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).

A Note on Wavelet Correlation and Cointegration

In a recent paper Leong-Huang:2010 {Journal of Applied Statistics 37, 215–233} proposed a wavelet-correlation-based approach to test for cointegration between two time series. However, correlation and cointegration are two different concepts even when wavelet analysis is used. It is known that statistics based on nonstationary integrated variables have non-standard asymptotic distributions. However, wavelet analysis offsets the integrating order of nonstationary series so that traditional asymptotics on stationary variables suffices to ascertain the statistical properties of wavelet-based statistics. Based on this, this note shows that wavelet correlations cannot be used as a test of cointegration.

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.

Cointegration analysis of money demand in the Euro Area

The analysis of the evolution of the M3 money aggregate is an important element in the definition and implementation of monetary policy for the ECB. A well-defined and stable long run demand function is an essential requisite for M3 to be a valid monetary tool. Therefore, this paper analyzes based in cointegration techniques the existence of a long run money demand, estimating it and testing its stability for the Euro Area and for ten of its member countries. Specifically, bearing in mind the high degree of monetary instability that the current economic crisis has created in the Euro Area, we also test whether this has had a noticeable impact in the cointegration among real money demand and its determinants. The analysis gives evidence of the existence of a long run relationship when the aggregated Euro Area and six of the ten countries are considered. However, these relationships are highly instable since the outbreak of the financial crisis, leading in some cases to even rejecting cointegration. All this suggests that the ECB’s strategy of focusing in the M3 monetary aggregates could not be a convenient approach under the current circumstances

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.