The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neural network (MLP) models. The possibilities springing from these techniques have been applied to a broad range of personal income return data supplied by the Institute of Fiscal Studies (IEF). The use of the neural networks enabled taxpayer segmentation as well as calculation of the probability concerning an individual taxpayer’s propensity to attempt to evade taxes. The results showed that the selected model has an efficiency rate of 84.3%, implying an improvement in relation to other models utilized in tax fraud detection. The proposal can be generalized to quantify an individual’s propensity to commit fraud with regards to other kinds of taxes. These models will support tax offices to help them arrive at the best decisions regarding action plans to combat tax fraud.

Objectives: The goal of the present research is to establish for the first time a hierarchy of sociodemographic factors according to their importance influencing birth seasonality. Methods: We used Vital Statistics data on all births registered in Spain in the period 2016-2019. Differences in the degree of seasonality between sociodemographic groups (defined by maternal age, maternal marital status, maternal education, birth order, maternal job qualification, maternal employment status, maternal location population size, and maternal country of birth) were first examined with descriptive techniques. Secondly, analysis through alternative Data Mining techniques determined the association between sociodemographic factors and birth seasonality and the factors importance rank.Results: Those factors related to maternal labor status (employment status, job qualification, and education) were found to be the most relevant influencing birth seasonality. It was found that the overall seasonal pattern in Spain was driven by lower skilled employed mothers, in contrast with not employed or high skilled employed mothers, who showed a different or weaker seasonality. Finally, we found that a change in the rhythm pattern has taken place in the last decades in Spain.Conclusions: Birth seasonality is to a large extent related to maternal employment status. Employed mothers, normally more affected by the seasonality of work calendar than the unemployed, show higher conception rates structured around holidays. This may indicate that the observed change of seasonal pattern in Spain in the last decades, as in other European countries, may be specifically driven by the progressive higher participation of women in labor market.

durante el período 2012-15, orientado a mejorar la competitividad de pymes y agrupaciones empresariales. Utilizando información procedente de una encuesta "ad hoc" aplicada a una muestra de empresas beneficiarias y a un grupo de control, los resultados de la estimación de la evaluación, a partir de un modelo de diferencias en diferencias, establecen un impacto diferencial y positivo del programa sobre un indicador sintético de la competitividad empresarial. Palabras clave: innovación, competitividad, políticas de apoyo a la empresa, diferencias en diferencias, evaluación de programas.