Assessment of the effect of the financial crisis on agents’ expectations through symbolic regression

Agents’ perceptions on the state of the economy can be affected during economic crises. Tendency surveys are the main source of agents’ expectations. The main objective of this study is to assess the impact of the 2008 financial crisis on agents’ expectations. With this aim, we evaluate the capacity of survey-based expectations to anticipate economic growth in the United States, Japan, Germany and the United Kingdom. We propose a symbolic regression (SR) via genetic programming approach to derive mathematical functional forms that link survey-based expectations to GDP growth. By combining the main SR-generated indicators, we generate estimates of the evolution of GDP. Finally, we analyse the effect of the crisis on the formation of expectations, and we find an improvement in the capacity of agents’ expectations to anticipate economic growth after the crisis in all countries except Germany.Peer ReviewedPostprint (author's final draft

Modelling tourism demand to Spain with machine learning techniques. The impact of forecast horizon on model selection

This study assesses the influence of the forecast horizon on the forecasting performance of several machine learning techniques. We compare the fo recastaccuracy of Support Vector Regression (SVR) to Neural Network (NN) models, using a linear model as a benchmark. We focus on international tourism demand to all seventeen regions of Spain. The SVR with a Gaussian radial basis function kernel outperforms the rest of the models for the longest forecast horizons. We also find that machine learning methods improve their forecasting accuracy with respect to linear models as forecast horizons increase. This results shows the suitability of SVR for medium and long term forecasting.Peer ReviewedPostprint (published version

Dos nuevos fragmentos de sarcófagos romanos con el tema de las estaciones

En el presente artículo se tratan dos fragmentos de sarcófagos romanos que no figuran en el corpus de los sarcófagos de las estaciones realizado por P. Kranz (1984). El primero, conservado en el Museu Nacional Arqueològic de Tarragona (número de inventario 45652), ofrece la particularidad de pertenecer a una limitada serie de sarcófagos manufacturados en Roma, constituyentes del llamado «ciclo de erotes Pisa/Ostia», y cuyo distintivo reside en la actitud danzante de sus personificaciones estacionales. El segundo, hallado en la Plaza de Sant Miquel de Barcelona en 1989 (ref. UE 1276-9), corresponde a una cubierta con el tema de las estaciones encarnadas por Horae, cuya cronología se fija en el segundo cuarto del siglo III. Su iconografía aporta un nuevo ejemplo para con el escaso número de tapas conservadas del tema, en las que la hoz se asocia con la Hora del verano.A Roman sarcophagus fragment preserved in Tarragona (Archeological Museum nº. Inv. 45652) is presented as belonging to the specific group of the seasons sarcophagi showing the dacing erotes cicle Pisa/Ostia. A second fragment, found in Barcelona (Plaza de Sant Miquel ref. UE 1276-9), is defined as a sommer Hora from a season's sarcophagus lid. It is dated in the second quarter of the 3rd. century

Orbits for eighteen visual binaries and two double-line spectroscopic binaries observed with HRCAM on the CTIO SOAR 4m telescope, using a new Bayesian orbit code based on Markov Chain Monte Carlo

We present orbital elements and mass sums for eighteen visual binary stars of spectral types B to K (five of which are new orbits) with periods ranging from 20 to more than 500 yr. For two double-line spectroscopic binaries with no previous orbits, the individual component masses, using combined astrometric and radial velocity data, have a formal uncertainty of ~0.1 MSun. Adopting published photometry, and trigonometric parallaxes, plus our own measurements, we place these objects on an H-R diagram, and discuss their evolutionary status. These objects are part of a survey to characterize the binary population of stars in the Southern Hemisphere, using the SOAR 4m telescope+HRCAM at CTIO. Orbital elements are computed using a newly developed Markov Chain Monte Carlo algorithm that delivers maximum likelihood estimates of the parameters, as well as posterior probability density functions that allow us to evaluate the uncertainty of our derived parameters in a robust way. For spectroscopic binaries, using our approach, it is possible to derive a self-consistent parallax for the system from the combined astrometric plus radial velocity data ("orbital parallax"), which compares well with the trigonometric parallaxes. We also present a mathematical formalism that allows a dimensionality reduction of the feature space from seven to three search parameters (or from ten to seven dimensions - including parallax - in the case of spectroscopic binaries with astrometric data), which makes it possible to explore a smaller number of parameters in each case, improving the computational efficiency of our Markov Chain Monte Carlo code.Comment: 32 pages, 9 figures, 6 tables. Detailed Appendix with methodology. Accepted by The Astronomical Journa

Enfoques de aprendizaje y enfoques de enseñanza en la educación superior chilena: Un análisis comparativo

El presente artículo describe y analiza los resultados de una investigación realizada en los años 2015 y 2016, en una muestra de estudiantes y profesores proveniente de tres universidades regionales, sobre sus enfoques de enseñanza y aprendizaje. Los resultados obtenidos demuestran una correlación entre los enfoque de enseñanza y aprendizaje en la muestra de profesores y alumnos consultados. Se reconoce diferencias de género en cuanto al tipo motivación, donde las mujeres poseen una motivación más profunda para su aprendizaje. También existen diferencias en los alumnos según el tipo establecimiento de la educación secundaria, donde egresados de liceos técnicos profesional alcanzar mayores niveles de motivación y estrategias utilizadaThis article describes and analyzes the results of a research carried out in 2015 and 2016 in a sample of students and professors from three regional universities on their approaches to teaching and learning..The results obtained show a correlation between the teaching and learning approach in the sample of teachers and students consulted. Gender differences in the type of motivation are recognized, where women have a deeper motivation for their learning. There are also differences in the students according to the type of secondary education, where graduates of high school technical professionals achieve higher levels of motivation and strategies use

A multivariate neural network approach to tourism demand forecasting

This study compares the performance of different Artificial Neural Networks models for tourist demand forecasting in a multiple-output framework. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron network, a radial basis function network and an Elman neural network. We use official statistical data of inbound international tourism demand to Catalonia (Spain) from 2001 to 2012. By means of cointegration analysis we find that growth rates of tourist arrivals from all different countries share a common stochastic trend, which leads us to apply a multivariate out-of-sample forecasting comparison. When comparing the forecasting accuracy of the different techniques for each visitor market and for different forecasting horizons, we find that radial basis function models outperform multi-layer perceptron and Elman networks. We repeat the experiment assuming different topologies regarding the number of lags used for concatenation so as to evaluate the effect of the memory on the forecasting results, and we find no significant differences when additional lags are incorporated. These results reveal the suitability of hybrid models such as radial basis functions that combine supervised and unsupervised learning for economic forecasting with seasonal data.Preprin