建立房价公信度有效途径:政府的科学控制与决策

中央和地方政府出台了许多"救市"政策但楼市依旧低迷的根本原因在于缺乏房价的公信度。要建立房价公信度,科学制定各地的房价,能让社会民众参与和监督,实现房价的透明化,政府的科学控制与决策是关键。这是彻底解决楼市低迷的根本途径,是建立稳定、健康、发展的房地产市场的根本所在。     

上市公司股利分配倾向研究:基于数据挖掘方法的分析

股利分配是上市公司的一项十分重要的财务决策。而影响股利分配的因素有许多,国内现有文献一般是采用多元统计回归建模方法对其进行实证分析。本文应用数据挖掘中的决策树方法寻找股利分配的原因,这是文章的创新点。从决策树来看,现金股利分配不仅受股本结构、公司规模、当年可分配利润、成长机会及经营风险等客观财务因素的影响,而且与控股股东性质存在显著的影响,且国家控股股东分配倾向低于民营控股股东。     

满意与否对维持现状偏差的影响

维持现状偏差（Status Quo Bias）描述了一种在个体决策时普遍存在的偏离理性决策模型的行为倾向,这种倾向使个体偏好已经做出的选择或偏好能维持现状的选项。研究者从有限理性的满意型决策原则出发来观察维持现状偏差,弥补了以往相关研究中的不足之处,证明维持现状偏差并不是一种普遍存在的决策偏差,仅在个体对现状满意时才会发生,当个体对现状感到不满意时,维持现状偏差则不复存在。     

决策行为与认知偏差——管理者过度自信研究述评

过度自信是个体过高估计自身判断精确度的一种认知偏差。研究表明,我国金融行业管理者普遍存在过度自信的现象。管理者的过度自信对投资决策、公司的并购以及管理的薪酬和晋升都会产生影响。经济心理学对管理者过度自信的研究将会成为该领域研究的一大趋势。     

两阶段实物期权的供应链模型研究

在一个单期、两级供应链中供应商和销售商共同开发投资一种新型产品,在此情况下,本文分别对不考虑期权和引入期权两种情况进行分析:考虑期权的情况下,在投资和销售两阶段分别引入投资延迟期权和销售量担保期权,通过对模型分析与求解发现,销售商通过购买期权将风险部分转移给供应商,供应商获得风险补偿的同时,由于承担了更多的风险将谨慎投资,从而使供应链整体风险得到有效控制,并且实现资金的有效配置。     

基于集对故障树方法的电网安全运行风险评估模型

本文首先对电网安全运行风险进行分析,并结合实际情况,运用故障树法构建电网安全运行模型;然后,利用集对分析的概念及其运算法则推导出集对与门算子和集对或门算子;接着,采取集对分析方法,得出具有确定性与不确定性的各个底事件的联系度;最后,以算例表明本文所提出的集对故障树分析法是可行的,既能实现对电网安全运行风险的度量,又避免了以往采用概率度量的不准确性,能更好地描述电网运行风险的真实程度。     

关于农村公共产品供给机制问题

农村公共产品的供给主体主要是政府.当前农村公共产品严重短缺,政府应该把公共资源的分配重点放在农村.建立农村公益事业建设"一事一议"财政奖补制度十分必要."一事一议"的改革要遵循民主决策,筹补结合;直接受益,注重实效;规范管理,阳光操作三个基本原则和划分村级公益事业建设责任、明确一事一议财政奖补范围两个重点.     

政府农村公共项目投资决策失范的诱因研究

政府农村公共项目投资决策失范是普遍存在的现象,要解决这一问题必须找出导致这种失范产生的诱因。对于该问题的研究,要抓住一个主线,就是利益。导致该决策失范的诱因,除决策程序外,更重要的是作为投资主体的政府追求自身利益所导致的对农村公共利益的偏差,以及令这一问题更加复杂化的政府内部博弈行为。从利益偏差、内部博弈和决策过程角度对决策失范的诱因进行了研究,这种分析框架对于其他领域政府行为的研究也有一定的借鉴意义。     

Optimizing the shares of native tree species in forest plantations with biased financial parameters

Addressing uncertainty is a key requirement to follow the principle of precaution in sustainable ecosystem management. The maximization of worst-case outcomes according to the “maximin” decision rule, based on the two parameters mean and variance of a financial indicator, is a prominent approach to integrate uncertainty in decision-making. In forestry, the problem of selecting the optimum tree species combination for a forest plantation investment can be seen as a problem of optimal portfolio selection, to be solved according to the “maximin” decision rule. Yet, it is well known that portfolios computed from expected means and variances are highly sensitive to changes in the estimated parameters. The financial results may be poor if we rely too much on the historical data. This paper tests an extended worst-case model that considers a lower bound for the expected mean net present value (NPV) of a tree species portfolio and an upper bound for its variance. Biased expected mean NPVs, variances and correlations for the tree species Picea abies [L.] Karst. (Spruce) and Fagus sylvatica L. (Beech) were used to test the variability of the resulting tree species portfolios (27 scenarios). A comprehensive simulated data set, which was adopted from an existing study and defined as the independent reference, served to evaluate the financial performance of the tree species portfolios obtained from optimization with the biased data. Compared with the results of classical worst-case optimization instances, it was feasible to reduce the variability of tree species shares effectively when the optimization was carried out with the extended worst-case approach. Furthermore, the financial performance of this approach was better when tested with the independent data. The worst-case forest NPVs achieved with the extended approach were on average 10% (statistical confidence 0.95) or 147% (statistical confidence 0.99) greater in comparison to the results of the classical approach. The influence of the uncertainty parameter selection was tested and the results were discussed against the controversial viewpoints on the usefulness of the “information-gap decision theory”. Finally, the significance of our results for sustainable ecosystem management is pointed out.     

Climate change and its marginalizing effect on agriculture

The agriculture of some areas considered marginal in the EU agricultural context is being questioned due to its low productivity and growing dependence on economic aid programs Common Agricultural Policy (CAP). This study shows that climate change increases these areas marginalisation of since worsens crop growth conditions. The influence of climate change on the agricultural sector is analyzed using the Multicriteria Decision Paradigm with information provided by the Erosion-Productivity Impact Calculator (EPIC) and a General Circulation Model (GCM) as inputs for multicriteria mathematical programming models. The results obtained show climate change effects on the crop portfolio. Further results suggest that climate change effects are not only economics and environmental, reducing the suitable area for crops, but also social as it causes loss of jobs in the agricultural sector.