A note on adaptive l-statistics

The purpose of this note is to give a simple demonstration of the apparently widely-known principle that, under suitable conditions (primarily of a symmetry nature) an adaptive L-sta-tistic has the same asymptotic distribution as a non-adaptive L-statistic.     

野生动物资源最优管理的动态经济模型及实证研究

研究自然条件、社会发展和经济政策等多方面对野生动物资源管理的约束与系统分析野生动物资源管理的动态经济均衡,对于野生动物保护管理具有十分重要的理论支持和实践指导。在自然条件方面,以开放生物种群资源生长的Logistic增长模型作为约束条件;在社会发展方面,考虑产业资本投入的影响;在经济政策方面,以税收或补贴为约束条件,运用成本收益分析建立野生动物资源持续利用的动态经济均衡模型,并利用常微分方程、最大值原理等数学方法求解得到最优资源存量水平和最优收获量。同时以麝为例进行应用性实证分析,得到麝类资源的最优种群水平为143．01万只,最优持续收获量为66．24万只。当贴现率从0．01到0．1之间变化时,麝类资源最优种群水平将在149．93到134．36万只之间,而最优持续产量将维持在66．44到65．59万只之间。     

议价能力对审计定价的影响——基于双边随机边界模型的分析

审计收费中的最终价格确定是审计双方博弈的结果。使用双边随机边界模型分析框架分析审计收费中的定价,以及审计双方议价能力对审计定价的影响。结果发现:事务所的议价能力使得审计收费比理论均衡价格高出大约24.02%,上市公司的议价能力使得审计收费比理论均衡价格低了大约17.29%,两者的最终博弈结果使得中国审计收费比均衡价格高大约6.73%,中国事务所审计收费存在一定的高收费现象,事务所对大规模企业有收费溢价,2006年后,国际四大事务所存在高收费溢价现象。     

A unified approach to marginal equivalence in the general framework of group invariance

ABSTRACT

Two Bayesian models with different sampling densities are said to be marginally equivalent if the joint distribution of observables and the parameter of interest is the same for both models. We discuss marginal equivalence in the general framework of group invariance. We introduce a class of sampling models and derive marginal equivalence when the prior for the nuisance parameter is relatively invariant. We also obtain some robustness properties of invariant statistics under our sampling models. Besides the prototypical example of v-spherical distributions, we apply our general results to two examples—analysis of affine shapes and principal component analysis.     

Forecasting the industrial production using alternative factor models and business survey data

This paper compares the forecasting performance of three alternative factor models based on business survey data for the industrial production in Italy. The first model uses static principal component analysis, while the other two apply dynamic principal component analysis in frequency domain and subspace algorithms for state-space representation, respectively. Once the factors are extracted from the business survey data, then they are included into a single equation to predict the industrial production index. The forecast results show that the three factor models have a better performance than that of a simple autoregressive benchmark model regardless of the specification and estimation methods. Furthermore, the state-space model yields superior forecasts amongst the factor models.     

Detection of multiple change-points in multivariate data

The statistical analysis of change-point detection and estimation has received much attention recently. A time point such that observations follow a certain statistical distribution up to that point and a different distribution – commonly of the same functional form but different parameters after that point – is called a change-point. Multiple change-point problems arise when we have more than one change-point. This paper develops a method for multivariate normally distributed data to detect change-points and estimate within-segment parameters using maximum likelihood estimation.     

Some basic concepts of numerical treatment of Markov decision models

This survey reviews some results on numerical treatment of MARKOV Decision Models with respect to iV-stage-optimality, discounted optimality, and average optimality criteria. Especially, we deal with accelerated algorithms, approximation procedures and structured problems.

AMS 1980 subject classifications: 93C55, 90C40, 93D35     

On the Performance of Popular Unit-Root Tests Against Various Nonlinear Dynamic Models: A Simulation Study

ABSTRACT

There is a widespread perception that standard unit-root tests have poor discriminatory power when they are applied to time series with nonlinear dynamics. Via Monte Carlo simulations this study re-examines the finite sample properties of selected univariate tests for unit-root and stationarity under a broad class of nonlinear dynamic models. Our simulation experiments produce a couple of interesting findings. First, performance of tests is driven by the degree of underlying persistence rather than the nonlinear dynamics per se. Tests under study exhibit reasonable performance for nonlinear models with mild persistence, while the accuracy of inference deteriorates substantially when the models are highly persistent regardless of the linearity. Second, when it comes to deciding which one to identify first between linearity and stationarity, our results suggest to conduct linearity test first to enhance the reliability of test inference.     

Learning the Wealth of Nations

We study the evolution of market‐oriented policies over time and across countries. We consider a model in which own and neighbors' past experiences influence policy choices through their effect on policymakers' beliefs. We estimate the model using a large panel of countries and find that it fits a large fraction of the policy choices observed in the postwar data, including the slow adoption of liberal policies. Our model also predicts that there would be reversals to state intervention if nowadays the world was hit by a shock of the size of the Great Depression.     

文本类型与翻译策略

有史以来,人们对翻译的标准各执己见,争论不休,著名翻译理论家纽马克对文本类型进行划分,并相应地提出两种翻译方法,即语义翻译和交际翻译。本文对纽氏的理论和方法进行分析,以期对翻译策略的选择有所裨益。