Explicative Variables Research Articles

VAIC as a Tool for Measuring Intangibles Value in Voluntary Multi-Stakeholder Disclosure

The aim of this paper is to investigate the effects of value added intellectual coefficient (VAIC) on the voluntary disclosure of a sample of listed companies in the years 2006, 2009, and 2012, according to a multi-stakeholder approach. This research has been organized in two parts. Firstly, the paper discusses the literature on voluntary disclosure in a multi-stakeholder approach. From this point of view, the paper contributes to the previous literature, which mainly relates the voluntary disclosure to individual and distinct stakeholder classes. Among the literature review, the paper also focuses on the themes of intellectual capital and its measurement. In the second part of the paper, we propose an empirical investigation of a sample of 143 companies, listed on Milan Stock Exchange in the years 2006, 2009, and 2012, in order to identify—through a statistical model—the variables that affect voluntary disclosure. Among the explicative variables (firm size, company’s age, recorded intangible assets, VAIC and Tobin Q), the model also includes VAIC to test the relationship between this indicator and the voluntary disclosure. Our results show that the disclosure index is positively influenced by the size of the company and the financial structure as well as the market value of intangible assets. The relationship between voluntary disclosure and VAIC is instead negative.

A Methodology for Automatised Outlier Detection in High-Dimensional Datasets: An Application to Euro Area Banks’ Supervisory Data

Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our method aims to utilise the entire relevant information present in a dataset to detect outliers in an automatized way, a feature that renders the method suitable for application in large dimensional datasets. Our proposed five-step procedure for regression outlier detection entails a robust selection stage of the most explicative variables, the estimation of a robust regression model based on the selected variables, and a criterion to identify outliers based on robust measures of the residuals' dispersion. The proposed procedure deals also with data redundancy and missing observations which may inhibit the statistical processing of the data due to the ill-conditioning of the covariance matrix. The method is validated in a simulation study and an application to actual supervisory data on banks’ total assets.

New Factors Predicting Delayed Graft Function: a Multi-Center Cohort Study of Kidney Donation After Brain Death Followed by Circulatory Death

Background/Aims: Delayed graft function (DGF) is a common complication following kidney transplantation adversely affecting graft outcomes. Donation after brain death followed by circulatory death (DBCD), a novel donation pattern, is expected to correlate with high incidence of DGF. However, little information is available about factors associated with DGF in DBCD. Methods: A total of 383 kidney transplants from DBCD donation in three institutions were enrolled. Associations of DGF with the clinical characteristics of recipients and donors were quantified. Results: In this retrospective multi-center study, the incidence of DGF was 19.3%. Lower incidence of DGF was found in recipients for whom antithymocyte globulin was used for induction (p < 0.05), which was an independent protective factor against DGF (odds ratio [OR] = 0.48; 95% CI 0.27-0.86). Two novel explicative variables were recognized as independent risk factors, including use of vasoactive drugs (OR = 3.15; 95% CI 1.39-7.14) and cardiopulmonary resuscitation (OR = 2.51; 95% CI 1.05-6.00), which contributed significantly to increased risk of DGF (p < 0.05). Prolonged warm ischemia time (> 18 min; OR = 2.42; 95% CI 1.36-4.32), was also predictive of DGF in DBCD. A prediction model was developed and achieved an area under the curve of 0.89 in predicting DGF when combined with reported parameters. Conclusion: The novel factors, confirmed for the first time in our study, will help to improve risk prediction of DGF and to determine optimal interventions to prevent DGF in clinical practice.

