A test for the parametric form of the variance function in a partial linear regression model

We consider the problem of testing for a parametric form of the variance function in a partial linear regression model. A new test is derived, which can detect local alternatives converging to the null hypothesis at a rate n^-1/2$n^{-1/2}$ and is based on a stochastic process of the integrated variance function. We establish weak convergence to a Gaussian process under the null hypothesis, fixed and local alternatives. In the special case of testing for homoscedasticity the limiting process is a scaled Brownian bridge. We also compare the finite sample properties with a test based on an L²$L^2$-distance, which was recently proposed by You and Chen [2005. Testing heteroscedasticity in partially linear regression models. Statist. Probab. Lett. 73, 61–70].     

基于VAR模型的四川经济增长与投资消费关系实证研究

选取1990-2010年四川省经济数据,运用格兰杰因果检验、VAR模型和脉冲响应分析等方法对四川省经济增长与投资消费之间的关系进行了实证研究,结果表明：不论时间长短,投资水平对经济增长和消费水平的影响相对显著,而经济增长和消费水平在短期内对其他两项的影响不显著。     

论大学英语词汇教学

英语语言学家威尔金斯对词汇的定义和最新颁布的《大学英语课程教学要求(》试行)对大学英语词汇教学的要求,都阐释了词汇在大学英语教学中的重要性。文章介绍了现阶段大学英语教学的情况,并通过调查分析,发现以大学英语四、六级考试为目的的大学英语词汇教学的弊病,提出科学的词汇教学方法,并对词汇教学与大学英语教学之间的关系进行了阐释。     

A test of the normality assumption in ordered probit model

This paper presents a Lagrange multiplier test of the normality assumption underlying the ordered probit model. The test is presented both for the standard ordered probit model and a version in which censoring is present in the dependent variable. The test is then compared to normality tests proposed here compares favorably to tests based on artificial regression techinques.     

A monte carlo comparison of tests based on the durbin-watson statistic with other autocorrelation tests in dynamic models

This paper examines the sampling properties of a number of serial correlation tests in dynamic linear models which include one or two lags of the dependent variable. Among the tests considered are the Durbin-Watson (DW) bounds test, modified versions of the DW proposed recently by King and Wu and Inder, Durbin's m test, Inder's point optimal test and a Hausman type test. Sampling designs include models with one or two lags of the dependent variable. The m, Hausman, and Inder's tests have the best performance, while Inder's modified DW test appears to be better than the other DW based tests. Results also suggest that tests are less powerful and more sensitive to design parameters in models with higher dynamics, with the DW-based tests being the most sensitive.     

Bootstrapping a consistent nonparametric goodness-of-fit test

In this paper, we employ the parametric bootstrap to approximate the finite sample distribution of a goodness-of-fit test statistic in Fan (1994). We show that the proposed bootstrap procedure works in that the bootstrap distribution conditional on the random sample tends to the asymptotic distribution of the test statistic in probability. A simulation study demonstrates that the bootstrap approximation works extremely well in small samples with only 25 observations and is very robust to the value of the smoothing parameter in the kernel density estimation.     

地方保护主义和地区间贸易壁垒的检验性分析

随着市场经济的发展,贸易作为经济运行中的一个环节,其重要性越来越凸现出来,而阻碍贸易正常进行的地方保护主义和贸易壁垒对宏观经济的良性发展起到了消极的作用。准确把握我国地方保护主义和地区间贸易壁垒的现状意义重大。本文基于国务院发展研究中心发展战略和区域经济研究部与北京大学光华管理学院所作的“地区间经济联系障碍的调查问卷”,对前期回收的有效样本,运用统计检验分析的方法,就当前地方保护和贸易壁垒的存在性以及企业的不同类型是否与其面临的地方保护和贸易壁垒有程度上的关联等问题做了相关研究,认为企业的规模和所有制性质对企业面临的地方保护和贸易壁垒基本没有程度上的影响;同时,统计分析结果还表明目前国内地区间贸易壁垒偏重于无形和隐形的形式。     

The application of the durbin-watson test to the dynamic regression model under normal and non-normal errors

Until recently, a difficulty with applying the Durbin-Watson (DW) test to the dynamic linear regression model has been the lack of appropriate critical values. Inder (1986) used a modified small-disturbance distribution (SDD) to find approximate critical values. King and Wu (1991) showed that the exact SDD of the DW statistic is equivalent to the distribution of the DW statistic from the regression with the lagged dependent variables replaced by their means. Unfortunately, these means are unknown although they could be estimated by the actual variable values. This provides a justification for using the exact critical values of the DW statistic from the regression with the lagged dependent variables treated as non-stochastic regressors. Extensive Monte Carlo experiments are reported in this paper. They show that this approach leads to reasonably accurate critical values, particularly when two lags of the dependent variable are present. Robustness to non-normality is also investigated.     

Extending the Barnard’s test to non-inferiority

In 1945, George Alfred Barnard presented an unconditional exact test to compare two independent proportions. Critical regions for this test, by construction accomplish the very useful property of being Barnard convex sets. Besides, there are empirical findings suggesting that Barnard’s test is the most generally powerful. For Barnard’s test, calculation of critical regions is complicated due that they are constructed in an iterative form until is obtained a test size, as close as possible to the nominal significance level and less than or equal to it. In this article we present an extension to non-inferiority of this very leading test. This extension was contructed for any dissimilarity measure and tables were constructed for the difference between proportions. Also we calculate the critical regions for this extended test for sample sizes less or equal than 30, nominal significance level 0.01, 0.025, 0.05, and 0.10 and for non-inferiority margins 0.05, 0.10, 0.15, and 0.20. Additionally, we computed test sizes for the mentioned configurations. To do this calculations, we have written a program in the R environment.     

Testing hypotheses about covariance matrices using bootstrap methods

The usual chi-squared approximation to test statistics based on normal theory for testing covariance structures of multivariate populations is very sensitive to the normality assumption. Two general bootstrap procedures are developed in this paper to obtain approximately valid critical values for these test statistics when the data are not normally distributed. The first is based on separate sampling from individual samples, and the second is based on sampling from pooled samples. Although the second method requires more assumptions, its small sample properties are better.