统计概念解析

本文从分析统计的本质属性出发,根据统计广泛性特点,归纳广义统计和狭义统计的概念,建立“统计概念总系”,力求能够包罗统计万象,体现统计全貌,使统计这一事物有一个总纲纪,为人们全面认识统计提供了一个新的视角。文中重点对政府统计纵向构成进行了分析和解读,解开人们在传统认识上的挽扣儿,这是正确理解政府统计构成的关键认识点,由此方能建立起统计概念体系。     

Bootstrap方法在死亡模型中的应用

 由于不同国家死亡率改善现象不同,世界各国所使用的死亡率模型皆不尽相同,而且不同年龄段的死亡率模型也不同。实际中,我们常常采用Gompertz模型、Makeham模型、Weibull模型等拟合高年龄段人口的死亡率,但是因高年龄段人口的死亡数据资料不够充分,较少有人以统计的观点给出模型适合性的检验过程。因此本研究提出利用Bootstrap方法检验死亡模型假设的方法,包括模型适合性的检验、参数估计、参数假设检验等。最后,本文应用中国1997－2007年65－89岁人口的粗死亡率数据,提出适合的死亡模型,然后给出利用Bootstrap方法进行死亡模型检验的全过程。     

An empirical comparison of ensemble methods based on classification trees

In this paper, we perform an empirical comparison of the classification error of several ensemble methods based on classification trees. This comparison is performed by using 14 data sets that are publicly available and that were used by Lim, Loh and Shih [Lim, T., Loh, W. and Shih, Y.-S., 2000, A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms. Machine Learning, 40, 203–228.]. The methods considered are a single tree, Bagging, Boosting (Arcing) and random forests (RF). They are compared from different perspectives. More precisely, we look at the effects of noise and of allowing linear combinations in the construction of the trees, the differences between some splitting criteria and, specifically for RF, the effect of the number of variables from which to choose the best split at each given node. Moreover, we compare our results with those obtained by Lim et al. [Lim, T., Loh, W. and Shih, Y.-S., 2000, A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms. Machine Learning, 40, 203–228.]. In this study, the best overall results are obtained with RF. In particular, RF are the most robust against noise. The effect of allowing linear combinations and the differences between splitting criteria are small on average, but can be substantial for some data sets.     

Robust likelihood functions in Bayesian inference

In order to deal with mild deviations from the assumed parametric model, we propose a procedure for accounting for model uncertainty in the Bayesian framework. In particular, in the derivation of posterior distributions, we discuss the use of robust pseudo-likelihoods, which offer the advantage of preventing the effects caused by model misspecifications, i.e. when the underlying distribution lies in a neighborhood of the assumed model. The influence functions of posterior summaries, such as the posterior mean, are investigated as well as the asymptotic properties of robust posterior distributions. Although the use of a pseudo-likelihood cannot be considered orthodox in the Bayesian perspective, it is shown that, also through some illustrative examples, how a robust pseudo-likelihood, with the same asymptotic properties of a genuine likelihood, can be useful in the inferential process in order to prevent the effects caused by model misspecifications.     

从三维视角分析农村基本公共服务现状与问题

本报告利用“三农”专家、县乡村干部和农户问卷调查数据,从三维视角分析了现阶段农村民生类、生产类、公共安全类基本公共服务存在问题,指出政府尤其是基层政府公共服务能力不足和公共财政体制不完善是造成农村基本公共服务供求矛盾的主要根源。因此,为农民提供基本而有保障的公共服务必须建立城乡统一的公共服务体制,完善公共财政制度,增强各级政府基本公共服务的能力。     

上海股票市场的基于小波去噪的混沌性检验

由于经济混沌需要大样本、低噪声的时间序列,所以文章首先利用小波变换对上证指数日收盘价序列进行去噪处理,然后由去噪后的日收盘价序列计算出日收益率序列,姑且称其为去噪后的日收益率序列,并把它同未经过去噪处理得到的日收益率序列进行比较,发现该方法较好地保留了序列自身固有的特性,只是剔除了由于日常细微波动产生的噪声,为有效地探测我国上海证券市场的混沌性打下了基础。最后分别计算去噪前后收益率的关联维数和Lyapunov指数,发现小波去噪并未改变上海证券市场的混沌性,但是去噪后的市场的复杂度要小于去噪前的市场的复杂度。所以进行混沌性探测的时候必须对数据进行去噪处理。     

