Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

A new generalized Weibull distribution in income economic inequality curves

Researchers have been developing various extensions and modified forms of the Weibull distribution to enhance its capability for modeling and fitting different data sets. In this note, we investigate the potential usefulness of the new modification to the standard Weibull distribution called odd Weibull distribution in income economic inequality studies. Some mathematical and statistical properties of this model are proposed. We obtain explicit expressions for the first incomplete moment, quantile function, Lorenz and Zenga curves and related inequality indices. In addition to the well-known stochastic order based on Lorenz curve, the stochastic order based on Zenga curve is considered. Since the new generalized Weibull distribution seems to be suitable to model wealth, financial, actuarial and especially income distributions, these findings are fundamental in the understanding of how parameter values are related to inequality. Also, the estimation of parameters by maximum likelihood and moment methods is discussed. Finally, this distribution has been fitted to United States and Austrian income data sets and has been found to fit remarkably well in compare with the other widely used income models.     

Beyond Piketty: A new perspective on poverty and inequality in India

The socio-economic literature has focused much on how overall inequality in income distribution (frequently measured by the Gini coefficient) undermines the “trickle down” effect. In other words, the higher the inequality in the income distribution, the lower is the growth elasticity of poverty. However, with the publication of Piketty’s magnum opus (2014), and a subsequent study by Chancel and Piketty (2017) of evolution of income inequality in India since 1922, the focus has shifted to the income disparity between the richest 1% (or 0.01%) and the bottom 50%. Their central argument is that the rapid growth of income at the top end of millionaires and billionaires is a by-product of growth. The present study extends this argument by linking it to poverty indices in India. Based on the India Human Development Survey 2005–12 – a nationwide panel survey-we examine the links between poverty and income inequality, especially in the upper tail relative to the bottom 50%, state affluence (measured in per capita income) and their interaction or their joint effect. Another feature of our research is that we analyse their effects on the FGT class of poverty indices. The results are similar in as much as direction of association is concerned but the elasticities vary with the poverty index. The growth elasticities are negative and significant for all poverty indices. In all three cases, the disparity between the income share of the top 1% and share of the bottom 50% is associated with greater poverty. These elasticities are much higher than the (absolute) income elasticities except in the case of the poverty gap. The largest increase occurs in the poverty gap squared – a 1% greater income disparity is associated with a 1.24% higher value of this index. Thus the consequences of even a small increase in the income disparity are alarming for the poorest.     

中国近年来消费需求增长乏力的原因探析

消费需求增长乏力是近年来我国宏观经济面临的突出问题,这是居民消费能力、消费动力和消费环境三方面因素共同作用的结果。首先,居民收入增加与GDP增长不同步导致居民消费能力有限,而收入差距不断拉大则引起消费能力分配失衡;其次,未来收入和支出的预期不稳定、消费信贷制度滞后等在很大程度上降低了居民消费动力;最后,相关配套体制和设施不健全、与市场经济不协调的消费习惯等也都影响了消费需求的增加。     

完善我国个人所得税制的思考

个人所得税是调节国家与个人利益分配关系的重要杠杆,随着我国经济的快速发展、居民收入水平的大幅提高,个人所得税将是一项最有前途、最有发展潜力的税种。但我国个人所得税政策不尽人意,执行起来既失公平,又欠效率。文章分析了我国个人所得税制存在的问题,提出了相应的对策。     

谈分级显性意义假说对反语中的认知参照点的解释力

本文运用Giora的分级显性意义假说分析了Langacker的认知参照点理论，并对反语中的认知参照点进行分析，得出反语中的认知参照点也是层级突显的结论，为反语的理解提供一个新的视角。     

网络社会各阶层的分析

网络社会是一种新的社会形态,其内部结构是不同接点组成的亚网络。具有相同信息编码的接点就是网络社会的一个阶层。由互联网重构的网络社会,结构上可分为三个大类,在每个大类下面又可以分成若干阶层。网络社会的每一个阶层之间也存在着不平等,如果这种不平等演变出巨大的数字鸿沟,将给现实世界带来新的社会问题。     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.     

Public Attitudes towards Income Redistribution: Evidence from Hong Kong

The drivers of public support for redistributive policy have stimulated academic debate around the world. The majority of studies use cross‐country surveys conducted in the Organisation for Economic Co‐operation and Development countries to contribute to the debate on whether self‐interest or social values have more influence on public attitudes towards redistribution. Drawing on a phone survey conducted in 2013, this study advances the discussion by investigating public attitudes towards redistribution and social policy changes against the backdrop of buoyant government revenues in Hong Kong. The Hong Kong welfare model, best seen as a parallel to the liberal welfare state, is selective and residual. Contrary to the usual assumption, the social values hypothesis, viewing poverty as societal problems instead of individual reasons, has been supported in the Hong Kong context. It lends support to greater redistribution in a residual welfare state. The policy implications of the findings are also discussed.     

Multiple hypothesis tests based On conditional differences in means

Many hypothesis tests are univariate tests and cannot cope with multiple hypothesis without an auxiliary procedure as e. g. the Bonferroni-Holm-procedure. At the same time, there is an urgent need for testing multiple hypothesis due to the very simple existing methods as the Bonferroni-correction or the Bonferroni-Holm-procedure, which suffers from a very small local significance level to detect statistical inferences or the drawback that logical and statistical dependencies among the test statistics are not used, whereby its detection is NP-hard. In honour of this occasion, we present a multiple hypothesis test for i.i.d. random variables based on conditional differences in means, which is capable to cope with multiple hypothesis and does not suffer on such drawbacks as the Bonferroni-correction or the Bonferroni-Holm-procedure. Thereby, the computation time can be neglected.