Characterizing the Performance of the Conway‐Maxwell Poisson Generalized Linear Model

Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model based on the Conway‐Maxwell Poisson (COM‐Poisson) distribution was recently proposed, a model that has the potential to overcome the limitations of the traditional model. However, the statistical performance of this new model has not yet been fully characterized. This article assesses the performance of a maximum likelihood estimation method for fitting the COM‐Poisson generalized linear model (GLM). The objectives of this article are to (1) characterize the parameter estimation accuracy of the MLE implementation of the COM‐Poisson GLM, and (2) estimate the prediction accuracy of the COM‐Poisson GLM using simulated data sets. The results of the study indicate that the COM‐Poisson GLM is flexible enough to model under‐, equi‐, and overdispersed data sets with different sample mean values. The results also show that the COM‐Poisson GLM yields accurate parameter estimates. The COM‐Poisson GLM provides a promising and flexible approach for performing count data regression.     

Post-2008 Multi-Sited Household Practices: Between Morocco,Spain and Norway

The recent outmigration patterns from Southern Europe since the outbreak of the global economic crisis have interested many migration researchers. Despite their long migration history towards Europe, little is known about the onward migration of the Moroccan-born, yet this group was one of the most affected by the recession. Furthermore, studies on onward migration tend to focus on the individual perspective and overlook the non-economic factors that shape migration decisions. This article focuses on Moroccan-born migrants who, after several years in Spain, migrated to Norway after 2008. Through analysis of ten semi-structured interviews and fieldwork observations, onward migration practices are studied from the perspective of broader dynamics at the household level, which combine different types of migration and non-migration. Looking beyond the economic factors that triggered remigration, the article contributes to the discussion on onward migration, stressing its non-linear character and inserting it in wider multi-sited household projects in constant change.     

Statistical analysis of rank data from a visual matching of colored textures

Nowadays, sensory properties of materials are subject to growing attention both in an hedonic point of view and in an utilitarian one. Hence, the formulation of the foundations of an instrumental metrological approach that will allow for the characterization of visual similarities between textures belonging to the same type becomes a challenge of the research activities in the domain of perception. In this paper, our specific objective is to link an instrumental approach of metrology of the assessment of visual textures with a metrology approach based on a softcopy experiment performed by human judges. The experiment consisted in ranking of isochromatic colored textures according to the visual contrast. A fixed effects additive model is considered for the analysis of the rank data collected from the softcopy experiment. The model is fitted to the data using a least-squares criterion. The resulting data analysis gives rise to a sensory scale that shows a non-linear correlation and a monotonic functional relationship with the physical attribute on which the ranking experiment is based. Furthermore, the capacity of the judges to discriminate the textures according to the visual contrast varies according to the color ranges and the textures types.     

Lag Specification in Rational Distributed Lag Structural Models

This article presents methods for the preliminary specification of distributed lags in structural models in the absence of sufficient a priori information. It is argued that an instrumental-variables procedure produces good results as long as the goodness of fit in the instrument equations is satisfactory. When this is not the case, simple OLS specification is preferable to more complex instrumental-variables methods, even though it may produce some spurious parameters. The procedures are illustrated with a simulated two-equation system and a model of annual supply and price of hogs.     

Grouping strategies and thresholding for high dimensional linear models

The estimation problem in a high regression model with structured sparsity is investigated. An algorithm using a two-step block thresholding procedure called GR-LOL is provided. Convergence rates are produced: they depend on simple coherence-type indices of the Gram matrix – easily checkable on the data – as well as sparsity assumptions of the model parameters measured by a combination of l₁ within-blocks with _lq$l_q$, q<1$q<1$ between-blocks norms. The simplicity of the coherence indicator suggests ways to optimize the rates of convergence when the group structure is not naturally given by the problem or is unknown. In such a case, an auto-driven procedure is provided to determine the regressor groups (number and contents). An intensive practical study compares our grouping methods with the standard LOL algorithm. We prove that the grouping rarely deteriorates the results but can improve them very significantly. GR-LOL is also compared with group-Lasso procedures and exhibits a very encouraging behavior. The results are quite impressive, especially when GR-LOL algorithm is combined with a grouping pre-processing.     

A Time-Series Study of the Formation and Predictive Performance of EEC Production Survey Expectations

Generalized method of moments (GMM) has been an important innovation in econometrics. Its usefulness has motivated a search for good inference procedures based on GMM. This article presents a novel method of bootstrapping for GMM based on resampling from the empirical likelihood distribution that imposes the moment restrictions. We show that this approach yields a large-sample improvement and is efficient, and give examples. We also discuss the development of GMM and other recent work on improved inference.     

Lessons of privatization

Lord King's informative and stimulating views on the lessons of the privatization programme which has so far been carried out and his discussion of what the future might hold in this sphere, are the subject of this article.     

Characterizations of egalitarian binary relations as transitive closures with a special reference to Lorenz dominance and to single-crossing conditions

This article considers, in the context of the fixed-population constant-sum comparison of income distributions, a number of intransitive binary relations smaller than Lorenz dominance. We determine their transitive closure, and we study how they relate to each other and to other relations that have appeared in the literature. Among other results, we provide alternative characterizations of Lorenz dominance.