我国少数民族构成要素的因子分析

本文用总人口、自治地方本民族人口、自治地方少数民族人口、人均GDP、农业人口、识字人口、在校生、母语人、单语人、双语人人数等 10项指标作为民族的地区、经济、教育和语言构成要素 ,对这些要素在我国现有少数民族中的构成情况作了描述、相关和因子提取等统计分析 ,以说明目前我国少数民族构成的基本社会状况 ,以及这些要素对少数民族整体和个体的构成的作用或代表的信息量有多大。文章还依据已有的经验知识对统计分析结果作了相应的说明和解释。结论是 ,目前我国少数民族之间的区别特征主要在于经济发展水平、人口的教育水平、居住地区、使用语言等方面的社会差别 ;但是从发展趋势看 ,传统意义上的各民族构成要素的作用将逐渐减弱 ,民族间的差别将逐渐缩小     

Psychometric properties of the “parent-child relationship inventory” (PCRI) in a portuguese forensic sample

In Portugal, there is a gap regarding psychological tests validated for forensic contexts, particularly those related to child custody issues. The Parent–Child Relationship Inventory (PCRI) is one of the most used instruments in child custody contexts. This study aimed to analyze the psychometric properties of PCRI in a Portuguese forensic sample. PCRI factorial structure and psychometric properties were analyzed in a sample of 144 parents involved in child custody assessments. The questionnaire showed good internal consistency, except for the parental support, autonomy, and role orientation scales. It also showed good discriminant capacity. The confirmatory factor analysis did not replicate the 7-factor model proposed by Gerard. The results were discussed based on the use of PCRI in the context of child custody assessment.     

Role of stylized features in constructing better estimators

This article discusses the role played by stylized features of financial time series in constructing better estimators for the model parameters. We study in detail one such estimator for the transition probabilities of a simple regime switching model. The estimator is based on the squared autocovariances of the time series, which has been discussed in several empirical studies of economic and financial time series. The effectiveness of this estimator in improving the estimation accuracy is investigated, using both finite sample and asymptotic computations. We also report simulation results to confirm our findings and to extend our conclusions over a bigger region of the parameter space.     

The Aging Semantic Differential in Mandarin Chinese: Measuring Attitudes toward Older Adults in China

ABSTRACT

The Aging Semantic Differential (ASD) is the most widely used instrument to measure young people’s attitudes towards older adults. This study translated the ASD to Mandarin and examined its psychometric properties. The Mandarin-ASD contains three latent factors (Personality and Mental Health, Societal Participation, and Physical) that have high internal reliability and reasonable discriminate validity. Social work researchers, practitioners and allied professionals may utilize the ASD-Mandarin instrument to measure young people’s attitudes towards older adults in China. We issue a call for a universal-ASD that can be applied across different cultural contexts.     

Estimation of structural mean breaks for long-memory data sets

In long-memory data sets such as the realized volatilities of financial assets, a sequential test is developed for the detection of structural mean breaks. The long memory, if any, is adjusted by fitting an HAR (heterogeneous autoregressive) model to the data sets and taking the residuals. Our test consists of applying the sequential test of Bai and Perron [Estimating and testing linear models with multiple structural changes. Econometrica. 1998;66:47–78] to the residuals. The large-sample validity of the proposed test is investigated in terms of the consistency of the estimated number of breaks and the asymptotic null distribution of the proposed test. A finite-sample Monte-Carlo experiment reveals that the proposed test tends to produce an unbiased break time estimate, while the usual sequential test of Bai and Perron tends to produce biased break times in the case of long memory. The experiment also reveals that the proposed test has a more stable size than the Bai and Perron test. The proposed test is applied to two realized volatility data sets of the S&P index and the Korea won-US dollar exchange rate for the past 7 years and finds 2 or 3 breaks, while the Bai and Perron test finds 8 or more breaks.     

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.     

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.     

Bootstrap forecast intervals for asymmetric volatilities via EGARCH model

Bootstrap forecast intervals are developed for volatilities having asymmetric features, which are accounted for by fitting EGARCH models. A Monte-Carlo simulation compares the proposed forecast intervals with those based on GARCH fittings which ignore asymmetry. The comparison reveals substantial advantage of addressing asymmetry through EGARCH fitting over ignoring it as the conventional GARCH forecast. The EGARCH forecast intervals have empirical coverage probabilities closer to the nominal level and/or have shorter average lengths than the GARCH forecast intervals. The finding is also supported by real dataset analysis of Dow–Jones index and financial times stock exchange (FTSE) 100 index.     

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.     

An approximate dual-self model and paradoxes of choice under risk

We derive a simplified version of the model of Fudenberg and Levine, 2006, Fudenberg and Levine, 2011 and show how this approximate model is useful in explaining choice under risk. We show that in the simple case of three outcomes, the model can generate indifference curves that “fan out” in the Marschak–Machina triangle, and thus can explain the well-known Allais and common ratio paradoxes that models such as prospect theory and regret theory are designed to capture. At the same time, our model is consistent with modern macroeconomic theory and evidence and generates predictions across a much wider set of domains than these models.