一类二阶中立型时滞差分方程的振动定理

研究了一类具有变系数的二阶中立型时滞差分方程的振动性,得到了该类方程振动及差分算子△振动的一个充分条件.     

非线性时滞差分方程解的振动性

讨论了时滞差分系统yn＋1－yn＋Pnf（yn－k）＝0n＝0,1,2,...（y≠0）的振动性,得到了上式方程解振动的一组充分条件．     

常系数齐次线性微分方程组与其相应的差分方程组之间的联系

给出了求解常系数线性齐次微分方程组和常系数线性齐次差分方程组的一个方法,指出了这两种方程组之间存在的一个有趣关系．     

The role of parenthood in shaping the gender wage gap – A comparative analysis of 26 European countries

We use cross-national data on 26 EU countries to estimate how parenthood contributes to the gender wage gap, and assess how institutional elements affect this relationship. We find that irrespective of cultural norms and policies, fathers receive a wage premium, which increases the gender gap. Motherhood gaps vary across countries. The highest gaps are seen in Eastern European countries, where policies and norms lead to long absences from work. Moderate to small penalties are found in Continental Europe, Anglo-Saxon and Nordic countries, alongside higher maternal employment. No motherhood penalties are found for Southern EU countries, where mothers return to work quickly or exit the labor market indefinitely.     

空间效率、外部性与区域收入差异研究

从空间效率和外部性的角度来探讨区域收入差异问题,以新经济地理学经典的工资方程为理论基础,利用中国2000-2009年30个省份的面板数据以及分位数回归的方法,检验了各种类型的市场潜能(金融外部性或空间效率)、就业密度(技术外部性)和地区工资的关系.研究发现:无论是全国样本还是分地区样本,市场潜能对地区工资的正向效应显著;在分样本中,就业密度外部性对地区工资具有“门槛”效应;除中西部地区,国外市场潜能(出口开放)和国内市场潜能之间具有明显的替代关系;不同分位点处,不同区域下的解释变量对于职工平均工资的影响具有鲜明的区域特征.     

U-Statistics based on spacings

In this paper, we investigate the asymptotic theory for U-statistics based on sample spacings, i.e. the gaps between successive observations. The usual asymptotic theory for U-statistics does not apply here because spacings are dependent variables. However, under the null hypothesis, the uniform spacings can be expressed as conditionally independent Exponential random variables. We exploit this idea to derive the relevant asymptotic theory both under the null hypothesis and under a sequence of close alternatives.The generalized Gini mean difference of the sample spacings is a prime example of a U-statistic of this type. We show that such a Gini spacings test is analogous to Rao's spacings test. We find the asymptotically locally most powerful test in this class, and it has the same efficacy as the Greenwood statistic.     

中美利差对人民币汇率变动的影响分析

以利差对汇率传导机制和路径的理论分析为基础,通过建立汇率行为路径分析模型,检验有关名义利差与名义汇率关系的理论和经验方面的问题。中美实证研究结果表明,名义利差变动对名义汇率变动的影响支持利率平价理论,但利差对汇率变动的传导路径较利率平价理论更为复杂,且传导方式和效应大小在2005年7月汇改前后有显著差别。     

Estimation of parameters in heavy-tailed distribution when its second order tail parameter is known

Estimating parameters in heavy-tailed distribution plays a central role in extreme value theory. It is well known that classical estimators based on the first order asymptotics such as the Hill, rank-based and QQ estimators are seriously biased under finer second order regular variation framework. To reduce the bias, many authors proposed the so-called second order reduced bias estimators for both first and second order tail parameters. In this work, estimation of parameters in heavy-tailed distributions are studied under the second order regular variation framework when the second order parameter in the distribution tail is known. This is motivated in large part by a recent work by the authors showing that the second order tail parameter is known for a large class of popular random difference equations (for example, ARCH models). The focus is on least squares estimators that generalize rank-based and QQ estimators. Though other possible estimators are also briefly discussed, the least squares estimators are most simple to use and perform best for finite samples in Monte Carlo simulations.     

The failure of meta-analytic asymptotics for the seemingly efficient estimator of the common risk difference

We consider the case of a multicenter trial in which the center specific sample sizes are potentially small. Under homogeneity, the conventional procedure is to pool information using a weighted estimator where the weights used are inverse estimated center-specific variances. Whereas this procedure is efficient for conventional asymptotics (e. g. center-specific sample sizes become large, number of center fixed), it is commonly believed that the efficiency of this estimator holds true also for meta-analytic asymptotics (e.g. center-specific sample size bounded, potentially small, and number of centers large). In this contribution we demonstrate that this estimator fails to be efficient. In fact, it shows a persistent bias with increasing number of centers showing that it isnot meta-consistent. In addition, we show that the Cochran and Mantel-Haenszel weighted estimators are meta-consistent and, in more generality, provide conditions on the weights such that the associated weighted estimator is meta-consistent.     

Statistics for weighing benefits and harms in a proposed genetic substudy of a randomized cancer prevention trial

Summary.  When evaluating potential interventions for cancer prevention, it is necessary to compare benefits and harms. With new study designs, new statistical approaches may be needed to facilitate this comparison. A case in point arose in a proposed genetic substudy of a randomized trial of tamoxifen versus placebo in asymptomatic women who were at high risk for breast cancer. Although the randomized trial showed that tamoxifen substantially reduced the risk of breast cancer, the harms from tamoxifen were serious and some were life threaten-ing. In hopes of finding a subset of women with inherited risk genes who derive greater bene-fits from tamoxifen, we proposed a nested case–control study to test some trial subjects for various genes and new statistical methods to extrapolate benefits and harms to the general population. An important design question is whether or not the study should target common low penetrance genes. Our calculations show that useful results are only likely with rare high penetrance genes.