On testing for independence between the innovations of several time series

Test statistics for checking the independence between the innovations of several time series are developed. The time series models considered allow for general specifications for the conditional mean and variance functions that could depend on common explanatory variables. In testing for independence between more than two time series, checking pairwise independence does not lead to consistent procedures. Thus a finite family of empirical processes relying on multivariate lagged residuals are constructed, and we derive their asymptotic distributions. In order to obtain simple asymptotic covariance structures, Möbius transformations of the empirical processes are studied, and simplifications occur. Under the null hypothesis of independence, we show that these transformed processes are asymptotically Gaussian, independent, and with tractable covariance functions not depending on the estimated parameters. Various procedures are discussed, including Cramér–von Mises test statistics and tests based on non‐parametric measures. The ranks of the residuals are considered in the new methods, giving test statistics which are asymptotically margin‐free. Generalized cross‐correlations are introduced, extending the concept of cross‐correlation to an arbitrary number of time series; portmanteau procedures based on them are discussed. In order to detect the dependence visually, graphical devices are proposed. Simulations are conducted to explore the finite sample properties of the methodology, which is found to be powerful against various types of alternatives when the independence is tested between two and three time series. An application is considered, using the daily log‐returns of Apple, Intel and Hewlett‐Packard traded on the Nasdaq financial market. The Canadian Journal of Statistics 40: 447–479; 2012 © 2012 Statistical Society of Canada     

Predictors of the emergence of transformational leadership in virtual decision teams

This study examined the etiology of transformational leadership in virtual team contexts. First, we compared 127 members of virtual decision-making teams with 135 members of traditional face-to-face teams in terms of the relationship between aspects of personality and the emergence of transformational leadership. The type of communication media (face-to-face versus “pure” virtual) was found to interact with extraversion and emotional stability in the prediction of emerging transformational leadership. In line with prior findings, we showed how these personality characteristics were relevant to transformational leadership emergence in our face-to-face teams. However, they were largely unrelated to such leadership in the virtual team context. We also focused specifically on the virtual context by analyzing the content of team interactions. After accounting for the effect of degree of activity level, the linguistic quality in one's written communication was found to predict the emergence of transformational leadership in virtual teams.     

Internal migration and the politics of place: a comparative analysis of China and Indonesia

Spontaneous and organized population movements have long been used as a means of promoting a country's goals of development and national integration. At the local level, on the other hand, these movements have frequently done the opposite, fueling local grievances, sharpening group distinctions, and at times creating ‘sons-of-the-soil’ conflicts. In this paper, I explore this apparent tension between the national political rationale for internal migration and the political impact such migration has had locally, in four minority regions of China and Indonesia. I argue that the specific manner in which migration affects local politics is influenced by a country's political regime. In Indonesia, the impact of migration is observed in electoral politics, where ‘politics of place’ have been allowed to emerge. In China, it is perceived in the curbing of national minorities’ territorial autonomy. The role played by local elites and group competition between indigenous people and migrants are also reviewed.     

Testing for a Unit Root in a Time Series With a Changing Mean: Corrections and Extensions

This article explores the relation between nonexponential waiting times between events and the distribution of the number of events in a fixed time interval. It is shown that within this framework the frequently observed phenomenon of overdispersion—that is, a variance that exceeds the mean—is caused by a decreasing hazard function of the waiting times, whereas an increasing hazard function leads to underdispersion. Using the assumption of iid gamma-distributed waiting times, a new count-data model is derived. Its use is illustrated in two applications, the number of births and the number of doctor consultations.     

Global Sensitivity Analysis Applied to a Contamination Assessment Model of Listeria monocytogenes in Cold Smoked Salmon at Consumption

In this study, a variance‐based global sensitivity analysis method was first applied to a contamination assessment model of Listeria monocytogenes in cold smoked vacuum packed salmon at consumption. The impact of the choice of the modeling approach (populational or cellular) of the primary and secondary models as well as the effect of their associated input factors on the final contamination level was investigated. Results provided a subset of important factors, including the food water activity, its storage temperature, and duration in the domestic refrigerator. A refined sensitivity analysis was then performed to rank the important factors, tested over narrower ranges of variation corresponding to their current distributions, using three techniques: ANOVA, Spearman correlation coefficient, and partial least squares regression. Finally, the refined sensitivity analysis was used to rank the important factors.     

Robust normative comparisons of socially risky situations

In this paper, we theoretically characterize robust empirically implementable normative criteria for evaluating socially risky situations. Socially risky situations are modeled as distributions, among individuals, of lotteries on a finite set of state-contingent pecuniary consequences. Individuals are assumed to have selfish Von Neumann–Morgenstern preferences for these socially risky situations. We provide empirically implementable criteria that coincide with the unanimity, over a reasonably large class of such individual preferences, of anonymous and Pareto-inclusive Von Neuman Morgenstern social rankings of risks. The implementable criteria can be interpreted as sequential expected poverty dominance. An illustration of the usefulness of the criteria for comparing the exposure to unemployment risk of different segments of the French and US workforce is also provided.