Efficiency Change, Technological Progress and Sources of Long Term Agricultural Productivity Growth in Selected MENA Countries

We investigate the factors that affect total factor productivity growth in MENA countries. To this end, we start first by examining levels and trends in agricultural outputs and productivity growth using Torqnovist Indexes and then computing Malmquist Indexes for three MENA countries representing three different agro-ecological areas; irrigated (Egypt), rainfed (Tunisia) and rangeland (Jordan) over the period 1961-2012. We make use of data drawn from the Food and Agriculture Organization (FAO) dataset. The advantage of this decomposition is that allows decomposing TFP into its two components, namely technical efficiency (TEF) and technological change (TECH). The analysis was complemented by econometric regression of the obtained TECH, considered as the most important long-run driver of TFP growth, scores on a set of potential explicative variables. Turning to the determinants of the components of TECH, the paper findings showed that TFP can be increased due to the increasing in human capital, share of the main crop harvested in each country, and resource reallocation-agricultural employment share. The main implication policy of this research is that growth and determinants of TFP are essential for assessing the country past and potential economic performance, and the gains in TFP drive gains in income and growth.

ADOÇÃO DA VARIEDADE DE MILHO MATUBA PELOS PEQUENOS PRODUTORES DO DISTRITO DE SUSSUNDENGA, MOÇAMBIQUE

O estudo analisou a adoção da variedade melhorada de milho Matuba pelos pequenos produtores agrários do distrito de Sussundenga. Os dados foram coletados através da administração de entrevistas semiestruturadas a 160 pequenos produtores no mês de julho de 2014. O modelo de regressão Logit foi usado para determinar as variáveis com efeito significativo na adoção da variedade Matuba. Um conjunto de variáveis socioeconômicas e institucionais foi usado para compor as variáveis explicativas no modelo em referência. Os resultados mostram que apenas cerca de 40% dos produtores adotaram o milho Matuba. As variáveis estatisticamente significativas na adoção de milho Matuba foram o nível escolar, o sexo do chefe do agregado familiar e a prática de outras atividades diferentes da agricultura. Por outro lado, o acesso aos serviços de extensão agrária, o acesso ao crédito agrário, a idade do chefe do agregado familiar, o tamanho do agregado familiar e a pertença a uma associação ou grupo de produtores não foram significativos na adoção de Matuba.

Per- and poly-fluoroalkyl compounds in freshwater fish from the Rhône River: Influence of fish size, diet, prey contamination and biotransformation

Pools of aquatic plants and benthic invertebrates were collected along with 47 individuals from three cyprinid fish species (Barbus barbus, Gobio gobio, Rutilus rutilus) at a site in the Rhône River (France). Carbon and nitrogen isotopic ratios (δ13C and δ15N) and a wide range of per- and poly-fluorinated chemicals (PFASs) were analysed in all samples. The sum of PFAS concentrations (ΣPFAS) increased from aquatic plants to fish dorsal muscles; molecular profiles were dominated by C9–C13 perfluorocarboxylic acids (PFCAs), while perfluorooctane sulfonate (PFOS) and perfluorooctane sulfonamide (FOSA) were detected in all samples at lower concentrations. ΣPFAS and especially ΣPFCAs were higher in barbels (B. barbus) than in other species, while roaches (R. rutilus) were less contaminated by PFOS than barbels and gudgeons (G. gobio). Gudgeons accumulated significantly higher FOSA concentrations. Young (small) barbels displayed significantly higher PFOS, perfluorononanoic acid (PFNA) and perfluorodecanoic acid (PFDA) concentrations than did large specimens; conversely, perfluorotetradecanoic acid (PFTeDA) concentrations were significantly higher in large barbels. Multiple linear regressions were performed on the whole set of fish samples with size, mass and isotopic ratios as explicative variables, and several single compounds as explained variables. Regardless of the compound, the regressions did not explain much of the contamination variability. However, adding species as a qualitative variable, i.e. performing analyses of covariance (ANCOVAs) improved the fit greatly, while adding sex did not. Diet (i.e. δ13C and δ15N) was the main factor explaining interspecific differences. Biotransformation was assessed by comparing concentration ratios of PFOS or FOSA to their precursors in the food-web compartments. These ratios increased from invertebrates to fish, and differed among fish species, suggesting that biotransformation occurred but was species-specific. Biomagnification factor calculations showed that C11–C13 PFCAs, PFOS and FOSA were apparently biomagnified in barbels and gudgeons.

