A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers

In this article, a general class of estimators for the linear regression model affected by outliers and collinearity is introduced and studied in some detail. This class of estimators combines the theory of light, maximum entropy, and robust regression techniques. Our theoretical findings are illustrated through a Monte Carlo simulation study.     

Robust Bayesian inference in STAR models with neighbourhood effects

In this paper we propose a robust Bayesian procedure of estimation, testing, validation and selection of spatio-temporal autoregressive models (STAR) with neighbourhood effects applied to the appraisal of dwelling prices. The methodology does not depend on asymptotic results and, unlike previously procedures proposed in the literature, takes into account the uncertainty associated to the estimation of the neighbourhood parameters of the model, giving more realism to the analysis. Moreover, a sequential algorithm to elaborate fast on-line forecast, is provided. The methodology is illustrated by means of a practical case of the real estate market of Zaragoza.     

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.     

The Diffusion of Innovations: A Methodological Reappraisal

Studies of diffusion have traditionally relied on specific distributions, primarily the logistic, to characterize and estimate those processes. We argue that such an approach gives rise to serious problems of comparability and interpretation and may result in large biases in the estimates of the parameters of interest. We propose instead the Gini's expected mean difference as a measure of diffusion speed. We discuss its advantages over the traditional approach, present a nonparametric estimation procedure, and tackle with it the problems of truncated processes and of intergroup comparisons. We also elaborate on the use of the hazard rate and suggest various extensions. The diffusion of computed tomography scanners is presented as an illustration.     

On the potential in the estimation of linear functions in regression

New aspects of potential in Cook's Influence measure for linear combinations are explored. It is shown that this potential can be considered as a case influence measure in the scatter of estimated combinations. The potential is related to precise estimation directions and multicollinearity concepts; It Is also used as a basis for selection of new cases.     

A coordinate-free approach to testable hypotheses

Using the coordinate-free version of the linear model and geometrical considerations, the usual definition of testable hyptheses is extended. The concept of partially testable hypotheses is defined in that context. This new approach provides an alternative to the one given by Peixoto (1986), offering some complementary aspects. Simple and direct techniques for testing the new testable hyptheses by means of the classical testing procedure are given.     

Problematizing the “informal sector”: 50 years of critique,clarification, qualification,and more critique

Since its coining in 1971, the concept of the “informal sector” has been used to draw scholarly, political, and philanthropic attention to hundreds of millions of workers who lack basic labor protections. But as the term proliferated, so too did its detractors. Critics claim that the label of “informal” homogenizes the world's poor and distorts understandings of the sources of and solutions to their economic woes. What are the origins of the concept's contradictory nature? What strategies have scholars used to increase the likelihood that it will be used to illuminate and uplift, rather than to distort and denigrate? This article analyzes how scholars have resignified and retheorized the informal economy in response to five conceptual challenges: stigmatization, definitional fuzziness, homogenization, an either/or fallacy, and the presumption of “formalization” as the solution. Such efforts have preserved the concept's analytic potency and political relevance. In the longer term, however, a true testament to the concept's value would be if it outlives its own utility; that is, if it mobilizes enough recognition and resources to the invisibilized majority of the world's workers that scholars and state bureaucrats no longer feel the need to lump them together under a misleading catchall label.