Is a Brownian Motion Skew?

We study the asymptotic behaviour of the maximum likelihood estimator corresponding to the observation of a trajectory of a skew Brownian motion, through a uniform time discretization. We characterize the speed of convergence and the limiting distribution when the step size goes to zero, which in this case are non‐classical, under the null hypothesis of the skew Brownian motion being an usual Brownian motion. This allows to design a test on the skewness parameter. We show that numerical simulations can be easily performed to estimate the skewness parameter and provide an application in Biology.     

Genderacing immigrant subjects: ‘anchor babies’ and the politics of birthright citizenship

Birthright citizenship is often a subject of important national debates on immigration. From a historical perspective, the influx of Mexican and Chinese immigrants to the United Stated has elicited politically charged efforts to deny the right of US citizenship to their children. Based on a review of popular discursive frames concerning the politics of birthright citizenship, this essay identifies and critiques the arguments from both ends of the political spectrum. We conclude that, by and large, the substance of their legal and philosophical arguments is old, hackneyed responses from decades ago. However, on many symbolic levels, the current rhetoric is quite uncharacteristically caustic, with a focus on racialized and gendered discourses among nationalist groups. We seek to explain why this is the case. Framed as ‘genderacing immigrant subjects’, this essay examines the politics of naming (or nomenclature) through the construction of the racially gendered referent in public discourse, thereby ascribing socially resonant meanings that naturalize a call for draconian policy measures in order to socially engineer the national body.     

A Bayesian approach to zero-inflated data in extremes

Abstract

The generalized extreme value (GEV) distribution is known as the limiting result for the modeling of maxima blocks of size n, which is used in the modeling of extreme events. However, it is possible for the data to present an excessive number of zeros when dealing with extreme data, making it difficult to analyze and estimate these events by using the usual GEV distribution. The Zero-Inflated Distribution (ZID) is widely known in literature for modeling data with inflated zeros, where the inflator parameter w is inserted. The present work aims to create a new approach to analyze zero-inflated extreme values, that will be applied in data of monthly maximum precipitation, that can occur during months where there was no precipitation, being these computed as zero. An inference was made on the Bayesian paradigm, and the parameter estimation was made by numerical approximations of the posterior distribution using Markov Chain Monte Carlo (MCMC) methods. Time series of some cities in the northeastern region of Brazil were analyzed, some of them with predominance of non-rainy months. The results of these applications showed the need to use this approach to obtain more accurate and with better adjustment measures results when compared to the standard distribution of extreme value analysis.     

Board characteristics effects on performance in family and non-family business: a multi-theoretical approach

This paper examines the role of the board of directors in influencing the value of Italian listed firms from 2003 to 2013. In particular, employing agency, stewardship and resource dependence theories, the study aims to compare board characteristics in family and non-family firms and define the theory that best applies to family firms. Empirical results show that the presence of CEO duality and busy directors has a positive effect on the value of family firms, while gender diversity has a negative impact on the value when a member of the family leads a family firm. Conversely, the size of the board positively affects the value of non-family firms. Our main findings suggest the prevalence, in family firms, of the benefits of the board structure argued by stewardship and resource dependence theories rather than the disadvantages expected from agency theory.     

Ranking opportunity sets in the space of functionings

We develop a ranking of compact, convex and comprehensive opportunity sets defined in the evaluative space of individual functionings. We suppose the existence of a target, that is a multi-dimensional bliss point in terms of functionings. This leads us to define concepts such as essentiality and freedomin a novel way. As a main result, we give an axiomatic characterization of the ranking obtained by minimizing the Euclidean distance between each opportunity set and the target.     

DEVELOPMENT OF PRACTICE

In this paper it is described how the work of the Balay Rehabilitation Centre in the Philippines has changed over time as the political and human rights conditions of the country's affected areas have changed. Balay's psychosocial rehabilitation programmes address the needs of individuals and communities and offer support and healing. Originally Balay focused on individual and family-level psychological and social intervention in accordance with clinical diagnoses; however, as the political and human rights situation of the Philippines changed and large numbers of people became victims of trauma and displacement the intervention strategies changed. Balay became increasingly interested in assisting communities to become empowered to participate in their own healing and the frameworks of community research and participatory action research (PAR) are now being explored by Balay as valid methods of integrating research with rehabilitation activities on the community level.     

A new method of edge correction for estimating the nearest neighbor distribution

Analysis of data in the form of a set of points irregularly distributed within a region of space usually involves the study of some property of the distribution of inter-event distances. One such function is G, the distribution of the distance from an event to its nearest neighbor. In practice, point processes are commonly observed through a bounded window, thus making edge effects an important component in the estimation of G. Several estimators have been proposed, all dealing with the edge effect problem in different ways. This paper proposes a new alternative for estimating the nearest neighbor distribution and compares it to other estimators. The result is an estimator with relatively small mean squared error for a wide variety of stationary processes.