Acceptance of homosexuality through education? Investigating the role of education,family background and individual characteristics in the United Kingdom

Higher educated people tend to be more accepting of homosexuality than lower educated people. This has inspired claims that education leads to a higher acceptance of homosexuality. Alternatively, the association between education and acceptance of homosexuality could be confounded by (un)observed family background and stable individual characteristics. This study investigated the association between education and acceptance of homosexuality and the role of potential confounders in a unique longitudinal sample of British siblings. Multilevel and fixed effects analyses show that both perspectives apply. A large part of the association between education and acceptance of homosexuality could be attributed to family background and observed individual characteristics (one third), as well as unobserved individual characteristics (an additional third), but the positive association remains. Findings are discussed in light of existing explanations regarding the effect of education on the acceptance of homosexuality.     

Treatment Evaluation in the Presence of Sample Selection

Sample selection and attrition are inherent in a range of treatment evaluation problems such as the estimation of the returns to schooling or training. Conventional estimators tackling selection bias typically rely on restrictive functional form assumptions that are unlikely to hold in reality. This paper shows identification of average and quantile treatment effects in the presence of the double selection problem into (i) a selective subpopulation (e.g., working—selection on unobservables) and (ii) a binary treatment (e.g., training—selection on observables) based on weighting observations by the inverse of a nested propensity score that characterizes either selection probability. Weighting estimators based on parametric propensity score models are applied to female labor market data to estimate the returns to education.     

我国商业信用的资源再配置效应与强制性特征——基于工业企业数据的实证检验

商业信用的资源再配置假说认为,商业信用可实现银行信贷资金的再配置,从而提高资源配置效率。以2004—2007年中国工业企业微观数据为基础,对我国商业信用的资源配置效应以及恶意拖欠基础上的强制性信用特征进行的检验结果表明,在我国,获取更多银行信贷的企业(包括国有企业)不仅未能提供更多商业信用,反而获取了更多商业信用,而市场势力的存在可能是导致这一配置结果的扭曲性因素;拥有更多应收账款的企业倾向于扩大应付账款规模,从而使企业间债务关系呈现出较强的"三角债"趋势。此外,与出口企业相比,产品内销企业在商业信用的供给中面临着更多的坏账损失风险。这说明我国商业信用的产生具有显著的恶意拖欠特征与违约风险。我国的商业信用不仅未能改善资源配置效率,反而增大了市场的交易费用和运行风险。     

Where do we stand? Recent AEA member views on professionalization

The professionalization of evaluation continues to be debated at numerous conferences in the U.S. and abroad. At this time, AEA member views on the potential benefits and negative side effects of professionalization are essential as the discussion evolves. This study provides recent views on major topics in professionalization, including potential benefits, negative side effects, processes, competencies, and procedures. Results from in-depth interviews and an online survey demonstrate that AEA members view potential benefits of professionalization to be stakeholder trust, evaluator reputation and identity, while concerns about a potential negative side effect known as the “narrowing effect” (i.e., some evaluators will be alienated based on their background, competencies, etc.) were expressed by participants. These recent findings can inform the ongoing discussion of professionalization, and suggest new directions for future research on evaluation.     

基于动态因子Copula模型的行业间系统性风险分析

国际金融市场间的相关关系以及系统性风险受到很多学者的重视，本文则以我国股市的行业指数作为研究对象进行实证研究。通过构建动态因子Copula模型，文章对行业的日收益率数据进行了动态相关性分析，并基于风险预期占比度量了我国行业之间系统性风险的溢出效应。本文分析了2006年1月4日至2016年7月1日的28个行业指数数据，基于GAS动态负荷因子的变化路径来刻画其相关关系，通过风险预期占比来研究行业间的风险溢出效应。研究表明，各个行业指数收益率之间存在较强的关联性。就单个行业来说，化工行业与其他行业关系最为不稳定。就金融与非金融行业而言，金融行业对非金融行业的影响较大且较为平稳。本文所得研究结果可以为投资者和风险管理者在进行决策时提供一定的指导。     

