宏观经济调控执行绩效的一个数量评价:1985～2005年

有效实施宏观经济调控是各国政府的一个中心职能,其目的在于熨平经济周期波动,维持经济总量大体平衡,从而为市场有效配置资源,实现经济的长期增长创造有利条件。客观评价宏观经济调控的执行绩效有助于政策当局反思政策制定过程中的不适当行为,不断改进宏观经济管理水平,从而更好地实现政策目标。在本文中,我们忽略宏观经济调控政策的内部构成,视其为一个整体,基于政策当局的损失函数,设计了一个新的模型框架,对宏观经济调控执行绩效进行数量评价。     

Predicting loss given default in leasing: A closer look at models and variable selection

Since the introduction of the Basel II Accord, and given its huge implications for credit risk management, the modeling and prediction of the loss given default (LGD) have become increasingly important tasks. Institutions which use their own LGD estimates can build either simpler or more complex methods. Simpler methods are easier to implement and more interpretable, but more complex methods promise higher prediction accuracies. Using a proprietary data set of 1,184 defaulted corporate leases in Germany, this study explores different parametric, semi-parametric and non-parametric approaches that attempt to predict the LGD. By conducting the analyses for different information sets, we study how the prediction accuracy changes depending on the set of information that is available. Furthermore, we use a variable importance measure to identify the input variables that have the greatest effects on the LGD prediction accuracy for each method. In this regard, we provide new insights on the characteristics of leasing LGDs. We find that (1) more sophisticated methods, especially the random forest, lead to remarkable increases in the prediction accuracy; (2) updating information improves the prediction accuracy considerably; and (3) the outstanding exposure at default, an internal rating, asset types and lessor industries turn out to be important drivers of accurate LGD predictions.     

非寿险业未决赔款准备金调整行为的实证研究

保险企业破产主要原因是准备金提存不足。国外相关文献认为公司通过调整未决赔款准备金的目的有四种,但对该行为的检验方法都存在一个明显缺点,就是要等5年之后才可以研究当前行为。据未决赔款准备金估算模型,同期影响因素有保费收入与赔款支出。运用多元统计方法,建立未决赔款准备与净保费收入和净赔款支出回归模型,结果表明,我国非寿险业不存在较普遍的人为调整现象。     

检验检疫背景符合性条件风险严重度评价研究——基于证据理论

针对检验检疫背景符合性条件风险严重度综合评价的特点,即多指标、多层次、评价标准模糊、属性复杂等,建立了综合风险严重度评价体系,提出了基于证据理论的动态综合模糊评价方法,并给出了具体的评价步骤：按指标属性将评价指标分为定性和定量两类;对各指标进行量化、一致性和无量纲化处理;从评价体系指标层开始进行动态立体综合评价;逐层合成综合绩效值。     

Is it obligor or instrument that explains recovery rate: Evidence from US corporate bond

This study investigates the impacts of unobservable firm heterogeneity on modelling corporate bond recovery rates at the instrument level. Based on the recovery information over a long horizon from 1986 to 2012, we find that an obligor-varying linear factor model presents significant improvements in explaining the variations of recovery rates with a remarkably high intra-class correlation being observed. It emphasizes that the inclusion of an obligor-varying random effect term has effectively explained the unobservable firm level information shared by instruments of the same issuer and thus results in an improvement of predictive accuracy of recovery rates. The empirical results show that the latent economic cyclical effects have been well represented by firm level heterogeneity, and strong evidence is presented for the normal distributional assumption of the recovery rates. Finally, we demonstrate the choice of recovery rate models may influence portfolio risk with the obligor-varying factor model generating a more right clustered loss distribution than other regression methods on the aggregated portfolio.     

Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks

Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%–16%) more accuracy than without using clustering, while the percentage split achieves (2%–5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.     

Garner ν. Murray–A Re-appraisal

The decision in Garner v. Murray was a departure from what had been accepted partnership practice. In the elementary accounting texts the decision in the case is widely quoted although, surprisingly, the legal merits of the case have not been examined in the literature. It is to this question that this paper is directed. The analysis shows that the main points in the case were incorrectly decided and would have provided grounds for an appeal. The final part of the paper examines the implications of the analysis for the problems identified by Houghton (1981).     

Statistical Inference under Symmetry

We explore the consequences of adjoining a symmetry group to a statistical model. Group actions are first induced on the sample space, and then on the parameter space. It is argued that the right invariant measure induced by the group on the parameter space is a natural non-informative prior for the parameters of the model. The permissible sub-parameters are introduced, i.e., the subparameters upon which group actions can be defined. Equivariant estimators are similarly defined. Orbits of the group are defined on the sample space and on the parameter space; in particular the group action is called transitive when there is only one orbit. Credibility sets and confidence sets are shown (under right invariant prior and assuming transitivity on the parameter space) to be equal when defined by permissible sub-parameters and constructed from equivariant estimators. The effect of different choices of transformation group is illustrated by examples, and properties of the orbits on the sample space and on the parameter space are discussed. It is argued that model reduction should be constrained to one or several orbits of the group. Using this and other natural criteria and concepts, among them concepts related to design of experiments under symmetry, leads to links towards chemometrical prediction methods and towards the foundation of quantum theory.     

个人所得税流失问题探析

随着我国社会主义市场经济体制的逐步建立和完善，个人所得税在税收中的地位和作用越来越明显。但由于长期以来征管乏力，公民纳税意识淡漠，税收法制不健全，造成个人所得税流失严重。这一现象对我国财政收入、收入分配制度都有极大的危害，关系到我国全面建设小康社会目标的实现，应引起各方面的高度重视。     

Properties of optimal forecasts under asymmetric loss and nonlinearity

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. Using analytical results we show that standard properties of optimal forecasts can be invalid under asymmetric loss and nonlinear data generating processes and thus may be very misleading as a benchmark for an optimal forecast. We establish instead that a suitable transformation of the forecast error—known as the generalized forecast error—possesses an equivalent set of properties. The paper also provides empirical examples to illustrate the significance in practice of asymmetric loss and nonlinearities and discusses the effect of parameter estimation error on optimal forecasts.