、管理者角度去考察，思想政治教育时间规律群大致包括思想政治教育一定要适合时代发展状况规律、思想政治品德形成发展的时间规律、对人们进行思想政治教育的时间规律和思想政治教育时间管理规律等四大类型的一级时间规律。其中，每一类型的一级规律包含诸多二级规律或曰子规律。自觉把握和科学应用这些规律，有助于推动思想政治教育不断从实然状态向应然状态、从必然王国向自由王国飞跃。     

A new approach to statistical efficiency of weighted least squares fitting algorithms for reparameterization of nonlinear regression models

We study nonlinear least-squares problem that can be transformed to linear problem by change of variables. We derive a general formula for the statistically optimal weights and prove that the resulting linear regression gives an optimal estimate (which satisfies an analogue of the Rao-Cramer lower bound) in the limit of small noise.     

Work performance and tax compliance in flat and progressive tax systems

Different tax systems, and their impact on work motivation and tax compliance are significant issues in contemporary political and economic debates. The proportional feature of a flat tax system is assumed to lead to higher performance, while the fairness of the redistributive progressive tax system is assumed to result in higher tax compliance. However, empirical findings on the topic are inconclusive. Both work performance and tax compliance under different tax systems were examined in an experiment, with special attention devoted to the effect of a change in tax systems. A flat tax system was supposed to induce greater work performance, whereas a progressive tax system was expected to increase tax compliance based on fairness perceptions, allowing for the opposite effect due to higher complexity. Furthermore, it was assumed that performance and tax payments would be influenced by motives of self-interest. The design included 20 rounds with a real-effort task in each round, determining participants’ experimental income. Participants (N = 191) made decisions about their tax payments from round-to-round in four different experimental conditions: (1) a flat tax system, (2) a progressive tax system, (3) starting with a flat and changing to a progressive, and (4) starting with a progressive and changing to a flat tax system. Results indicate higher work performance in a progressive system. However, a change from a progressive tax system to a flat system led to increased tax compliance.     

Record-breaking data: a parametric comparison of the inverse-sampling and the random-sampling schemes

In many industrial quality control experiments and destructive stress testing, the only available data are successive minima (or maxima)i.e., record-breaking data. There are two sampling schemes used to collect record-breaking data: random sampling and inverse sampling. For random sampling, the total sample size is predetermined and the number of records is a random variable while in inverse-sampling the number of records to be observed is predetermined; thus the sample size is a random variable. The purpose of this papper is to determinevia simulations, which of the two schemes, if any, is more efficient. Since the two schemes are equivalent asymptotically, the simulations were carried out for small to moderate sized record-breaking samples. Simulated biases and mean square errors of the maximum likelihood estimators of the parameters using the two sampling schemes were compared. In general, it was found that if the estimators were well behaved, then there was no significant difference between the mean square errors of the estimates for the two schemes. However, for certain distributions described by both a shape and a scale parameter, random sampling led to estimators that were inconsistent. On the other hand, the estimated obtained from inverse sampling were always consistent. Moreover, for moderated sized record-breaking samples, the total sample size that needs to be observed is smaller for inverse sampling than for random sampling.