The effect of intent and character information on children's evaluations of third-party transgressions

Research in adults suggests that their perception of moral transgressions is affected by the moral character of the agent performing the transgression, such that undesirable actions enacted by ‘good’ agents are seen as less serious than those performed by ‘bad’ agents. This may be partly driven our tendency to view undesirable acts as less intentional when the agent has a perceived good moral character. It is currently unclear whether or not children make similar judgements. Therefore, we investigated if children's use of moral character information is consistent with their judgements of transgressions when the intent behind the act was ambiguous or blatant. Children aged 6–8-years (N = 60) viewed a series of six moral transgressions in which the protagonist's intent was ambiguous or blatantly harmful, and their moral character was described as being good, mixed or bad. The children were then asked how much they felt the behaviour was intentional, how severe it was and the degree of punishment it deserved. Transgressions performed by ‘good’ characters were viewed as less intentional than those by ‘bad’ characters, but only when the intent behind it was ambiguous. Similarly, transgressions performed by good characters were viewed as less severe and deserving of less punishment than those performed by bad characters, although this effect was not moderated by intent information. These pattern of findings suggest that the view of transgressions performed by good individuals as less serious than the same act performed by bad individuals is established early in development.     

On linear aggregation of infinitely many finitely additive probability measures

Theory and Decision - We discuss Herzberg’s (Theory Decis 78(2):319–337, 2015) treatment of linear aggregation for profiles of infinitely many finitely additive probabilities and...     

Detection of a changepoint,a mean-shift accompanied with a trend change,in short time-series with autocorrelation

In this study, a changepoint model, which can detect either a mean shift or a trend change when accounting for autocorrelation in short time-series, was investigated with simulations and a new method is proposed. The changepoint hypotheses were tested using a likelihood ratio test. The test statistic does not follow a known distribution and depends on the length of the time-series and the autocorrelation. The results imply that it is not possible to detect autocorrelation and that the estimate of the autocorrelation parameter is biased. It is therefore recommended to use critical values from the empirical distribution for a fixed autocorrelation.     

Are national levels of employee harassment cultural covariations of climato-economic conditions?

Conflict in a workgroup turns into harassment if a group member is persistently confronted with negative acts with few possibilities to retaliate. Cross-national differences in such intragroup harassment are considerable but wait to be understood. In this study, survey data from 44,836 employees in 44 countries revealed that a cultural in-group orientation was associated with lower employee harassment. In addition, and in agreement with Van de Vliert's climato-economic theory of culture, workforces reported more harassment in poorer countries with more demanding climates of colder-than-temperate winters, hotter-than-temperate summers, or both. Finally, it was found that the impact of climato-economic hardships on harassment suppressed the impact of cultural in-group orientation on harassment. Using the regression equation obtained for the sample of 44 countries, national levels of employee harassment for a broader pool of 103 countries were estimated and scrutinized for their validity for future research. Data from the World Values Surveys were used to validate the estimations. The results provide the basis for a further hypothesis, that employee harassment is more prevalent in countries with either survival or self-expression cultures than in countries with cultures that are intermediate between those two extremes. The results have implications for prevention and remedial measures.     

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.     

Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration

In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods. The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that (1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, (2) all the estimators are fairly robust to conditionally heteroscedastic errors, (3) the local polynomial Whittle and bias-reduced log-periodogram regression estimators are shown to be more robust to short-run dynamics than other semiparametric (frequency domain and wavelet) estimators and in some cases even outperform the time domain parametric methods, and (4) without sufficient trimming of scales the wavelet-based estimators are heavily biased.