Determinants of Bank Performance in a Developing Country: Evidence From Morocco

This paper aims to define long-term determinants of Moroccan commercial banks performance, for the period 2005-2015, using the Johansen cointegration test. For this purpose, we use bank performance ratios (ROA, ROE and NIM) as dependent variables, and deposits, liquidity ratios, bank-specific and macroeconomic variables as explicative variables. Results obtained show that long-term performance of Moroccan commercial banks depends on deposits, short-term, long-term and funding liquidity, the size of the bank and its square, internal and external funding, deposits interest rates and foreign direct investments. These results show the significance of bank-specific variables as long-term determinants of the performance of Moroccan commercial banks.&#x0D;

E-waste collection in Italy: Results from an exploratory analysis

This study looks at the performance of household electrical and electronic waste (WEEE) collection in 20 Italian regions from 2008 to 2015. The impact of several explicative variables on the results of e-waste collection is evaluated. The independent variables are socio-economic and demographic ones (age, gender, household size, education level, migration and income) along with technical-organisational variables (population density, presence of metropoles, macro regions, characteristics of the territory, percentage of household waste collected separately and number of e-waste collection points). The results show that the presence of collection points, the percentage of household waste collected separately and the percentage of females are positively correlated with the kg collected per inhabitant per year. For example, a variation of 1% of input (presence of collection points) corresponds to a 0.25% variation in the output (collection results) while 1% difference in the percentage of females in the population corresponds to a 7.549% difference in the collection rate. Population density, instead, is negatively correlated. It is interesting to note that there is a discrepancy between the Southern regions and the Centre regions (the former have an outcome 0.66 times lower than the latter) while the Northern regions perform similarly to the Centre ones. Moreover, the first year (2008) had a very low performance compared to the following years when the scheme constantly improved, mainly due to the additional collection points available. The Stochastic Frontier Model allows for the identification of the optimal production function among the 20 Italian regions. The best performing region is Tuscany (in the Centre), followed by Sardinia and Sicily (in the South).

Modelling the spatial distribution of snake species in northwestern Tunisia using maximum entropy (Maxent) and Geographic Information System (GIS)

We used GIS and maximum entropy to predict the potential distribution of six snake species belong to three families in Kroumiria (Northwestern Tunisia): Natricidae (Natrix maura and Natrix astreptophora), Colubridae (Hemorrhois hippocrepis, Coronella girondica and Macroprotodon mauritanicus), and Lamprophiidae (Malpolon insignitus). The suitable habitat for each species was modelled using the maximum entropy algorithm, combining presence field data (collected during 16 years: 2000–2015) with a set of seven environmental variables (mean annual precipitation, elevation, slope gradient, aspect, distance to watercourses, land surface temperature and normalized Differential Vegetation Index. The relative importance of these environmental variables was evaluated by jackknife tests and the predictive power of our models was assessed using the area under the receiver operating characteristic. The main explicative variables of the species distribution were distance from streams and elevation, with contributions ranging from 60 to 77 and from 10 to 25%, respectively. Our study provided the first habitat suitability models for snakes in Kroumiria and this information can be used by conservation biologists and land managers concerned with preserving snakes in Kroumiria.

The dynamic behaviour of metabolic syndrome and its components in an eight-year population-based cohort from the Mediterranean.

