Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks

Although it is commonly accepted that most macroeconomic variables are nonstationary, it is often difficult to identify the source of the non-stationarity. In particular, it is well-known that integrated and short memory models containing trending components that may display sudden changes in their parameters share some statistical properties that make their identification a hard task. The goal of this paper is to extend the classical testing framework for I(1) versus I(0)+ breaks by considering a a more general class of models under the null hypothesis: non-stationary fractionally integrated (FI) processes. A similar identification problem holds in this broader setting which is shown to be a relevant issue from both a statistical and an economic perspective. The proposed test is developed in the time domain and is very simple to compute. The asymptotic properties of the new technique are derived and it is shown by simulation that it is very well-behaved in finite samples. To illustrate the usefulness of the proposed technique, an application using inflation data is also provided.

The evolution of recent research on Catalan literature through the production of PhD theses: a bibliometric and social network analysis

Introduction. This paper studies the situation of research on Catalan literature between 1976 and 2003 by carrying out a bibliometric and social network analysis of PhD theses defended in Spain. It has a dual aim: to present interesting results for the discipline and to demonstrate the methodological efficacy of scientometric tools in the humanities, a field in which they are often neglected due to the difficulty of gathering data. Method. The analysis was performed on 151 records obtained from the TESEO database of PhD theses. The quantitative estimates include the use of the UCINET and Pajek software packages. Authority control was performed on the records. Analysis. Descriptive statistics were used to describe the sample and the distribution of responses to each question. Sex differences on key questions were analysed using the Chi-squared test. Results. The value of the figures obtained is demonstrated. The information obtained on the topic and the periods studied in the theses, and on the actors involved (doctoral students, thesis supervisors and members of defence committees), provide important insights into the mechanisms of humanities disciplines. The main research tendencies of Catalan literature are identified. It is observed that the composition of members of the thesis defence committees follows Lotka's Law. Conclusions. Bibliometric analysis and social network analysis may be especially useful in the humanities and in other fields which are lacking in scientometric data in comparison with the experimental sciences.

Pathway databases and tools for their exploitation: benefits, current limitations and challenges

In past years, comprehensive representations of cell signalling pathways have been developed by manual curation from literature, which requires huge effort and would benefit from information stored in databases and from automatic retrieval and integration methods. Once a reconstruction of the network of interactions is achieved, analysis of its structural features and its dynamic behaviour can take place. Mathematical modelling techniques are used to simulate the complex behaviour of cell signalling networks, which ultimately sheds light on the mechanisms leading to complex diseases or helps in the identification of drug targets. A variety of databases containing information on cell signalling pathways have been developed in conjunction with methodologies to access and analyse the data. In principle, the scenario is prepared to make the most of this information for the analysis of the dynamics of signalling pathways. However, are the knowledge repositories of signalling pathways ready to realize the systems biology promise? In this article we aim to initiate this discussion and to provide some insights on this issue.

Temporal issues in e-learning research: A literature review

Peer-reviewed

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Integration in strategic alliances : a conceptual framework of IT use in marketing as NPD key factor

En una economia basada en el coneixement, la innovació del producte es considera un factor clau a l'hora de determinar la competitivitat, la productivitat i el creixement d'una companyia. No obstant això, l'experiència de les companyies demostra la necessitat d'un nou model de gestió de la innovació del producte: una gestió basada en el màrqueting, en què la cooperació i l'ús intensiu de les tecnologies de la informació i de la comunicació (TIC) són especialment importants. En els darrers anys, la bibliografia sobre màrqueting ha analitzat el paper de la cooperació en l'èxit del procés d'innovació. No obstant això, fins ara pocs treballs han estudiat el paper que té l'ús de les TIC en el màrqueting en l'èxit del desenvolupament de nous productes (NPD, New Product Development en anglès). És una omissió curiosa, tenint en compte que el nou entorn competitiu és definit per una economia i una societat basades principalment en l'ús intensiu de les TIC i del coneixement. L'objectiu d'aquest treball és investigar el paper que l'ús de les TIC en el màrqueting té en el procés de desenvolupament de nous productes, com a element que reforça la integració d'agents al projecte, afavorint l'establiment de relacions dirigides a la cooperació i l'adquisició d'intel·ligència de mercat útil en el procés de desenvolupament de nous productes. L'estudi d'una mostra de 2.038 companyies de tots els sectors de l'activitat econòmica a Catalunya ens permet contrastar hipòtesis inicials i establir un perfil de companyia innovadora basat en les importants relacions que hi ha entre la innovació, l'ús de TIC en el màrqueting i la integració. Sobresurten dues idees en la nostra anàlisi. En primer lloc, l'ús intensiu de les TIC en el màrqueting fa que la companyia sigui més innovadora, ja que percep que el seu ús ajuda a superar barreres a la innovació i accelera els processos, que es tornen més eficients. En segon lloc, incrementant l'ús de les TIC en el màrqueting es fa augmentar la predisposició de la companyia a integrar agents particulars en l'entorn de negoci en el desenvolupament del procés d'innovació i a col·laborar-hi, de manera que es millora el grau d'adaptació del nou producte a les demandes del mercat.

