Blinking While Speaking and Talking,Hearing, and Listening: Communication or Individual Underlying Process?

Journal of Nonverbal Behavior - Why do eye-blinks activate during conversation? We manipulated informational content and communicative intent exchanged within dyads. By comparison to a silent...     

Biospheric values as predictor of climate change risk perception: A multinational investigation

Climate change is one of the big challenges of our time. A better understanding of how individuals form their evaluation of the risk related to climate change seems to be key to win broad support for climate change mitigation efforts. Extant research indicates that biospheric values (BV) are an important antecedent of individuals’ perception of the risk and consequences related to climate change. However, risk perception scholars have only recently started to study how BV relate to individuals’ climate change risk perception (CCRP) and much is still to be learned about this relationship. The present study contributes to this growing literature by studying the BV–CCRP relationship in a multinational context. The results suggest that the BV – CCRP relationship varies in strength between different countries. These differences can be explained in part by societies’ cultural leanings (i.e., individualism vs. collectivism) and societies’ wealth. The present research adds to our understanding of why individuals in different countries perceive climate change related risk differently and how this perception is shaped differently by biospheric values in different countries. In this way, the findings help to build a more nuanced theory of how CCRP are formed. The presented results also have implications for policymakers and NGOs who wish to increase individuals’ engagement with climate change and its consequences in different populations. In particular, the findings suggests that it might be necessary to use different strategies in different societies to achieve a greater awareness of climate change related risks.     

Pathways to social value and social change: An integrative review of the social entrepreneurship literature

Social entrepreneurship has emerged as an important means of addressing grand challenges. Although research on the topic has accelerated, scholars have yet to articulate an overarching framework that links the different pathways taken by social entrepreneurs with the positive effects of these efforts. To address this shortcoming, we conducted a systematic literature review which enabled us to conceptually differentiate between social value and social change as distinct outcomes of social entrepreneurship and identify seven pathways for achieving these outcomes. Building on our analysis, we outline a research agenda for questions pertaining to: the dynamics between social value and social change; how contextual factors and social entrepreneurs influence various pathways; design principles of business models and innovations that facilitate social value and social change; and defining, measuring, and ensuring accountability for social value and social change.     

Monitoring correlated processes with binomial marginals

Few approaches for monitoring autocorrelated attribute data have been proposed in the literature. If the marginal process distribution is binomial, then the binomial AR(1) model as a realistic and well-interpretable process model may be adequate. Based on known and newly derived statistical properties of this model, we shall develop approaches to monitor a binomial AR(1) process, and investigate their performance in a simulation study. A case study demonstrates the applicability of the binomial AR(1) model and of the proposed control charts to problems from statistical process control.     

On the Ghoudi,Khoudraji, and Rivest test for extreme‐value dependence

Ghoudi, Khoudraji & Rivest [The Canadian Journal of Statistics 1998;26:187–197] showed how to test whether the dependence structure of a pair of continuous random variables is characterized by an extreme‐value copula. The test is based on a U‐statistic whose finite‐ and large‐sample variance are determined by the present authors. They propose estimates of this variance which they compare to the jackknife estimate of Ghoudi, Khoudraji & Rivest ( 1998 ) through simulations. They study the finite‐sample and asymptotic power of the test under various alternatives. They illustrate their approach using financial and geological data. The Canadian Journal of Statistics © 2009 Statistical Society of Canada     

The “wrong skewness” problem in stochastic frontier models: A new approach

Stochastic frontier models are widely used to measure, e.g., technical efficiencies of firms. The classical stochastic frontier model often suffers from the empirical artefact that the residuals of the production function may have a positive skewness, whereas a negative one is expected under the model, which leads to estimated full efficiencies of all firms. We propose a new approach to the problem by generalizing the distribution used for the inefficiency variable. This generalized stochastic frontier model allows the sample data to have the wrong skewness while estimating well-defined and nondegenerate efficiency measures. We discuss the statistical properties of the model, and we discuss a test for the symmetry of the error term (no inefficiency). We provide a simulation study to show that our model delivers estimators of efficiency with smaller bias than those of the classical model even if the population skewness has the correct sign. Finally, we apply the model to data of the U.S. textile industry for 1958–2005 and show that for a number of years our model suggests technical efficiencies well below the frontier while the classical one estimates no inefficiency in those years.     

Probability and statistics: A tale of two worlds?

This comparative study of research productivity and publication habits in probability and statistics completes the paper that was published in this Journal at the end of 1997. It is based on a ten-year survey of eighteen international journals, half of which are specialized in probability theory and the other half in statistics. Paper, author and adjusted page counts yield cursory measures of productivity for countries and institutions that contributed to fundamental research in these two related fields during the period 1986-1995. These data also reveal significant cultural differences between probabilists and statisticians in the volume of research, the length of papers, coauthorship practices, etc. Canada is seen to be one of the strongest contributors to the development of these two disciplines.