国民时间资产和闲暇活动核算研究

一、问题的提出2 0世纪 60年代 ,发达国家经济已经达到了很高的水平。人们开始重视生活质量 ,探讨什么是真正的幸福等一系列问题。人们开始意识到仅用ＧＮＰ(ＧＤＰ)不能反映生活质量和幸福程度。例如 ,拥有很高的人均ＧＮＰ ,但是没有闲暇时间的生活 ,并不认为是高质量的生活。另外 ,2 0世纪中叶 ,伴随着妇女解放运动的开展 ,人们开始注意到家务劳动的价值 ,因此许多社会学家提出了建立社会指标的问题 ,也有许多经济学家提出家务劳动核算的问题。生活时间分配研究不仅可以从平均的角度反映国民个人的生活时间分配状况和生活方式 ,也可以从…     

On Bartlett correction of empirical likelihood for regularly spaced spatial data

Bartlett correction constitutes one of the attractive features of empirical likelihood because it enables the construction of confidence regions for parameters with improved coverage probabilities. We study the Bartlett correction of spatial frequency domain empirical likelihood (SFDEL) based on general spectral estimating functions for regularly spaced spatial data. This general formulation can be applied to testing and estimation problems in spatial analysis, for example testing covariance isotropy, testing covariance separability as well as estimating the parameters of spatial covariance models. We show that the SFDEL is Bartlett correctable. In particular, the improvement in coverage accuracies of the Bartlett‐corrected confidence regions depends on the underlying spatial structures. The Canadian Journal of Statistics 47: 455–472; 2019 © 2019 Statistical Society of Canada     

Perimeter-area ratio effects of urbanization intensity on forest characteristics,landscape patterns and their associations in Harbin City,Northeast China

To maximize the ecological services of urban forests, a better understanding of the effects of urbanization on urban forest characteristics, landscape metrics, and their associations is needed for landscape-related regulations in space-limited green infrastructure of metropolitan regions. In this study, Harbin, a typical fast-growing provincial-capital city in Northeast China, is used as a case study. Based on remote sensing images, field surveys, and correlation and variation partitioning analyses, we conclude that landscape characteristics and forest attributes have large variations among different urbanization intensity (UI) regions. Forest patch density (PD), landscape shape index, woody plants species richness, and the Shannon–Wiener index (H′) increased linearly, while stem section area and tree height decreased linearly with the increasing of UIs. UI had a greater influence on tree size and forest community attributes than the forest landscape pattern. Accordingly, any landscape regulation on forest attributes should be implemented according to UIs. In addition, Euclidean nearest neighbor distance(ENN-MN), mean perimeter-area ratio (PARA-MN), fractal dimension index(FRAC-MN), and PD could probably indicate forest attributes the most, e.g., the increase of PARA-MN may be accompanied with taller trees in low and heavy UI regions, but lower woody plants species evenness in low and medium UI regions. More diversified woody plants species, and afforested areas should be advocated in a low UI region, while in a heavy UI region, the conservation of large trees should be implemented. Our results highlight that the implementation of urban forest management should vary according to different urbanization regions to maximize ecological services.

     

The Role of Self-Conscious Emotions in the Sexual Health of Gay and Bisexual Men: Psychometric Properties and Theoretical Validation of the Sexual Shame and Pride Scale

Researchers have theorized about the role of sexual shame as a mechanism through which sexual minority stress manifests into mental health difficulties, such as sexual compulsivity for gay and bisexual men (GBM), and about the resilience-promoting effects of sexual pride. However, no validated measures to date have directly tapped into these constructs rather than using proxies for them, such as internalized homonegativity. We developed the Sexual Shame and Pride Scale (SSPS) and conducted a psychometric evaluation of it using a sample of 260 highly sexually active GBM. The scale had the expected structure in factor analysis and showed evidence of internal consistency and test–retest reliability. Correlational analyses demonstrated the convergent validity of sexual shame and sexual pride with relevant constructs. Regression analyses demonstrated the predictive validity of sexual shame in relation to sexual compulsivity, accounting for unique variability even after adjusting for previously demonstrated etiological factors, and the predictive validity of both shame and pride, which interacted to consistently predict four sexual behavior outcomes. Findings suggest the SSPS is a psychometrically valid and reliable measure that may be useful in future empirical work and highlight preliminary evidence for the role of these constructs in the sexual health of GBM.     