BackgroundThe significant rise in the prevalence of obesity coincides with the considerable increase in the prevalence of metabolic syndrome (MS) currently being observed worldwide. The components of MS are not static and their dynamics, such as the order of their occurrence, or the time of exposure to them are, as yet, unknown but could well be clinically relevant. Our objective was to study the dynamic behaviour of MS and its components in a large population-based cohort from a Mediterranean region.Methods and findingsOur study employed a retrospective cohort (between January 1, 2005 and December 31, 2012) made up of individuals from the general population in a region in the northeast of Catalonia, Spain. Given that most of the explicative variables of the risk of having MS were time dependent and, therefore, the risk was not proportional, we used the Andersen-Gill (AG) model to perform a multivariate survival analysis and inferences were performed using a Bayesian framework.Thirty-nine percent of the participants developed MS; 44.6% of them with a single limited episode. Triglycerides and low HDL cholesterol, together with obesity, are components associated with the first occurrence of MS. Components related to the metabolism of glucose are associated with a medium risk of having a first episode of MS, and those related to blood pressure are associated with a lower risk. When the components related to blood pressure and the metabolism of glucose appear first, they determine the appearance of the first episode of MS. The variables concerning the persistence of MS are those that correspond to clinical conditions that do not have well-established drug treatment criteria.ConclusionsOur results suggest that the components related to the metabolism of glucose and to high blood pressure appear early on and act as biomarkers for predicting MS, while the components related to obesity and dyslipidaemia, although essential for the development of MS, appear later. Making lifestyle changes reduces the conditions associated with the persistence of MS.

Analyse Economique De La Restauration Des Aires Protegees En Côte D’ivoire : Cas Du Parc National De Taï

This paper analyses the optimal conditions of the imperative restoration of the National Park of Tai. Particularly, it aims to study, using the contingent valuation method, the feasibility of a voluntary retrocession of agricultural parcels located in the vicinity of this park. Thus a simple censored tobit model is used to identify the determinants of willingness to accept of smallholders. Data collection was conducted among 508 households settled in the neighboring localities of this park. Statistical analysis of survey data reveals initially the unpopularity and difficulties of implementing such a measure given the low commitment of smallholders to the proposed policy. Secondly, econometric analysis identifies the instruction attainment, part-time practice of farming, membership in some support group, previous farming experience, the extend of ceded parcel, farm-home distance and environmental sensitivity of the individual like the main explicative variables of the willingness to accept of smallholders.

How to Restore Forest Areas in a Smallholder Agriculture-Dominated Country?

This study deals with ways of addressing more effectively the problems of forest restoration in a smallholder agriculture-dominated area like the southwest Côte d’Ivoire. An empirical estimation based on a probit model is used to analyze the farmer decisions concerning their eventual participation to the national program of forest development based on a policy of large-scale reforestation.The results show that the main explicative variables of smallholders’ adhesion to this project are agricultural training, ethnic group, access to credit, the age of the head of household and the household’s residence area. Contrary to all expectations, some variables such as literacy, out-farm income, and the status of landowner and whole-time farmer do not explain the decision of smallholder.

Does risk culture affect banks’ volatility? The case of the G-SIBs

The recent financial crisis highlights the weaknesses of the traditional measures of risk in the banking sector, as Banking Authorities have missed considering the behavioural aspect of the risk culture, which is an essential tool for the value creation process of risk management (Financial Stability Board, 2014; Carretta et al., 2015; Schwizer, 2013; Guiso, Sapienza and Zingales, 2015), usually measured using the survey method. Our paper addresses a central question: What is an alternative measure of risk that estimates the banking risk-taking behaviour, also considering their risk culture? By analysing a panel of the thirty Global Systematically Important Banks (G-SIBs) from 2006 and 2013, our paper provides empirical evidence that the presence of a Risk Committee, the size of the Risk Committee and the number of the Risk Committee’s meetings have a positive impact on a bank’s volatility. Using multiple regression analysis on panel data, we verify the relationship between the bank asset risk and explicative variables that measure risk governance, banks’ size and traditional banks’ risk indicators. Our study extends the literature by providing evidence that separates RCs as having a significant impact on reducing firms’ volatility and as being an important risk governance tool in the hands of boards. Moreover, given the recent emphasis of regulatory bodies on strengthening the risk management and risk reporting systems of financial firms and the overwhelming trend of firms to form a separate RC, our study responds to the opportunity to investigate this relationship.

