A Bistochastic Nonparametric Estimator

We explore the relevance of adopting a bistochastic nonparametric estimator. This estimator has two main implications. First, the estimator reduces variability according to the robust criterion of second-order stochastic (and Lorenz) dominance. This is a universally criterion in risk and welfare economics, which expands the applicability of nonparametric estimation in economics, for instance to the measurement of economic discrimination. Second, the bistochastic estimator produces smaller errors than do positive-weights nonparametric estimators, in terms of the bias-variance trade-off. This result is verified in a general simulation exercise. This improvement is due to a significant reduction in boundary bias, which makes the estimator itself useful in empirical applications. Finally, consistency, preservation of the mean value, and multidimensional extension are some other useful properties of this estimator.nonparametric estimation, second-order stochastic dominance, bistochastic estimator

Industrial and Tramp Ship Routing Problems: Closing the Gap for Real-Scale Instances

Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo selection, ship-dependent starting locations, travel times and costs, time windows, and incompatibility constraints, among other features. Together, these characteristics pose considerable challenges for exact and heuristic methods, and some cases with as few as 18 cargoes remain unsolved. To face this challenge, we propose an exact branch-and-price (B&P) algorithm and a hybrid metaheuristic. Our exact method generates elementary routes, but exploits decremental state-space relaxation to speed up column generation, heuristic strong branching, as well as advanced preprocessing and route enumeration techniques. Our metaheuristic is a sophisticated extension of the unified hybrid genetic search. It exploits a set-partitioning phase and uses problem-tailored variation operators to efficiently handle all the problem characteristics. As shown in our experimental analyses, the B&P optimally solves 239/240 existing instances within one hour. Scalability experiments on even larger problems demonstrate that it can optimally solve problems with around 60 ships and 200 cargoes (i.e., 400 pickup and delivery services) and find optimality gaps below 1.04% on the largest cases with up to 260 cargoes. The hybrid metaheuristic outperforms all previous heuristics and produces near-optimal solutions within minutes. These results are noteworthy, since these instances are comparable in size with the largest problems routinely solved by shipping companies

Primeiro registro de Eudorylas schreiteri (Shannon) (Diptera: Pipunculidae) como parasitóide da cigarrinha do milho (Hemiptera: Cicadellidae) na Argentina, e uma tabela dos hospedeiros de pipunculídeos na região neotropical

The big-headed fly Eudorylas schreiteri (Shannon) is recorded for the first time as an endoparasitoid of the corn leafhopper Dalbulus maidis (DeLong & Wolcott) in Northern Argentina. A table of known Neotropical pipunculid-host associations is presented.Eudorylas schreiteri (Shannon) é registrada pela primeira vez como endoparasitóide da cigarrinha do milho Dalbulus maidis (DeLong & Wolcott) no norte da Argentina. Uma tabela das espécies neotropicais de pipunculídeos com hospedeiros conhecidos é apresentada.Fil: Virla, Eduardo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Planta Piloto de Procesos Industriales Microbiológicos; ArgentinaFil: Moya Raygoza, Gustavo. Universidad de Guadalajara; MéxicoFil: Rafael, José A. Instituto de Pesquisa da Amazônia; Brasi

Technology Integration around the Geographic Information: A State of the Art

One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented

Modelling Cell Cycle using Different Levels of Representation

Understanding the behaviour of biological systems requires a complex setting of in vitro and in vivo experiments, which attracts high costs in terms of time and resources. The use of mathematical models allows researchers to perform computerised simulations of biological systems, which are called in silico experiments, to attain important insights and predictions about the system behaviour with a considerably lower cost. Computer visualisation is an important part of this approach, since it provides a realistic representation of the system behaviour. We define a formal methodology to model biological systems using different levels of representation: a purely formal representation, which we call molecular level, models the biochemical dynamics of the system; visualisation-oriented representations, which we call visual levels, provide views of the biological system at a higher level of organisation and are equipped with the necessary spatial information to generate the appropriate visualisation. We choose Spatial CLS, a formal language belonging to the class of Calculi of Looping Sequences, as the formalism for modelling all representation levels. We illustrate our approach using the budding yeast cell cycle as a case study

A theoretical model of wage discrimination with inspection fines

In neoclassical models, workers are classified a priori into discrimination groups. We develop a probabilistic model of wage discrimination in which workers need not be classified a priori. Our model is a generalization of the standard framework, whereas Becker's model is an extreme case. A second implication is that the traditional approach to measuring discrimination (the Oaxaca–Blinder approach) must be modified to take into account this probabilistic framework.

On The Measurement Of Illegal Wage Discrimination: The Michael Jordan Paradox

Standard wage discrimination models assume that independent observers are able to distinguish a priori which workers are suffering from discrimination. However, this assumption may be inadequate when severe penalties can be imposed on discriminatory employers. Antidiscrimination laws will induce firms to behave in such a way that independent observers (for instance, lawyers, economists) cannot easily detect discriminatory practices. This problem can be solved by estimating the discriminatory wage gap using finite mixture or latent class models because these procedures do not require the a priori classification of workers. In fact, the standard discrimination model can be seen as a particular case of our method when the probabilities of belonging to a group are fixed (to one or zero). We estimate discrimination coefficients for Germany and United Kingdom using the European Community Household Panel (ECHP). We obtain unambiguous higher discrimination in Germany for a wide set of measuresdiscrimination; wages; latent class model; finite mixture models.

Is an inequality-neutral flat tax reform really neutral?

Let us assume a revenue- and inequality-neutral flat tax reform shifting from a graduated-rate tax. Is this reform really distributional neutral? Traditionally, there has been a bias toward the inequality analysis, forgetting other relevant aspects of the income distribution. This kind of reforms implies a set of composite transfers, both progressive and regressive, even though inequality remains unchanged. This paper shows that polarization is a useful tool for characterizing this set of transfers caused by inequality-neutral tax reforms. A simulation exercise illustrates how polarization can be used to discriminate between two inequality-neutral tax alternatives.polarization, inequality, flat tax

POLARIZATION CHARACTERIZATION OF INEQUALITY-NEUTRAL TAX REFORMS

In this article, polarization measurement is presented as a useful tool for characterizing the net transfers of income between individuals caused by a tax reform. The bipolarization measure, which considers just two poles and involves the disappearance of the middle class, may complement inequality measures insofar as it provides an alternative explanation of the distributional impact of inequality neutral tax reforms. Some theoretical implications of an inequality- and revenue-neutral tax reform concerning polarization are examined. We conclude with an empirical application where we carry out a simulation to evaluate the effects on polarization of a potential substitution of the current Spanish tax system for an inequality- and revenue- neutral linear tax.