Using narratives to study the impact of social networks on the educational paths of immigrant students

This paper presents the qualitative data collection process aimed at the study of the impactsocial relations and networks have on educational paths of immigrant students. In theframework of a R & D longitudinal study funded by the Ministry of Science and Innovation(2012-2014), the research team tracked the path of 87 immigrant students, from whom only 17successfully achieved the transition through the first and second year of Post-16 Education.A vast range of literature notes that relationships are an important part of migration process andsocial integration analysis, as well as school history in terms of success or failure. Through thefieldwork researchers collect the personal networks of all immigrant students from 3 highschools who were at that time attending last course of compulsory school. The network structureinfluences their social capital and therefore determines the resources, goods and types of supportindividuals can access. All these aspects are influential elements in the configuration anddevelopment of academic trajectories of immigrant students.At the end of the second year of Post-16 Education (two years later), the study captures personalnetworks of these students again, analyses and discusses their evolution and influence on theirpaths through qualitative interviews. Such interviews facilitated the discussion of theirrelationships while providing interesting narratives that are presented in the text. In order to do so, the biographical interpretive narrative method of interviewing is implemented.

Using narratives to study the impact of social networks on the educational paths of immigrant students

This paper presents the qualitative data collection process aimed at the study of the impactsocial relations and networks have on educational paths of immigrant students. In theframework of a R & D longitudinal study funded by the Ministry of Science and Innovation(2012-2014), the research team tracked the path of 87 immigrant students, from whom only 17successfully achieved the transition through the first and second year of Post-16 Education.A vast range of literature notes that relationships are an important part of migration process andsocial integration analysis, as well as school history in terms of success or failure. Through thefieldwork researchers collect the personal networks of all immigrant students from 3 highschools who were at that time attending last course of compulsory school. The network structureinfluences their social capital and therefore determines the resources, goods and types of supportindividuals can access. All these aspects are influential elements in the configuration anddevelopment of academic trajectories of immigrant students.At the end of the second year of Post-16 Education (two years later), the study captures personalnetworks of these students again, analyses and discusses their evolution and influence on theirpaths through qualitative interviews. Such interviews facilitated the discussion of theirrelationships while providing interesting narratives that are presented in the text. In order to do so, the biographical interpretive narrative method of interviewing is implemented.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Prevalence of smoking among dentists in Catalonia - Spain (2006). Literature review of smoking cessation practices in the dental office

Objective: The objective of this study was to collect data on the prevalence of smokers among Catalonian dentists (by age and sex) and compare them with existing data on the general population, doctors, registered nurses and pharmacists. The overall prevalence of smokers in Catalonia (2006) was 34.5% of men and 24.3% of women. Data available on the prevalence of smoking among doctors (26.3% men and 22.1% women), pharmacists (19.8% men and 20.6% women) and registered nurses (34.1% men and 35.3% women) relates to the year 2002. Study design: In September 2006, Catalonian dentists (n=3,799) were asked about their habits in relation to tobacco in a self-administered questionnaire, on use and opinions with respect to dental amalgam. Five hundred and seventynine questionnaires were received, of which 538 answered the question on smoking (14.2% of the sample universe). Results: The prevalence of smokers among dentists is lower (24.9% of men and 18.4% of women) than in the general population and other healthcare professionals. In dentists in the age group between 25 and 34 years, the prevalence was 26.1% in men and 14.9% in women, while the prevalence in this age group in the general population was 43.6% and 37.1%, respectively. Conclusion: Catalonian dentists have a much lower prevalence of tobacco use than the general population and lower even than other healthcare professionals. Given that non-smoking healthcare professionals have better awareness for providing recommendations for smoking prevention and cessation, Catalonian dentists may be a valid group for performing this task for which there is scientific evidence.