A methodology for stochastic inventory modelling with ARMA triangular distribution for new products

This paper proposes a stochastic inventory policy of continuous review with random demand described with temporal dependence through an autoregressive moving average (ARMA) model with explicative variables, of usefulness in new products without a history of demand data, assuming a triangular distribution. Optimization of the cost function related to the inventory model is obtained considering the expected value and variance marginal stationary of the demand per unit time and stochastic programming. The proposed policy is exemplified with real-world demand data from a Chilean hospital, where the demand of products (drugs) are correlated with other products and autocorrelated. The proposed methodology shows a useful tool for administrators who must decide optimal batch sizes and their reorder points when there is a low availability of demand data and is known to have a temporal structure.

French bank mergers and acquisitions performance

In this paper, we empirically investigate the impact of mergers and acquisitions on French bank performance. Performance is measured by potential gains in efficiency and value creation. We first analyzed efficiency using the data envelopment analysis (DEA) under input oriented with variable returns to scale to obtain the efficiency scores. Second, we analyzed the impact on French bank value creation following mergers-acquisitions operations of a set of control variables (model 1) and explicative variables measuring strategic similarities between bidders and targets (model 2). The sample studied is composed of French bank mergers-acquisitions happening between 1996 and 2006 and implying one of the 14 greatest French banking groups. Empirical result showed that mergers and acquisitions have been traduced by an improvement in the overall efficiency by 17.82% and a shareholder value reduction by 5.14%.

Corrigendum

Journal of EcologyVolume 105, Issue 2 p. 559-560 CorrigendumFree Access Corrigendum This article corrects the following: Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar Ghislain Vieilledent, Oliver Gardi, Clovis Grinand, Christian Burren, Mamitiana Andriamanjato, Christian Camara, Charlie J. Gardner, Leah Glass, Andriambolantsoa Rasolohery, Harifidy Rakoto Ratsimba, Valéry Gond, Jean-Roger Rakotoarijaona, Emily Lines, Volume 104Issue 3Journal of Ecology pages: 703-715 First Published online: February 25, 2016 First published: 24 October 2016 https://doi.org/10.1111/1365-2745.12679Citations: 1AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Vieilledent, G., Gardi, O., Grinand, C., Burren, C., Andriamanjato, M., Camara, C., Gardner, C.J., Glass, L., Rasolohery, A., Ratsimba, H.R., Gond, V. & Rakotoarijaona, J.R. (2016) Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar. Journal of Ecology, 104, 703–715. doi:10.1111/1365-2745.12548. In the paper by Vieilledent et al. (2016), the authors inadvertently inverted the captions of Figs 2 and 3. The authors and journal would like to correct this error. The results and conclusions of the article are not affected. The figures with their correct captions are below. Figure 2Open in figure viewerPowerPoint Forest carbon map in 2010 for Madagascar. We derived a national forest carbon map in 2010 for Madagascar at 250-m resolution. We fitted our model using above-ground carbon density for 1771 forest plots measured between 1996 and 2013. Our model included six explicative variables: two vegetation indexes (VCF and EVI from 2000 to 2010 MODIS satellite images at 250 m), one topographic variable (elevation from SRTM at 90 m) and three climatic variables [mean annual temperature, mean annual precipitation and temperature seasonality from WorldClim at 30 arc-seconds (~1 km)]. Our predictions are limited to the extent of the forest in 2010. Clear differences appear for the forest carbon stocks between the three ecoregions including moist, dry and spiny forest (see black lines for delimitations). Figure 3Open in figure viewerPowerPoint Relationships between explicative variables and ACD. Graphics show the marginal effect of the variable on ACD. Range of predicted ACD is reduced compared to the observed range of ACD in forest plots because variables other than the target variable are set to their mean values. Hash marks at the bottom of the plot indicate the deciles of the explicative variable. Percentage in the top-left or top-right corner of each panel is the percentage of increase in mean square error when the variable was randomly permuted, which indicates the variable relative importance in determining ACD. Reference Vieilledent, G., Gardi, O., Grinand, C., Burren, C., Andriamanjato, M., Camara, C., Gardner, C.J., Glass, L., Rasolohery, A., Ratsimba, H.R., Gond, V. & Rakotoarijaona, J.R. (2016) Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar. Journal of Ecology, 104, 703– 715. doi:10.1111/1365-2745.12548 Citing Literature Volume105, Issue2March 2017Pages 559-560 FiguresReferencesRelatedInformation

Internal migration in Italy. Long-run analysis of push and pull factors across regions and macro-areas of the country.

