分位数回归及应用简介

文章介绍了分位数回归法的概念、算法及主流统计软件R和SAS计算时的语法,并通过实例与以普通最小二乘法为基础的线性回归进行了对比,展现了分位数回归的巨大魅力。     

OLS and IV estimation of regression models including endogenous interaction terms

We analyze a class of linear regression models including interactions of endogenous regressors and exogenous covariates. We show how to generate instrumental variables using the nonlinear functional form of the structural equation when traditional excluded instruments are unknown. We propose to use these instruments with identification robust IV inference. We furthermore show that, whenever functional form identification is not valid, the ordinary least squares (OLS) estimator of the coefficient of the interaction term is consistent and standard OLS inference applies. Using our alternative empirical methods we confirm recent empirical findings on the nonlinear causal relation between financial development and economic growth.     

On regression modelling with dummy variables versus separate regressions per group: Comment on Holgersson et al.

In a recent issue of this journal, Holgersson et al. [Dummy variables vs. category-wise models, J. Appl. Stat. 41(2) (2014), pp. 233–241, doi:10.1080/02664763.2013.838665] compared the use of dummy coding in regression analysis to the use of category-wise models (i.e. estimating separate regression models for each group) with respect to estimating and testing group differences in intercept and in slope. They presented three objections against the use of dummy variables in a single regression equation, which could be overcome by the category-wise approach. In this note, I first comment on each of these three objections and next draw attention to some other issues in comparing these two approaches. This commentary further clarifies the differences and similarities between dummy variable and category-wise approaches.     

Pitfalls in Estimating Cointegrating Vector when Cointegration Relationship has Nonlinear Adjustment

This article investigates the properties of the estimators of the cointegrating vector when the cointegration error has a nonlinear adjustment. We investigate the properties of three estimators, namely, ordinary least squares (OLS), dynamic OLS (DOLS), and autoregressive distributed lag (ADL) models. Monte Carlo simulation results demonstrate that although all the estimators have consistency under cointegration with a nonlinear adjustment, they suffer from severe size distortions for the t-statistics of the cointegrating vector when the cointegration error has a highly persistent nonlinear adjustment and endogeneity. The results imply that the use of DOLS and ADL for cointegration with nonlinear adjustment cannot sufficiently improve the estimates and size performances.     

Eating Disordered Behaviors and Body Disapproval in Adolescent Males Adjudicated for Sexual and Nonsexual Crimes

Using a large sample of adjudicated delinquent male youth (N = 696), we compared data from youth who had been adjudicated for sexually aggressive crimes and those who had been adjudicated for nonsexual offenses on eating dysfunction, body disapproval, history of sexual abuse, and pornography exposure. The sample included 526 (75.8%) youth adjudicated for sexual offenses and 170 (24.4%) youth adjudicated for nonsexual crimes. The average age of the sample was 16.8 years (SD = 1.6), and approximately half of the sample (47.7%, n = 310) self-identified as White. The results of hierarchical multiple regressions indicated that sexually aggressive youth scored significantly higher than nonsexually offending youth on both eating dysfunction and body disapproval measures. Pornography exposure and substance use predicted body disapproval and eating dysfunction in the entire sample of adjudicated youth. History of sexual abuse was a significant predictor of body disapproval in all adjudicated youth but was not a significant predictor of eating dysfunction. Implications for research and practice are offered.     

我国股票型开放式基金业绩实证分析

运用夏普指数模型、基于横截面数据的OLS分析法以及H—M折线模型,从基金的收益率、基金收益的持续性、基金经理选股与择时能力三方面对我国股票型开放式基金进行较为全面的检验分析。结果显示,股票型开放式基金的收益总体上优于市场基准组合,基金收益的持续性不明显,基金经理没有明显的选股能力与择时能力。在此基础上,对我国股票型开放式基金业绩做出总体评价,并提出促进其发展的对策建议。     