Asymptotics for a class of dynamic recurrent event models

Asymptotic properties, both consistency and weak convergence, of estimators arising in a general class of dynamic recurrent event models are presented. The class of models take into account the impact of interventions after each event occurrence, the impact of accumulating event occurrences, the induced informative and dependent right-censoring mechanism due to the data-accrual scheme, and the effect of covariate processes on the recurrent event occurrences. The class of models subsumes as special cases many of the recurrent event models that have been considered in biostatistics, reliability, and in the social sciences. The asymptotic properties presented have the potential of being useful in developing goodness-of-fit and model validation procedures, confidence intervals and confidence bands constructions, and hypothesis testing procedures for the finite- and infinite-dimensional parameters of a general class of dynamic recurrent event models, albeit the models without frailties.     

群体分析视角下商业银行对金融体系的风险溢出效应研究

本文基于异质市场假说和高频数据,利用高频数据采样频率高及富含波动信息的特点,构造多银行和系统间多元联合分布过程,并将银行间的动态联系纳入考虑,构建了蕴含丰富经济意义、形式灵活的高频动态多条件CoVaR模型及基于此的群体性系统性风险贡献指标。从群体分析视角出发,研究了不同商业银行群体对金融体系的风险溢出效应。结果显示：就系统性风险贡献度而言,该模型准确刻画了近年不同时期下我国三类商业银行系统性风险贡献度的时变特征,其表现为在次贷危机及欧债危机、我国“钱荒”时期及股票市场异常动荡时期,由于风险的传染性等特征导致三类商业银行的系统性风险贡献度均有所上升,而在其他时期则相对平稳;就单个银行对系统的风险溢出影响而言,工商银行的风险溢出比率最大,与其庞大的资产规模以及在金融体系中的重要地位与作用密不可分;当分析同类型银行群体的风险冲击时,国有商行类的系统性风险溢出比率值最高,其次为股份制商行类,该两类的溢出比率相差无几,且均远大于城商行类,表明股份制商行对金融系统的风险溢出影响不可小觑;当剖析不同类型银行群体时,此模型同样适用。本文所构模型能够实现多个银行对金融系统极端风险贡献的度量,可为监管部门的分类监管及有限能力下银行救助顺序的确定提供一定参考依据。     

关于中国数据库调查方法与资本化核算方法研究

随着信息技术、互联网、人工智能、云计算的迅速发展,数据呈爆炸式增长,已逐渐成为一种极具价值的资产,世界主要国家纷纷出台扶持数据产业发展战略。国民经济核算国际标准《国民账户体系(2008)》明确建议将数据库作为知识产权产品包括在固定资产中。但目前包括中国在内的大部分国家还未对数据库资产建立完善的统计调查制度。本文梳理了目前发达国家有关数据库统计的经验,结合中国实际,对中国数据库调查方法和数据库资本化核算方法进行了研究,从生产法、收入法、支出法三个角度探讨了数据库资本化核算对GDP产生的影响,讨论了数据库类型转化与数据库资产价值未来调整方向,辅之以案例分析,旨在为中国数据库调查和资本化核算工作提供有益参考。     

Some aspects of modern population mathematics

The purpose of this paper is to survey a number of the technical tools and models that have found use in the study of human and other populations, and to indicate some problems of current interest. These tools and models are varied: integral equations, nonlinear oscillations, differential geometry, dynamical systems, nonlinear operations, bifurcation theory, semigroup theory, martingale theory, Markov processes, diffusion processes, branching processes, ergodic theory, prediction theory and state-space models. A fairly extensive bibliography is provided. Also an Appendix has been added describing the analysis of a classical entomological data set.     

Realized Volatility and Long Memory: An Overview

The challenge of modeling, estimating, testing, and forecasting financial volatility is both intellectually worthwhile and also central to the successful analysis of financial returns and optimal investment strategies. In each of the three primary areas of volatility modeling, namely, conditional (or generalized autoregressive conditional heteroskedasticity) volatility, stochastic volatility and realized volatility (RV), numerous univariate volatility models of individual financial assets and multivariate volatility models of portfolios of assets have been established. This special issue has eleven innovative articles, eight of which are focused directly on RV and three on long memory, while two are concerned with both RV and long memory.     

