Jorge Sainz

This paper presents a structured, open dataset derived from the Cartulario de Santo Toribio de Liébana, a monastic cartulary from northern Spain edited by Sánchez Belda (1948). The dataset converts 566 charters (790–1626) into five linked relational files: (i) 328 payment events; (ii) 531 payment items, retaining goods, quantities, units and legal context; (iii) a gazetteer of 603 place names with medieval variants, municipal attribution and, for 94 places, geographic coordinates; (iv) an index of 1,348 persons with their attested roles; and (v) a concordance between cartulary and edition numbering. The extraction pipeline, implemented in Python 3.12, is released with the data, alongside an audit trail recording penal-clause contamination and Optical Character Recognition (OCR) defects. The dataset supports research on medieval monetisation, diplomatic formulae, historical toponymy and the economic history of northern Iberia.

1. State-funded Catholic education’s mere existence in secularised Spain is far from secure. Most EU countries, like the Netherlands and Belgium, have secured constitutional financial parity for fa...

Marketing Mix Modelling (MMM) optimizes budget allocation and determines the return on advertising investment through market response analysis. MMM are vital tools to help marketers define their marketing strategies according to the firm's business and marketing objectives while reducing uncertainty in the decision-making process. As AI and automated MMM out-of-the-box packages gain popularity among marketers, it has become evident there is a theoretical and empirical gap in the understanding of the benefits and inconveniences of these new methods over traditional econometric models. To shed light on these questions, two different models using the same database from a telecommunications firm have been developed and tested using a traditional econometric model and Robyn, an AI-powered open-sourced MMM package from Meta Marketing Science. The research compares both methods' development processes and subsequent outputs from different perspectives: technical, business, and practical. It shows the advantages and shortcomings of each, providing insightful recommendations for academics and practitioners to navigate through the process of adoption of econometric and AI models for budget allocation decision-making. Econometric models are easy to explain and replicate, while AI complexity from the combination of several methods, their parametrization, and the random initialization of iterations during training, hinders its explainability.

El confinamiento y el consiguiente cierre de los centros educativos provocó un aumento de la proporción de niños y adolescentes con problemas de salud mental desde el 10,9% al 16,0% en Inglaterra, uno de los países para los que mejor se ha medido este impacto. Sin embargo, hay varios aspectos que matizarían esta primera conclusión. El primero es que la experiencia de España, uno de los primeros países en Europa en abrir de forma generalizada y prolongada los centros educativos, muestra que una parte importante de los jóvenes se recupera en su bienestar emocional al volver a las clases presenciales y, con ellas, tener de nuevo la interacción con sus compañeros y docentes y reencontrarse con un espacio como el de los colegios e institutos con el que se sienten identificados. Los novedosos datos de GAD3 para Ernst & Young analizados en este capítulo muestran que la proporción de estudiantes con un estado de ánimo bajo a muy bajo disminuyó desde el 29,9% durante el confinamiento en el último trimestre del curso 2019-2020 al 7,2% del 2020-2021 con las clases presenciales o semipresenciales. El segundo aspecto que gradúa el impacto de la pandemia en la salud mental de los jóvenes es que no todos los estudios encuentran que el bienestar emocional de niños y adolescentes ha empeorado o al menos no en todas las dimensiones.

This research investigates homogeneity in the transposition of European Directives using as an example the EU policy on tobaccos regulated by Directive 2011/64. We analyse the effect of excise duties on tobacco consumption in Europe from 2002 to 2017 using an Artificial Intelligence counterfactual strategy. To our knowledge, this the first time that this AI strategie has been used in the economic analysis of law. Our results show that countries have different responses to changes in prices or taxation on tobacco. The lack of homogeneity across countries creates distortions and frontier effects and shows the need of harmonization.