The Features of Development in the Pacific Countries of the African,Caribbean and Pacific Group

In this article we present a new proposal for the measurement of development, applied to the Pacific Countries of the African, Caribbean and Pacific Group (ACP), conditional on their insularity, and with privileged relations with the European Union. Our index has been constructed attending to the criteria defined in the Goals of the Millennium Declaration. For this purpose we will use the P₂ distance method for the year 2007, the last year for which data are available. This index integrates socio-economic variables that permit a territorial ordering of the Pacific ACPs, in terms of those partial indicators.     

Explaining welfare recidivism: what role do unemployment and initial spells have?

The question of high welfare re-entry rates has attracted great attention from economists and policymakers. Using a very rich administrative data set for the minimum income program of the Madrid Government (over 50,000 spells), this paper aims to broach various questions arising from the issue of welfare re-entry. We try to identify what factors determine observed differences in the durations of the first off-welfare spell. We analyze the combined effects of the length and type of exit of the first spell, unemployment, and sociodemographic characteristics. The experience of the first spell and, to a lesser extent, employability can contribute toward lengthening the time spent outside the program. Our results also show that off-welfare spells of households leaving the program in periods of low economic growth will be longer than those that do so during economic expansions. With the exception of unemployment effects, our estimates yield very similar results to those obtained in the U.S. studies, suggesting that U.S. welfare policies and analyses are not entirely irrelevant for European discussions of welfare policies.     

An Index of Child Health in the Least Developed Countries (LDCs) of Africa

In this article we present a new composite index of child health, applied to the Least Developed Countries (LDCs) of Africa, one of the areas of the planet most castigated by poverty. Our index has been constructed attending to the variables defined in the Goals of the Millennium Declaration. For this purpose we will use the P₂ distance method for the year 2008, the last year for which data are available. This index integrates variables of child health that permit a territorial ordering of the LDCs of Africa, in terms of those partial indicators.     

Percentiles of sums of heavy-tailed random variables: beyond the single-loss approximation

A perturbative approach is used to derive approximations of arbitrary order to estimate high percentiles of sums of positive independent random variables that exhibit heavy tails. Closed-form expressions for the successive approximations are obtained both when the number of terms in the sum is deterministic and when it is random. The zeroth order approximation is the percentile of the maximum term in the sum. Higher orders in the perturbative series involve the right-truncated moments of the individual random variables that appear in the sum. These censored moments are always finite. As a result, and in contrast to previous approximations proposed in the literature, the perturbative series has the same form regardless of whether these random variables have a finite mean or not. For high percentiles, and specially for heavier tails, the quality of the estimate improves as more terms are included in the series, up to a certain order. Beyond that order the convergence of the series deteriorates. Nevertheless, the approximations obtained by truncating the perturbative series at intermediate orders are remarkably accurate for a variety of distributions in a wide range of parameters.     

On the use of priors in goodness‐of‐fit tests

Priors are introduced into goodness‐of‐fit tests, both for unknown parameters in the tested distribution and on the alternative density. Neyman–Pearson theory leads to the test with the highest expected power. To make the test practical, we seek priors that make it likely a priori that the power will be larger than the level of the test but not too close to one. As a result, priors are sample size dependent. We explore this procedure in particular for priors that are defined via a Gaussian process approximation for the logarithm of the alternative density. In the case of testing for the uniform distribution, we show that the optimal test is of the U‐statistic type and establish limiting distributions for the optimal test statistic, both under the null hypothesis and averaged over the alternative hypotheses. The optimal test statistic is shown to be of the Cramér–von Mises type for specific choices of the Gaussian process involved. The methodology when parameters in the tested distribution are unknown is discussed and illustrated in the case of testing for the von Mises distribution. The Canadian Journal of Statistics 47: 560–579; 2019 © 2019 Statistical Society of Canada     

Model Selection Using Conditional Densities

In this article we propose a new method to select a discrete model f(x; θ), based on the conditional density of a sample given the value of a sufficient statistic for θ. The main idea is to work with a broad family of discrete distributions, called the family of power series distribution, for which there is a common sufficient statistic for the parameter of interest. The proposed method uses the maximum conditional density in order to select the best model.

We compare our proposal with the usual methodology based on Bayes factors. We provide several examples that show that our proposal works fine in most instances. Bayes factors are strongly dependent on the prior information about the parameters. Since our method does not require the specification of a prior distribution, it provides a useful alternative to Bayes factors.     

Shortening the distance between Edgeworth and Berry–Esseen in the classical case

We obtain near optimal Berry–Esseen bounds for standardized sums of independent identically distributed random variables. This is achieved by distinguishing the lattice and the non-lattice cases, as one-term Edgeworth expansions do. The main tool is an easy inequality involving the usual second modulus of continuity, in substitution of Esseen's smoothing inequality. An illustrative example concerning the exponential distribution is also considered.     

An analytical management framework for new product development processes featuring uncertain iterations

This paper presents an analytical framework for effective management of projects with uncertain iterations. The framework is based upon: (1) the combination of two complementary techniques, one focused on improving iterative process architectures, the Design Structure Matrix, and one focused on predicting project performance, the Graphical Evaluation Review Technique; and (2) the introduction of an activity set-based criticality measure. The intent of the framework is to help project managers and researchers identify and evaluate alternative process architectures, in order to help them determine the alternative which best balances risk and other project performance parameters, as illustrated through an example application.