Privatisation des télécommunications et relations de travail en Amérique latine

This article deals with the privatization of telecommunications in the three largest Latin American countries, Argentina, Brazil and Mexico. Labor unions have strongly affected the way telecommunications have been privatized in Latin America and its timing, but they have not been able to keep their traditional influence from waning. Comparing Argentina and Mexico brings to light opposite models of labor relations based, for the one, on the denationalization of management and loss of guaranteed jobs for wage-earners and, for the other, on the maintenance of control over telecommunications by local entrepreneurs and the preservation of guaranteed employment. The more recent privatization implemented in Brazil has fueled debate about the consequences on collective action in an era of open-market telecommunications. — Special issue: Latin America.     

Bayesian deconvolution of oil well test data using Gaussian processes

We use Bayesian methods to infer an unobserved function that is convolved with a known kernel. Our method is based on the assumption that the function of interest is a Gaussian process and, assuming a particular correlation structure, the resulting convolution is also a Gaussian process. This fact is used to obtain inferences regarding the unobserved process, effectively providing a deconvolution method. We apply the methodology to the problem of estimating the parameters of an oil reservoir from well-test pressure data. Here, the unknown process describes the structure of the well. Applications to data from Mexican oil wells show very accurate results.     

Consistent Smooth Bootstrap Kernel Intensity Estimation for Inhomogeneous Spatial Poisson Point Processes

Non‐parametric estimation and bootstrap techniques play an important role in many areas of Statistics. In the point process context, kernel intensity estimation has been limited to exploratory analysis because of its inconsistency, and some consistent alternatives have been proposed. Furthermore, most authors have considered kernel intensity estimators with scalar bandwidths, which can be very restrictive. This work focuses on a consistent kernel intensity estimator with unconstrained bandwidth matrix. We propose a smooth bootstrap for inhomogeneous spatial point processes. The consistency of the bootstrap mean integrated squared error (MISE) as an estimator of the MISE of the consistent kernel intensity estimator proves the validity of the resampling procedure. Finally, we propose a plug‐in bandwidth selection procedure based on the bootstrap MISE and compare its performance with several methods currently used through both as a simulation study and an application to the spatial pattern of wildfires registered in Galicia (Spain) during 2006.     

Trends in the Quantiles of the Life Table Survivorship Function

We offer a new approach for modeling past trends in the quantiles of the life table survivorship function. Trends in the quantiles are estimated, and the extent to which the observed patterns fit the unit root hypothesis or, alternatively, an innovative outlier model, are conducted. Then a factor model is applied to the detrended data, and it is used to construct quantile cycles. We enrich the ongoing discussion about human longevity extension by calculating specific improvements in the distribution of the survivorship function, across its full range, and not only at the central-age ranges. To illustrate our proposal, we use data for the UK from 1922 to 2013. We find that there is no sign in the data of any reduction in the pace of longevity extension during the last decades.     

Global Economic Integration and Local Community Resilience: Road Paving and Rural Demographic Change in the Southwestern Amazon

Recent years have witnessed an expansion in international investment in large‐scale infrastructure projects with the goal of achieving global economic integration. We focus on one such project, the Inter‐Oceanic Highway in the “MAP” region, a trinational frontier where Bolivia, Brazil, and Peru meet in the southwestern Amazon. We adopt a resilience approach as an integrative framework to understand various types of road‐paving impacts. We focus on migration activity as an indicator of retention of collective memory, a concept associated with resilience. We pursue a comparative analysis of the three sides of the MAP frontier as well as subregions within each side. Since road paving may be mediated by other factors, we distinguish among the effects of multiple explanatory factors. Data come from a multinational survey of rural communities. The findings show considerable net migration and turnover, both indicative of eroding collective memory and a lack of demographic resilience to externally induced change in the MAP frontier. The findings indicate variation across the frontier, which road paving helps explain, along with some of the mediating factors. These findings contribute to the literature on the impacts of new infrastructure and integration as well as the study of social‐ecological resilience.     

Some properties of the tukey g and h family of distributions

The g and h family of distributions, introduced by J.W. Tukey, is generated by a single transformation of the standard normal which allows for symmetry and heavier tails. Selected percentage points are tabulated, and a closed-form solution for the moments, when they exist, is found. A comparison is made with the Pearson system of distributions. The g and h distributions cover most of the Pearson family to an adequate approximation, when the first four moments exist, and also generate a variety of other types of distributions. Selected distributions graphically illustrate the great variety of possible shapes.     

Use of bayesian analysis to design of clinical trials with one treatment

Assuming a Weibull distribution, the posterior distribution for the median survival time is derived in the presence of arbitrary right censorship. In the design of clinical triaLs, suppose k follow-up periods have been completed and it is desired to plan the follow-up period k+1. In this context, criteria are presented that can be employed in determining the number of new patients to be enrolled in the follow-up period k+1.     

The Relationship of Birth Order and Gender with Academic Standing and Substance Use Among Youth in Latin America

Alfred Adler attempted to understand how family affects youth outcomes by considering the order of when a child enters a family (Adler, 1964). Adler's theory posits that birth order formation impacts individuals. We tested Adler's birth order theory using data from a cross-sectional survey of 946 Chilean youths. We examined how birth order and gender are associated with drug use and educational outcomes using three different birth order research models including: (1) Expedient Research, (2) Adler's birth order position, and (3) Family Size theoretical models. Analyses were conducted with structural equation modeling (SEM). We conclude that birth order has an important relationship with substance use outcomes for youth but has differing effects for educational achievement across both birth order status and gender.