Mercedes Castro-Nuño

Bio: Mercedes Castro-Nuño is an academic researcher from University of Seville. The author has contributed to research in topics: European union & Poison control. The author has an hindex of 16, co-authored 38 publications receiving 715 citations.

Tourism and GDP: A Meta-analysis of Panel Data Studies

Abstract: This article provides a meta-analysis of a selected sample of 87 estimates from studies based on panel data techniques published through until 2012 The purpose is to obtain a summary measure of the effects of tourism on economic growth by applying models for both fixed and random effects The results show a positive elasticity between GDP and tourism, although the magnitude of the effect varies according to the methodological procedure employed in the original studies for empirical estimates In this sense, when estimates exclude other explanatory variables of economic growth, elasticities are overvalued

Measuring the effect of ARS on academic performance

Abstract: An increasing number of studies have addressed the impact of Audience Response Systems (ARS) on academic performance at all stages of education, although the evidence does not seem conclusive. With the aim of shedding light on the extent and diversity of the research outcomes, we conduct a meta-analysis of studies worldwide on this topic to assess whether the exam scores of students included in ARS experiments achieve better results than others taught using more conventional teaching tools. From an initial sample of 254 studies, data from 51 papers published between 2008 and 2012 (involving 14,963 participants) that set academic quality criteria, were extracted and analyzed following technical protocols for meta-analyses. Their high degree of heterogeneity shows that the effect of ARS on exam scores seems to be moderated by specific features. So, through a random-effects model, our results provide a positive, although moderated pooled effect of ARS on examination scores that is much greater in experiments performed in non-university contexts (Hedges' g?=?0.48; S.E.?=?.2665) than at the university level (Hedge's g?=?0.22, S.E.?=?.0434). Specifically, the categories of university disciplines in which ARS interventions are implemented seem to influence their usefulness for achieving better academic marks, being more effective when either Pure Soft Sciences or Applied Hard Sciences are considered. These findings might provide guidance for governments, researchers and educators into the effectiveness of learning based on the new interactive technologies. The prior literature offers no consensus on the effect of ARS on examination scores in education.Our research conducts a meta-analysis to synthesize all recent ARS evaluations worldwide.Our results suggest that there is a positive, although moderated effect of ARS on examination scores.The effect of ARS is greater in non-university education than at the university level.In university disciplines, ARS is more effective in Pure Soft and Applied Hard Sciences.

Forecasting, Structural Time Series Models and the Kalman Filter

Abstract: In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Getting to the truth: evaluating national tobacco countermarketing campaigns (vol 92, pg 901, 2002)

Abstract: OBJECTIVES This study examines how the American Legacy Foundation's "truth" campaign and Philip Morris's "Think. Don't Smoke" campaign have influenced youths' attitudes, beliefs, and intentions toward tobacco. METHODS We analyzed 2 telephone surveys of 12- to 17-year-olds with multivariate logistic regressions: a baseline survey conducted before the launch of "truth" and a second survey 10 months into the "truth" campaign. RESULTS Exposure to "truth" countermarketing advertisements was consistently associated with an increase in anti-tobacco attitudes and beliefs, whereas exposure to Philip Morris advertisements generally was not. In addition, those exposed to Philip Morris advertisements were more likely to be open to the idea of smoking. CONCLUSIONS Whereas exposure to the "truth" campaign positively changed youths' attitudes toward tobacco, the Philip Morris campaign had a counterproductive influence.

Commuting by Bicycle:An Overview of the Literature

Abstract: Commuting by bicycle has advantages over other modes of transport,both for the commuter and for society.Although cycling is an option for many commuters,a considerable number of them choose to use other forms of trans-port.In order to underpin policies that promote commuting by bicy-cle,this paper investigates the de-terminants for commuting to work.As many bicycle commuters do notcycle every day,we also examine people’s daily choices,in terms of frequency.We conducted a survey of the current literature in order to identify the determinants for com-muting by bicycle.We found many determinants,not all of which are addressed by conventional mode choice studies and models.This suggests that predicting and influ-encing bicycle use needs to be grounded in other kinds of knowl-edge than those currently available for motorized forms of transport.