Output composition and the US output volatility decline

We argue that the role played by output-composition changes on the decline in US output volatility has been incorrectly assessed in the recent literature. We obtain that shifts across broad sectors in the economy account for about thirty-percent of the volatility decline since the 1950’s.volatility, business fluctuations

Inflation and Factor Shares

We use results from the literature on the determinants of price-cost margins to derive an equation relating labor's share of national income to the inflation rate (as well as to the output gap, the unemployment rate and the capital stock per worker). The equation is tested with a panel of 15 OECD countries. We obtain a robust positive relationship between inflation and the labor share. Our results suggest that disinflation is not distributively neutral, provide empirical support for the distinct concern about price stability shown by trade unions and employers' organizations, and help explaining the negative impact of inflation on growth.Inflation, Functional Distribution of Income, Markups.

Drone-based platform system for reflectometry mapping

Work focused on the use of the drone as a new platform for the installation and assembly of a payload (Intel camera) and a GNSS antenna for reflectometry acquisition data.Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructur

Choice of Metrics used in Collaborative Filtering and their Impact on Recommender Systems

The capacity of recommender systems to make correct predictions is essentially determined by the quality and suitability of the collaborative filtering that implements them. The common memory-based metrics are Pearson correlation and cosine, however, their use is not always the most appropriate or sufficiently justified. In this paper, we analyze these two metrics together with the less common mean squared difference (MSD) to discover their advantages and drawbacks in very important aspects such as the impact when introducing different values of k-neighborhoods, minimization of the MAE error, capacity to carry out a sufficient number of predictions, percentage of correct and incorrect predictions and behavior when attempting to recommend the n-best items. The paper lists the results and practical conclusions that have been obtained after carrying out a comparative study of the metrics based on 135 experiments on the MovieLens database of 100,000 ratios