A Note on Missing Data Effects on the Hausman (1978) Simultaneity Test: Some Monte Carlo Results.

This short paper demonstrates the effects of using missing data on the power of the well-known Hausman (1978) test for simultaneity in structural econometric models. This test is a reliable test and is widely used for testing simultaneity in linear and nonlinear structural models. Using Monte Carlo techniques, we find that the existence of missing data could affect seriously the power of the test. As their number is getting larger, the probability of rejecting simultaneity with Hausman test is increasing significantly especially in small samples. A Full Information Maximum Likelihood Missing Data correction technique is used to overcome the problem and then we find out that that the test is more effective when we retrieve these data and include them in the sample.Hausman (1978) simultaneity test, structural econometric models, FIML, missing data, simulation

Inter-gender interaction and communication in ultimatum games

In this paper, we focus on bargaining within male–female pairs, the most pervasive partnership in humankind. We analyze data from an ultimatum game played by Greek subjects. Parallel to this, we introduce a one-way communication protocol according to which the responders can send short messages to the receivers, after making their decisions. The analysis shows that gender and message effects exist and that males are more effective bargainers

Evaluating Google Trends as a Tool for Integrating the ‘Smart Health’ Concept in the Smart Cities’ Governance in USA

AbstractThe aim of this paper is to introduce the methodology of using online search traffic data in order to integrate the public's online behavior in Smart Health; a concept that is currently rising concerning the health factor of Smart Cities. We use normalized data from Google Trends from January 2013 to December 2015 in the US, aiming at exploring the change in interest in various medical terms, and examine if Google Trends is a possible tool for evaluating health search queries by nowcasting the public's online interest. The results show that Google Trends’ data can be used for measuring the public's interest in health related terms, in order to assist with the evaluation of ‘Smart Health’

Predictability analysis of the Pound's Brexit exchange rates based on Google Trends data

During the last decade, the use of online search traffic data is becoming popular in examining, analyzing, and predicting human behavior, with Google Trends being a popular tool in monitoring and analyzing the users' online search patterns in several research areas, like health, medicine, politics, economics, and finance. Towards the direction of exploring the Sterling Pound’s predictability, we employ Google Trends data from the last 5 years (March 1st, 2015 to February 29th, 2020) and perform predictability analysis on the Pound’s exchange rates to Euro and Dollar. The period selected includes the 2016 UK referendum as well as the actual Brexit day (January 31st, 2020), with the analysis aiming at analyzing the Pound’s relationships with Google query data on Pound-related keywords and topics. A quantile dependence method is employed, i.e., cross-quantilograms, to test for directional predictability from Google Trends data to the Pound’s exchange rates for lags from zero to 30 (in weeks). The results indicate that statistically significant quantile dependencies exist between Google query data and the Pound’s exchange rates, which point to the direction of one of the main implications in this field, that is to examine whether the movements in one economic variable can cause reactions in other economic variables

Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era

Background: With the internet’s penetration and use constantly expanding, this vast amount of information can be employed in order to better assess issues in the US health care system. Google Trends, a popular tool in big data analytics, has been widely used in the past to examine interest in various medical and health-related topics and has shown great potential in forecastings, predictions, and nowcastings. As empirical relationships between online queries and human behavior have been shown to exist, a new opportunity to explore the behavior toward asthma—a common respiratory disease—is present. Objective: This study aimed at forecasting the online behavior toward asthma and examined the correlations between queries and reported cases in order to explore the possibility of nowcasting asthma prevalence in the United States using online search traffic data. Methods: Applying Holt-Winters exponential smoothing to Google Trends time series from 2004 to 2015 for the term “asthma,” forecasts for online queries at state and national levels are estimated from 2016 to 2020 and validated against available Google query data from January 2016 to June 2017. Correlations among yearly Google queries and between Google queries and reported asthma cases are examined. Results: Our analysis shows that search queries exhibit seasonality within each year and the relationships between each 2 years’ queries are statistically significant (P < .05). Estimated forecasting models for a 5-year period (2016 through 2020) for Google queries are robust and validated against available data from January 2016 to June 2017. Significant correlations were found between (1) online queries and National Health Interview Survey lifetime asthma (r=–.82, P=.001) and current asthma (r=–.77, P=.004) rates from 2004 to 2015 and (2) between online queries and Behavioral Risk Factor Surveillance System lifetime (r=–.78, P=.003) and current asthma (r=–.79, P=.002) rates from 2004 to 2014. The correlations are negative, but lag analysis to identify the period of response cannot be employed until short-interval data on asthma prevalence are made available. Conclusions: Online behavior toward asthma can be accurately predicted, and significant correlations between online queries and reported cases exist. This method of forecasting Google queries can be used by health care officials to nowcast asthma prevalence by city, state, or nationally, subject to future availability of daily, weekly, or monthly data on reported cases. This method could therefore be used for improved monitoring and assessment of the needs surrounding the current population of patients with asthma

The “discard problem” in Mediterranean fisheries, in the face of the European Union landing obligation: the case of bottom trawl fishery and implications for management