Does a More Diversified Revenue Structure Lead to Greater Financial Capacity and Less Vulnerability in Nonprofit Organizations? A Bibliometric and Meta-Analysis

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This article explores how and to what extent revenue diversification and concentration strategies affect financial...     

北京企业空间嵌入天津与河北的探讨

笔者从经济学视角探究省际中心城市经济职能向临近省份嵌入,提出了嵌入势差和嵌入性优势,探讨了双方收益分割。笔者把嵌入过程分为嵌入性优势形成阶段、嵌入阶段、脱嵌阶段和再嵌入阶段四个阶段,通过阶段的划分揭示了发达省份与邻近落后省份之间的一种经济联系。以北京企业嵌入天津和河北为例进行了较为深入的探讨,认为天津与北京的关系处于嵌入过程中的第四个阶段,河北与北京的关系处于嵌入过程的第二个阶段。     

Subsampling-extrapolation bandwidth selection in bivariate kernel density estimation

This paper focuses on bivariate kernel density estimation that bridges the gap between univariate and multivariate applications. We propose a subsampling-extrapolation bandwidth matrix selector that improves the reliability of the conventional cross-validation method. The proposed procedure combines a U-statistic expression of the mean integrated squared error and asymptotic theory, and can be used in both cases of diagonal bandwidth matrix and unconstrained bandwidth matrix. In the subsampling stage, one takes advantage of the reduced variability of estimating the bandwidth matrix at a smaller subsample size m (m < n); in the extrapolation stage, a simple linear extrapolation is used to remove the incurred bias. Simulation studies reveal that the proposed method reduces the variability of the cross-validation method by about 50% and achieves an expected integrated squared error that is up to 30% smaller than that of the benchmark cross-validation. It shows comparable or improved performance compared to other competitors across six distributions in terms of the expected integrated squared error. We prove that the components of the selected bivariate bandwidth matrix have an asymptotic multivariate normal distribution, and also present the relative rate of convergence of the proposed bandwidth selector.     

Bayesian nonparametric modelling of the link function in the single-index model using a Bernstein–Dirichlet process prior

This paper proposes the use of the Bernstein–Dirichlet process prior for a new nonparametric approach to estimating the link function in the single-index model (SIM). The Bernstein–Dirichlet process prior has so far mainly been used for nonparametric density estimation. Here we modify this approach to allow for an approximation of the unknown link function. Instead of the usual Gaussian distribution, the error term is assumed to be asymmetric Laplace distributed which increases the flexibility and robustness of the SIM. To automatically identify truly active predictors, spike-and-slab priors are used for Bayesian variable selection. Posterior computations are performed via a Metropolis-Hastings-within-Gibbs sampler using a truncation-based algorithm for stick-breaking priors. We compare the efficiency of the proposed approach with well-established techniques in an extensive simulation study and illustrate its practical performance by an application to nonparametric modelling of the power consumption in a sewage treatment plant.     

Robust inference for estimating equations with nonignorably missing data based on SIR algorithm

Nonresponse is a very common phenomenon in survey sampling. Nonignorable nonresponse – that is, a response mechanism that depends on the values of the variable having nonresponse – is the most difficult type of nonresponse to handle. This article develops a robust estimation approach to estimating equations (EEs) by incorporating the modelling of nonignorably missing data, the generalized method of moments (GMM) method and the imputation of EEs via the observed data rather than the imputed missing values when some responses are subject to nonignorably missingness. Based on a particular semiparametric logistic model for nonignorable missing response, this paper proposes the modified EEs to calculate the conditional expectation under nonignorably missing data. We can apply the GMM to infer the parameters. The advantage of our method is that it replaces the non-parametric kernel-smoothing with a parametric sampling importance resampling (SIR) procedure to avoid nonparametric kernel-smoothing problems with high dimensional covariates. The proposed method is shown to be more robust than some current approaches by the simulations.