Are niche-based species distribution models transferable in space?

Aim To assess the geographical transferability of niche-based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice-versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3-0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter-specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land-use history, or to species-specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche-based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche-based models for assessing the fate of species in future environments.

The handaxe and the microscope: individual and social learning in a multidimensional model of adaptation

When individuals learn by trial-and-error, they perform randomly chosen actions and then reinforce those actions that led to a high payoff. However, individuals do not always have to physically perform an action in order to evaluate its consequences. Rather, they may be able to mentally simulate actions and their consequences without actually performing them. Such fictitious learners can select actions with high payoffs without making long chains of trial-and-error learning. Here, we analyze the evolution of an n-dimensional cultural trait (or artifact) by learning, in a payoff landscape with a single optimum. We derive the stochastic learning dynamics of the distance to the optimum in trait space when choice between alternative artifacts follows the standard logit choice rule. We show that for both trial-and-error and fictitious learners, the learning dynamics stabilize at an approximate distance of root n/(2 lambda(e)) away from the optimum, where lambda(e) is an effective learning performance parameter depending on the learning rule under scrutiny. Individual learners are thus unlikely to reach the optimum when traits are complex (n large), and so face a barrier to further improvement of the artifact. We show, however, that this barrier can be significantly reduced in a large population of learners performing payoff-biased social learning, in which case lambda(e) becomes proportional to population size. Overall, our results illustrate the effects of errors in learning, levels of cognition, and population size for the evolution of complex cultural traits. (C) 2013 Elsevier Inc. All rights reserved.

Do political factors matter in explaining under- and overweight outcomes in developing countries?

We construct a rich dataset covering 47 developing countries over the years 1990-2007, combining several micro and macro level data sources to explore the link between political factors and body mass index (BMI). We implement a heteroskedastic generalized ordered logit model allowing for different covariate effects across the BMI distribution and accounting for the unequal BMI dispersion by geographical area. We find that systems with democratic qualities are more likely to reduce under-weight, but increase overweight/obesity, whereas effective political competition does entail double-benefits in the form of reducing both under-weight and obesity. Our results are robust to the introduction of country fixed effects.

EMU sovereign debt market crisis: Fundamentals-based or pure contagion?

We empirically investigate whether the transmission of the recent crisis in euro area sovereign debt markets was due to fundamentals-based or pure contagion. To do so, we examine the behaviour of EMU sovereign bond yield spreads with respect to the German bund for a sample of both central and peripheral countries from January 1999 to December 2012. First we apply a dynamic approach to analyse the evolution of the degree of Grangercausality within the 90 pairs of sovereign bond yield spreads in our sample, in order to detect episodes of significantly increased causality between them (which we associate with contagion) and episodes of significantly reduced interconnection (which we associate with immunisation). We then use an ordered logit model to assess the determinants of the occurrence of the episodes detected. Our results suggest the importance of variables proxying market sentiment and of variables proxying macrofundamentals in determining contagion and immunisation outcomes. Therefore, our findings underline the coexistence of “pure” and “fundamentals-based contagion” during the recent European debt crisis.

EMU sovereign debt market crisis: Fundamentals-based or pure contagion?

We empirically investigate whether the transmission of the recent crisis in euro area sovereign debt markets was due to fundamentals-based or pure contagion. To do so, we examine the behaviour of EMU sovereign bond yield spreads with respect to the German bund for a sample of both central and peripheral countries from January 1999 to December 2012. First we apply a dynamic approach to analyse the evolution of the degree of Grangercausality within the 90 pairs of sovereign bond yield spreads in our sample, in order to detect episodes of significantly increased causality between them (which we associate with contagion) and episodes of significantly reduced interconnection (which we associate with immunisation). We then use an ordered logit model to assess the determinants of the occurrence of the episodes detected. Our results suggest the importance of variables proxying market sentiment and of variables proxying macrofundamentals in determining contagion and immunisation outcomes. Therefore, our findings underline the coexistence of “pure” and “fundamentals-based contagion” during the recent European debt crisis.

