Difference-based matrix perturbation method for semi-parametric regression with multicollinearity

This paper addresses the collinearity problems in semi-parametric linear models. Under the difference-based settings, we introduce a new diagnostic, the difference-based variance inflation factor (DVIF), for detecting the presence of multicollinearity in semi-parametric models. The DVIF is then used to device a difference-based matrix perturbation method for solving the problem. The electricities distribution data set is analyzed, and numerical evidences validate the effectiveness of the proposed method.     

Smoothing the difference-based estimates of variance using variational mode decomposition

We propose a variational mode decomposition approach to estimate the variance function in a nonparametric heteroscedastic fixed design regression model. A data-driven estimator is constructed by applying variational mode decomposition technique to the difference-based initial estimates. The numerical results show that the proposed estimator performs better than the existing variance estimation procedures in the mean square sense.     

Evaluating modified generalized information criterion in presence of multicollinearity

When there are many explanatory variables in the regression model, there is a chance that some of these are intercorrelated. This is where the problem of multicollinearity creeps in due to which precision and accuracy of the coefficients is marred, and the quest to find the best model becomes tedious. To tackle such a situation, Model selection criteria are applied for selecting the best model that fits the data. Current study focuses on the evaluation of the four unmodified and four modified versions of generalized information criteria—Akaike Information Criterion, Schwarz's Bayes Information Criteria, Hannan-Quinn Information Criterion, and Akaike Information Criterion corrected for small samples. A simulation study using SAS software was carried out in order to compare the unmodified and modified versions of the generalized information criteria and to discover the best version amongst the four modified model selection criteria, for identifying the best model, when the collinearity assumption is violated. For the proposed simulation, two samples of size 50 and 100, for three explanatory variables X₁, X₂, and X₃, are drawn from Normal distribution. Two situations of collinearity violations between X₁ and X₂ are looked into, first when ρ = 0.6 and second when ρ = 0.8. The outcomes of the simulations are displayed in the tables along with visual representations. The results revealed that modified versions of the generalized information criteria are more sensitive in identifying models marred with high multicollinearity as compared to the unmodified generalized information criteria.     

Construction of bivariate and multivariate weighted distributions via conditioning

Weighted distributions (univariate and bivariate) have received widespread attention over the last two decades because of their flexibility for analyzing skewed data. In this article, we propose an alternative method to construct a new family of bivariate and multivariate weighted distributions. For illustrative purposes, some examples of the proposed method are presented. Several structural properties of the bivariate weighted distributions including marginal distributions together with distributions of the minimum and maximum, evaluation of the reliability parameter, and verification of total positivity of order two are also presented. In addition, we provide some multivariate extensions of the proposed models. A real-life data set is used to show the applicability of these bivariate weighted distributions.     

Simultaneous decomposition of the variance by sources and subgroups – new insights

There are two types of decompositions: of linear combinations of random variables into contributions of individual variables (sources) and associations between them, and of populations into contributions of their subpopulations. Simultaneous treatment of the two types is called for, which takes into account the correlations between sources within subpopulations and between subpopulation means. The expected values of the subcomponents are derived and their sensitivity to correlations among sources within groups and among source group means is conducted. An example is provided, in which the correlations contribute 20--25% to total variability. This additional information is hidden when decompositions are not simultaneous.     

Adaptation of the short version of the Psychological Capital Questionnaire (PCQ-12) into Spanish / Adaptación al español de la versión reducida del Cuestionario de Capital Psicológico (PCQ-12)

Psychological capital (PsyCap) has been a topic of increasing interest in the last decade. However, there is a lack of validated instruments in Spanish to map PsyCap and its consequences for individuals’ well-being. Consequently, the goal of this study is to adapt the 12-item short version of the Psychological Capital Questionnaire (PCQ-12) to the Spanish context by analysing its internal consistency and reliability, factor solution and external validity. Results indicated that the PCQ-12 exhibited good Cronbach’s alpha (.87) and omega coefficient (.93) values in a sample from a vehicle inspection company (n = 798). As expected, results also revealed that a second-order factor structure provided the best fit. Moreover, PsyCap is associated with increased job engagement (β = .579; R²_adjusted = .333), decreased job burnout (β = ?.409; R²_adjusted = .166), and lower psychological distress (β = ?.349; R²_adjusted = .121) (all p < .01), which provided additional support for using the PCQ-12 in the Spanish context. Implications for theory and practice are discussed.     

生态价值:基于马克思劳动价值论的一个引申分析

检视和比较中西方关于生态价值问题的研究文献,基于马克思劳动价值论,并将其引申扩展到探索生态价值的致思路径是:沿着人类社会生产力发展水平不断提升的线索,从经济系统、生态系统和生态经济系统考察商品总价值、生态总价值和商品价值总量之间的内在关联及其数量变化关系。随着人类社会生产力水平由低到高的提升,商品总价值、生态总价值和商品价值总量三者之间呈现由同向递增变动到无序变动、再到更高层次的同向递增变动的趋势。在中国当前经济社会发展面临严峻生态问题的状况下,重新认识和理解生态价值问题,将有利于改变当前衡量经济社会发展指标过度单一的局面,有利于转变人们对自然生态资源、生态环境的不合理开发和利用的传统发展理念,有利于有效推动自然资源定价和参与市场化治理,并为其提供理论基础,从而使自然生态环境能够被科学、合理、协调、可持续地开发和利用。     

中国旅游上市公司全要素生产率研究

旅游上市公司是旅游业发展的微观主体,其全要素生产率全面反映了该行业的实际经营效率和发展趋势。本文基于Malmquist指数探讨了20家中国旅游上市公司2004-2009年的全要素生产率。Malmquist指数及其分解结果显示:中国旅游上市公司Malmquist指数年均增长率为-0.4%,其中纯技术效率的增长显著,年均增幅为1.3%;时间跨度层面,中国旅游上市公司的全要素生产率的年度波动性较大。此外,样本中旅游上市公司Malmquist指数与营业收入增长率未能兼顾;2008-2009年度粗放型增长的特征显著。     

马克思视域内的社会形态理论研究

本文从社会形态理论的前提出发,以马克思社会形态理论的视域为主线,研究了马克思视域内的社会形态理论,即生产力视域内的社会形态理论、生产方式视域内的社会形态理论和人的发展视域内的社会形态理论以及三者之间的递进关系。生产方式视域以生产力视域为基础,但又不限于生产力视域,人的发展视域以生产方式视域为基础,但又不限于生产方式视域,从而得出马克思视域内的社会形态的概念。一方面,中国社会主义社会形态建立、建设和改革开放的实践,为我们准确全面地认识马克思视域内的社会形态理论创造了条件;另一方面,新世纪、新实践和新任务要求中国人重新准确地全面地把握马克思视域内的社会形态理论。     

IT投资转化为企业生产率的影响因素研究

关于"IT投资是否能提高企业生产率"这一命题,学界一直众说纷纭,一个很重要的原因在于这些研究建立在IT投资能对企业生产率产生直接影响的假设前提之上,而忽略了IT作用于企业生产率的中间过程。IT投资必须与企业内部生产环境相吻合才能提高企业生产率,IT投资转化为企业生产率的影响因素包括内部因素和外部因素,其中内部因素包括企业管理特征、企业员工特征及企业结构特征;外部因素指的是企业所面临的外部环境。