Testing symmetry under a skew Laplace model

We develop tests of hypothesis about symmetry based on samples from possibly asymmetric Laplace distributions and present exact and limiting distribution of the test statistics. We postulate that the test statistic derived under the Laplace model is a rational choice as a measure of skewness and can be used in testing symmetry for other, quite general classes of skew distributions. Our results are applied to foreign exchange rates for 15 currencies.     

新资本结构理论综述

随着资本结构研究的深入,理论界进一步放宽MM定理的基本假设。以Jensen,Myers,Ross,Leland,Harris,Hart等学者为代表的新资本结构理论引入最新的研究方法,对资本结构展开分析。本文按照新资本结构理论发展的历史轨迹,全面评述了资本结构理论中最为重要的各种理论,同时系统地描述了各有关理论的基本内容。     

Allocation of resources in asymmetric competitions: How do the weak maintain a chance of winning?

To maintain a chance of occasionally beating a stronger player in a competition waged over several fields, a weaker player should give up on some of the fields and concentrate resources on the remaining ones. But when do weak players actually do this? And which fields do they give up when the fields differ in their likelihood of being assessed? We report an experimental study of resource allocation in which asymmetric pairs of players compete over asymmetric fields. Symmetric players and symmetric fields are used for control. We find that players behave as follows: (1) Average wins are the same in the symmetric and asymmetric fields conditions and correspond to relative player strength. (2) The proportion of fields given up on decreases with a player’s greater relative strength, increases for asymmetric field likelihoods, and increases when competitions are framed in meaningful context; this proportion is related to wins. (3) When field likelihoods are asymmetric, players’ resource allocation is correlated with likelihood. Wins generally increase with that correlation but the relation is different for players of different strength. (4) The proportion of fields given up on and the correlation with likelihood change with experience towards the values corresponding to higher wins.     

Improved communality estimation in factor analysis

The symmetric treatment of an asymmetric approach to factor analysis is shown to provide accurate communality estimates. In comparison with existing estimates including upper and lower bounds, the present approach is shown to be superior. In one example with known communalities, the present approach perfectly captures those communalities. In two empirical examples, it is shown to produce better communality estimates than any existing method.     

A non-iterative posterior sampling algorithm for linear quantile regression model

In this article, a non-iterative posterior sampling algorithm for linear quantile regression model based on the asymmetric Laplace distribution is proposed. The algorithm combines the inverse Bayes formulae, sampling/importance resampling, and the expectation maximization algorithm to obtain independently and identically distributed samples approximately from the observed posterior distribution, which eliminates the convergence problems in the iterative Gibbs sampling and overcomes the difficulty in evaluating the standard deviance in the EM algorithm. The numeric results in simulations and application to the classical Engel data show that the non-iterative sampling algorithm is more effective than the Gibbs sampling and EM algorithm.     

Measuring Social Tension from Income Class Segregation

We develop an index that effectively measures the level of social tension generated by income class segregation. We adopt the basic concepts of between-group difference (or alienation) and within-group similarity (or identification) from the income [bi]polarization literature; but we allow for asymmetric degrees of between-group antagonism in the alienation function, and construct a more effective identification function using both the relative degree of within-group clustering and the group size. To facilitate statistical inference, we derive the asymptotic distribution of the proposed measure using results from U-statistics. As the new measure is general enough to include existing income polarization indices as well as the Gini index as special cases, the asymptotic result can be readily applied to these popular indices. Evidence from the Panel Study of Income Dynamics data suggests that, while the level of social tension shows an upward trend over the sample period of 1981 to 2005, government’s taxes and transfers have been effective in reducing the level of social tension significantly.     

印度对中印跨境河流水关系的认知及战略选择

近年来,印度对中印在跨境河流水关系中的不平衡问题非常重视.其中,水文信息不对称以及收益不平衡是印度对水关系不平衡的两个主要认知.基于中印边境的互动历史,印度在对水关系的认知形成中往往会夸大中国的敌意与威胁.据此,印度试图通过建立制度框架、将中印水争议国际化以及竞争性开发跨境河流水资源的战略思维,平衡中国在雅鲁藏布江—布拉马普特拉河水关系中的优势地位.然而受水外交两面性特征和内政的掣肘,印度平衡战略的影响有限,而且更强化了其对雅鲁藏布江—布拉马普特拉河战略安全收益的重视,并使未来中印双方基于水资源共同利益进行合作的难度加大.     

Bayesian quantile regression for skew-normal linear mixed models

Linear mixed models have been widely used to analyze repeated measures data which arise in many studies. In most applications, it is assumed that both the random effects and the within-subjects errors are normally distributed. This can be extremely restrictive, obscuring important features of within-and among-subject variations. Here, quantile regression in the Bayesian framework for the linear mixed models is described to carry out the robust inferences. We also relax the normality assumption for the random effects by using a multivariate skew-normal distribution, which includes the normal ones as a special case and provides robust estimation in the linear mixed models. For posterior inference, we propose a Gibbs sampling algorithm based on a mixture representation of the asymmetric Laplace distribution and multivariate skew-normal distribution. The procedures are demonstrated by both simulated and real data examples.     

A new nonlinear asymmetric cointegration approach using error correction models

In this article, two new powerful tests for cointegration are proposed. The general idea is based on an intuitively appealing extension of the traditional, rather restrictive cointegration concept. In this article, we allow for a nonlinear, but most importantly a different, asymmetric convergence process to account for negative and positive changes in our cointegration approach. Using Monte Carlo simulations we verify, that the estimated size of the first test depends on the unknown value of a signal-to-noise ratio q. However, our second test—which is based on the original ideas of Kanioura and Turner—is more successful and robust in the sense that it works in all of the different evaluated situations. Furthermore it is shown to be more powerful than the traditional residual based Enders and Siklos method. The new optimal test is also applied in an empirical example in order to test for potential nonlinear asymmetric price transmission effects on the Swedish power market. We find that there is a higher propensity for power retailers to rapidly and systematically increase their retail electricity prices subsequent to increases in Nordpool's wholesale prices, than there is for them to reduce their prices subsequent to a drop in wholesale spot prices.     

Bootstrap forecast intervals for asymmetric volatilities via EGARCH model

Bootstrap forecast intervals are developed for volatilities having asymmetric features, which are accounted for by fitting EGARCH models. A Monte-Carlo simulation compares the proposed forecast intervals with those based on GARCH fittings which ignore asymmetry. The comparison reveals substantial advantage of addressing asymmetry through EGARCH fitting over ignoring it as the conventional GARCH forecast. The EGARCH forecast intervals have empirical coverage probabilities closer to the nominal level and/or have shorter average lengths than the GARCH forecast intervals. The finding is also supported by real dataset analysis of Dow–Jones index and financial times stock exchange (FTSE) 100 index.