Éxito académico, características personales y proceso de Bolonia: Una aproximación econométrica

La universidad española se encuentra en pleno proceso de implementación del espacio europeo de la enseñanza superior (EEES), aspecto que modificará las metodologías docentes que habitualmente se han venido utilizando. Este trabajo tiene como objetivo principal examinar en qué medida las nuevas metodologías docentes pueden influir en las calificaciones obtenidas por los alumnos. Para ello se ha elaborado una encuesta entre los alumnos de la asignatura de Política Económica I de la Universitat de Barcelona, donde podemos distinguir dos grupos de estudiantes: los que han seguido la metodología docente del EEES por un lado, y los que han mantenido la metodología tradicional de evaluación. Este hecho conforma una estructura de experimento natural, en el que existe un grupo afectado por el cambio en la metodología docente, y un grupo de control que no se ve afectado por el cambio. La estimación de un modelo logit ordenado nos permite observar como las nuevas metodologías docentes basadas en la implementación del EEES ayudan a mejorar substancialmente las calificaciones obtenidas por los alumnos. Otras variables que ayudan a obtener mejores calificaciones son las horas de estudio, la asistencia a clase así como los conocimientos previos de los alumnos. En este sentido, una implantación exitosa del EEES exigirá desarrollar las estrategias de motivación pertinentes para que aumente las horas que los alumnos dedican al estudio, aumente el porcentaje de asistencia a las clases magistrales y haya una coordinación adecuada de los diferentes programas de las asignaturas. En definitiva, la implementación del EEES puede ser un buen instrumento para mejorar el rendimiento académico de los estudiantes universitarios españoles siempre que la reforma tenga en cuenta aquellos aspectos que influyen en dicho rendimiento. Esto debe tenerse en cuenta a la hora de valorar una reforma tan compleja que será exigente tanto para alumnos como para profesores.

Bayesian Networks for the Age Classification of Living Individuals: a Study on Transition Analysis

Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.

Determinantes internos y externos en el proceso de aprendizaje. Una aproximación al caso español a partir de la ECV-05

El principal objetivo del trabajo es determinar el grado de influencia de los diferentes factores individuales y del entorno, familiar y social, en la capacidad de los individuos para alcanzar o no ciertos objetivos educativos, teniendo en cuenta los efectos posteriores de aquellos en relación con su inserción en el mercado de trabajo, su nivel salarial y su productividad (Card, 1999). Para ello, se ha aplicado un método de estimación de máxima verosimilitud, mediante la utilización de un logit ordenado, empleando el modulo especial de 2007 de la Encuesta de Condiciones de Vida de EUROSTAT dedicado a la transmisión intergeneracional de la pobreza. Esta base de datos cuenta con valiosa información acerca del individuo y la situación personal y familiar de éste cuando tenía entre 12 y 16 años, resultando representativa para las Comunidades Autónomas españolas y para la población inmigrante. Los resultados obtenidos, que van en la línea de la literatura empírica analizada; indican la relevancia del género, del estado de salud y del lugar de nacimiento, en cuanto a las variables referidas directamente al individuo y, en relación al resto de las variables utilizadas; destaca la importancia de la educación y el tipo de ocupación de los padres, de la estructura familiar y de la situación financiera existente en el momento en que el individuo se estaba educando

Energy efficiency determinants: An empirical analysis of Spanish innovative firms

This paper examines the extent to which innovative Spanish firms pursue improvements in energy efficiency (EE) as an objective of innovation. The increase in energy consumption and its impact on greenhouse gas emissions justifies the greater attention being paid to energy efficiency and especially to industrial EE. The ability of manufacturing companies to innovate and improve their EE has a substantial influence on attaining objectives regarding climate change mitigation. Despite the effort to design more efficient energy policies, the EE determinants in manufacturing firms have been little studied in the empirical literature. From an exhaustive sample of Spanish manufacturing firms and using a logit model, we examine the energy efficiency determinants for those firms that have innovated. To carry out the econometric analysis, we use panel data from the Community Innovation Survey for the period 2008‐2011. Our empirical results underline the role of size among the characteristics of firms that facilitate energy efficiency innovation. Regarding company behaviour, firms that consider the reduction of environmental impacts to be an important objective of innovation and that have introduced organisational innovations are more likely to innovate with the objective of increasing energy efficiency. Keywords: energy efficiency, corporate targets, innovation, Community Innovation Survey. JEL Classification: Q40, Q55, O31