The great majority of empirical studies on internal migration across Italian regions either ignores the long-run perspective of the phenomenon or do not consider push and pull factors separately. In addition, Centre-North to South flows, intra-South and intra-Centre-North migration have not been studied. We aim to fill this gap and tackle interregional migration flows from different geographical perspectives. We apply four panel data estimators with different statistical assumptions and show that long-run migration flows from the Mezzogiorno towards Centre-Northern regions are well explained by a gravity model in which per capita GDP, unemployment and population play a major role. On the contrary, migration flows from Centre-North to South has probably much to do with other social and demographic factors. Finally, intra Centre-North and intra South migration flows roughly obey to the gravity model, though not all explicative variables are relevant.

Informal employment, unpaid care work, and health status in Spanish-speaking Central American countries: a gender-based approach.

To assess the relationship between paid work, family characteristics and health status in Central American workers; and to examine whether patterns of association differ by gender and informal or formal employment. Cross-sectional study of 8680 non-agricultural workers, based on the First Central American Survey of Working Conditions and Health (2011). Main explicative variables were paid working hours, marital status, caring for children, and caring for people with functional diversity or ill. Using Poisson regression models, adjusted prevalence ratios of poor self-perceived and mental health were calculated by sex and social security coverage (proxy of informal employment). A clear pattern of association was observed for women in informal employment who were previously married, had care responsibilities, long working hours, or part-time work for both self-perceived and mental health. No other patterns were found. Our results show health inequalities related to unpaid care work and paid work that depend on the interaction between gender and informal employment. To reduce these inequalities suitable policies should consider both the labor (increasing social security coverage) and domestic spheres (co-responsibility of care).

The Demand for Football in Portugal

The aim of this study is to identify variables that influence the stadium attendance in Portugal, and how these variables may affect decision management. Deriving a demand curve for stadium attendance in the Portuguese First Division Football League for 898 matches of five seasons (2010/2011-2014/2015), the results highlight five main explicative variables: cost, habit persistence, expected quality, team performance, and outcome uncertainty. With regard to outcome uncertainty, we employ the framework proposed by Humphreys and Zhou and we conclude for the importance of alternative factors affecting consumer choice like loss aversion and home win preference.

Central Body Fat Mass Measured by Bioelectrical Impedanciometry But Not Body Mass Index Is a High-Grade Prostate Cancer Risk Factor

Objective: To evaluate the association between body fat mass distribution measured by bioelectrical impedanciometry (BEI) and high-grade prostate cancer (HGPC). Methods: We prospectively analyze 323 patients who underwent prostate biopsy. BEI was performed prior to biopsy. Prostate cancer (PC) was stratified according to D'Amico classification. For univariate analysis, Student t test was done. For multivariate analysis, bivariate logistic regression was performed using PSA, body mass index (BMI), percentage central body fat, percentage total body fat, and visceral fat as explicative variables for the diagnosis of HGPC. Results: PC was found in 134 patients. Thirty seven (27.2%) were HGPC. This group had higher age, PSA, and percentage central body fat (p = 0.001, p = 0.001, p = 0.04). BMI showed no association with HRPC. Age, PSA, and percentage central body fat (OR 1,123, 95% CI 1,022-1,233, p = 0.001) were independent risk factors. Conclusions: Central body fat measured by BEI could explain the association between obesity and HGPC better than BMI suggesting the use of this technique to study body fat distribution.