Inequality for Wage Earners and Self-Employed: Evidence from Panel Data

Published as an article in: Oxford Bulletin of Economics and Statistics, 2009, vol. 71, issue 4, pages 491-518.

Identification of a biomarker panel for colorectal cancer diagnosis

Background: Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60- mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality–lost values imputation, probes quality, data smoothing and intraclass variability filtering–the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).

Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain) using analogues and analogues followed by random forests and multiple linear regression

In this paper, reanalysis fields from the ECMWF have been statistically downscaled to predict from large-scale atmospheric fields, surface moisture flux and daily precipitation at two observatories (Zaragoza and Tortosa, Ebro Valley, Spain) during the 1961-2001 period. Three types of downscaling models have been built: (i) analogues, (ii) analogues followed by random forests and (iii) analogues followed by multiple linear regression. The inputs consist of data (predictor fields) taken from the ERA-40 reanalysis. The predicted fields are precipitation and surface moisture flux as measured at the two observatories. With the aim to reduce the dimensionality of the problem, the ERA-40 fields have been decomposed using empirical orthogonal functions. Available daily data has been divided into two parts: a training period used to find a group of about 300 analogues to build the downscaling model (1961-1996) and a test period (19972001), where models' performance has been assessed using independent data. In the case of surface moisture flux, the models based on analogues followed by random forests do not clearly outperform those built on analogues plus multiple linear regression, while simple averages calculated from the nearest analogues found in the training period, yielded only slightly worse results. In the case of precipitation, the three types of model performed equally. These results suggest that most of the models' downscaling capabilities can be attributed to the analogues-calculation stage.

Development of appropriateness explicit criteria for cataract extraction by phacoemulsification

Background: Consensus development techniques were used in the late 1980s to create explicit criteria for the appropriateness of cataract extraction. We developed a new appropriateness of indications tool for cataract following the RAND method. We tested the validity of our panel results. Methods: Criteria were developed using a modified Delphi panel judgment process. A panel of 12 ophthalmologists was assembled. Ratings were analyzed regarding the level of agreement among panelists. We studied the influence of all variables on the final panel score using linear and logistic regression models. The explicit criteria developed were summarized by classification and regression tree analysis. Results: Of the 765 indications evaluated by the main panel in the second round, 32.9% were found appropriate, 30.1% uncertain, and 37% inappropriate. Agreement was found in 53% of the indications and disagreement in 0.9%. Seven variables were considered to create the indications and divided into three groups: simple cataract, with diabetic retinopathy, or with other ocular pathologies. The preoperative visual acuity in the cataractous eye and visual function were the variables that best explained the panel scoring. The panel results were synthesized and presented in three decision trees. Misclassification error in the decision trees, as compared with the panel original criteria, was 5.3%. Conclusion: The parameters tested showed acceptable validity for an evaluation tool. These results support the use of this indication algorithm as a screening tool for assessing the appropriateness of cataract extraction in field studies and for the development of practice guidelines.

Desarrollo de componentes para el panel de administración de GeoServicios® on-line

Panel de Administración que ofrece una solución completa a la hora de realizar visores para mapas y que permite al cliente configurar un visor en base a sus necesidades, mediante diferentes módulos. Dicho panel, se ha realizado utilizando un desarrollo basado en el prototipado. En el caso de este proyecto, se especifica el desarrollo de los dos primeros prototipos. Los módulos desarrollados son los siguientes: Panel de login: Este panel permite el acceso a la aplicación. Módulo de usuarios/grupos: Este componente permite gestionar grupos y usuarios, tanto la creación, edición de los mismos como la visualización de estos. Módulo de datos: Este componente permite gestionar las fuentes de datos del cliente. Crear plantillas a partir de datos procedentes de BBDD propias, así como la edición de dichas plantillas. Módulo GeoAsset: Este componente permite configurar aplicaciones web o visores. Un visor tendrá asociado un mapa, una lista de control de accesos, etc. Siguiendo la estructura de módulos, también es objeto del proyecto la realización de un segundo prototipo que contiene la mejora de uno de los módulos ya creados: Mejora de módulo de datos: Este componente implementa además de las funcionalidades creadas en la anterior versión, una funcionalidad para permitir la subida de datos a la aplicación.

Crecimiento y rentabilidad en el mercado emergente brasileño

[ES] En los últimos años, las economías emergentes están tomando las primeras posiciones a nivel mundial. Las consecuencias de la crisis financiera han provocado que inversores y empresas dirijan sus capitales y esfuerzo hacia los mercados emergentes en busca de crecimiento y rentabilidad empresarial que los países desarrollados no ofrecen. En este contexto, el objetivo del presente estudio consiste en analizar el crecimiento empresarial en Brasil durante el periodo 1995-2011 y, más específicamente, sus variables explicativas y la interrelación con la rentabilidad empresarial. Para ello, en primer lugar realizamos la estimación de un modelo de regresión dinámico con datos de panel empleando el Método Generalizado de los Momentos (GMM). En segundo lugar, empleamos un sistema de Vectores Autorregresivos (VAR) para analizar la relación entre crecimiento y rentabilidad. Los principales resultados obtenidos nos indican que la obtención de mayores tasas de rentabilidad proporcionan un mayor crecimiento empresarial, pero no al contrario. Además cabe señalar que el comportamiento del crecimiento empresarial es diferente según la propiedad y el control de las empresas. Además, aportan un mayor conocimiento del comportamiento del crecimiento empresarial en Brasil, siendo útil para la toma de decisiones de empresarios e inversores, y así pueden ser utilizados para la toma de decisiones en el ámbito de la política regional y social.

Political Institutions, Technology and Growth: a dynamic panel approach

This paper investigates whether the effect of political institutions on sectoral economic performance is determined by the level of technological development of industries. Building on previous studies on the linkages among political institutions, technology and economic growth, we employ the dynamic panel Generalized Method of Moments (GMM) estimator for a sample of 4,134 country-industries from 61 industries and 89 countries over the 1990-2010 period. Our main findings suggest that changes of political institutions towards higher levels of democracy, political rights and civil liberties enhance economic growth in technologically developed industries. On the contrary, the same institutional changes might retard economic growth of those industries that are below a technological development threshold. Overall, these results give evidence of a technologically conditioned nature of political institutions to be growth-promoting.