Finanssikriisin 2007-2009 syiden identifiointi yhdysvaltalaisella aineistolla

Tutkimuksen tavoitteena on selvittää, mitkä syyt ovat vaikuttaneet Yhdysvalloissa vuonna 2007 puhjenneeseen finanssikriisiin ja kyetäänkö näistä syistä identifioimaan muuttujia, joilla pystytään ennustamaan kriisin puhkeamisen todennäköisyys. Tutkielman empiirinen osio toteutetaan logistisen regressioanalyysin avulla. Aiempaan kirjallisuuteen perustuen logistiseen regressiomallin otetaan 18 finanssikriisiä selittävää muuttujaa. Selitettävänä muuttujana on yhdysvaltalaisten pankkien tilaa kuvaava muuttuja, joka saadaan jakamalla pankkien järjestämättömät saatavat kokonaislainakannalla. Tutkimus osoitti, että aiempaan kirjallisuuteen ja aiempiin kriisejä ennustaviin malleihin perustuen kyetään logistista regressiomenetelmää käyttäen muodostamaan malli, jonka avulla löytyy tilastollisesti merkitseviä muuttujia ja joilla on vaikutusta kriisin puhkeamisen todennäköisyyteen. Kriisin puhkeamisen todennäköisyyttä lisäävien muuttujien identifiointi on haastavaa vaikka tilastollisesti merkitseviä muuttujia löytyy.

Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

Les déterminants des faillites bancaires dans les pays en développement: le cas des pays de l'Union économique et monétaire Ouest-africaine (UEMOA)

L’objectif de ce papier est de déterminer les facteurs susceptibles d’expliquer les faillites bancaires au sein de l’Union économique et monétaire ouest-africaine (UEMOA) entre 1980 et 1995. Utilisant le modèle logit conditionnel sur des données en panel, nos résultats montrent que les variables qui affectent positivement la probabilité de faire faillite des banques sont : i) le niveau d’endettement auprès de la banque centrale; ii) un faible niveau de comptes disponibles et à vue; iii) les portefeuilles d’effets commerciaux par rapport au total des crédits; iv) le faible montant des dépôts à terme de plus de 2 ans à 10 ans par rapport aux actifs totaux; et v) le ratio actifs liquides sur actifs totaux. En revanche, les variables qui contribuent positivement sur la vraisemblance de survie des banques sont les suivantes : i) le ratio capital sur actifs totaux; ii) les bénéfices nets par rapport aux actifs totaux; iii) le ratio crédit total sur actifs totaux; iv) les dépôts à terme à 2 ans par rapport aux actifs totaux; et v) le niveau des engagements sous forme de cautions et avals par rapport aux actifs totaux. Les ratios portefeuilles d’effets commerciaux et actifs liquides par rapport aux actifs totaux sont les variables qui expliquent la faillite des banques commerciales, alors que ce sont les dépôts à terme de plus de 2 ans à 10 ans qui sont à l’origine des faillites des banques de développement. Ces faillites ont été considérablement réduites par la création en 1989 de la commission de réglementation bancaire régionale. Dans l’UEMOA, seule la variable affectée au Sénégal semble contribuer positivement sur la probabilité de faire faillite.

Functional Forms and Educational Production Functions

Different Functional Forms Are Proposed and Applied in the Context of Educational Production Functions. Three Different Specifications - the Linerar, Logit and Inverse Power Transformation (Ipt) - Are Used to Explain First Grade Students' Results to a Mathematics Achievement Test. with Ipt Identified As the Best Functional Form to Explain the Data, the Assumption of Differential Impact of Explanatory Variables on Achievement Following the Status of the Student As a Low Or High Achiever Is Retained. Policy Implications of Such Result in Terms of School Interventions Are Discussed in the Paper.