Wage dynamics and promotions inside and between firms

We focus on the dynamic relation between wage increases, promotions and job changes. In the empirical analyses, we use the Portuguese-matched employer–employee data Quadros de Pessoal. We find substantial wage returns to both promotions and job-to-job transitions. Our results are not consistent with models of full information and symmetric learning in a competitive and frictionless market. This might suggest that there is asymmetric information. An alternative explanation is that workers might search for a good match. Finally, we show that employer-reported promotions differ to a large extent from changes in hierarchical levels.     

Urban risks due to climate change in the Andean municipality of Pasto,Colombia: A Bayesian network approach

The current trends of climate change will increase people's exposure to urban risks related to events such as landslides, floods, forest fires, food production, health, and water availability, which are stochastic and very localized in nature. This research uses a Bayesian network (BN) approach to analyze the intensity of such urban risks for the Andean municipality of Pasto, Colombia, under climate change scenarios. The stochastic BN model is linked to correlational models and local scenarios of representative concentration trajectories (RCP) to project the possible risks to which the municipality of Pasto will be exposed in the future. The results show significant risks in crop yields, food security, water availability and disaster risks, but no significant risks on the incidence of acute diarrheal diseases (ADD) and acute respiratory infections (ARI), whereas positive outcomes are likely to occur in livestock production, influenced by population growth. The advantage of the BN approach is the possibility of updating beliefs in the probabilities of occurrence of events, especially in developing, intermediate cities with information-limited contexts.     

Predicting Public Corruption with Neural Networks: An Analysis of Spanish Provinces

We contend that corruption must be detected as soon as possible so that corrective and preventive measures may be taken. Thus, we develop an early warning system based on a neural network approach, specifically self-organizing maps, to predict public corruption based on economic and political factors. Unlike previous research, which is based on the perception of corruption, we use data on actual cases of corruption. We apply the model to Spanish provinces in which actual cases of corruption were reported by the media or went to court between 2000 and 2012. We find that the taxation of real estate, economic growth, the increase in real estate prices, the growing number of deposit institutions and non-financial firms, and the same political party remaining in power for long periods seem to induce public corruption. Our model provides different profiles of corruption risk depending on the economic conditions of a region conditional on the timing of the prediction. Our model also provides different time frameworks to predict corruption up to 3 years before cases are detected.     

Analysing the Effect of Legal System on Corporate Social Responsibility (CSR) at the Country Level,from a Multivariate Perspective

In this paper, we analyse the effect of coercive isomorphism (legal system) on Corporate Social Responsibility (CSR) at the country level by using the multivariate statistical techniques X-STATIS and HJ-biplot, which allow us to capture the role that these institutional forces play in the evolution and patterns of behaviour regarding the commitment to sustainability. The results evidence that coercive forces have an important influence on the social and environmental commitment of companies. Analysis of the legal system shows that firms located in civil law countries have a greater interest in their CSR practices and in disclosing information than companies in common law countries; the most likely companies to act in a responsible way are those operating in institutional environments with a large and developed legal system oriented towards stakeholder protection. Consequently, our results show that companies operating in countries with similar legal systems adopt homogeneous patterns of behaviour regarding the commitment to sustainability, but their degrees of development are strongly determined by the coercive institutional characteristics.     

The Moderating Effect of Countries’ Development on the Characterization of the Social Entrepreneur: An Empirical Analysis with GEM Data

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - The objective of this paper is to analyze the moderating effect that the level of development of countries exerts on the...     

Are There Gender-based Effects for an Educational Program for Parents of Adolescents With Risk Behaviors?

The goals of this study were to evaluate the gender-based effectiveness of the parental intervention of the Suspertu (“recovery” in English) prevention program for adolescents with risk behaviors in Spain. The sample included 229 parents (105 fathers and 124 mothers). One open-label trial with repeated measures was used. Parents received a family therapy and a group education. The intervention improved parents’ authoritative parenting style, decreasing the degree of parental stress and reducing parent’s psychopathological symptoms and maladjustment. Improvement in both groups (fathers and mothers) was mainly observed from pre- to post-intervention assessment. According to the results, prevention programs for adolescents with risk behaviors may be a suitable context both to teach parents to deal appropriately with their children’s risk behaviors, and to improve parent’s psychological state.     

Urbanization homogenizes the interactions of plant-frugivore bird networks

Urban Ecosystems - Anthropogenic activities are the main cause of habitat loss and fragmentation, which directly affects biodiversity. Disruption in landscape connectivity among populations may...     

Welfare gains of the poor: An endogenous Bayesian approach with spatial random effects

We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We find through a limited Monte Carlo experiment that our proposal works well in terms of point estimates and prediction. We apply our method to analyze the welfare effects generated by a process of electricity tariff unification on the poorest households. In particular, we deduce an Equivalent Variation measure where there is a budget constraint for a two-tiered pricing scheme, and find that 10% of the poorest municipalities attained welfare gains above 2% of their initial income.     

Window strikes: bird collisions in a Neotropical green city

Urban Ecosystems - Window strikes are among the most worrisome causes of bird mortality. Being responsible for billions of avian deaths, bird-window collisions have been widely studied in the US...     

The perfect storm? How to explain the rise of intergovernmental conflicts in Spain? (1984–2014)

As in other federal-like countries, intergovernmental relations in Spain are characterised by a series of conflicts between central and regional governments. But, which factors explain this dynamic of contention? This investigation operationalises intergovernmental conflicts through a specific dataset constituted by the volume of contestations between regional and central executives (and vice versa) in Spain before the Constitutional Court. This research demonstrates that from 1984 to 2014 the periods of absolute majority at the Congress and the victory of peripheral nationalist parties at the head of autonomous communities increased the level of intergovernmental contestations.