Singling out individual inventors from patent data

An increasing number of studies in recent years have sought to identify individual inventors from patent data. A variety of heuristics have been proposed for using the names and other information disclosed in patent documents to establish who is who in patents. This paper contributes to this literature by describing a methodology for identifying inventors using patents applied to the European Patent Office, EPO hereafter. As in much of this literature, we basically follow a threestep procedure : 1- the parsing stage, aimed at reducing the noise in the inventor’s name and other fields of the patent; 2- the matching stage, where name matching algorithms are used to group similar names; and 3- the filtering stage, where additional information and various scoring schemes are used to filter out these similarlynamed inventors. The paper presents the results obtained by using the algorithms with the set of European inventors applying to the EPO over a long period of time.

Overeducation, skills and wage penalty: Evidence for Spain using PIAAC data

The literature on educational mismatches finds that overeducated workers suffer a wage penalty compared with properly educated workers with the same level of education. Recent literature also suggests that individuals’ skill heterogeneity could explain wage differences between overeducated and properly matched workers. The hypothesis is that overeducated workers earn less due to their lower competences and skills in relative terms. However, that hypothesis has been rarely tested due to data limitations on individuals’ skills. The aim of this paper is to test the individuals’ skill heterogeneity theory in Spain using microdata from PIAAC, because it is one of the developed countries supporting the highest overeducation rates and where its adult population holds the lowest level of skills among a set of developed countries. Our hypothesis is that the wage penalty of overeducation in Spain is explained by the lower skill level of overeducated workers. The obtained evidence confirms this hypothesis but only to a certain extent as skills only explain partially the wage penalty of overeducation.

The regional distribution of unemployment. What do micro-data tell us?

Regional disparities in unemployment rates are large and persistent. The literature provides evidence of their magnitude and evolution, as well as evidence of the role of certain economic, demographic and environmental factors in explaining the gap between regions of low and high unemployment. Most of these studies, however, adopt an aggregate approach and so do not account for the individual characteristics of the unemployed and employed in each region. This paper, by drawing on micro-data from the Spanish wave of the Labour Force Survey, seeks to remedy this shortcoming by analysing regional differentials in unemployment rates. An appropriate decomposition of the regional gap in the average probability of being unemployed enables us to distinguish between the contribution of differences in the regional distribution of individual characteristics from that attributable to a different impact of these characteristics on the probability of unemployment. Our results suggest that the well-documented disparities in regional unemployment are not just the result of regional heterogeneity in the distribution of individual characteristics. Non-negligible differences in the probability of unemployment remain after controlling for this type of heterogeneity, as a result of differences across regions in the impact of the observed characteristics. Among the factors considered in our analysis, regional differences in the endowment and impact of an individual’s education are shown to play a major role.

jxSensor: a sensor network integration layer for JXTA

Nowadays, Wireless Sensor Networks (WSN) arealready a very important data source to obtain data about the environment. Thus, they are key to the creation of Cyber-Physical Systems (CPS). Given the popularity of P2P middlewares as ameans to efficiently process information and distribute services, being able to integrate them to WSN¿s is an interesting proposal. JXTA is a widely used P2P middleware that allows peers to easily exchange information, heavily relying on its main architectural highlight, the capability to organize peers with common interests into peer groups. However, right now, approaches to integrate WSNs to a JXTA network seldom take advantage of peer groups. For this reason, in this paper we present jxSensor, an integrationlayer for sensor motes which facilitates the deployment of CPS¿s under this architecture. This integration has been done taking into account JXTA¿s idiosyncrasies and proposing novel ideas,such as the Virtual Peer, a group of sensors that acts as a single entity within the peer group context.

General Equilibrium Long-Run Determinants for Spanish FDI: A Spatial Panel Data Approach

While general equilibrium theories of trade stress the role of third-country effects, little work has been done in the empirical foreign direct investment (FDI) literature to test such spatial linkages. This paper aims to provide further insights into long-run determinants of Spanish FDI by considering not only bilateral but also spatially weighted third-country determinants. The few studies carried out so far have focused on FDI flows in a limited number of countries. However, Spanish FDI outflows have risen dramatically since 1995 and today account for a substantial part of global FDI. Therefore, we estimate recently developed Spatial Panel Data models by Maximum Likelihood (ML) procedures for Spanish outflows (1993-2004) to top-50 host countries. After controlling for unobservable effects, we find that spatial interdependence matters and provide evidence consistent with New Economic Geography (NEG) theories of agglomeration, mainly due to complex (vertical) FDI motivations. Spatial Error Models estimations also provide illuminating results regarding the transmission mechanism of shocks.