Mobile Livelihoods: The Sociocultural Practices of Circular Migrants between Puerto Rico and the United States1

This article focuses on the bilateral flow of people between Puerto Rico and the United States ‐ what has come to be known as circular, commuter, or revolving‐door migration. It documents the migrants' livelihood practices based on a recent field study of population flows between Puerto Rico and the mainland. Specifically, the basic characteristics of multiple movers, one‐time movers and nonmovers residing in Puerto Rico are compared. More broadly, the article assesses the implications of circular migration for Puerto Rican communities on and off the island. The author's basic argument is that the constant displacement of people ‐ both to and from the island ‐ blurs the territorial, linguistic, and juridical boundaries of the Puerto Rican nation. As people expand their means of subsistence across space, they develop multiple attachments to various localities. In the Puerto Rican situation, such mobile livelihoods are easier to establish than in other places because of the free movement of labor and capital between the island and the mainland. The author hypothesizes that circulation does not entail major losses in human capital for most Puerto Ricans, but rather often constitutes an occupational, educational, and linguistic asset.     

Optimal sampling for spatial prediction of functional data

This paper combines optimal spatial sampling designs with geostatistical analysis of functional data. We propose a methodology and design criteria to find the set of spatial locations that minimizes the variance of the spatial functional prediction at unsampled sites for three functional predictors: ordinary kriging, simple kriging and simple cokriging. The last one is a modification of an existing predictor that uses ordinary cokriging based on the basis coefficients. Instead, we propose to use a simple cokriging predictor with the scores resulting from a representation of the functional data with the empirical functional principal components, allowing to remove restrictions and complexity of the covariance models and constraints on the estimation procedure. The methodology is applied to a network of air quality in Bogotá city, Colombia.     

Does higher income equal higher levels of happiness in every society? The case of the Mayan people

Guardiola J, González‐Gómez F, García‐Rubio MA, Lendechy‐Grajales Á. Does higher income equal higher levels of happiness in every society? The case of the Mayan people This study analysed happiness and several domains of life of Mayan people in the poor rural areas of Yucatan, Mexico. Using a sample of 373 households, we examined the influence of income on happiness and its domains, obtaining results that lend support to the ‘paradox of happy peasants and miserable millionaires’. According to the results, income influences happiness among the Mayan people, as do material domains and health, but income does not influence the domains related to intangible feelings and public goods. A number of reasons, such as a lack of a means for comparison, close contact with nature, adaptation to deprivation, general material improvements compared with the past, low aspirations and a Mayan culture that is devoted to solidarity and enjoyment of social relationships, could explain why the sample population reported high levels of happiness. Although the Mayans' level of happiness is high, their situation nevertheless requires political attention.     

Feasibility Study on the Use of Probabilistic Migration Modeling in Support of Exposure Assessment from Food Contact Materials

The use of probabilistic approaches in exposure assessments of contaminants migrating from food packages is of increasing interest but the lack of concentration or migration data is often referred as a limitation. Data accounting for the variability and uncertainty that can be expected in migration, for example, due to heterogeneity in the packaging system, variation of the temperature along the distribution chain, and different time of consumption of each individual package, are required for probabilistic analysis. The objective of this work was to characterize quantitatively the uncertainty and variability in estimates of migration. A Monte Carlo simulation was applied to a typical solution of the Fick's law with given variability in the input parameters. The analysis was performed based on experimental data of a model system (migration of Irgafos 168 from polyethylene into isooctane) and illustrates how important sources of variability and uncertainty can be identified in order to refine analyses. For long migration times and controlled conditions of temperature the affinity of the migrant to the food can be the major factor determining the variability in the migration values (more than 70% of variance). In situations where both the time of consumption and temperature can vary, these factors can be responsible, respectively, for more than 60% and 20% of the variance in the migration estimates. The approach presented can be used with databases from consumption surveys to yield a true probabilistic estimate of exposure.     

An effective algorithm for obtaining the whole set of minimal cost pairs of disjoint paths with dual arc costs

In telecommunication networks design the problem of obtaining optimal (arc or node) disjoint paths, for increasing network reliability, is extremely important. The problem of calculating k _c disjoint paths from s to t (two distinct nodes), in a network with k _c different (arbitrary) costs on every arc such that the total cost of the paths is minimised, is NP-complete even for k _c =2. When k _c =2 these networks are usually designated as dual arc cost networks.     

Associational Performance: The Influence of Cohesion, Decision-Making, and the Environment

The importance of associations in contemporary democratic societies is out of the question. Still, there is a need for a new approach that considers them as a specific and singular organization type, different from business firms and government agencies. There is also a need to evaluate their performance. Based on case studies and diverse theoretical insights, this article lays out some criteria for assessing the effects on associational performance of cohesion, decision-making and relation to environment.     

Monetary policy in the New-Keynesian model: An application to the Euro Area

This paper analyzes monetary policy in a stylized New-Keynesian model. A number of issues are focused upon: (i) optimal monetary policy under commitment or discretion versus ad-hoc monetary policy based on simple rules, (ii) the effects of fiscal policies and foreign variables on monetary policy, (iii) the effects of fiscal deficit and interest rate smoothing objectives and the role of forward-backward linkages in the model. The model is estimated for the Euro Area. Using simulations of the estimated model, it is analyzed how these aspects might affect monetary policy of the ECB and macroeconomic fluctuations in the Euro Area.     

Do unions always decrease wage dispersion? The case of Brazilian manufacturing

The literature on the impact of unions on wages has established that unionized workers earn a wage premium when compared to their nonunion counterparts and that the dispersion of wages within the union sector is lower than in the nonunion sector. I examine the validity of these findings in the context of a developing country labor market and show that unionism does create a positive wage differential but that wage dispersion is greater in the union sector. These findings are explained by the greater variance in the characteristics of unionized workers, the vulnerability of nonunion workers to market conditions, and the structure of wage bargaining.     

Practical modeling strategies for unbalanced longitudinal data analysis

In practice, data are often measured repeatedly on the same individual at several points in time. Main interest often relies in characterizing the way the response changes in time, and the predictors of that change. Marginal, mixed and transition are frequently considered to be the main models for continuous longitudinal data analysis. These approaches are proposed primarily for balanced longitudinal design. However, in clinic studies, data are usually not balanced and some restrictions are necessary in order to use these models. This paper was motivated by a data set related to longitudinal height measurements in children of HIV-infected mothers that was recorded at the university hospital of the Federal University in Minas Gerais, Brazil. This data set is severely unbalanced. The goal of this paper is to assess the application of continuous longitudinal models for the analysis of unbalanced data set.     

Goodness-of-fit tests for parametric regression with selection biased data

Consider the nonparametric location-scale regression model Y=m(X)+σ(X)ε$Y=m(X)+\sigma (X)\epsilon$, where the error ε$\epsilon$ is independent of the covariate X$X$, and m$m$ and σ$\sigma$ are smooth but unknown functions. The pair (X,Y)$(X,Y)$ is allowed to be subject to selection bias. We construct tests for the hypothesis that m(·)$m(·)$ belongs to some parametric family of regression functions. The proposed tests compare the nonparametric maximum likelihood estimator (NPMLE) based on the residuals obtained under the assumed parametric model, with the NPMLE based on the residuals obtained without using the parametric model assumption. The asymptotic distribution of the test statistics is obtained. A bootstrap procedure is proposed to approximate the critical values of the tests. Finally, the finite sample performance of the proposed tests is studied in a simulation study, and the developed tests are applied on environmental data.