A note on the moments of the Riesz distribution

This paper derives the first two moments of the two versions of the Riesz distribution in the terms of their characteristic functions.     

Properties and Inference on the Skew-Curved-Symmetric Family of Distributions

In this article, we study some results related to a specific class of distributions, called skew-curved-symmetric family of distributions that depends on a parameter controlling the skewness and kurtosis at the same time. Special elements of this family which are studied include symmetric and well-known asymmetric distributions. General results are given for the score function and the observed information matrix. It is shown that the observed information matrix is always singular for some special cases. We illustrate the flexibility of this class of distributions with an application to a real dataset on characteristics of Australian athletes.     

Double Generalized Spatial Econometric Models

The authors offer a unified method extending traditional spatial dependence with normally distributed error terms to a new class of spatial models based on the biparametric exponential family of distributions. Joint modeling of the mean and variance (or precision) parameters is proposed in this family of distributions, including spatial correlation. The proposed models are applied for analyzing Colombian land concentration, assuming that the variable of interest follows normal, gamma, and beta distributions. In all cases, the models were fitted using Bayesian methodology with the Markov Chain Monte Carlo (MCMC) algorithm for sampling from joint posterior distribution of the model parameters.     

A Simulation Study Comparing Modeling Approaches in an Illness-Death Multi-State Model

In many medical studies, there are covariates that change their values over time and their analysis is most often modeled using the Cox regression model. However, many of these time-dependent covariates can be expressed as an intermediate event, which can be modeled using a multi-state model. Using the relationship of time-dependent (discrete) covariates and multi-state models, we compare (via simulation studies) the Cox model with time-dependent covariates with the most frequently used multi-state regression models. This article also details the procedures for generating survival data arising from all approaches, including the Cox model with time-dependent covariates.     

The macroeconomic impact of reforming a PAYG system: The Portuguese case

Abstract   The article analyses the impact of various types of reform options on social security pension system financial sustainability and on a range of macroeconomic variables. The HERPOR model is used to consider the likely effects of parametric reforms of the existing pay-as-you-go system, as well as those of a systemic reform. The article concludes that the former are sufficient to ensure financial sustainability, although they should be accompanied by employment implementation measures. The article concludes that a fully pre-funded system does not seem to be a viable option for policy-makers in the redesigning of social security pension systems, due to the high transition costs involved.     

The power piecewise exponential model

In this paper an extension of the piecewise exponential distribution based on the distribution of the maximum of a random sample is considered. Properties of its density and hazard function are investigated. Maximum likelihood inference is discussed and the Fisher information matrix is identified. Results of two real data applications are reported, where model fitting is implemented by using maximum likelihood. The applications illustrate the better performance of the new distribution when compared with other recently proposed alternative models.     

A novel weighted likelihood estimation with empirical Bayes flavor

We propose a novel approach to estimation, where a set of estimators of a parameter is combined into a weighted average to produce the final estimator. The weights are chosen to be proportional to the likelihood evaluated at the estimators. We investigate the method for a set of estimators obtained by using the maximum likelihood principle applied to each individual observation. The method can be viewed as a Bayesian approach with a data-driven prior distribution. We provide several examples illustrating the new method and argue for its consistency, asymptotic normality, and efficiency. We also conduct simulation studies to assess the performance of the estimators. This straightforward methodology produces consistent estimators comparable with those obtained by the maximum likelihood method. The method also approximates the distribution of the estimator through the “posterior” distribution.     

Effect of autocorrelation when estimating the trend of a time series via penalized least squares with controlled smoothness

This paper studies the effect of autocorrelation on the smoothness of the trend of a univariate time series estimated by means of penalized least squares. An index of smoothness is deduced for the case of a time series represented by a signal-plus-noise model, where the noise follows an autoregressive process of order one. This index is useful for measuring the distortion of the amount of smoothness by incorporating the effect of autocorrelation. Different autocorrelation values are used to appreciate the numerical effect on smoothness for estimated trends of time series with different sample sizes. For comparative purposes, several graphs of two simulated time series are presented, where the estimated trend is compared with and without autocorrelation in the noise. Some findings are as follows, on the one hand, when the autocorrelation is negative (no matter how large) or positive but small, the estimated trend gets very close to the true trend. Even in this case, the estimation is improved by fixing the index of smoothness according to the sample size. On the other hand, when the autocorrelation is positive and large the simulated and estimated trends lie far away from the true trend. This situation is mitigated by fixing an appropriate index of smoothness for the estimated trend in accordance to the sample size at hand. Finally, an empirical example serves to illustrate the use of the smoothness index when estimating the trend of Mexico’s quarterly GDP.     

The effect of teaching strategies on student achievement: An analysis using TALIS-PISA-link

The present study investigates the effects of different teaching strategies on student achievement using data from the so-called TALIS-PISA link created by the OECD. This is a recently developed instrument that allows for connecting data about teacher characteristics and practices collected in the TALIS (Teaching and Learning International Survey) survey with students’ academic performance measured in PISA (Programme for International Student Assessment). Our empirical strategy is based on an instrumental variable (IV) approach. Our results suggest that traditional teaching methods have a positive influence on students’ proficiency in mathematics, while the implementation of more innovative active learning strategies seem to have a negative impact on student achievement.     

Dialogic literary gatherings and out‐of‐home child care: Creation of new meanings through classic literature

Research on out‐of‐home child care has revealed that foster care programmes focused on educational attainment and reading have the potential to improve the academic outcomes of children in care. However, no studies have examined which elements of these programmes positively benefit children's emotional well‐being. This article presents evidence of the positive effects of implementing a successful educational action, dialogic literary gatherings, in a children's residential care institution. A qualitative study using a communicative‐oriented methodology was conducted and involved five participant observations and eight daily life stories with children in out‐of‐home care in Catalonia (Spain). The children's reflections demonstrated that reading classic books, such as Dickens' Oliver Twist, deeply influenced their feelings and self‐conceptions and created new and exciting meaning in their lives.