Since the first introduction of the landing obligation (a.k.a. Discard ban) in 2015, the EU Mediterranean fisheries are facing some unforeseen challenges. The demersal bottom trawl fisheries, being the most significant contributors to the so-called 'discard problem', are confronted with the greatest challenges. Data from the Italian and the Greek fleet, spanning over two decades (1995–2015), were analysed with the intention of revealing the diversity and heterogeneity of the discard problem, especially for regulated species. Species composition of discards, as well as discarding rates, were shown to be irregular, fluctuating among areas, depth strata, seasons and years. Although fish dominated the discarded gross catch in weight, benthic invertebrates (other than commercial cephalopods and crustaceans) were the taxa discarded almost exclusively. The established minimum conservation reference size was largely ignored by fishers. From a management point of view, the present investigation suggests that the recently established Discard Management Plans lack scientific evidence (given the high intrinsic variability of the parameters and confusion regarding the rules) and provide exemptions from the landing obligation that will in practice allow the average Mediterranean bottom trawl vessel to continue business as usual. Moreover, detecting if these rules are actually respected is an almost impossible task for the Mediterranean control and enforcement authorities. Incentivizing the adoption of fishing technologies and practices that reduce pre-harvest mortality and post-harvest discards, while avoiding damage to sensitive marine species and habitats, seems the only way to move forward, rather than dealing with the problem after it has occurred

Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review

Background: In the era of information overload, are big data analytics the answer to access and better manage available knowledge? Over the last decade, the use of Web-based data in public health issues, that is, infodemiology, has been proven useful in assessing various aspects of human behavior. Google Trends is the most popular tool to gather such information, and it has been used in several topics up to this point, with health and medicine being the most focused subject. Web-based behavior is monitored and analyzed in order to examine actual human behavior so as to predict, better assess, and even prevent health-related issues that constantly arise in everyday life. Objective: This systematic review aimed at reporting and further presenting and analyzing the methods, tools, and statistical approaches for Google Trends (infodemiology) studies in health-related topics from 2006 to 2016 to provide an overview of the usefulness of said tool and be a point of reference for future research on the subject. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for selecting studies, we searched for the term “Google Trends” in the Scopus and PubMed databases from 2006 to 2016, applying specific criteria for types of publications and topics. A total of 109 published papers were extracted, excluding duplicates and those that did not fall inside the topics of health and medicine or the selected article types. We then further categorized the published papers according to their methodological approach, namely, visualization, seasonality, correlations, forecasting, and modeling. Results: All the examined papers comprised, by definition, time series analysis, and all but two included data visualization. A total of 23.1% (24/104) studies used Google Trends data for examining seasonality, while 39.4% (41/104) and 32.7% (34/104) of the studies used correlations and modeling, respectively. Only 8.7% (9/104) of the studies used Google Trends data for predictions and forecasting in health-related topics; therefore, it is evident that a gap exists in forecasting using Google Trends data. Conclusions: The monitoring of online queries can provide insight into human behavior, as this field is significantly and continuously growing and will be proven more than valuable in the future for assessing behavioral changes and providing ground for research using data that could not have been accessed otherwise

a4a short research project: Stock assessment of Hellenic Small Pelagic Stocks

With the objective of applying the a4a methods to real life situations the JRC held a Workshop on stock assessment for the Hellenic small pelagic stocks in the Aegean Sea (JRC, Italy) between the 4th and 7th of May 2015. The main objectives were to compare assessment models and incorporate environmental indices into stock forecasts.JRC.G.3-Maritime affair

Flow Cytometry as a Diagnostic Tool in the Early Diagnosis of Aggressive Lymphomas Mimicking Life-Threatening Infection

Aggressive lymphomas can present with symptoms mimicking life-threatening infection. Flow cytometry (FC) is usually recommended for the classification and staging of lymphomas in patients with organomegaly and atypical cells in effusions and blood, after the exclusion of other possible diagnoses. FC may also have a place in the initial diagnostic investigation of aggressive lymphoma. Three cases are presented here of highly aggressive lymphomas in young adults, which presented with the clinical picture of fever of unknown origin (FUO) in patients severely ill. All followed a life-threatening clinical course, and two developed the hemophagocytic syndrome (HPS), but microbiological, immunological, and morphological evaluation and immunohistochemistry (IHC) failed to substantiate an early diagnosis. FC was the technique that provided conclusive diagnostic evidence of lymphoma, subsequently verified by IHC. Our experience with these three cases highlights the potential role of FC as an adjunct methodology in the initial assessment of possible highly aggressive lymphoma presenting with the signs and symptoms of life-threatening infection, although the definitive diagnosis should be established by biopsy. In such cases, FC can contribute to the diagnosis of lymphoma, independently of the presence of HPS

Strong fisheries management and governance positively impact ecosystem status

Fisheries have had major negative impacts on marine ecosystems, and effective fisheries management and governance are needed to achieve sustainable fisheries, biodiversity conservation goals and thus good ecosystem status. To date, the IndiSeas programme (Indicators for the Seas) has focussed on assessing the ecological impacts of fishing at the ecosystem scale using ecological indicators. Here, we explore fisheries Management Effectiveness' and Governance Quality' and relate this to ecosystem health and status. We developed a dedicated expert survey, focused at the ecosystem level, with a series of questions addressing aspects of management and governance, from an ecosystem-based perspective, using objective and evidence-based criteria. The survey was completed by ecosystem experts (managers and scientists) and results analysed using ranking and multivariate methods. Results were further examined for selected ecosystems, using expert knowledge, to explore the overall findings in greater depth. Higher scores for Management Effectiveness' and Governance Quality' were significantly and positively related to ecosystems with better ecological status. Key factors that point to success in delivering fisheries and conservation objectives were as follows: the use of reference points for management, frequent review of stock assessments, whether Illegal, Unreported and Unregulated (IUU) catches were being accounted for and addressed, and the inclusion of stakeholders. Additionally, we found that the implementation of a long-term management plan, including economic and social dimensions of fisheries in exploited ecosystems, was a key factor in successful, sustainable fisheries management. Our results support the thesis that good ecosystem-based management and governance, sustainable fisheries and healthy ecosystems go together.IOC-UNESCO; EuroMarine; European FP7 MEECE research project; European Network of Excellence Eur-Oceans; FRB EMIBIOS project [212085]info:eu-repo/semantics/publishedVersio