企业竞争力的综合测度

企业竞争力是企业求得自身生存与发展、战胜竞争对手的优势和能力。企业竞争力包括企业产品竞争力、企业技术开发和创新竞争力、企业市场营销竞争力、企业制度创新竞争力、企业管理创新竞争力、企业文化竞争力等六个方面。我们采用AHP法(层次分析法)综合测度A、B、C三个企业的竞争力并排序。     

区块链技术对国民经济核算发展的影响

区块链在记账技术方面实现了重大创新,从根本上影响了国民经济核算的发展方向。本文从改变工商会计数据基础、重新界定数据资产权益、金融中介服务去中心化以及大规模开发应用微观数据等几个角度探讨了区块链技术重大突破对国民经济核算发展的影响。本文认为,为了适应区块链技术的发展,国民经济核算应在改变机构单位和基层单位的划分方法、扩展数据生产边界、拓展数据资产核算范围、完善金融产出和金融资产处理方法、加强跨境经济活动核算等方面进一步优化创新。     

Copula-Based Models for the Power of Independence Tests

ABSTRACT

We consider independence tests and the methods to evaluate their efficiency. First, we observe that many of the most used independence tests are functions of the empirical copula, which is a sufficient statistic. Hence, the power of these tests, such as the tests based on Spearman's ρ, on Kendall's τ, and on Gini's γ, depend solely on the theoretical copula, and not on the marginal distributions. Then, we consider monotone dependence tests and we propose a parametric model to define the power function. Such a model is based on a path of copulas, from the copula of discordance to the copula of concordance, and can be characterized by the copula of the underlying joint distribution. Moreover, we introduce a consistent estimator of the path of copulas. Finally, we provide some examples of applications, and in particular, a bootstrap-plug-in estimator of the power curve, all useful for power comparison.     

Bootstrap diagnostics and remedies

Bootstrap diagnostics are used to assess the reliability of bootstrap calculations and may suggest useful modified calculations when these are possible. Concern focuses on susceptibility to peculiarities in data, incorrectness of a resampling model, incorrect use of resampling simulation output, and inherent inaccuracy of the bootstrap approach. The last involves issues such as inconsistency of a bootstrap method, the order of correctness of a consistent bootstrap method, and approximate pivotality. The authors review here some of these problems, provide workable diagnostic methods where possible, and discuss fast and simple ways to effect the necessary computations.     

Multivariate Stochastic Volatility: A Review

The literature on multivariate stochastic volatility (MSV) models has developed significantly over the last few years. This paper reviews the substantial literature on specification, estimation, and evaluation of MSV models. A wide range of MSV models is presented according to various categories, namely, (i) asymmetric models, (ii) factor models, (iii) time-varying correlation models, and (iv) alternative MSV specifications, including models based on the matrix exponential transformation, the Cholesky decomposition, and the Wishart autoregressive process. Alternative methods of estimation, including quasi-maximum likelihood, simulated maximum likelihood, and Markov chain Monte Carlo methods, are discussed and compared. Various methods of diagnostic checking and model comparison are also reviewed.     

Reliability Studies of the Log-Exponential Inverse Gaussian Distribution

In this article, we investigate the monotonicity of the density, failure rate, and mean residual life functions of the log-exponential inverse Gaussian distribution. It turns out that, in this case, the monotonicity of the density, failure rate, and mean residual life functions take different forms depending on the range of the parameters. Maximum likelihood estimators of the critical points of the density, failure rate, and mean residual life functions of the model are evaluated using Monte Carlo simulations. An example of a published data set is used to illustrate the estimation of the critical points.     

Addressing the problem of missing data in decision tree modeling

Tree-based models (TBMs) can substitute missing data using the surrogate approach (SUR). The aim of this study is to compare the performance of statistical imputation against the performance of SUR in TBMs. Employing empirical data, a TBM was constructed. Thereafter, 10%, 20%, and 40% of variable values appeared as the first split was deleted, and imputed with and without the use of outcome variables in the imputation model (IMP? and IMP+). This was repeated one thousand times. Absolute relative bias above 0.10 was defined as sever (SARB). Subsequently, in a series of simulations, the following parameters were changed: the degree of correlation among variables, the number of variables truly associated with the outcome, and the missing rate. At a 10% missing rate, the proportion of times SARB was observed in either SUR or IMP? was two times higher than in IMP+ (28% versus 13%). When the missing rate was increased to 20%, all these proportions were approximately doubled. Irrespective of the missing rate, IMP+ was about 65% less likely to produce SARB than SUR. Results of IMP? and SUR were comparable up to a 20% missing rate. At a high missing rate, IMP? was 76% more likely to provide SARB estimates. Statistical imputation of missing data and the use of outcome variable in the imputation model is recommended, even in the content of TBM.