错误分析及其对外语教学实践的启迪——外语教育语言学研究之三

本文就错误分析产生的背景、错误分析对外语教学研究的意义、以及错误分析的程序进行了阐述；并提出和探讨了错误分析对外语教学实践所起到的三个方面的启迪作用。     

社会转型时期学术期刊的管理与评价

当前,学术期刊正面临着从传统走向现代化的转变,这是新的时代赋予学术期刊的历史机遇,也是对学术期刊的挑战。因此,学术期刊管理者应具备现代化的素质;学术期刊也需要加强管理,提高学术期刊的利用率,同时,对学术期刊的评价应该科学化。     

费孝通功能主义思想形成与发展初探

费孝通先生是我国著名的社会人类学家,为我国社会学的重建与发展作出了巨大的贡献。费先生在史禄国和马林诺夫斯基的影响之下接受了重视个人需求的功能主义,后来在实践和在学习过程中又倾向于拉德克利夫-布朗的结构功能主义。费先生功能主义思想的形成与发展过程不仅反映了个人在理论上的进步历程,也与整个功能主义理论的发展是同步的。     

邓小平对外开放理论与中国现代化生长路径的转换

现代化生长方式和生长路径影响着现代化进程。在我国,现代化是为摆脱贫穷落后、实现独立富强的被迫选择。从生长路径来说,中国的现代化道路最初是外生式的。外生式现代化由于国家作用强化,社会发育不良,因而缺乏内在的和持久的动力,社会发展不能持久。为此,邓小平一方面破除思想禁忌,提出大胆吸收和借鉴人类社会创造的一切文明成果;另一方面以主动对外开放的姿态,吸收资金、先进技术、有效制度等,变被动为主动,最终把它们内化为促进中国经济现代化建设的“内生”力量,培育社会基础,从而把政府的作用与社会发育结合起来,奠定了中国现代化持续发展的基础。     

"思想库"研究:西方研究综述

本文综述了近几十年西方思想库研究领域的三个传统:历史路径、实证主义和国际比较研究,并分别从政治学、政策过程理论与知识运用理论的宏观、中观和微观三个层面梳理了思想库影响力的理论脉络,最后比较了中西方学者对"中国思想库"的研究的两种不同视角.     

What Determines the Extent to which Employers will Comply with their Social Security Obligations? Evidence from Chinese Firm‐level Data

This article aims to extend understanding of employer responses to social protection regulations enacted by government to ensure the well‐being and security of employees. By utilizing firm‐specific data collected from Shanghai we explore the relationship between firm characteristics, employer behaviour, and the effectiveness of compliance mechanisms that have been adopted to contain contribution evasion by employers. We offer empirical evidence about the impact of the size of the firm, ownership structure, and incidence of risk on employer evasion behaviour in social protection payments. These results should enable enforcement agencies to improve compliance levels and also contribute to building theory as regards the significance of social policies to employers and the impact of social protection on human resource policy.     

A new algorithm to estimate monotone nonparametric link functions and a comparison with parametric approach

The generalized linear model (GLM) is a class of regression models where the means of the response variables and the linear predictors are joined through a link function. Standard GLM assumes the link function is fixed, and one can form more flexible GLM by either estimating the flexible link function from a parametric family of link functions or estimating it nonparametically. In this paper, we propose a new algorithm that uses P-spline for nonparametrically estimating the link function which is guaranteed to be monotone. It is equivalent to fit the generalized single index model with monotonicity constraint. We also conduct extensive simulation studies to compare our nonparametric approach for estimating link function with various parametric approaches, including traditional logit, probit and robit link functions, and two recently developed link functions, the generalized extreme value link and the symmetric power logit link. The simulation study shows that the link function estimated nonparametrically by our proposed algorithm performs well under a wide range of different true link functions and outperforms parametric approaches when they are misspecified. A real data example is used to illustrate the results.     

An additive–multiplicative mean model for panel count data with dependent observation and dropout processes

This paper discusses regression analysis of panel count data with dependent observation and dropout processes. For the problem, a general mean model is presented that can allow both additive and multiplicative effects of covariates on the underlying point process. In addition, the proportional rates model and the accelerated failure time model are employed to describe possible covariate effects on the observation process and the dropout or follow‐up process, respectively. For estimation of regression parameters, some estimating equation‐based procedures are developed and the asymptotic properties of the proposed estimators are established. In addition, a resampling approach is proposed for estimating a covariance matrix of the proposed estimator and a model checking procedure is also provided. Results from an extensive simulation study indicate that the proposed methodology works well for practical situations, and it is applied to a motivating set of real data.     

Generalized information matrix tests for copulas

We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White and so relate to the copula test proposed by Huang and Prokhorov. The idea is that eigenspectrum-based statements of the IM equality reduce the degrees of freedom of the test’s asymptotic distribution and lead to better size-power properties, even in high dimensions. The gains are especially pronounced for vine copulas, where additional benefits come from simplifications of score functions and the Hessian. We derive the asymptotic distribution of the generalized tests, accounting for the nonparametric estimation of the marginals and apply a parametric bootstrap procedure, valid when asymptotic critical values are inaccurate. In Monte Carlo simulations, we study the behavior of the new tests, compare them with several Cramer–von Mises type tests and confirm the desired properties of the new tests in high dimensions.     

Dynamic optimal capital growth of diversified investment

We investigate the problem of dynamic optimal capital growth of diversified investment. A general framework that the trader maximize the expected log utility of long-term growth rate of initial wealth was developed. We show that the trader's fortune will exceed any fixed bound when the fraction is chosen less than critical value. But, if the fraction is larger than that value, ruin is almost sure. In order to maximize wealth, we should choose the optimal fraction at each trade. Empirical results with real financial data show the feasible allocation. The larger the fraction and hence the larger the chance of falling below the desired wealth growth path.