非线性Granger因果检验方法的检验功效及有限样本性质的模拟分析

为了克服传统Granger因果检验方法因忽略经济变量的非线性特征而导致结论出现显著偏差的局限性,非线性Granger因果检验方法在近年来正逐步成为经济学研究领域的重要分析工具。然而,迄今为止,学术界仍较少对非线性Granger因果检验方法在不同非线性模型中的有限样本性质展开系统性的比较与分析,因此,本文通过数据生成过程（DGP）,结合Monte Carlo模拟对Diks和Panchenko（2006）等主流的非线性Granger因果检验方法的检验功效、过度拒绝等问题展开比较研究,并对共同滞后阶数、带宽参数的不同设置可能引发结论敏感性变化进行深入分析,在此基础上我们从动态非线性滚动分析的角度对其有限样本性质展开进一步的讨论,并提出对未来非线性应用研究具有实际指导价值的若干建议。     

LSTAR-GARCH模型的单位根检验

LSTAR模型的单位根检验往往易忽视其条件方差的时变性,实际上,对许多经济变量尤其是金融变量建立LSTAR模型后,经常发现其条件方差存在GARCH效应。针对LSTAR-GARCH模型的平稳性检验,本文构建了检验统计量tNG,之后在极大似然估计的基础上,推导出tNG的渐近分布,通过蒙特卡洛模拟方法得到该统计量的渐近临界值,并在此基础上研究了tNG检验的检验功效。在与刘雪燕和张晓峒(2009)提出的tNL检验、Ling等(2003)提出的tLG检验以及DF单位根检验进行比较后,发现tNG检验具备明显优势。     

我国正规就业者的教育收益率

针对教育收益率测算中可能存在的弱工具变量问题,本文利用2006年中国健康与营养调查数据,结合工具变量估计框架下的各种模型设定检验,对我国正规就业者的教育收益率进行测算。检验和测算结果表明：受教育程度的变量存在内生性,个体配偶的受教育年限是内生变量受教育程度的强工具变量,而个体的出生季度是弱工具变量。广义矩估计结果显示我国正规就业者的教育收益率为10.1%。     

一类基于非参数回归的条件异方差检验

现有基于参数模型构造的条件异方差检验往往存在模型设定偏误问题。为了避免模型误设对检验结果的影响,并且同时捕获多种条件异方差现象,本文基于非参数回归构造了不依赖于特定模型形式的条件异方差检验统计量。该统计量可视作条件方差和无条件方差之间差异的加权平均,在原假设成立时渐近服从标准正态分布。数值模拟结果一方面表明本文统计量具有良好的有限样本性质,另一方面也说明条件均值模型误设会导致错误地拒绝条件同方差的原假设,凸显了本文引入非参数方法构造条件异方差检验的必要性。实证分析采用本文统计量探讨了国际主要股指收益率的条件异方差现象,得到了与Engle (1982)不同的检验结果,可能意味着股指收益率呈现出非线性动态特征。     

Customizing Generalizations of the Kolmogorov-Smirnov Goodness-of-fit Test

This paper presents a method of customizing goodness-of-fit tests that transforms the empirical distribution function in such a way as to create tests for certain alternatives. Using the @ , g transform described in Blom(1958), one can create non-parametric tests for an assortment of alternative distributions. As examples, three new ( f , g )-corrected Kolmogorov-Smirnov tests for goodness-of-fit are discussed. One of these tests is powerful for testing whether or not the data come from an alternative that is heavier in the tails. Another test identifies whether or not the data come from an alternative which is heavier in the middle of the distribution. The last test identifies if the data come from an alternative in which the first or third quartile is far from the corresponding quartile of the hypothesized distribution. The behavior of the three new tests is investigated through a power study.     

决定论的含义与真假问题

古代已有因果决定论和神灵决定论,近代学者又以力学规律充实因果决定论而使之发展成严格定量的形式。从中可以看到决定论的基本含义:过去未来的一切皆有定数;其之形成根据则是因果关系和客观规律的普遍存在。但自由意志论却长期支持着非决定论的存在;现代科学又在微观过程和复杂系统中揭示出了许多新的不确定性现象,致使一些论者提出各种折衷性的弱决定论观点。然而我们通过对于各种新不确定性现象的实质分析表明,它们都不真是"本质上的偶然性",并不否定决定论的严格存在;而且人也并没有超越神经生理活动的自由意志。真正使决定论不能成立的乃是世界的无限性:无限世界是不能完成综合的,故而不是一个可总括的整体或系统,因果规律对其不能适用;同时,无限世界中的有限系统和事物也因会有无限的外来影响因素而不能有决定论的未来定数。     

Testing the equality of two independent regression models

In some situations, for example in agriculture, biology, hydrology, and psychology, researchers wish to determine whether the relationship between response variable and predictor variables differs in two populations. In other words, we are interested in comparing two regression models for two independent datasets. In this work, we will use the parametric and nonparametric methods to establish hypothesis testing for the equality of two independent regression models. Then the simulation study is provided to investigate the performance of the proposed method.     

Estimating the error distribution function in semiparametric additive regression models

We consider semiparametric additive regression models with a linear parametric part and a nonparametric part, both involving multivariate covariates. For the nonparametric part we assume two models. In the first, the regression function is unspecified and smooth; in the second, the regression function is additive with smooth components. Depending on the model, the regression curve is estimated by suitable least squares methods. The resulting residual-based empirical distribution function is shown to differ from the error-based empirical distribution function by an additive expression, up to a uniformly negligible remainder term. This result implies a functional central limit theorem for the residual-based empirical distribution function. It is used to test for normal errors.     

A new way of quantifying the symmetry of a random variable: Estimation and hypothesis testing

New measures of skewness for real-valued random variables are proposed. The measures are based on a functional representation of real-valued random variables. Specifically, the expected value of the transformed random variable can be used to characterize the distribution of the original variable. Firstly, estimators of the proposed skewness measures are analyzed. Secondly, asymptotic tests for symmetry are developed. The tests are consistent for both discrete and continuous distributions. Bootstrap versions improving the empirical results for moderated and small samples are provided. Some simulations illustrate the performance of the tests in comparison to other methods. The results show that our procedures are competitive and have some practical advantages.     

购买力平价及其在亚洲新兴市场中的实证分析

 作为最重要的汇率决定理论之一,购买力平价被广泛应用于实证研究,但是重点针对亚洲新兴市场的研究依然有限。本文对七个亚洲新兴市场进行了购买力平价理论长期均衡关系的实证检验分析。针对购买力平价理论,作者运用单位根检验和协整检验进行数据分析。数据采用1957年至2011年的汇率（以美元作为基础汇率）及季度价格水平（本文采用CPI作为价格水平指数）。实证检验结果表明购买力平价理论的长期均衡在亚洲新兴市场中均不成立。文章最后提出了一些或许会导致其不理想结论的因素,并针对文章的实证研究得出新的改进方法。