The Danish psychosocial work environment and symptoms of stress: The main,mediating and moderating role of sense of coherence

The aim of this cross-sectional study was to explore the main, mediating and moderating role of sense of coherence (SOC) on stress symptoms and on the association between perceived psychosocial work environment and stress symptoms. The sample includes 2053 Danish employees from 52 workplaces. Hierarchical regression models were applied for each measure of stress. The results strongly supported the presence of a main effect for SOC. People with high levels of SOC experienced fewer stress symptoms. A mediating effect of SOC was also supported. Thus, SOC in part explained the association between work environment and stress symptoms. In addition, some support for a moderating effect of SOC was found, suggesting that people with higher SOC coped more efficiently with work environmental strain that people with lower SOC. Taken together the regression models explained 11–32% of the variance in stress symptoms. The results suggest that measures of individual factors such as SOC should be included in analyses of the effects of work environmental factors on stress and well-being.     

Empirical Likelihood for Threshold Autoregressive Models

This article develops empirical likelihood for threshold autoregressive models. We propose general estimating equations based on moment constraint. Under some suitable conditions, we show the empirical likelihood estimators for parameter are asymptotically normally distributed, and the proposed log empirical likelihood ratio statistic asymptotically follows a standard chi-squared distribution.     

C239. The continued fraction for lnr( z): a stieljes conjecture

Estimation in logistic-normal models for correlated and overdispersed binomial data is complicated by the numerical evaluation of often intractable likelihood functions. Penalized quasilikelihood (PQL) estimators of fixed effects and variance components are known to be seriously biased for binary data. A simple correction procedure has been proposed to improve the performance of the PQL estimators. The proposed method is illustrated by analyzing infectious disease data. Its performance is compared, by means of simulations, with that of the Bayes approach using the Gibbs sampler.     

开征环境税对经济增长影响的实证研究——基于十二个发达国家二氧化碳税开征经验的面板数据分析

本文利用芬兰等十二个已开征二氧化碳税的发达国家1980～2009年间的跨国面板数据进行随机效应估计.结果发现:开征环境税在短期内可能给经济增长带来负向冲击；但环境税对经济增长的影响更多地体现为长期冲击,且这种长期冲击是显著的负向影响.因此,开征环境税时,不仅要通过税收体系调整缓解企业成本上升在短期内给经济增长带来的不利冲击,更应从长期影响的视角出发,设计配套政策,降低环境税在长期内对经济增长和社会福利可能存在的不利影响.     

Confidence Intervals Following Group Sequential Tests in Clinical Trails with Multivariate Observations

Several authors ( e.g. Kim and DeMets, 1987a, Biometrics) have developed methods for estimation following group sequential tests in clinical trials when each patient has only one response. In many long-term clinical trials, the subjects enter the study sequentially and yield repeated measurements or other types of multivariate observations at successive follow-up visits. Typically, investigators want to compare a parameter of interest such as the slope over time in a repeated measures trial etc. In this article, we propose an exact confidence interval for these parameters in a repeated measures trial, and compare it with a naive confidence interval using Monte Carlo simulation. This method is illustrated with a real example for bone density measurements.     

当前农村人情文化的负面效应和正向功能——以温州农村为例

在我国的广大农村,无处不在的人情文化已成为一种人际关系创设与维持的常识与准则.人情作为一种传统习俗,是在长期发展过程中代代传承而逐渐积淀起来的文化现象,它以非正式的形式规定了农民所应遵守的行为规范和价值观念.在当前的温州农村,浓郁的人情文化显现不少负面效应,如加重农民经济和精神负担、容易形成狭隘封闭的圈子而有损道德建设、交易色彩浓郁有损社会公正、规则意识淡薄而有违法治精神.但是,当前人情文化依然被广大农民所认同,源于它也承担了较多的经济社会功能,人情来往是获得社会资源的重要途径,人情交往有经济协作功能、社会福利与民间互助功能、娱乐团聚和社会评价功能、行为约束和社会稳定功能等,只有辩证地加以分析和引导,才能扬长避短.     

Correlations among centrality indices and a class of uniquely ranked graphs

Various centrality indices have been proposed to capture different aspects of structural importance but relations among them are largely unexplained. The most common strategy appears to be the pairwise comparison of centrality indices via correlation. While correlation between centralities is often read as an inherent property of the indices, we argue that it is confounded by network structure in a systematic way. In fact, correlations may be even more indicative of network structure than of relationships between indices. This has substantial implications for the interpretation of centrality effects as it implies that competing explanations embodied in different indices cannot be separated from each other if the network structure is close to a certain generalization of star graphs.     

Flexible Threshold Models for Modelling Interest Rate Volatility

This paper focuses on interest rate models with regime switching and extends previous nonlinear threshold models by relaxing the assumption of a fixed number of regimes. Instead we suggest automatic model determination through Bayesian inference via the reversible jump Markov Chain Monte Carlo (MCMC) algorithm. Moreover, we allow the thresholds in the volatility to be driven not only by the interest rate but also by other economic factors. We illustrate our methodology by applying it to interest rates and other economic factors of the American economy.     

Human population as a dynamic factor in environmental degradation

The environmental consequences of increasing human population size are dynamic and nonlinear, not passive and linear. The role of feedbacks, thresholds, and synergies in the interaction of population size and the environment are reviewed here, with examples drawn from climate change, acid deposition, land use, soil degradation, and other global and regional environmental issues. The widely-assumed notion that environmental degradation grows in proportion to population size, assuming fixed per capita consumption and fixed modes of production, is shown to be overly optimistic. In particular, feedbacks, thresholds, and synergies generally amplify risk, causing degradation to grow disproportionally faster than growth in population size. Based on a presentation to the Bixby Symposium on Population and Conservation, UC Berkeley, May 2006.     

服务业集聚能否促进城镇化进程——基于中国省际面板数据的分析

本文基于2000—2010年我国省际面板数据,采用面板单位根检验和固定效应模型分析,研究了我国服务业集聚对城镇化进程的影响.结果表明:从全国来看,服务业集聚对城镇化进程具有促进作用;从东中西部地区来看,服务业集聚对各地区的促进作用存在差异,对西部地区的作用大于东中部地区;从东中西部地区城镇化各影响因素的弹性系数来看,东部地区对城镇化进程影响最大的为服务业集聚,中部地区为经济发展水平,而在西部地区,服务业集聚与工业水平具有同样重要的作用.