Robust Bayesian nonlinear mixed‐effects modeling of time to positivity in tuberculosis trials

Early phase 2 tuberculosis (TB) trials are conducted to characterize the early bactericidal activity (EBA) of anti‐TB drugs. The EBA of anti‐TB drugs has conventionally been calculated as the rate of decline in colony forming unit (CFU) count during the first 14 days of treatment. The measurement of CFU count, however, is expensive and prone to contamination. Alternatively to CFU count, time to positivity (TTP), which is a potential biomarker for long‐term efficacy of anti‐TB drugs, can be used to characterize EBA. The current Bayesian nonlinear mixed‐effects (NLME) regression model for TTP data, however, lacks robustness to gross outliers that often are present in the data. The conventional way of handling such outliers involves their identification by visual inspection and subsequent exclusion from the analysis. However, this process can be questioned because of its subjective nature. For this reason, we fitted robust versions of the Bayesian nonlinear mixed‐effects regression model to a wide range of TTP datasets. The performance of the explored models was assessed through model comparison statistics and a simulation study. We conclude that fitting a robust model to TTP data obviates the need for explicit identification and subsequent “deletion” of outliers but ensures that gross outliers exert no undue influence on model fits. We recommend that the current practice of fitting conventional normal theory models be abandoned in favor of fitting robust models to TTP data.     

Can the welfare state replace parents? Children's cognition in the United States and Great Britain

We compare family and parental effects on child verbal facility, verbal achievement and mathematics achievement in the United States and Great Britain. We study 3,438 5–13 year-old children from the 1994 NLSY Child-Mother Data Set and 1429 same-aged children from the National Child Development Study, also known as the British Child. Multivariate analyses suggest that the processes through which families invest in child cognition are similar across societies, with factors including low birth weight, child health, maternal cognition, family size and children's home environments being consequential. We conclude that parental investments are equally important across the two societies. The more developed welfare state in Great Britain does not notably compensate for parental investments in that society, although it may play a greater role when parental resources are absent or stretched thin.     

The impact of internal communication on strategic and economic effects in Serbian companies

This paper presents the research results in relation to examining and defining dependences and the impact of internal communication on certain strategic and economic business effects. Serbian companies were the focus of this research. The data were collected by polling 100 managers from 100 companies. Afterwards, multivariate regression and correlation was carried out in the aim of the final determination of requested dependences. This research confirmed a strong positive relation between internal communication and strategic and economic business effects.     

The effect of sociodemographic (mis)match between interviewers and respondents on unit and item nonresponse in Belgium

Interviewer characteristics affect nonresponse and measurement errors in face-to-face surveys. Some studies have shown that mismatched sociodemographic characteristics – for example gender – affect people's behavior when interacting with an interviewer at the door and during the survey interview, resulting in more nonresponse. We investigate the effect of sociodemographic (mis)matching on nonresponse in two successive rounds of the European Social Survey in Belgium. As such, we replicate the analyses of the effect of (mis)matching gender and age on unit nonresponse on the one hand, and of gender, age and education level (mis)matching on item nonresponse on the other hand. Recurring effects of sociodemographic (mis)match are found for both unit and item nonresponse.     

Testing variance components in balanced linear growth curve models

It is well known that the testing of zero variance components is a non-standard problem since the null hypothesis is on the boundary of the parameter space. The usual asymptotic chi-square distribution of the likelihood ratio and score statistics under the null does not necessarily hold because of this null hypothesis. To circumvent this difficulty in balanced linear growth curve models, we introduce an appropriate test statistic and suggest a permutation procedure to approximate its finite-sample distribution. The proposed test alleviates the necessity of any distributional assumptions for the random effects and errors and can easily be applied for testing multiple variance components. Our simulation studies show that the proposed test has Type I error rate close to the nominal level. The power of the proposed test is also compared with the likelihood ratio test in the simulations. An application on data from an orthodontic study is presented and discussed.