Model selection criteria in beta regression with varying dispersion

We address the issue of model selection in beta regressions with varying dispersion. The model consists of two submodels, namely: for the mean and for the dispersion. Our focus is on the selection of the covariates for each submodel. Our Monte Carlo evidence reveals that the joint selection of covariates for the two submodels is not accurate in finite samples. We introduce two new model selection criteria that explicitly account for varying dispersion and propose a fast two step model selection scheme which is considerably more accurate and is computationally less costly than usual joint model selection. Monte Carlo evidence is presented and discussed. We also present the results of an empirical application.     

The bivariate alpha-skew-normal distribution

In this paper, we propose a new bivariate distribution, namely bivariate alpha-skew-normal distribution. The proposed distribution is very flexible and capable of generalizing the univariate alpha-skew-normal distribution as its marginal component distributions; it features a probability density function with up to two modes and has the bivariate normal distribution as a special case. The joint moment generating function as well as the main moments are provided. Inference is based on a usual maximum-likelihood estimation approach. The asymptotic properties of the maximum-likelihood estimates are verified in light of a simulation study. The usefulness of the new model is illustrated in a real benchmark data.     

A general long-term aging model with different underlying activation mechanisms: Modeling,Bayesian estimation,and case influence diagnostics

In this paper we propose a general cure rate aging model. Our approach enables different underlying activation mechanisms which lead to the event of interest. The number of competing causes of the event of interest is assumed to follow a logarithmic distribution. The model is parameterized in terms of the cured fraction which is then linked to covariates. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis for the proposed model. Moreover, some discussions on the model selection to compare the fitted models are given, as well as case deletion influence diagnostics are developed for the joint posterior distribution based on the ψ-divergence, which has several divergence measures as particular cases, such as the Kullback–Leibler (K-L), J-distance, L₁ norm, and χ²-square divergence measures. Simulation studies are performed and experimental results are illustrated based on a real malignant melanoma data.     

The impact of migration on the well-being of transnational families: new data from sending communities in Mexico

We present results from a new study of the effects of migration to the USA on the well-being of transnational families in high emigration communities within Mexico. Our survey measured the well-being of family members in a variety of domains: economic, health, education, and child development for a representative sample drawn from high migration municipalities. Compared to those with no recent emigrants to the USA, Mexican households sending non-caregivers to the USA appear to gain economically without contributing to problems faced by children. However, when family caregivers migrate to the USA, the remaining members in Mexico struggle to meet the family's needs and children are more vulnerable to educational, emotional, and health problems. Children in households where a caregiver migrated were more likely to have frequent illnesses (10% vs. 3%, p<0.0001), chronic illness (7% vs. 3%, p=0.011), emotional problems (10% vs. 4%, p=0.006), and behavioral problems (17% vs. 10%, p=0.018) compared with children in households where the migrant was not a caregiver. Research, policy, and program implications of these findings are discussed.     

Bivariate Birnbaum-Saunders accelerated lifetime model: estimation and diagnostic analysis

In this paper, we discuss the bivariate Birnbaum-Saunders accelerated lifetime model, in which we have modeled the dependence structure of bivariate survival data through the use of frailty models. Specifically, we propose the bivariate model Birnbaum-Saunders with the following frailty distributions: gamma, positive stable and logarithmic series. We present a study of inference and diagnostic analysis for the proposed model, more concisely, are proposed a diagnostic analysis based in local influence and residual analysis to assess the fit model, as well as, to detect influential observations. In this regard, we derived the normal curvatures of local influence under different perturbation schemes and we performed some simulation studies for assessing the potential of residuals to detect misspecification in the systematic component, the presence in the stochastic component of the model and to detect outliers. Finally, we apply the methodology studied to real data set from recurrence in times of infections of 38 kidney patients using a portable dialysis machine, we analyzed these data considering independence within the pairs and using the bivariate Birnbaum-Saunders accelerated lifetime model, so that we could make a comparison and verify the importance of modeling dependence within the times of infection associated with the same patient.     

Dynamic factor structure of team performances in Liga MX

Team performance of the Mexican Football League (Liga MX), measured as the percentage of the total points obtained during each short tournament, is analyzed using Dynamic Factor Models (DFMs). The estimation of the common components is carried out with Principal Components and the stochastic nature of the DFM is studied through Panel Analysis of Non-stationarity in Idiosyncratic and Common Components. The results reveal that there are two common factors, one being possibly non-stationary. These factors show an interesting dynamic behavior in the league and allow to split the teams into two groups, namely, top competitors and emerging or relegated teams. Some discussion is given in this direction.     

QUALITY DIFFERENCES,THIRD‐DEGREE PRICE DISCRIMINATION,AND WELFARE

We propose a model with two markets to analyze the welfare implications of price discrimination with quality differences. In each market a local firm that operates in that market only competes against a global firm that operates in both markets. Local firms produce higher‐quality goods than the global firm. If the quality levels of the local firms' products are the same, price discrimination is never welfare‐decreasing. If they differ, discrimination is welfare‐increasing if quantity increases. Because of a positive allocation effect of price discrimination, there are parameter values such that welfare increases while total output decreases with price discrimination. (JEL D43, D60)     

Analysis of the non-native flora of Ensenada, a fast growing city in northwestern Baja California

Urbanized areas show a high proportion of non-native plants and can work as dispersal points to the surrounding areas. Ensenada is a fast growing city located in the northwestern peninsula of Baja California (Mexico). It is the southern extreme of a bi-national, coastal urban corridor that extends from Los Angeles, California south to Ensenada. This corridor is part of the biodiversity hotspot of the California Floristic Province. The aim of this study was to analyze the composition and distribution of the spontaneous flora in the city of Ensenada. We systematically sampled two differentiated urban environments, vacant lots and arroyos, in 2006 and 2007. We found a total of 158 plant species, 61% of them were non-native species. Arroyo areas showed higher non-native species richness than vacant lots (21.9 vs. 13.6 species/transect) and could be potential dispersal vectors for non-native species to natural areas outside of the city, or in the reverse direction also.     

The Impact of Public Services Expenditure on the Spanish Income Distribution

This paper performs an assessment and imputation of the benefits produced to the individuals and households well-being by the public services provision. This analysis is very relevant in the current framework of economic crisis of the European economies. Although most of the papers in the literature compare countries, decentralization processes are included in this paper by accounting the effect of public expenditure on regional health care and education upon the levels of inequality and rates of poverty in each Spanish region. This case is relevant because of the high decentralization degree of the Spanish political structure and the persistent regional disparities. The results show a clear downward tendency in both phenomena following imputation, although education shows a greater impact. Furthermore, a decomposition, used in this context for the first time, of the effects shows the very relevant redistributive effect of this public expenditure.     

The eigenstructure of block-structured correlation matrices and its implications for principal component analysis

Block-structured correlation matrices are correlation matrices in which the p variables are subdivided into homogeneous groups, with equal correlations for variables within each group, and equal correlations between any given pair of variables from different groups. Block-structured correlation matrices arise as approximations for certain data sets’ true correlation matrices. A block structure in a correlation matrix entails a certain number of properties regarding its eigendecomposition and, therefore, a principal component analysis of the underlying data. This paper explores these properties, both from an algebraic and a geometric perspective, and discusses their robustness. Suggestions are also made regarding the choice of variables to be subjected to a principal component analysis, when in the presence of (approximately) block-structured variables.