Social interactions and the salience of social identity

We explore the effect of identity salience on behaviour in a simple social interaction. Specifically, we compare ultimatum bargaining across three treatments: priming subjects with a shared identity, priming subjects with an identity distinct from those with whom they will interact, and priming subjects with no particular identity. We find that subjects are most cooperative in the identity-priming treatment and least cooperative in the distinctiveness-priming treatment. Similarly, subjects reveal the highest demands in the identity-priming treatment and the lowest demands in the distinctiveness-priming treatment. We discuss the implications of these results with respect to the literature on organizational identity.     

Bayesian inference for dynamic social network data

We consider a continuous-time model for the evolution of social networks. A social network is here conceived as a (di-) graph on a set of vertices, representing actors, and the changes of interest are creation and disappearance over time of (arcs) edges in the graph. Hence we model a collection of random edge indicators that are not, in general, independent. We explicitly model the interdependencies between edge indicators that arise from interaction between social entities. A Markov chain is defined in terms of an embedded chain with holding times and transition probabilities. Data are observed at fixed points in time and hence we are not able to observe the embedded chain directly. Introducing a prior distribution for the parameters we may implement an MCMC algorithm for exploring the posterior distribution of the parameters by simulating the evolution of the embedded process between observations.     

Best monotone M‐estimators

The author shows how to find M‐estimators of location whose generating function is monotone and which are optimal or close to optimal. It is easy to identify a consistent sequence of estimators in this class. In addition, it contains simple and efficient approximations in cases where the likelihood function is difficult to obtain. In some neighbourhoods of the normal distribution, the loss of efficiency due to the approximation is quite small. Optimal monotone M‐estimators can also be determined in cases when the underlying distribution is known only up to a certain neighbourhood. The author considers the e‐contamination model and an extension thereof that allows the distributions to be arbitrary outside compact intervals. His results also have implications for distributions with monotone score functions. The author illustrates his methodology using Student and stable distributions.     

On the detection of changes in autoregressive time series I. Asymptotics

Various test statistics are discussed which can be used for detecting changes in the parameters of an autoregressive time series. In this first part of our study, the limiting behavior of the test statistics is derived under the null hypothesis of no change as well as under alternatives. In a forthcoming second part of our investigation, these asymptotic results will be compared to some corresponding bootstrap procedures, and a small simulation study will be conducted.     

On robust forecasting in dynamic vector time series models

In this article, robust estimation and prediction in multivariate autoregressive models with exogenous variables (VARX) are considered. The conditional least squares (CLS) estimators are known to be non-robust when outliers occur. To obtain robust estimators, the method introduced in Duchesne [2005. Robust and powerful serial correlation tests with new robust estimates in ARX models. J. Time Ser. Anal. 26, 49–81] and Bou Hamad and Duchesne [2005. On robust diagnostics at individual lags using RA-ARX estimators. In: Duchesne, P., Rémillard, B. (Eds.), Statistical Modeling and Analysis for Complex Data Problems. Springer, New York] is generalized for VARX models. The asymptotic distribution of the new estimators is studied and from this is obtained in particular the asymptotic covariance matrix of the robust estimators. Classical conditional prediction intervals normally rely on estimators such as the usual non-robust CLS estimators. In the presence of outliers, such as additive outliers, these classical predictions can be severely biased. More generally, the occurrence of outliers may invalidate the usual conditional prediction intervals. Consequently, the new robust methodology is used to develop robust conditional prediction intervals which take into account parameter estimation uncertainty. In a simulation study, we investigate the finite sample properties of the robust prediction intervals under several scenarios for the occurrence of the outliers, and the new intervals are compared to non-robust intervals based on classical CLS estimators.     

On the relation between Hodges-Lehmann efficiency and Pitman efficiency

The relation between Hodges–Lehmann efficiency and Pitman efficiency is studied in the context of testing one-sided hypotheses about a real-valued parameter. It is first shown that for tests based on sums of independently and identically distributed observations local Hodges-Lehmann efficiency is equivalent to Pitman efficiency. Then, it is proved that this equivalence also carries over to tests based on two broad classes of M -estimators for the location problem. In all cases considered explicit formulas of the Hodges-Lehmann efficacies are obtained.     

Unemployment and economic psychology: An introduction

Starting from literature a short sequential scheme is being presented, including contextual and causal factors of employment, phenomenal aspects of unemployment, moderator variables, effects and lastly interventions and solutions.General aspects as well as more restricted aspects of unemployment as an area of research within economic psychology are mentioned. The contributions within this issue are discussed in connection with the scheme and the different aspects that were distinguished.     

广义对角占优矩阵的充分条件

研究具有广泛应用背景的广义对角占优矩阵的充分条件，获得了几个简捷的实用结果。所得条件允许矩阵的非对角占优行可达ｎ－１行，运用于广泛的矩阵类。     

论波爱修斯的模态逻辑与上帝的预知

波爱修斯的模态逻辑直接来自古代,特别是亚里士多德的模态逻辑。中世纪早期模态理论主要关注关于将来事件模态命题的解释。基于此,波爱修斯首次对上帝的预知与人的自由意志一致性进行了逻辑论证。     

论《海商法》中实际承运人的相关法律问题

实际承运人是海上货物运输实践中的重要当事方 ,由于《海商法》对实际承运人的法律界定很不明晰 ,造成了实践中的混乱。本文以实际承运人的概念阐述为基础 ,对多种情况下实际承运人识别问题进行了划分 ,并探讨了实际承运人责任认定的相关法律问题。