On the power of goodness-of-fit tests for the exponential distribution under progressive Type-II censoring

The aim of this article is to review existing goodness-of-fit tests for the exponential distribution under progressive Type-II censoring and to provide some new ideas and adjustments. In particular, we consider two-parameter exponentially distributed random variables and adapt the proposed test procedures to our scenario if necessary. Then, we compare their power by an extensive simulation study. Furthermore, we propose five new test procedures that provide reasonable alternatives to those already known.     

Testing the dilation order by using cumulative residual Tsallis entropy

In this paper, we introduce a new test for the dilation order based on cumulative residual Tsallis entropy of order α. The effect of the values of parameter α on the power of the test statistics is numerically investigated. The asymptotic distribution of the test statistic is given. The performance of the test statistic is evaluated using a simulation study. Finally, some numerical examples illustrating the theory are also given.     

On comparing,classifying and clustering several dependent regression models

Classifying several regression models fitted on a dataset is one of the most problems in data analysis. In other words, scientists are interested in comparing several regression models that can be used for a dataset. In this paper, an approach will be used to compare and classify several dependent regression models. Then the performance of the proposed method is investigated using simulation study and real example.     

A misspecification test for the higher order co-moments of the factor model

The traditional estimation of higher order co-moments of non-normal random variables by the sample analog of the expectation faces a curse of dimensionality, as the number of parameters increases steeply when the dimension increases. Imposing a factor structure on the process solves this problem; however, it leads to the challenging task of selecting an appropriate factor model. This paper contributes by proposing a test that exploits the following feature: when the factor model is correctly specified, the higher order co-moments of the unexplained return variation are sparse. It recommends a general to specific approach for selecting the factor model by choosing the most parsimonious specification for which the sparsity assumption is satisfied. This approach uses a Wald or Gumbel test statistic for testing the joint statistical significance of the co-moments that are zero when the factor model is correctly specified. The asymptotic distribution of the test is derived. An extensive simulation study confirms the good finite sample properties of the approach. This paper illustrates the practical usefulness of factor selection on daily returns of random subsets of S&P 100 constituents.     

On Hotelling’s T2 test in a special paired sample case

In a special paired sample case, Hotelling’s T² test based on the differences of the paired random vectors is the likelihood ratio test for testing the hypothesis that the paired random vectors have the same mean; with respect to a special group of affine linear transformations it is the uniformly most powerful invariant test for the general alternative of a difference in mean. We present an elementary straightforward proof of this result. The likelihood ratio test for testing the hypothesis that the covariance structure is of the assumed special form is derived and discussed. Applications to real data are given.     

Identifying Systemically Important Banks: A temporal approach for macroprudential policies

Contrary to the general belief, systemic risk does not only regard the risk posed by balance sheet relationships and interdependencies among institutions. It also features a temporal dimension related to the inappropriate responses of financial market participants to changes in risk over time. This paper proposes a method to simultaneously address the cross-sectional and the time dimension in which systemic risk materializes. The method is based on the TOPHITS algorithm. It provides three scores, namely borrowing, lending and time scores: the first two represent the systemic importance of the borrowing and the lending activity associated with each financial institution,while the third represents an empirical Early Warning Signal of the financial crisis. Our findings reveal that the identification of the time score as an indicator for an incoming market distress could be relevant to design macro prudential policies.     

电价波动的产业结构效应——基于CGE模型的分析

为探索电价波动与产业结构变化的关系,本文主要应用CGE(Computable General Equilibrium)模型对中国的电价波动与产业结构变化进行了实证研究。结果表明,各行业产出对电价的交叉弹性系数虽然很小,但耗电越多的行业对电价变化的反映越敏感。因此,本文认为,出于抑制高耗能产业膨胀、促进能效提高的目的,可以适当提高电价,但不能对电价的产业结构效应期望过高。同时应采取适当的电价调整方式,以避免电价波动的其他负面影响,促进电力合理利用和经济社会的可持续发展。     

个人教育投资的风险收益测度

将教育资本分解成受教育程度和职业的各种组合,借鉴Markowiz的有效投资组合理论,计算Mincer收入方程中扰动项的均值—标准差来衡量投资风险收益,以此建立中国教育投资风险和收益之间的平衡关系,并且利用F检验衡量投资组合的均值方差张成。结果表明,有效的教育资本组合不仅与所接受教育程度有关,还与未来职业选择有关。在以受教育程度为高中和中等职业的基础上,高中(06)可以张成其他全部14个投资组合的均值方差边界。因此,个体和政府在进行教育投资时,都需要全面衡量投资组合的风险收益平衡问题。     

Double and group acceptance sampling plan for truncated life test based on inverse log-logistic distribution

This paper introduces a double and group acceptance sampling plans based on time truncated lifetimes when the lifetime of an item follows the inverse log-logistic (ILL) distribution with known shape parameter. The operating characteristic function and average sample number (ASN) values of the double acceptance sampling inspection plan are provided. The values of the minimum number of groups and operating characteristic function for various quality levels are obtained for a group acceptance sampling inspection plan. A comparative study between single acceptance sampling inspection plan and double acceptance sampling inspection plan is carried out in terms of sample size. One simulated example and four real-life examples are discussed to show the applicability of the proposed double and group acceptance sampling inspection plans for ILL distributed quality parameters.     

论经济增长的驱动因素:劳动生产效率与产业结构——以江苏省为例

本文利用LMDI指数分解方法建立了人均增长率测算模型。该模型可以分析产业GDP结构、产业劳动力结构、产业全员劳动生产效率以及劳动力占总人口比重等因素对人均GDP增长率的影响。江苏省人均GDP增长率的实证分析,表明产业全员劳动生产率和产业结构是该省2010年实现人均GDP增长率200%的主要影响因素。