中国经济转型期城镇少数民族教育收益率的实证研究

文章分别使用了OLS方法和分位回归技术,考察了1995—2007年间中国城镇少数民族教育收益率的总体水平及其长期变化趋势,并将之与汉族进行了比较,发现在经济转型期,中国城镇居民教育收益率总体上呈逐年上升趋势,少数民族与汉族之间的教育收益率没有显著差异。政策的力量与市场的力量有机结合、相互叠加,是转型时期中国城镇少数民族的地位并没有发生逆转的重要原因。与汉族相同,少数民族的教育收益率随着收入分位点提高而逐渐减小,即收入水平越高,教育收益率越低。     

Immigration,ethnicity, and housing—Success hierarchies in Israel

The study assesses housing hierarchies among immigrants in Israel by investigating three different but complementary paths: homeownership, crowding, and access to housing goods. Data from the most recent Israeli census in 1995 (the 20% version file) allows us to classify the immigrant population by 46 countries or areas of origin, each meeting the criterion of having a minimum of 100 sample cases. I controlled for several confounding factors: immigration characteristics, community of residence, demographic and human-capital variables, household composition, and housing characteristics. The results of multivariate analyses suggest that membership in approximately half of the immigrant groups has a statistically significant effect on homeownership. Representing very different origin groups from developing countries in Asia and Africa, as well as developed areas in Western Europe and America, most of the effects are negative relative to the reference group of Polish Jews. The pace of home acquisition is fastest among immigrants from several former Soviet republics and slowest among Syrian and Ethiopian Israelis. A better ethnic hierarchy was found for the other two characteristics, crowding and housing goods, with immigrants from Asia, Africa, and Eastern Europe being at a disadvantage. Many of these gaps close as immigrants purchase housing and gain tenure in Israel. The pace of advancement, however, is not uniform. I speculate that the differences in pace reflect structural characteristics, cultural background, and immigration processes, as well as absorption policy, which were not fully indexed by the census data. The discussion addresses broader implications of the findings for ethnic differences and social stratification in immigration countries.     

农民工对中国经济的贡献测算

中国的农民工阶层是改革开放以后才出现的。根据公开的统计数据,近年来,农民工流动的规模每年已经超过1亿人。农民工占城市第二、第三产业劳动力的比重很多地方已经超过50%。可以说,农民工已经成为城市第二、第三产业劳动力大军的重要组成部分,农民工对中国国民经济的贡献功不可没。文章利用农业部农村固定观察点的数据,测算了农民工对全国第二、第三产业产值增长的贡献。研究结果表明,1995年至2005年,如果假设农民工劳动生产率与城市产业工人一样,则农民工对中国第二、第三产业产值贡献占到这些产业产值的14.77%~24.35%,平均每年为19.98%;如果假设农民工劳动生产率低于城市产业工人,则农民工对中国第二、第三产业产值贡献占到这些产业产值的1.67%~4.71%,平均每年为3.26%,而且贡献份额有逐年增长的趋势。     

Cluster-based multivariate outlier identification and re-weighted regression in linear models

A cluster methodology, motivated by a robust similarity matrix is proposed for identifying likely multivariate outlier structure and to estimate weighted least-square (WLS) regression parameters in linear models. The proposed method is an agglomeration of procedures that begins from clustering the n-observations through a test of ‘no-outlier hypothesis’ (TONH) to a weighted least-square regression estimation. The cluster phase partition the n-observations into h-set called main cluster and a minor cluster of size n?h. A robust distance emerge from the main cluster upon which a test of no outlier hypothesis’ is conducted. An initial WLS regression estimation is computed from the robust distance obtained from the main cluster. Until convergence, a re-weighted least-squares (RLS) regression estimate is updated with weights based on the normalized residuals. The proposed procedure blends an agglomerative hierarchical cluster analysis of a complete linkage through the TONH to the Re-weighted regression estimation phase. Hence, we propose to call it cluster-based re-weighted regression (CBRR). The CBRR is compared with three existing procedures using two data sets known to exhibit masking and swamping. The performance of CBRR is further examined through simulation experiment. The results obtained from the data set illustration and the Monte Carlo study shows that the CBRR is effective in detecting multivariate outliers where other methods are susceptible to it. The CBRR does not require enormous computation and is substantially not susceptible to masking and swamping.